DHH: Future of Programming, AI, Agentic Engineering, Vibe Coding & Linux | Lex Fridman Podcast #501

TL;DR

• 13 months after his AI-skeptic appearance, DHH returns fully converted: Omarchy Quattro (his Arch-based Linux distro) shipped with 100% agent-written code — he reviewed shape and critical model-layer lines, but hand-wrote nothing. "There are decades where nothing happens and weeks where decades happen."
• His timeline of the agentic era: Opus 4.5 (Nov 24, 2025) was the dividing line; sub-agents arrived in spring; and with Opus 5, Fable, and GPT Soul the relationship inverted — he describes the problem, the agent picks the path. He ranks Fable the best model (especially planning/review), Opus 5 second, with Claude Code the best harness and Codex xhigh as his standing reviewer.
• His benchmark story: one-shotting a Python→Rust translation of a terminal-effects library — Fable finished in 45 min (~$550 token-value), GPT Soul ($46) and Grok 46 ($55) also completed it, DeepSeek Pro did it for $23, budget models failed; auto-research loops eventually hit a 46x speedup. "This is AGI, isn't it?"
• Big theses: agents are better than the median programmer (Shopify found agent-reviewed PRs caused fewer production incidents); open source is entering its best era (1,000+ PRs merged on Omarchy in 3 months, 330 plugins in 3 days); implementation is no longer the bottleneck — ideas, vision, and taste are; and Linux will win the desktop because "everything in Linux is either a config file or a CLI tool" — perfect for agents.
• The back half goes wide: his multi-machine setup (Herder + Tailscale + KVMs, 16 parallel agent threads, 4 Claude Max subscriptions), criticism of Anthropic's pettiness (claude.md vs agents.md, cutting off OpenCode, refusing to translate his essay), fatherhood as "the peak experience of being on the planet," his mass-immigration politics, quitting his Oura ring, and a memento-mori easter egg in Omarchy's calendar.

Key moments

• [02:56] The conversion — 13 months after his skeptical appearance, DHH is "incredibly excited... 100% pure unadulterated joy"; Opus 4.5 on Nov 24, 2025 was his dividing line ([07:21]).
• [15:15] 100% AI-pilled — Omarchy Quattro: three months, zero hand-written shipped code; but Basecamp 5's February "let the designers vibe" experiment destroyed the architecture and needed manual cleanup ([16:59]).
• [18:44] Why big companies aren't faster — the bottleneck is human bandwidth and approval layers, not implementation: "That's where all the productivity goes to die."
• [29:13] Open source's best era — agent PRs with "all the boxes ticked," easier to reject ("it's just a clanker"), 330 plugins in 3 days; agents review Omarchy PRs before he sees them.
• [36:43] Ideas come from models now — "I have seen things you people wouldn't believe. Ideas coming out of models so great that it makes me humble."
• [47:05] Vibe coding defined — telling an agent to build without looking at implementation; distinct from programming; over-specifying now hurts — Opus 5's system prompt shrank 80% ([56:22]).
• [91:57] The new setup — parallel agents in Herder (tmux + notifications), 4-5 machines via Tailscale + GLi.NET Comet KVMs, ~16 threads; bandwidth went "from dialup to fiber."
• [104:13] The birthday gift — DHH gives Lex a Dell XPS 14 preloaded with Omarchy, installed live in under a minute; install-time world record is 45 seconds, 12-second turbo images planned ([115:36]).
• [146:59] Bot anecdotes — his Omarchy bot filed 28 GitHub issues in 12 seconds and got banned as spam; then emailed a bug report for unreleased software to the mise maintainer ([147:47]).
• [149:49] Model rankings + the Rust test — Fable #1, Opus 5 #2; the TTE→Rust one-shot: Fable 45min/$550, Soul $46, Grok 46 $55, DeepSeek Pro $23, cheap models failed; 46x final speedup ([157:47]).
• [184:00] Fake email jobs — Graeber's thesis; layoffs are pandemic overhiring corrections with AI as the excuse; Toby Lütke's F1 analogy for post-work employment ([185:34]).
• [190:31] Fatherhood — "creating life with another human that you love is literally the peak experience of being on the planet."
• [205:09] Anthropic gripes — claude.md vs agents.md pettiness, OpenCode subscription cutoff, refusing to translate his immigration essay to Italian ("I'm sorry Dave"); a Chinese open-weight model answered Tiananmen bluntly while a US frontier model refused a translation ([209:55]).
• [218:56] Linux wins — "not only can I see it, I find it to be the most probable outcome"; Linus welcomes AI contributions; PewDiePie as the model of the new builder ([229:52]).
• [262:18] The politics section — mass immigration, Danish statistics, Overton window: "The Overton window does not open itself."
• [295:00] Mortality — anti-longevity-optimization (quit his Oura ring), his wife's "longevity focus is like anorexia" line, Omarchy's memento-mori calendar easter egg ([304:04]), and choosing the '80s for eternal recurrence ([312:46]).

Hook microscope (0-10s)

• Frames: 20 at 2 fps
• Word-level transcript (19 words):

  [  0.00s] There
  [  0.34s] are
  [  1.18s] decades
  [  1.84s] where
  [  2.08s] nothing
  [  2.34s] happens
  [  2.82s] and
  [  3.22s] weeks
  [  3.56s] where
  [  4.00s] decades
  [  4.40s] happen
  [  5.78s] And
  [  6.00s] we
  [  6.18s] have
  [  6.64s] seen
  [  7.68s] decades
  [  8.52s] of
  [  9.04s] progress
  [  9.52s] happen

Hook pattern: montage-of-peaks cold open. Lex's standard formula executed on highlight-reel steroids: 87 seconds of DHH's most quotable moments stitched together before any introduction — the Lenin "decades happen in weeks" quote (0:02), the genie-out-of-the-bottle OS riff (0:19), the race-car "Holy shit, I'm alive" (0:49), Overton window (1:00), and fatherhood as peak experience (1:15). Each clip is chosen to promise a different section of the 5-hour conversation (AI acceleration, Omarchy, racing, politics, fatherhood) — a table of contents rendered as adrenaline. The visual is a single static two-shot studio frame throughout; all hook energy is verbal.

Editorial profile

• Shots: 80
• Cuts/min: 0.25
• Mean shot length: 236.89s
• Median shot length: 65.63s
• Talking-head ratio: n/a (opencv not installed)

Marathon two-shot podcast (0.25 cuts/min over 5¼ hours): static studio angles alternating between guest and host, occasional inset stills (a Tobias Lütke card, an AI-generated racing video), live on-laptop demos described but rarely shown; classic Lex Fridman chapter-driven long form.

Quotable moments

• [00:02] "There are decades where nothing happens and weeks where decades happen — and we have seen decades of progress happen in the last nine months."
• [31:19] "I have the statistical basis to assert that most programmers... they suck. But do you know who will do all that stuff? Agents, if you tell them to."
• [38:20] "If you're not recognizing the gravity of the moment, that's the delusion. That's the psychosis."
• [153:04] "I'm just sitting there... and I still had to lean back and go: this is AGI, isn't it? This is what AGI looks like."
• [242:23] "If there is one programming language more beautiful than Ruby, it is the English language."
• [192:38] "Creating life with another human that you love is literally the peak experience of being on the planet."
• [80:04] "I'm sorry to channel some yins and wong here, but that's just loser talk. You don't have to be a loser. You can choose to lean in and win."

Quotes & references (DHH quoting others)

Every place DHH quotes or invokes someone else, with timestamps.

Direct quotations

• Lenin [04:03] — "I love this quote. I think it's Lenin: There are decades where nothing happens and weeks where decades happen. And we have seen decades of progress happen in the last nine months."
• Mitchell Hashimoto (Ghostty creator, HashiCorp founder) [112:26] — quoting his X post on the 60-second-install obsession: "The pursuit of excellence deserves no explanation. Wanting to make something as good and as fast and as beautiful as possible has no need for justification."
• Jeff Bezos [90:45] — "I keep coming back to this almost regret minimization framework, to borrow Jeff Bezos's terms: are you going to look at yourself two years from now and think 'I spent my time well being pissy about the present'... or be proud of yourself for leaning in?"
• Elon Musk [229:18] — "Elon has this line: Did you also think I was going to be a normal chill dude? What would the world gain if we got one more normal chill dude and we had to trade Elon?"
• William Gibson (unattributed but verbatim) [187:06] — "The future is always already here. It's just not evenly distributed."
• Blade Runner / Roy Batty (unattributed riff) [36:44] — "I have seen things you people wouldn't believe — ideas coming out of models so great that it makes me humble."
• Boris Cherny (Claude Code) [56:19] — relaying his interview claim that the Opus 5 system prompt shrank ~80% because the agent "was actually being damaged by overly prescriptive humans."

Invoked thinkers & frameworks

• Martin Luther [30:36] — AI as a Reformation moment: programmers were "a class of clerics and priests" intermediating the computer, now disintermediated like the 95 Theses — "you should have direct access to the higher intelligence."
• The Stoics / amor fati [69:42, 194:11] — "Stoic philosophy, amor fati — loving your fate — is an incredibly liberating way to live"; "you have these guys 2,500 years ago dealing with very familiar dilemmas... recognizing we're not so special is a great liberation."
• Peter Thiel [193:28] — the stagnation thesis: "basically nothing has happened in the physical world in quite a long time... maybe AI will be the thing that is more consequential."
• David Graeber [183:55] — the bullshit-jobs poll (~30% said their job made no difference to mankind) anchoring the fake-email-jobs argument.
• Toby Lütke [44:48, 179:03, 185:22, 260:01] — quoted four times ("I'm quoting Toby for the third time here"): the AI memo DHH initially dismissed, the "brains and hands" security pattern, the Formula 1 theory of post-AI employment, the agent that shops for him.
• The Fourth Turning (Strauss–Howe) [194:51] — "history is a circle more so than a straight line... whatever crisis feels so pressing until we zoom back."
• Richard Sutton (tentatively) [247:39] — "an interview with Sutton or maybe one of the other original guys" on intelligence living in the interaction/weights rather than one spot.
• Steve Jobs [141:21] — the first iPhone was "terrible in all sorts of ways... but the product was so compelling it just didn't matter" — don't let latency perfectionism delay shipping.
• Linus Torvalds [220:30, 224:29] — paraphrasing his post: "if you think Linux is an anti-AI project, think again... do the open source thing and fork it, because we're going to use AI."
• Jevons paradox + the ATM story [72:07] — cheaper programs → more demand; ATMs led to more bank tellers.
• The Luddites [73:11] — his preferred parallel for displaced programmers: "highly skilled professionals doing a job they liked on rather favorable conditions" — and yet nobody wants $400 t-shirts back.

DHH originals worth keeping

• The Rolex patron riff [122:46] — "You look at a mechanical watch and go, Rolex has one that can go down to 4,000 meters. No one outside of three people in the world who ever buy that watch will ever put it to the test. But don't you want to be the kind of person who is a patron of people who want to push the human race that much forward? I want the fastest car breaking the speed limits. I want the diver watch that can go down the Mariana Trench. I want the operating system that can install in less than 60 seconds." (Follows the Hashimoto quote and the Mercedes W126 story; excerpted in the cold open.)

Lex's, which DHH ran with

• Picasso discovers cubism [88:19] — DHH: "Picasso is actually a good parallel... he's reimagining the apple to be a freaking square, and he's getting excited about that."
• Nietzsche's eternal recurrence [312:15] — DHH's answer: the '80s, "but skip the orange pants."
• Emerson (Lex's outro) — "Once you make a decision, the universe conspires to make it happen."

Entities mentioned

• People: dhh (David Heinemeier Hansen), lex-fridman, tobias-lutke (Shopify CEO, Omarchy partner), ryan-hughes (Omarchy co-conspirator), linus-torvalds, boris-cherny (Claude Code), mitchell-hashimoto (Ghostty), pewdiepie, elon-musk, brian-johnson, jdx (mise), david-graeber, theo (t3)
• Companies: anthropic, openai, xai, deepseek, moonshot-kimi, shopify, 37signals, dell, apple, microsoft, google, fireworks-ai, higgsfield
• Tools / products: omarchy (Quattro), omakub, ruby-on-rails, basecamp, claude-code, fable, opus-5, gpt-soul, grok-46, kimi-k3, deepseek-v4, codex, open-code, copilot, herder, tmux, neovim, tailscale, ghostty, mise, hey-com, arch-linux, hyprland, dell-xps-14, commodore-64, typora, ia-writer
• Places: copenhagen, denmark, malibu, san-francisco, london, china, japan

Concepts surfaced

• agentic-engineering: AI does the implementation, the human steers with vision and taste; DHH hates the term but lives the practice — "let's just call it programming."
• vibe-coding: telling an agent to build software without looking at the implementation; distinct from programming, which implies understanding the primitives.
• implementation-is-not-the-bottleneck: organizations are bottlenecked on ideas, vision, and taste — plus human bandwidth and approval layers, "where all the productivity goes to die."
• under-specification-principle: be vague, manifest something, then react — the agile insight ("no one knows what they want until they receive it") applied to prompting; over-prescription damages agents (Opus 5's system prompt shrank 80%).
• differential-evaluation: humans excel at snap gut judgments between a few options — design workflows around picking, not specifying.
• jevons-paradox: cheaper programs → more demand for programs; the ATM/bank-teller story as the optimistic employment case.
• fake-email-jobs: Graeber's bullshit-jobs thesis; AI exposes unproductive roles, pandemic overhiring made layoffs inevitable, AI is the excuse.
• amor-fati: stoic love of fate as the emotional strategy for surviving paradigm shifts; grief is allowed but leaning in is the move.
• catch-up-in-two-weeks: no accumulating advantage in AI tooling — a year-long backpacker could reach the frontier in two weeks, so FOMO is irrational.
• brains-and-hands-pattern: run the model where coordination happens, execute untrusted code in isolated VMs — the security architecture for autonomous dev bots.
• pursuit-of-excellence: "needs no explanation" (Hashimoto) — the 45-second OS install as McLaren gram-shaving; frivolous metrics catalyze real innovation.
• malleable-computer: the agentic OS thesis — you should be able to vibe-code your operating system; Linux's config-files-and-CLIs nature makes it the winner.
• overton-window-nudging: controversial positions expand discussable space "one nudge at a time by people risking a little reputation."
• memento-mori: embracing finitude — against longevity over-optimization, for the calendar easter egg showing your life's percent-complete.

Transcript

Source: captions.

[00:03] There are decades where nothing happens and weeks where decades happen and we
[00:06] and weeks where decades happen and we have seen decades of progress happen in
[00:11] have seen decades of progress happen in the last nine months. If you're not
[00:13] the last nine months. If you're not recognizing the
[00:15] recognizing the gravity of the moment, that's the
[00:17] gravity of the moment, that's the delusion. That's the psychosis. Who
[00:20] delusion. That's the psychosis. Who would not get delirious if suddenly a
[00:22] would not get delirious if suddenly a genie pops out of the bottle and says,
[00:24] genie pops out of the bottle and says, "You can have whatever you want." Every
[00:27] "You can have whatever you want." Every feature you've ever dreamed of in an
[00:30] feature you've ever dreamed of in an operating system, I can deliver them to
[00:31] operating system, I can deliver them to you. Most of them in five minutes, a few
[00:34] you. Most of them in five minutes, a few in 20. And if we really go hog wild,
[00:36] in 20. And if we really go hog wild, it's going to take me 2 hours. I want
[00:39] it's going to take me 2 hours. I want the fastest car breaking the speed
[00:40] the fastest car breaking the speed limits. I want the diver watch that can
[00:42] limits. I want the diver watch that can go down the Mariana Trench. I want the
[00:46] go down the Mariana Trench. I want the operating system that can install in
[00:48] operating system that can install in less than 60 seconds. One of the things
[00:49] less than 60 seconds. One of the things I always loved about race cars was when
[00:52] I always loved about race cars was when I would stumble out of the car,
[00:54] I would stumble out of the car, absolutely smashed and barely able to
[00:56] absolutely smashed and barely able to hold my head up and I'd lay down on the
[00:58] hold my head up and I'd lay down on the garage floor and just think, "Holy
[01:01] garage floor and just think, "Holy I'm alive." The overtone window does not
[01:03] I'm alive." The overtone window does not open itself. It opens one nudge at a
[01:06] open itself. It opens one nudge at a time by people risking a little a little
[01:10] time by people risking a little a little reputation, a little push back, and a
[01:12] reputation, a little push back, and a little criticism or maybe sometimes a
[01:14] little criticism or maybe sometimes a lot of reputation or a lot of criticism
[01:16] lot of reputation or a lot of criticism or a lot of push back. Creating life
[01:18] or a lot of push back. Creating life with another human that you love is
[01:22] with another human that you love is literally the peak experience of being
[01:25] literally the peak experience of being on the planet.
[01:28] on the planet. The following is a conversation with
[01:30] The following is a conversation with David Heinmire Hansen, also known as
[01:33] David Heinmire Hansen, also known as DHH,
[01:34] DHH, creator of Ruby on Rails, CTO of 37
[01:37] creator of Ruby on Rails, CTO of 37 Signals, creator of the new Amachi Linux
[01:41] Signals, creator of the new Amachi Linux operating system, bestselling author,
[01:43] operating system, bestselling author, race car driver, and one of the most
[01:46] race car driver, and one of the most outspoken and prolific programmers in
[01:48] outspoken and prolific programmers in the world. For the past 20 plus years,
[01:51] the world. For the past 20 plus years, for him, programming meant meticulously
[01:54] for him, programming meant meticulously handcrafting beautiful Ruby code. But
[01:57] handcrafting beautiful Ruby code. But recently, since late 2025, GHH has
[02:01] recently, since late 2025, GHH has embraced the AI revolution and has
[02:03] embraced the AI revolution and has openly transformed himself into once
[02:06] openly transformed himself into once again one of the most outspoken and
[02:08] again one of the most outspoken and prolific agentic engineers, even though
[02:11] prolific agentic engineers, even though he hates that term. So let's say
[02:15] he hates that term. So let's say practitioners of whatever programming is
[02:18] practitioners of whatever programming is becoming where AI is doing most of the
[02:20] becoming where AI is doing most of the actual programming and the human steers
[02:23] actual programming and the human steers the ship with highle design vision and
[02:26] the ship with highle design vision and taste. Yes, it's true DHH is at times
[02:30] taste. Yes, it's true DHH is at times controversial, but he's always fearless,
[02:32] controversial, but he's always fearless, brilliant, and fun to talk to. This was
[02:35] brilliant, and fun to talk to. This was once again an intense, eye-opening, and
[02:38] once again an intense, eye-opening, and a wild roller coaster ride of a
[02:40] a wild roller coaster ride of a conversation. This is a Lex Freedman
[02:43] conversation. This is a Lex Freedman podcast. To support it, please check out
[02:45] podcast. To support it, please check out our sponsors in the description where
[02:47] our sponsors in the description where you can also find links to contact me,
[02:50] you can also find links to contact me, ask questions, give feedback, and so on.
[02:53] ask questions, give feedback, and so on. And now, dear friends, here's DHH.
[02:57] And now, dear friends, here's DHH. 13 months ago, we sat down right here to
[03:00] 13 months ago, we sat down right here to talk about programming and then uh
[03:02] talk about programming and then uh everything changed. At that time you
[03:05] everything changed. At that time you were a bit skeptical about the role of
[03:07] were a bit skeptical about the role of AI in the process of programming and
[03:10] AI in the process of programming and then we went through this rapid
[03:11] then we went through this rapid evolution of uh a agentic engineering.
[03:15] evolution of uh a agentic engineering. So uh simple question to start how has
[03:19] So uh simple question to start how has your view on AI's role in programming
[03:21] your view on AI's role in programming changed? Are you excited? Are you
[03:23] changed? Are you excited? Are you terrified? Are you on an emotional
[03:25] terrified? Are you on an emotional roller coaster ride?
[03:27] roller coaster ride? >> I am incredibly excited.
[03:30] >> I am incredibly excited. >> You've been talking about fun a lot.
[03:31] >> You've been talking about fun a lot. There is none of the existential doubt
[03:36] There is none of the existential doubt that doesn't exist for me as an
[03:38] that doesn't exist for me as an emotional component. It is only there as
[03:40] emotional component. It is only there as an intellectual component. And the
[03:42] an intellectual component. And the emotional component for me is 100% pure
[03:45] emotional component for me is 100% pure unadultered joy
[03:47] unadultered joy >> and optimism and amazement that we've
[03:51] >> and optimism and amazement that we've made computers do this. And I find it so
[03:54] made computers do this. And I find it so interesting that we talked just 13
[03:56] interesting that we talked just 13 months ago because
[03:59] months ago because it's like we talked in different
[04:01] it's like we talked in different universes, different eras. I love this
[04:04] universes, different eras. I love this quote. I think it's Lenin. There are
[04:07] quote. I think it's Lenin. There are decades where nothing happens and weeks
[04:09] decades where nothing happens and weeks where decades happen. And we have seen
[04:13] where decades happen. And we have seen decades of progress happen in the last
[04:17] decades of progress happen in the last nine months. I mean, imagine you're
[04:19] nine months. I mean, imagine you're there when the Wright brothers take
[04:21] there when the Wright brothers take flight.
[04:22] flight. Yesterday, the New York Times would
[04:24] Yesterday, the New York Times would write, "It's going to be 10,000 years
[04:25] write, "It's going to be 10,000 years before we fly." And then the day after,
[04:28] before we fly." And then the day after, we're up in the skies and just a few
[04:31] we're up in the skies and just a few years after that, there cross Atlantic
[04:33] years after that, there cross Atlantic planes. The whole world has completely
[04:36] planes. The whole world has completely changed. What a blessing to be there in
[04:38] changed. What a blessing to be there in that moment. If you zoom out and look at
[04:40] that moment. If you zoom out and look at all of human history, how many humans
[04:42] all of human history, how many humans got to live within the same epoch that
[04:47] got to live within the same epoch that they were born in? They never saw that
[04:49] they were born in? They never saw that complete change of the world and of
[04:52] complete change of the world and of society. And to have been blessed with
[04:56] society. And to have been blessed with two of those
[04:58] two of those feels just such a privilege. I got to
[05:01] feels just such a privilege. I got to see the internet
[05:02] see the internet >> from pre- internet to post internet and
[05:06] >> from pre- internet to post internet and then now preai post AI. What an amazing
[05:11] then now preai post AI. What an amazing run. How fortunate.
[05:12] run. How fortunate. >> Yeah. But the thing is this feels like a
[05:16] >> Yeah. But the thing is this feels like a thing that happened faster than anything
[05:17] thing that happened faster than anything else in human history. So I would say
[05:19] else in human history. So I would say somewhere around December, maybe late
[05:22] somewhere around December, maybe late November,
[05:23] November, >> November 24.
[05:25] >> November 24. >> This is, you know, when they talk about
[05:28] >> This is, you know, when they talk about when one nation invades another in a
[05:30] when one nation invades another in a world war or something like this that
[05:32] world war or something like this that this is how we talk about AI changing
[05:34] this is how we talk about AI changing everything. Yeah. And it really just
[05:37] everything. Yeah. And it really just shifted for many great developers. they
[05:40] shifted for many great developers. they shifted to where AI is doing some uh
[05:43] shifted to where AI is doing some uh basic autocomplete maybe writing 5 10 15
[05:47] basic autocomplete maybe writing 5 10 15 20% of code to writing 80% of code
[05:50] 20% of code to writing 80% of code >> or 100
[05:50] >> or 100 >> or 100 yeah especially if it's not a
[05:53] >> or 100 yeah especially if it's not a public facing product
[05:55] public facing product >> to me that's why even when I look back
[05:59] >> to me that's why even when I look back upon our conversation a year ago I don't
[06:02] upon our conversation a year ago I don't actually have different opinions I have
[06:04] actually have different opinions I have the same opinions a year ago I did not
[06:07] the same opinions a year ago I did not like the mode of AI we were offered it
[06:09] like the mode of AI we were offered it was the autocomplete mode or it was the
[06:12] was the autocomplete mode or it was the AI chatbot mode. Now, the chatbot I
[06:15] AI chatbot mode. Now, the chatbot I actually liked, as we talked about,
[06:16] actually liked, as we talked about, great tutor right from the get-go. Great
[06:19] great tutor right from the get-go. Great way of looking things up on the
[06:20] way of looking things up on the internet, not what was going to replace
[06:23] internet, not what was going to replace me chiseling code.
[06:26] me chiseling code. But then we get the agents.
[06:28] But then we get the agents. >> Yeah. And the agents start out being
[06:32] >> Yeah. And the agents start out being curiosities for about five minutes and
[06:35] curiosities for about five minutes and then they get amazing and then they get
[06:39] then they get amazing and then they get oh my god is this hi
[06:41] oh my god is this hi and all of that happened since last year
[06:45] and all of that happened since last year even just in within the last n months we
[06:48] even just in within the last n months we have basically these few faces here we
[06:51] have basically these few faces here we have AI in the pre-agentic era I was
[06:55] have AI in the pre-agentic era I was excited about that but it was not
[06:58] excited about that but it was not fundamentally
[06:58] fundamentally rewriting the rules of the game for me.
[07:01] rewriting the rules of the game for me. It was not completely changing how I
[07:03] It was not completely changing how I worked. I was still chling code. I just
[07:06] worked. I was still chling code. I just had a little helper, a little sidekick
[07:09] had a little helper, a little sidekick who could
[07:10] who could >> bounce ideas off and I could look up
[07:12] >> bounce ideas off and I could look up this uh information online and so forth
[07:15] this uh information online and so forth in a more efficient way. It was just a
[07:16] in a more efficient way. It was just a more efficient way to do what I was
[07:18] more efficient way to do what I was already doing and it didn't change the
[07:20] already doing and it didn't change the emotional connection I had to to the
[07:22] emotional connection I had to to the computer. Then we get to November 24th,
[07:26] computer. Then we get to November 24th, 2025. Opus 4.5 to me was the dividing
[07:31] 2025. Opus 4.5 to me was the dividing line where suddenly I didn't even try it
[07:34] line where suddenly I didn't even try it on the 24th. I think I tried it on the
[07:36] on the 24th. I think I tried it on the 26th.
[07:38] 26th. I give it a couple of tasks and I
[07:41] I give it a couple of tasks and I realize that the quality of the output
[07:45] realize that the quality of the output is uncanningly close to what I would
[07:48] is uncanningly close to what I would have written. And I I remember just
[07:52] have written. And I I remember just leaning back and thinking, what just
[07:55] leaning back and thinking, what just happened?
[07:56] happened? >> H how did we go from this autocomplete
[07:59] >> H how did we go from this autocomplete mess that I was talking to you about in
[08:01] mess that I was talking to you about in the summer to this just a few short
[08:04] the summer to this just a few short months later? How did we get both the
[08:07] months later? How did we get both the increase in intelligence and then also
[08:08] increase in intelligence and then also the increase in usability? this agent
[08:12] the increase in usability? this agent harness question where
[08:16] harness question where I don't know if Opus 4.5 was that much
[08:18] I don't know if Opus 4.5 was that much smarter than Opus 4 which is what we had
[08:20] smarter than Opus 4 which is what we had in the summer but its ability to
[08:24] in the summer but its ability to instrument your computer to use tools to
[08:26] instrument your computer to use tools to check its own work to apply its
[08:30] check its own work to apply its intelligence in such a way that you
[08:32] intelligence in such a way that you could get real meaningful work out of it
[08:35] could get real meaningful work out of it was completely different and I think
[08:37] was completely different and I think this is then the big change that happens
[08:40] this is then the big change that happens for almost anyone who paid attention and
[08:41] for almost anyone who paid attention and started playing with it over the
[08:43] started playing with it over the Christmas break. This is what I heard
[08:45] Christmas break. This is what I heard from Shopify and other places with lots
[08:47] from Shopify and other places with lots of employees who
[08:49] of employees who >> suddenly had a breather, suddenly had a
[08:51] >> suddenly had a breather, suddenly had a couple of weeks to lean back and just
[08:53] couple of weeks to lean back and just look at what was going on, gave it a try
[08:56] look at what was going on, gave it a try and had the same mindblowing experience
[09:00] and had the same mindblowing experience that these agents were of a different
[09:03] that these agents were of a different genre than what we had before. And then
[09:06] genre than what we had before. And then what we get to is
[09:08] what we get to is I'm already excited at this point. Like
[09:11] I'm already excited at this point. Like by December, I'm already revisiting sort
[09:14] by December, I'm already revisiting sort of all my priors and going like, "Wow,
[09:17] of all my priors and going like, "Wow, if it can do this, can it also do that?"
[09:19] if it can do this, can it also do that?" >> Oh, yeah, it can.
[09:21] >> Oh, yeah, it can. >> And again, Opus 4.5 now looks like a
[09:25] >> And again, Opus 4.5 now looks like a model.
[09:26] model. >> Yeah.
[09:27] >> Yeah. >> And this is the
[09:29] >> And this is the magic of this progress is you think you
[09:32] magic of this progress is you think you reached something. I remember thinking
[09:34] reached something. I remember thinking at the moment, if this is the last model
[09:37] at the moment, if this is the last model we get, I'll be set. I'll be happy. I
[09:40] we get, I'll be set. I'll be happy. I could live with Opus 4.5 for the next 20
[09:42] could live with Opus 4.5 for the next 20 years and you would hear no complaints
[09:44] years and you would hear no complaints from me because it was just so
[09:47] from me because it was just so incredibly
[09:48] incredibly >> amazing to see an agent do all this work
[09:51] >> amazing to see an agent do all this work in the way that I wanted it done because
[09:54] in the way that I wanted it done because it was not just about it being able to
[09:56] it was not just about it being able to solve a task. It was also that I could
[09:59] solve a task. It was also that I could look at its path there and go, "Yep,
[10:02] look at its path there and go, "Yep, yep. uh maybe not there but almost and
[10:04] yep. uh maybe not there but almost and it would give you two notes you'll get
[10:06] it would give you two notes you'll get to where I wanted to go in the way I
[10:09] to where I wanted to go in the way I wanted to go there you could produce
[10:11] wanted to go there you could produce code I wanted to merge you could produce
[10:14] code I wanted to merge you could produce code that actually looked beautiful if
[10:16] code that actually looked beautiful if it was written in Ruby Rust different
[10:19] it was written in Ruby Rust different question but
[10:22] question but this ability for the agents to truly
[10:26] this ability for the agents to truly become an extension of how I wanted to
[10:29] become an extension of how I wanted to work was very novel but then we wait
[10:32] work was very novel but then we wait just until early spring and suddenly we
[10:37] just until early spring and suddenly we get sub agents. We get harnesses that
[10:39] get sub agents. We get harnesses that can subdivide the task and something
[10:42] can subdivide the task and something that would take opus quite a while
[10:45] that would take opus quite a while suddenly took a fifth of the time, a
[10:48] suddenly took a fifth of the time, a tenth of the time because it could get
[10:50] tenth of the time because it could get chopped up and suddenly you got eight
[10:52] chopped up and suddenly you got eight sub aents working for you. But both of
[10:55] sub aents working for you. But both of those two first phases of the agentic
[10:58] those two first phases of the agentic age to me still felt like I had to
[11:01] age to me still felt like I had to drive. I could tell it what I wanted,
[11:04] drive. I could tell it what I wanted, where to look for it, and steer it a
[11:07] where to look for it, and steer it a little bit when it went off, and then
[11:09] little bit when it went off, and then we'll get there, and I would go much
[11:10] we'll get there, and I would go much faster, but I had to be in the driver's
[11:12] faster, but I had to be in the driver's seat. I had to tell it what I wanted,
[11:15] seat. I had to tell it what I wanted, and I had to be the
[11:18] and I had to be the reviewer, the auditor of what was coming
[11:20] reviewer, the auditor of what was coming out. And then finally now this summer
[11:24] out. And then finally now this summer with Opus 5, Fable and Soul, GPT Soul,
[11:29] with Opus 5, Fable and Soul, GPT Soul, and to a lesser extent some of the
[11:32] and to a lesser extent some of the openweight models, we've arrived at a
[11:35] openweight models, we've arrived at a new era where I'm not telling it where
[11:37] new era where I'm not telling it where we're going. I'm telling it the problem
[11:39] we're going. I'm telling it the problem I have. I'm telling it the fuzzy vague
[11:42] I have. I'm telling it the fuzzy vague idea I have. It tells me where we're
[11:46] idea I have. It tells me where we're going.
[11:47] going. >> It tells me which path to take. And I
[11:50] >> It tells me which path to take. And I will still look at it because I'm a
[11:52] will still look at it because I'm a curious person and I like computers and
[11:54] curious person and I like computers and I like the outcome of it. But I really
[11:56] I like the outcome of it. But I really kind of don't have to. I've become
[11:59] kind of don't have to. I've become optional in the part that produces the
[12:03] optional in the part that produces the code that picks the route. Remember when
[12:06] code that picks the route. Remember when early GPS systems came out?
[12:09] early GPS systems came out? >> They were amazing compared to looking at
[12:11] >> They were amazing compared to looking at a map, but you still want to pay
[12:13] a map, but you still want to pay attention. Is it going to drive you in
[12:15] attention. Is it going to drive you in the harbor? I remember these newspaper
[12:17] the harbor? I remember these newspaper articles. GPS are terrible because
[12:19] articles. GPS are terrible because people don't pay attention and they
[12:20] people don't pay attention and they drive in the harbor. When was the last
[12:22] drive in the harbor. When was the last time GPS drove anyone in the harbor?
[12:24] time GPS drove anyone in the harbor? Like that just doesn't happen anymore.
[12:25] Like that just doesn't happen anymore. In fact, the cars now just drive
[12:27] In fact, the cars now just drive themselves, right? And this is where
[12:29] themselves, right? And this is where we've arrived at now that I can trust
[12:33] we've arrived at now that I can trust for the domain I'm working in right now.
[12:35] for the domain I'm working in right now. I can trust it and feel completely
[12:39] I can trust it and feel completely confident that it's going to have my
[12:41] confident that it's going to have my back. It's not going to do something
[12:42] back. It's not going to do something stupid. And if it does something stupid,
[12:44] stupid. And if it does something stupid, it's going to be able to recover. Mhm.
[12:46] it's going to be able to recover. Mhm. We should mention that there's all kinds
[12:47] We should mention that there's all kinds of domains that programmers operate in.
[12:50] of domains that programmers operate in. There's
[12:51] There's >> I actually don't know, but I think the
[12:54] >> I actually don't know, but I think the most common
[12:56] most common domain in development is like web dev
[12:58] domain in development is like web dev crud. You have a database, you have a
[13:01] crud. You have a database, you have a userfacing interface and it does
[13:03] userfacing interface and it does something back and forth and it could be
[13:06] something back and forth and it could be internal to just one person to multiple
[13:08] internal to just one person to multiple people to a small number of people or to
[13:10] people to a small number of people or to to the world. And I think for that
[13:14] to the world. And I think for that it's I mean you could really get to the
[13:16] it's I mean you could really get to the 100% of code written by AI and really if
[13:21] 100% of code written by AI and really if you're a good programmer and you have a
[13:22] you're a good programmer and you have a good intuition about what's happening
[13:24] good intuition about what's happening behind the scenes, you can legitimately
[13:27] behind the scenes, you can legitimately not look at the code. At least that's
[13:29] not look at the code. At least that's that's been my experience. I don't know
[13:31] that's been my experience. I don't know how much uh prior experience with
[13:34] how much uh prior experience with programming you need to have to kind of
[13:36] programming you need to have to kind of know that things are working correctly
[13:39] know that things are working correctly behind the scenes like intuitively by
[13:41] behind the scenes like intuitively by observing the uh the the ripple effects
[13:44] observing the uh the the ripple effects the symptoms of the system but I think
[13:47] the symptoms of the system but I think for that domain
[13:49] for that domain uh it's uh it's close to 100%. And then
[13:52] uh it's uh it's close to 100%. And then there's domains like you're also
[13:53] there's domains like you're also operating in which is writing a Linux
[13:55] operating in which is writing a Linux distribution. There maybe there's more
[13:58] distribution. There maybe there's more because you're obsessed with speed and
[14:00] because you're obsessed with speed and all that kind of stuff there. Maybe you
[14:02] all that kind of stuff there. Maybe you need to look at the code a little bit
[14:03] need to look at the code a little bit more. Then there's maybe safety critical
[14:05] more. Then there's maybe safety critical systems all the way down to operating a
[14:07] systems all the way down to operating a nuclear power plant or a self-driving
[14:10] nuclear power plant or a self-driving car. Maybe you need to look at the code
[14:12] car. Maybe you need to look at the code more carefully.
[14:12] more carefully. >> Yes. But that said, AI is insanely
[14:16] >> Yes. But that said, AI is insanely capable at both finding and fixing
[14:20] capable at both finding and fixing >> security vulnerabilities. This was the
[14:21] >> security vulnerabilities. This was the whole blow up about Fable. This model
[14:23] whole blow up about Fable. This model was so capable of finding holes that a
[14:27] was so capable of finding holes that a attacker could exploit that it was
[14:29] attacker could exploit that it was simply not safe to release. So the irony
[14:32] simply not safe to release. So the irony here is that when you look at that
[14:34] here is that when you look at that field, it seems like we've reached
[14:37] field, it seems like we've reached levels of intelligence that virtually no
[14:40] levels of intelligence that virtually no human can match because many of these
[14:44] human can match because many of these security holes are about stringing combo
[14:47] security holes are about stringing combo moves together. You find one little
[14:50] moves together. You find one little vulnerability here that by itself might
[14:52] vulnerability here that by itself might not be the worst thing in the world, but
[14:54] not be the worst thing in the world, but then you combine it with four others and
[14:56] then you combine it with four others and suddenly you have RCE, remote command
[14:59] suddenly you have RCE, remote command execution.
[15:01] execution. Humans who are able to do that are very
[15:03] Humans who are able to do that are very rare. They usually work inside state
[15:06] rare. They usually work inside state sponsored organizations or other
[15:09] sponsored organizations or other clandestine operations. They're not just
[15:12] clandestine operations. They're not just out and about finding things. So they've
[15:15] out and about finding things. So they've gotten so good at that. The Linux
[15:17] gotten so good at that. The Linux distribution is why I've gotten 100% AI
[15:22] distribution is why I've gotten 100% AI pill because I've been working on Umachi
[15:24] pill because I've been working on Umachi for the last three months, this version
[15:27] for the last three months, this version that just dropped a few days ago called
[15:29] that just dropped a few days ago called Quattro
[15:31] Quattro and almost right from the beginning of
[15:34] and almost right from the beginning of working on that version, the agent
[15:36] working on that version, the agent acceleration neared 100%. And in the
[15:39] acceleration neared 100%. And in the last two months, it has been 100%. I
[15:42] last two months, it has been 100%. I have not written
[15:43] have not written >> really
[15:43] >> really >> any of the code that's shipped in
[15:47] >> any of the code that's shipped in Quattro by hand. I've reviewed the shape
[15:51] Quattro by hand. I've reviewed the shape of all of it. I've reviewed the
[15:54] of all of it. I've reviewed the individual lines of anything that's
[15:56] individual lines of anything that's critical in the model layer of the
[15:58] critical in the model layer of the system
[15:59] system >> and I've not looked at a bunch of the UI
[16:01] >> and I've not looked at a bunch of the UI code. I have not looked at the bunch of
[16:04] code. I have not looked at the bunch of the auxiliary code and I have not
[16:07] the auxiliary code and I have not written any of the new functionality
[16:10] written any of the new functionality entirely by hand. But then the web part
[16:15] entirely by hand. But then the web part actually evolving base camp and hey our
[16:18] actually evolving base camp and hey our professional products that have lots of
[16:19] professional products that have lots of users and are relatively large code
[16:21] users and are relatively large code bases have proven surprisingly tricky to
[16:26] bases have proven surprisingly tricky to fully accelerate with agents. We just
[16:29] fully accelerate with agents. We just released Base Camp 5 not too long ago.
[16:31] released Base Camp 5 not too long ago. That was the first product at 37 signals
[16:34] That was the first product at 37 signals that was really agent accelerated
[16:37] that was really agent accelerated because we were in this final sprint
[16:39] because we were in this final sprint phase from around February. By then
[16:42] phase from around February. By then agents were already good.
[16:43] agents were already good. >> Mhm.
[16:44] >> Mhm. >> And we had this
[16:46] >> And we had this early surge of it's solved. We can just
[16:50] early surge of it's solved. We can just have the designers do the programming.
[16:52] have the designers do the programming. They know what features they want. They
[16:53] They know what features they want. They know what shape they want it to take.
[16:55] know what shape they want it to take. Let just let them vibe. And we let them
[16:58] Let just let them vibe. And we let them vibe.
[16:59] vibe. >> Yeah. And we ended up with a lot of PRs
[17:03] >> Yeah. And we ended up with a lot of PRs that individually perhaps could have
[17:05] that individually perhaps could have been justified for a hot moment taken
[17:08] been justified for a hot moment taken altogether destroyed the architecture of
[17:10] altogether destroyed the architecture of the system. And we actually had to clean
[17:12] the system. And we actually had to clean up manually mop it up by hand by human
[17:16] up manually mop it up by hand by human hand to get back to an architecture that
[17:18] hand to get back to an architecture that felt cohesive and coherent. So we still
[17:22] felt cohesive and coherent. So we still have a bit of that. That was February by
[17:24] have a bit of that. That was February by the way. Things are quite different now.
[17:25] the way. Things are quite different now. >> Well, hold on a second. What's the
[17:26] >> Well, hold on a second. What's the lesson from that? Is there is is one of
[17:28] lesson from that? Is there is is one of the lessons from that that you have to
[17:29] the lessons from that that you have to be a programmer at this stage to be able
[17:32] be a programmer at this stage to be able to vibe code
[17:34] to vibe code >> to be able to vibe code on existing
[17:37] >> to be able to vibe code on existing substantial code bases even if they are
[17:40] substantial code bases even if they are CRUD if you want to retain the element
[17:43] CRUD if you want to retain the element of architecture that got that system to
[17:45] of architecture that got that system to where it was.
[17:46] where it was. That's also a point where I've stressed
[17:49] That's also a point where I've stressed many times that when people accuse vibe
[17:52] many times that when people accuse vibe coders of being slob generators, I go
[17:56] coders of being slob generators, I go right back at them and say, "Have you
[17:57] right back at them and say, "Have you looked at the average programmer's
[17:59] looked at the average programmer's output?" That is some other slob, too.
[18:02] output?" That is some other slob, too. If you've looked at behind the scenes of
[18:05] If you've looked at behind the scenes of many great companies and what their code
[18:07] many great companies and what their code bases look like after there's been 3,000
[18:10] bases look like after there's been 3,000 humans through them, they're awful.
[18:13] humans through them, they're awful. Absolutely awful. Can you tell me the
[18:15] Absolutely awful. Can you tell me the intuition you have? I seem to just
[18:18] intuition you have? I seem to just stepping back and observing the
[18:20] stepping back and observing the different apps that we all rely on. I
[18:22] different apps that we all rely on. I don't know Adobe Photoshop, all this
[18:24] don't know Adobe Photoshop, all this kind of stuff. It seems to be the
[18:25] kind of stuff. It seems to be the progress on development there has not
[18:28] progress on development there has not accelerated. So why is it what lessons
[18:31] accelerated. So why is it what lessons can you draw from base camp like
[18:32] can you draw from base camp like wellestablished huge user base? Why
[18:36] wellestablished huge user base? Why aren't we seeing like super rapid
[18:39] aren't we seeing like super rapid increase in like new updates, features,
[18:41] increase in like new updates, features, all this kind of stuff in these
[18:42] all this kind of stuff in these wellestablished apps? multiple reasons.
[18:45] wellestablished apps? multiple reasons. I'll start with the first one that's the
[18:47] I'll start with the first one that's the most critical. As soon as you're having
[18:50] most critical. As soon as you're having human teams work together on something,
[18:53] human teams work together on something, the bottleneck is rarely implementation.
[18:56] the bottleneck is rarely implementation. It's human bandwidth and communication.
[18:59] It's human bandwidth and communication. when you have a product manager and a
[19:01] when you have a product manager and a couple of designers and a VP above them
[19:05] couple of designers and a VP above them and a CTO above them and everyone wants
[19:09] and a CTO above them and everyone wants to be part of the shaping process
[19:11] to be part of the shaping process because we're all justifying why we're
[19:13] because we're all justifying why we're here.
[19:15] here. That's where all the productivity goes
[19:17] That's where all the productivity goes to die.
[19:19] to die. The revelation I've had working on
[19:23] The revelation I've had working on Amachi the last three months is that to
[19:27] Amachi the last three months is that to get that magical 10x 100x
[19:32] get that magical 10x 100x in a few rare cases a,000x productivity
[19:36] in a few rare cases a,000x productivity boost you have to interact with the
[19:39] boost you have to interact with the agents directly and you cannot
[19:42] agents directly and you cannot intermediate that bandwidth with another
[19:46] intermediate that bandwidth with another human because it's simply too slow. And
[19:50] human because it's simply too slow. And on the one hand, that's a bit of a
[19:52] on the one hand, that's a bit of a bummer. I mean, I like humans and it's
[19:54] bummer. I mean, I like humans and it's great to work together, but it also
[19:56] great to work together, but it also means we need to temper our expectations
[19:58] means we need to temper our expectations with what these agents can do. If it's
[20:01] with what these agents can do. If it's humans driving it and you have three
[20:03] humans driving it and you have three layers of approval and all the other
[20:06] layers of approval and all the other machinery of a large corporation,
[20:09] machinery of a large corporation, the implementation part is only a small
[20:13] the implementation part is only a small segment of it. The other thing I'd say
[20:16] segment of it. The other thing I'd say is that
[20:18] is that most organizations don't know what they
[20:21] most organizations don't know what they want. They don't know how to make it
[20:23] want. They don't know how to make it better. They're not bottlenecked on
[20:27] better. They're not bottlenecked on implementation. They're bottlenecked on
[20:28] implementation. They're bottlenecked on ideas. They're bottlenecked on vision.
[20:31] ideas. They're bottlenecked on vision. They're bottlenecked on taste. And if
[20:34] They're bottlenecked on taste. And if you don't have those element in excess
[20:37] you don't have those element in excess of your implementational
[20:39] of your implementational capacity, it doesn't help. So you can
[20:42] capacity, it doesn't help. So you can make a lot of shitty ideas come true.
[20:44] make a lot of shitty ideas come true. Then what are you going to ship that?
[20:46] Then what are you going to ship that? That sounds like I don't know something
[20:49] That sounds like I don't know something coming out of Microsoft. That's not what
[20:50] coming out of Microsoft. That's not what we're trying to replicate here. That
[20:52] we're trying to replicate here. That process is not actually because we
[20:54] process is not actually because we already had this. If you step back for a
[20:57] already had this. If you step back for a moment and think of the towering
[21:00] moment and think of the towering organizations we we have who have had
[21:02] organizations we we have who have had tens of thousands of programmers at
[21:05] tens of thousands of programmers at their disposal.
[21:06] their disposal. I mean, I'm picking on Microsoft here. I
[21:08] I mean, I'm picking on Microsoft here. I love Microsoft some of the time, but
[21:10] love Microsoft some of the time, but I'll pick on them in this case because
[21:12] I'll pick on them in this case because they have had endless resources, endless
[21:15] they have had endless resources, endless programming capacity for decades. Right?
[21:19] programming capacity for decades. Right? This is what's
[21:21] This is what's showing us that just being able to write
[21:23] showing us that just being able to write a lot of code does not produce great
[21:25] a lot of code does not produce great compelling software now. The other thing
[21:28] compelling software now. The other thing is we've had this capacity for about 6
[21:31] is we've had this capacity for about 6 months.
[21:33] months. That's not very long in human
[21:37] That's not very long in human life cycle capacity of internalizing
[21:40] life cycle capacity of internalizing what's going on. And I think it's
[21:42] what's going on. And I think it's actually funny that the critique of AI
[21:44] actually funny that the critique of AI is why isn't it going faster?
[21:47] is why isn't it going faster? >> Mhm.
[21:47] >> Mhm. >> What are you talking about? We've not
[21:49] >> What are you talking about? We've not had any other form of progress that has
[21:51] had any other form of progress that has moved as fast as AI. And you're
[21:53] moved as fast as AI. And you're impatient because in the last 3 months
[21:55] impatient because in the last 3 months we haven't rewritten the whole world and
[21:56] we haven't rewritten the whole world and made it a utopia of software goodness.
[21:59] made it a utopia of software goodness. >> You're basically saying everybody should
[22:00] >> You're basically saying everybody should be switching to Linux. Now, one of the
[22:02] be switching to Linux. Now, one of the arguments is like we can rewrite all the
[22:04] arguments is like we can rewrite all the software that's not available in Linux
[22:06] software that's not available in Linux and Linux. Linux has been the love of my
[22:08] and Linux. Linux has been the love of my life for many years, but one of the
[22:10] life for many years, but one of the reasons I'm still attached to Windows
[22:11] reasons I'm still attached to Windows and now uh Mac is uh because of video
[22:15] and now uh Mac is uh because of video editing, Premiere.
[22:16] editing, Premiere. >> We're going to fix that. But
[22:17] >> We're going to fix that. But >> so the question is who's going to build
[22:20] >> so the question is who's going to build Premiere and Photoshop for Linux? And it
[22:24] Premiere and Photoshop for Linux? And it feels like one person can now.
[22:27] feels like one person can now. >> 100% one person can. And so, and I'm I'm
[22:30] >> 100% one person can. And so, and I'm I'm allowed to be impatient. In fact, me or
[22:33] allowed to be impatient. In fact, me or anyone else,
[22:35] anyone else, >> impatience is the first step of doing it
[22:39] >> impatience is the first step of doing it yourself, right? Like,
[22:40] yourself, right? Like, >> correct. And there's a community of tens
[22:42] >> correct. And there's a community of tens of thousands of people that use Adobe
[22:44] of thousands of people that use Adobe Premiere or Da Vinci, all these
[22:46] Premiere or Da Vinci, all these nonlinear video editors
[22:48] nonlinear video editors >> that know the frustrations. Everybody
[22:50] >> that know the frustrations. Everybody shares them. You can look at Reddit, you
[22:52] shares them. You can look at Reddit, you can look at the forums, everybody knows
[22:54] can look at the forums, everybody knows it. Uh, I don't know what it is. It may
[22:56] it. Uh, I don't know what it is. It may be the management, it may be the
[22:57] be the management, it may be the meetings, all the things you've always
[22:59] meetings, all the things you've always discussed is the the the bureaucracy
[23:02] discussed is the the the bureaucracy that's in inside companies that's
[23:04] that's in inside companies that's slowing everything down, the development
[23:05] slowing everything down, the development of features. But it feels like they're
[23:09] of features. But it feels like they're if you just let some of the developers
[23:10] if you just let some of the developers loose with a bunch of agents, you can
[23:13] loose with a bunch of agents, you can fix all that. But again, based on
[23:15] fix all that. But again, based on everything you're saying, maybe the way
[23:17] everything you're saying, maybe the way to do that is to start over from
[23:20] to do that is to start over from scratch, maybe through open source or
[23:23] scratch, maybe through open source or somebody launches a new company that
[23:25] somebody launches a new company that within large companies now, it's hard to
[23:29] within large companies now, it's hard to to really accelerate into the agentic
[23:31] to really accelerate into the agentic era by letting developers just build.
[23:33] era by letting developers just build. This is the classic innovators dilemma.
[23:36] This is the classic innovators dilemma. These companies have gotten so good, so
[23:40] These companies have gotten so good, so established at the old way and therefore
[23:43] established at the old way and therefore their entire structure, management
[23:46] their entire structure, management layers, processes are tuned for a time
[23:50] layers, processes are tuned for a time that no longer exists. But you can't
[23:54] that no longer exists. But you can't pivot that. These are super tankers. It
[23:57] pivot that. These are super tankers. It just doesn't happen. This is why
[24:01] just doesn't happen. This is why we're finally getting this upset in the
[24:03] we're finally getting this upset in the technology industry. For a while, I was
[24:06] technology industry. For a while, I was very upset about the duopoly between
[24:10] very upset about the duopoly between Apple and Google on mobile because it
[24:11] Apple and Google on mobile because it felt like mobile was the most important
[24:13] felt like mobile was the most important computing platform that we had. And I
[24:16] computing platform that we had. And I could not see a path to unseat either
[24:20] could not see a path to unseat either Google or Apple sitting on top of that,
[24:22] Google or Apple sitting on top of that, controlling everything, taking their
[24:24] controlling everything, taking their toll booth money.
[24:26] toll booth money. But the game has changed. This is no
[24:29] But the game has changed. This is no longer the most important platform.
[24:32] longer the most important platform. Mobile phones are important, but there's
[24:34] Mobile phones are important, but there's also a lot of other form factors coming,
[24:36] also a lot of other form factors coming, whether it's glasses or it's earpieces
[24:39] whether it's glasses or it's earpieces or whatever else have you. It's all in
[24:42] or whatever else have you. It's all in play now, but the computing platforms
[24:44] play now, but the computing platforms themselves are in play for the first
[24:47] themselves are in play for the first time in probably 40 years. If you look
[24:51] time in probably 40 years. If you look at the desktop, Linux has been around
[24:53] at the desktop, Linux has been around since 91. It's not taken off or taken
[24:57] since 91. It's not taken off or taken over on the desktop. It's taken over
[24:59] over on the desktop. It's taken over everything else. All the devices you
[25:01] everything else. All the devices you have on your desk, your fridge, your
[25:03] have on your desk, your fridge, your toaster, everything runs Linux except
[25:07] toaster, everything runs Linux except for your computer. Now, funnily enough,
[25:09] for your computer. Now, funnily enough, your Android is actually Linux, but
[25:13] your Android is actually Linux, but wrapped so sufficiently that you can't
[25:15] wrapped so sufficiently that you can't really recognize it, but now there's an
[25:18] really recognize it, but now there's an opening. And the opening is exactly as
[25:21] opening. And the opening is exactly as you say it. If there's a piece of
[25:23] you say it. If there's a piece of software you depended on that bound you
[25:25] software you depended on that bound you to Windows, it is
[25:28] to Windows, it is completely within reach for you
[25:31] completely within reach for you personally to start rewriting it. And
[25:34] personally to start rewriting it. And maybe you won't get to 100% coverage,
[25:35] maybe you won't get to 100% coverage, but this is the old joke about Microsoft
[25:38] but this is the old joke about Microsoft Office. I only use 5%. Yeah, well, we
[25:41] Office. I only use 5%. Yeah, well, we all use a different 5%. Well, what if we
[25:43] all use a different 5%. Well, what if we all just built our own 5%.
[25:46] all just built our own 5%. >> What if I just took the functionality
[25:48] >> What if I just took the functionality that I need and just did that? That is a
[25:52] that I need and just did that? That is a completely different challenge and one
[25:54] completely different challenge and one agents are incredibly capable of doing
[25:57] agents are incredibly capable of doing right now today and I've done it a lot
[25:59] right now today and I've done it a lot of times over. So one of the amazing
[26:02] of times over. So one of the amazing things I found with the latest agent
[26:04] things I found with the latest agent gauge is I have become a polygot
[26:07] gauge is I have become a polygot programmer
[26:09] programmer something I was absolutely not before. I
[26:12] something I was absolutely not before. I was a Ruby programmer first and foremost
[26:15] was a Ruby programmer first and foremost and then I dabbled a little bit in bash.
[26:17] and then I dabbled a little bit in bash. >> Yeah. when I had to and in the last two
[26:20] >> Yeah. when I had to and in the last two months I've written C++ I've written
[26:23] months I've written C++ I've written three applications that have shipped in
[26:26] three applications that have shipped in omachi quattro I wrote a
[26:29] omachi quattro I wrote a >> writing app I was using this app called
[26:31] >> writing app I was using this app called topora which is a very nice app which in
[26:33] topora which is a very nice app which in itself is based on another app called IA
[26:36] itself is based on another app called IA writer which was my real love on the Mac
[26:39] writer which was my real love on the Mac for a clean simple markdown writing
[26:43] for a clean simple markdown writing environment that's where I write all my
[26:44] environment that's where I write all my essays
[26:45] essays >> and then I moved to Linux and I couldn't
[26:47] >> and then I moved to Linux and I couldn't at AI writer. So I moved over to this
[26:50] at AI writer. So I moved over to this other tool called Tapora. It was a piece
[26:52] other tool called Tapora. It was a piece of shareware and it had a lot of
[26:53] of shareware and it had a lot of features I just didn't need.
[26:56] features I just didn't need. And about
[26:58] And about six weeks, seven weeks ago, I thought,
[27:00] six weeks, seven weeks ago, I thought, do you know what? I only need 5% of
[27:02] do you know what? I only need 5% of Tapora, which is already a basic app. I
[27:04] Tapora, which is already a basic app. I literally told the agent to get going
[27:07] literally told the agent to get going that I wanted it written in C++ and
[27:09] that I wanted it written in C++ and cutie because that would fit well with
[27:11] cutie because that would fit well with the aesthetic of what I was building
[27:13] the aesthetic of what I was building with Quattro.
[27:15] with Quattro. And in I think about 20 minutes it had
[27:17] And in I think about 20 minutes it had the first version I started using and it
[27:19] the first version I started using and it wasn't quite right. Within 2 days I'd
[27:22] wasn't quite right. Within 2 days I'd given up Tupor and I wrote and have
[27:26] given up Tupor and I wrote and have written all of my essays since that
[27:28] written all of my essays since that moment in Amarite.
[27:30] moment in Amarite. >> Can I ask for your advice and your
[27:32] >> Can I ask for your advice and your vision about something? So what I find
[27:34] vision about something? So what I find with with agents you can actually write
[27:37] with with agents you can actually write something like a replacement for Tapora
[27:39] something like a replacement for Tapora that is perfectly customized to you to
[27:42] that is perfectly customized to you to your needs.
[27:43] your needs. >> Correct.
[27:44] >> Correct. with just one user in mind and then
[27:47] with just one user in mind and then there's a version of that that is starts
[27:50] there's a version of that that is starts with one user in mind but expands to a
[27:52] with one user in mind but expands to a larger audience. So I've actually
[27:54] larger audience. So I've actually written a large number of software just
[27:56] written a large number of software just for me and I find it easier to do and
[27:59] for me and I find it easier to do and better to get my situation done. For
[28:02] better to get my situation done. For example, I have a video editor I've
[28:04] example, I have a video editor I've written which is very easy to do just
[28:06] written which is very easy to do just for me.
[28:06] for me. >> Yes. I've never uh unlike you built
[28:09] >> Yes. I've never uh unlike you built something that's used by a large number
[28:11] something that's used by a large number of people and I find that a bit scary
[28:13] of people and I find that a bit scary and intimidating. So like at this with
[28:16] and intimidating. So like at this with this agentic age, how do you take a step
[28:19] this agentic age, how do you take a step to actually build something that solves
[28:21] to actually build something that solves your problem which I think is a
[28:23] your problem which I think is a beautiful way to build but also expand
[28:26] beautiful way to build but also expand it to actually useful for other people?
[28:28] it to actually useful for other people? Like is there advice you can give and do
[28:31] Like is there advice you can give and do you also see the problem of how easy it
[28:33] you also see the problem of how easy it is to just build a tool for yourself?
[28:35] is to just build a tool for yourself? Yes, but it is simpler than you think.
[28:38] Yes, but it is simpler than you think. By the time you're done building the
[28:40] By the time you're done building the tool for yourself, you simply tell your
[28:42] tool for yourself, you simply tell your agent to put it on GitHub.
[28:44] agent to put it on GitHub. >> Yeah,
[28:44] >> Yeah, >> you don't even have to do anything else.
[28:46] >> you don't even have to do anything else. It will figure out how to put that repo
[28:48] It will figure out how to put that repo on GitHub. It'll write a nice readme.
[28:50] on GitHub. It'll write a nice readme. It'll start using GitHub releases that
[28:52] It'll start using GitHub releases that you can track things. It'll actually be
[28:54] you can track things. It'll actually be a better software maintainer than you
[28:56] a better software maintainer than you could ever be because it is far more
[28:58] could ever be because it is far more patient. It is far more diligent in
[29:01] patient. It is far more diligent in doing the drudgery of managing open
[29:04] doing the drudgery of managing open source software than you are
[29:06] source software than you are >> and you can simply get on with the joy
[29:10] >> and you can simply get on with the joy of using the software that you built and
[29:12] of using the software that you built and evolving it as you see fit. Now this
[29:14] evolving it as you see fit. Now this gets into the big argument we've been
[29:17] gets into the big argument we've been having in open source for a while. Is AI
[29:20] having in open source for a while. Is AI contributions good or bad for the
[29:22] contributions good or bad for the maintainer? There's a lot of maintainers
[29:25] maintainer? There's a lot of maintainers right now who are quite upset about the
[29:28] right now who are quite upset about the fact that they're suddenly getting a
[29:31] fact that they're suddenly getting a huge influx of pull request of
[29:34] huge influx of pull request of contributions from people who may not be
[29:38] contributions from people who may not be the best programmers or programmers at
[29:40] the best programmers or programmers at all
[29:41] all >> towards their software.
[29:44] >> towards their software. I look at that argument and go are you
[29:46] I look at that argument and go are you kidding me? Here is a vein of free
[29:53] kidding me? Here is a vein of free contributions that you can take or don't
[29:56] contributions that you can take or don't take, but you're complaining about the
[29:59] take, but you're complaining about the fact that they're there. It sounds
[30:01] fact that they're there. It sounds straight out of my steak is too juicy
[30:04] straight out of my steak is too juicy and my lobster too buttery. What are you
[30:06] and my lobster too buttery. What are you complaining about? This is the most
[30:08] complaining about? This is the most amazing thing. This is what we
[30:10] amazing thing. This is what we >> proclamated for so long was going to be
[30:13] >> proclamated for so long was going to be the magic of open source that we could
[30:15] the magic of open source that we could all contribute to it. But it of course
[30:17] all contribute to it. But it of course never true. There was only a small
[30:19] never true. There was only a small subset of people who contributed to open
[30:21] subset of people who contributed to open source and that was the very highly
[30:23] source and that was the very highly skilled wizards. So this is a bit of a
[30:25] skilled wizards. So this is a bit of a reformation moment. We had this
[30:27] reformation moment. We had this disintermediation between us and the
[30:29] disintermediation between us and the computer and it was this class of
[30:32] computer and it was this class of clerics and priests called programmers.
[30:35] clerics and priests called programmers. And suddenly they're being
[30:36] And suddenly they're being disintermediated here by um was it the
[30:40] disintermediated here by um was it the 95 thesis by Luther in in 1500s nailing
[30:44] 95 thesis by Luther in in 1500s nailing them to the door. And one of those was
[30:46] them to the door. And one of those was very clearly about the intermediation
[30:48] very clearly about the intermediation that you should have direct access to
[30:50] that you should have direct access to the higher intelligence.
[30:52] the higher intelligence. >> But don't you need the wizards to keep a
[30:54] >> But don't you need the wizards to keep a high bar of excellence in the codebase?
[30:56] high bar of excellence in the codebase? >> 100% you do. Which is also something
[30:59] >> 100% you do. Which is also something that's always been true about open
[31:00] that's always been true about open source, which is the second argument
[31:02] source, which is the second argument that really grinds me. I've been running
[31:04] that really grinds me. I've been running open source projects for 25 years. I
[31:07] open source projects for 25 years. I have literally looked at the output of
[31:09] have literally looked at the output of thousands, if not tens of thousands of
[31:12] thousands, if not tens of thousands of programmers. I feel like I have the
[31:14] programmers. I feel like I have the statistical basis to assert that most
[31:17] statistical basis to assert that most programmers.
[31:20] programmers. They suck.
[31:22] They suck. And I don't mean that in the way it
[31:24] And I don't mean that in the way it sounds. That was why I paused for a hot
[31:26] sounds. That was why I paused for a hot second here. I mean they suck in the
[31:28] second here. I mean they suck in the sense that they don't write the code I
[31:30] sense that they don't write the code I want to have written. They don't prepare
[31:33] want to have written. They don't prepare their bug reports with all the relevant
[31:35] their bug reports with all the relevant information. They don't detail their
[31:38] information. They don't detail their pull requests with the why. They don't
[31:41] pull requests with the why. They don't bother to fill in needed code comments.
[31:44] bother to fill in needed code comments. They don't double check their work. They
[31:46] They don't double check their work. They don't write unit tests. They don't do
[31:48] don't write unit tests. They don't do all of these things it takes to create
[31:50] all of these things it takes to create good software. But do you know who will
[31:53] good software. But do you know who will do all that stuff? Agents if you tell
[31:55] do all that stuff? Agents if you tell them to. They're very diligent at
[31:57] them to. They're very diligent at following your instructions most of the
[31:59] following your instructions most of the time, sometimes to a fault. But it
[32:01] time, sometimes to a fault. But it actually means that if you take the
[32:03] actually means that if you take the median programmer and their pull
[32:06] median programmer and their pull requests towards an average open source
[32:08] requests towards an average open source project, they're already getting
[32:10] project, they're already getting outclassed by agents. I would rather get
[32:14] outclassed by agents. I would rather get an agent written pull request to one of
[32:16] an agent written pull request to one of my projects than I'd get one written by
[32:19] my projects than I'd get one written by a human. And it's not just because the
[32:21] a human. And it's not just because the quality is better. It's also because I
[32:25] quality is better. It's also because I feel a lot less bad if I just reject it.
[32:28] feel a lot less bad if I just reject it. You didn't even write it. So I could
[32:30] You didn't even write it. So I could simply look at what your agent wrote on
[32:31] simply look at what your agent wrote on your behalf and go eh don't want it.
[32:36] your behalf and go eh don't want it. That's always been true in open source.
[32:38] That's always been true in open source. And in fact I think this is one of the
[32:39] And in fact I think this is one of the problems with open source maintainers.
[32:42] problems with open source maintainers. They have way too much ball love
[32:46] They have way too much ball love neuroticism and anxiety that requires
[32:49] neuroticism and anxiety that requires them to look upon any contribution as an
[32:54] them to look upon any contribution as an obligation on their part to do
[32:56] obligation on their part to do everything to get that to land in the
[32:59] everything to get that to land in the codebase. That's not true at all. You
[33:01] codebase. That's not true at all. You can simply say no or even better you can
[33:04] can simply say no or even better you can say no thank you. And if you get into
[33:07] say no thank you. And if you get into the mode of realizing that your project
[33:10] the mode of realizing that your project is allowed to exist and evolve according
[33:14] is allowed to exist and evolve according to your vision, according to your road
[33:16] to your vision, according to your road map, it becomes so much easier in the
[33:18] map, it becomes so much easier in the agentic age to decline the contributions
[33:21] agentic age to decline the contributions you don't want because you don't even
[33:24] you don't want because you don't even inconvenience or hurt the feelings of a
[33:26] inconvenience or hurt the feelings of a human. It's just a clanker. And the
[33:29] human. It's just a clanker. And the clanker won't mind. In fact, the
[33:31] clanker won't mind. In fact, the producers of Clinkers, the labs love
[33:35] producers of Clinkers, the labs love when you spend tokens in vain. They get
[33:38] when you spend tokens in vain. They get paid just the same. So, in my opinion,
[33:41] paid just the same. So, in my opinion, this is the absolute best time to ever
[33:44] this is the absolute best time to ever have been an open-source software
[33:46] have been an open-source software maintainer. Not only do we get this
[33:50] maintainer. Not only do we get this wealth of glorious pull requests made by
[33:54] wealth of glorious pull requests made by agents with all the boxes ticked, we
[33:56] agents with all the boxes ticked, we also get to tap into a creativity of
[33:59] also get to tap into a creativity of people who did not have access to
[34:01] people who did not have access to contribute to a project before.
[34:03] contribute to a project before. >> I've been running the Zomachi project
[34:04] >> I've been running the Zomachi project now for a little over a year and in the
[34:08] now for a little over a year and in the last three months working on Quattro, I
[34:10] last three months working on Quattro, I have merged over a thousand pull
[34:11] have merged over a thousand pull requests. Quite a lot of those pull
[34:14] requests. Quite a lot of those pull requests were written by people who were
[34:16] requests were written by people who were not classical programmers or were
[34:19] not classical programmers or were programmers in other domains, not Linux
[34:22] programmers in other domains, not Linux operating system or distribution
[34:25] operating system or distribution development. They were able to
[34:26] development. They were able to contribute their good ideas because of
[34:28] contribute their good ideas because of agents and I got to cherrypick the very
[34:31] agents and I got to cherrypick the very best of that.
[34:32] best of that. >> Mhm.
[34:33] >> Mhm. >> Because it was there. Otherwise, those
[34:36] >> Because it was there. Otherwise, those ideas would just have lived inside their
[34:39] ideas would just have lived inside their heads. again is that's not the purpose
[34:41] heads. again is that's not the purpose of open source that we tap into the
[34:43] of open source that we tap into the collective intelligence and creativity
[34:46] collective intelligence and creativity of the whole goddamn planet and we
[34:48] of the whole goddamn planet and we channel that towards a comments where we
[34:52] channel that towards a comments where we all benefit from the combined efforts of
[34:55] all benefit from the combined efforts of everyone.
[34:56] everyone. >> Now there's currently I think about 400
[34:59] >> Now there's currently I think about 400 unmerged pull requests on Amachi about
[35:02] unmerged pull requests on Amachi about double what it was a week ago. So the
[35:04] double what it was a week ago. So the acceleration is real but so are the
[35:07] acceleration is real but so are the tools. I'm not reviewing every pull
[35:10] tools. I'm not reviewing every pull request anymore. I haven't been
[35:11] request anymore. I haven't been reviewing them for quite some time now.
[35:13] reviewing them for quite some time now. I have the agents review them for me
[35:17] I have the agents review them for me >> and then they will give me a summary
[35:19] >> and then they will give me a summary about whether something is ready for the
[35:21] about whether something is ready for the decision, the human decision. Should we
[35:23] decision, the human decision. Should we merge or should we not merge?
[35:25] merge or should we not merge? >> I don't need to look at all the pull
[35:27] >> I don't need to look at all the pull requests that are either wrong,
[35:29] requests that are either wrong, duplicated,
[35:31] duplicated, bad. An agent can sort that chaff away
[35:34] bad. An agent can sort that chaff away from me. I just get to look at the
[35:35] from me. I just get to look at the pearls, the good ideas that are ready to
[35:38] pearls, the good ideas that are ready to go, the bug fixes that the agent has
[35:41] go, the bug fixes that the agent has validated in a VM on my behalf. All the
[35:45] validated in a VM on my behalf. All the drudgery of replicating and managing
[35:47] drudgery of replicating and managing open source projects is evaporating at
[35:50] open source projects is evaporating at lightning speed and we are left with the
[35:55] lightning speed and we are left with the with the golden juicy parts, the bone
[35:58] with the golden juicy parts, the bone marrow of software development deciding
[36:01] marrow of software development deciding what should this thing do and where
[36:03] what should this thing do and where should it go. Do you think the good
[36:04] should it go. Do you think the good ideas ultimately the kernel of the good
[36:06] ideas ultimately the kernel of the good ideas are originated in the human mind?
[36:08] ideas are originated in the human mind? So the individual contributors
[36:11] So the individual contributors like can it be done by agents or is the
[36:14] like can it be done by agents or is the PR
[36:16] PR ultimately requires a human idea like
[36:19] ultimately requires a human idea like how to improve Aachi all those incoming
[36:22] how to improve Aachi all those incoming or can it all just be a pool of agents?
[36:25] or can it all just be a pool of agents? That was the mode and the way I was
[36:28] That was the mode and the way I was thinking about agents in the first
[36:30] thinking about agents in the first agentic age from November 24 to February
[36:35] agentic age from November 24 to February 28th.
[36:36] 28th. >> Mhm.
[36:36] >> Mhm. >> I thought all the ideas would originate
[36:38] >> I thought all the ideas would originate with the humans. They would tell their
[36:40] with the humans. They would tell their agents what to build and off they went.
[36:43] agents what to build and off they went. >> Mhm.
[36:43] >> Mhm. >> I don't think that's true anymore at
[36:45] >> I don't think that's true anymore at all. I have seen things you people
[36:47] all. I have seen things you people wouldn't believe. ideas coming out of
[36:50] wouldn't believe. ideas coming out of models so great that it makes me humble
[36:55] models so great that it makes me humble as a person who otherwise prides
[36:57] as a person who otherwise prides themselves on having good ideas. The
[37:00] themselves on having good ideas. The agents are incredibly capable of
[37:03] agents are incredibly capable of creative thought and folks who are still
[37:06] creative thought and folks who are still stuck in the analysis that agents are
[37:11] stuck in the analysis that agents are parrots
[37:12] parrots >> just regurgitating the ideas that are
[37:15] >> just regurgitating the ideas that are already there are delusional about the
[37:18] already there are delusional about the progress that's been made in the last 6
[37:20] progress that's been made in the last 6 to9 months. So some people listening to
[37:22] to9 months. So some people listening to you right now will say DHH is suffering
[37:24] you right now will say DHH is suffering from the old case of uh AI psychosis.
[37:28] from the old case of uh AI psychosis. Yeah. Can you steal man the case uh that
[37:31] Yeah. Can you steal man the case uh that you are in fact experiencing uh in a
[37:34] you are in fact experiencing uh in a state of delusion like one flew over the
[37:35] state of delusion like one flew over the cuckoo's nest and can you argue against
[37:37] cuckoo's nest and can you argue against it?
[37:37] it? >> I'm in a state of delirium. That's what
[37:40] >> I'm in a state of delirium. That's what the state I'm in because I have been
[37:43] the state I'm in because I have been working with computers for 40 years
[37:47] working with computers for 40 years and I've never seen the things that I've
[37:50] and I've never seen the things that I've seen in just the last two months.
[37:54] seen in just the last two months. >> Yeah. a whole career, a whole life
[37:57] >> Yeah. a whole career, a whole life dedicating to the love of computers as
[38:00] dedicating to the love of computers as my main
[38:02] my main focus for the working hours and then
[38:05] focus for the working hours and then some. Suddenly completely upended,
[38:08] some. Suddenly completely upended, suddenly completely rewritten. Of
[38:10] suddenly completely rewritten. Of course, I'm delirious.
[38:12] course, I'm delirious. Who looking at this reality is not if
[38:15] Who looking at this reality is not if you are not delirious or at the very
[38:18] you are not delirious or at the very least very excited. Actually, I guess
[38:21] least very excited. Actually, I guess that's not even true. If you're not
[38:22] that's not even true. If you're not recognizing the
[38:24] recognizing the gravity of the moment, that's the
[38:27] gravity of the moment, that's the delusion. That's the psychosis. The
[38:29] delusion. That's the psychosis. The psychosis is believing that the world is
[38:31] psychosis is believing that the world is barely different. We just have some
[38:34] barely different. We just have some electronic parrots reciting things to
[38:37] electronic parrots reciting things to us. Now, in my opinion, the reason this
[38:40] us. Now, in my opinion, the reason this argument is actually brought up is
[38:42] argument is actually brought up is because people are not able to see the
[38:44] because people are not able to see the fruits of the progress. That's goes to
[38:47] fruits of the progress. That's goes to your point earlier. Where is the amazing
[38:49] your point earlier. Where is the amazing software? Why isn't
[38:52] software? Why isn't American GDP running at 12%
[38:54] American GDP running at 12% year-over-year?
[38:55] year-over-year? First of all, give it a minute. It
[38:58] First of all, give it a minute. It hasn't even been a year. God damn it.
[39:01] hasn't even been a year. God damn it. But second of all, I feel on my own
[39:03] But second of all, I feel on my own account,
[39:05] account, I have actually brought the pudding.
[39:08] I have actually brought the pudding. >> Um Quattro launched on Friday. It's been
[39:12] >> Um Quattro launched on Friday. It's been downloaded by tens of thousands of
[39:14] downloaded by tens of thousands of people
[39:15] people >> and they like it. They like it a lot. We
[39:17] >> and they like it. They like it a lot. We should mention that going to perplexity
[39:19] should mention that going to perplexity here, Amachi is a highly opinionated
[39:22] here, Amachi is a highly opinionated Arch Linux- based desktop distribution
[39:24] Arch Linux- based desktop distribution centered on the Hyperland Whan tiling
[39:26] centered on the Hyperland Whan tiling compositor. It was created by David
[39:28] compositor. It was created by David Hynamire Hansen, DHH, as a polished
[39:32] Hynamire Hansen, DHH, as a polished developer workstation set up with a
[39:35] developer workstation set up with a cohesive visual style and many everyday
[39:38] cohesive visual style and many everyday tools already configured.
[39:40] tools already configured. >> Let me put it, Umachi is a beautiful,
[39:43] >> Let me put it, Umachi is a beautiful, modern, and opinionated Linux system.
[39:45] modern, and opinionated Linux system. It's an alternative operating system to
[39:48] It's an alternative operating system to Mac OS and Windows and it's freaking
[39:50] Mac OS and Windows and it's freaking amazing.
[39:51] amazing. >> And the Quattro thing is uh you're
[39:53] >> And the Quattro thing is uh you're pushing towards the age of agents.
[39:55] pushing towards the age of agents. >> That's right. That's the latest version
[39:56] >> That's right. That's the latest version that we just dropped out, which is also
[39:58] that we just dropped out, which is also funny. The Umachi project is only a year
[40:01] funny. The Umachi project is only a year old and a little bit. I started it last
[40:04] old and a little bit. I started it last summer in between sessions at the 24
[40:07] summer in between sessions at the 24 hours of LA.
[40:08] hours of LA. >> Yep. where I had watched uh one too many
[40:11] >> Yep. where I had watched uh one too many YouTube videos on Linux rising and got
[40:14] YouTube videos on Linux rising and got bitten by that bug. Started working on
[40:16] bitten by that bug. Started working on this
[40:18] this second iteration of my attempt at
[40:20] second iteration of my attempt at creating a better Linux operating
[40:22] creating a better Linux operating system. The first iteration we talked
[40:24] system. The first iteration we talked about last time was called Amakoup was
[40:25] about last time was called Amakoup was built on top of an existing system
[40:27] built on top of an existing system called Ubuntu and it was fine. But the
[40:31] called Ubuntu and it was fine. But the ambition I was able to pour into the new
[40:34] ambition I was able to pour into the new version um because I started seven
[40:36] version um because I started seven layers deeper down the stack was
[40:38] layers deeper down the stack was completely different. But it was still
[40:40] completely different. But it was still done in a pre-agentic world. I wrote all
[40:43] done in a pre-agentic world. I wrote all those bass scripts by hand in the
[40:46] those bass scripts by hand in the beginning and then I got to see the
[40:49] beginning and then I got to see the midway point where things changed over.
[40:52] midway point where things changed over. >> I did a couple of versions of Omachi
[40:54] >> I did a couple of versions of Omachi that had partial agent acceleration and
[40:57] that had partial agent acceleration and then three months ago
[40:59] then three months ago >> it was full throttle 100% everything is
[41:02] >> it was full throttle 100% everything is written by agents but steered by me.
[41:04] written by agents but steered by me. Mhm.
[41:05] Mhm. >> And that just ended up being a very
[41:08] >> And that just ended up being a very different experience and a very
[41:10] different experience and a very different operating system because I was
[41:13] different operating system because I was suddenly granted a limitless ceiling on
[41:16] suddenly granted a limitless ceiling on my ambition.
[41:17] my ambition. >> Mh.
[41:18] >> Mh. >> I could look at any feature in Windows,
[41:21] >> I could look at any feature in Windows, on Mac, on other Linux systems and say,
[41:25] on Mac, on other Linux systems and say, I want that
[41:28] I want that and the agents would deliver. So
[41:30] and the agents would deliver. So everything I wanted was suddenly within
[41:32] everything I wanted was suddenly within reach, which meant that
[41:34] reach, which meant that I got a little delirious.
[41:36] I got a little delirious. >> Mhm.
[41:36] >> Mhm. >> Who would not get delirious if suddenly
[41:38] >> Who would not get delirious if suddenly a genie pops out of the bottle and says,
[41:41] a genie pops out of the bottle and says, "You can have whatever you want. Every
[41:43] "You can have whatever you want. Every feature you've ever dreamed of in an
[41:46] feature you've ever dreamed of in an operating system, I can deliver them to
[41:48] operating system, I can deliver them to you. Most of them in 5 minutes, a few in
[41:51] you. Most of them in 5 minutes, a few in 20. And if we really go hog wild, it's
[41:53] 20. And if we really go hog wild, it's going to take me two hours."
[41:55] going to take me two hours." >> Have you seen uh Recu for a Dream, the
[41:57] >> Have you seen uh Recu for a Dream, the movie? So that there's a drug-like
[41:59] movie? So that there's a drug-like effect here. Yes.
[42:01] effect here. Yes. >> I I find it personally we'll talk about
[42:02] >> I I find it personally we'll talk about many levels of this but it it is
[42:05] many levels of this but it it is overwhelming
[42:07] overwhelming how much power is placed in our hands uh
[42:11] how much power is placed in our hands uh so suddenly and it's very hard to know.
[42:13] so suddenly and it's very hard to know. It's like with the hobbit or something
[42:15] It's like with the hobbit or something what to do with it. And I find myself
[42:18] what to do with it. And I find myself truly overwhelmed with the multitasking
[42:20] truly overwhelmed with the multitasking uh on the verge of almost burnt out.
[42:24] uh on the verge of almost burnt out. uh super excited about so many things
[42:27] uh super excited about so many things but uh ultimately looking back you want
[42:29] but uh ultimately looking back you want to focus on one thing and really ship
[42:32] to focus on one thing and really ship >> I don't have that sense I don't have the
[42:34] >> I don't have that sense I don't have the sense of overwhelm I don't have the
[42:36] sense of overwhelm I don't have the sense of dread I don't have the sense of
[42:39] sense of dread I don't have the sense of distortion because I have a mission
[42:42] distortion because I have a mission >> I'm going somewhere and therefore I can
[42:46] >> I'm going somewhere and therefore I can channel all this new power towards a
[42:49] channel all this new power towards a singular goal and outcome creating the
[42:52] singular goal and outcome creating the perfect computer And therefore all my
[42:56] perfect computer And therefore all my investigations with AI are focused
[42:59] investigations with AI are focused towards that end. Now I also have a day
[43:02] towards that end. Now I also have a day job
[43:02] job >> and we also use agents there and that's
[43:05] >> and we also use agents there and that's also targeted towards sort of specific
[43:06] also targeted towards sort of specific outcomes. But with the Yachi experience,
[43:09] outcomes. But with the Yachi experience, I got to
[43:12] I got to tab in
[43:14] tab in straight in the back of my head and
[43:18] straight in the back of my head and increase the bandwidth between ideas
[43:21] increase the bandwidth between ideas arriving in my brain and software
[43:23] arriving in my brain and software emerging on the screen. It was like
[43:26] emerging on the screen. It was like going from from dialup
[43:29] going from from dialup >> to fiber. I think on your podcast Elon
[43:33] >> to fiber. I think on your podcast Elon talked about the actual human bandwidth
[43:36] talked about the actual human bandwidth that Neurolink and other projects are
[43:39] that Neurolink and other projects are trying to accelerate. Like the bandwidth
[43:41] trying to accelerate. Like the bandwidth we're communicating over right now is
[43:43] we're communicating over right now is quite low because we're limited by our
[43:48] quite low because we're limited by our cognition. We're limited by the rate of
[43:50] cognition. We're limited by the rate of speech. You're not limited by those
[43:52] speech. You're not limited by those things when you're working with a swarm
[43:54] things when you're working with a swarm of agents. Now, let me caveat this by
[43:58] of agents. Now, let me caveat this by saying
[44:00] saying if id heard myself talk like this
[44:03] if id heard myself talk like this >> nine months ago, I would probably use
[44:06] >> nine months ago, I would probably use the label I AI psychosis. I think it
[44:09] the label I AI psychosis. I think it would be fitting because 9 months ago
[44:12] would be fitting because 9 months ago when people were talking like this, they
[44:14] when people were talking like this, they weren't shipping. And I think that's the
[44:16] weren't shipping. And I think that's the ultimate difference that there were
[44:18] ultimate difference that there were people who saw this early. I was not
[44:20] people who saw this early. I was not actually that early as we've talked
[44:22] actually that early as we've talked about. I was rather skeptical and I was
[44:24] about. I was rather skeptical and I was using AI in certain ways but I was not
[44:27] using AI in certain ways but I was not the first person who downloaded claude
[44:28] the first person who downloaded claude code. I think Boris released that in end
[44:30] code. I think Boris released that in end of February. I don't think I installed
[44:33] of February. I don't think I installed claude code until September. So there
[44:36] claude code until September. So there was about 6 months there where pioneers
[44:39] was about 6 months there where pioneers saw these glimmers of what the future
[44:42] saw these glimmers of what the future was going to look like. It wasn't there
[44:43] was going to look like. It wasn't there yet because the intelligence wasn't
[44:45] yet because the intelligence wasn't there. The harnesses weren't there but
[44:47] there. The harnesses weren't there but they could see the glimmers. I couldn't.
[44:48] they could see the glimmers. I couldn't. Toby Toby Luta the CEO of Shopify and
[44:52] Toby Toby Luta the CEO of Shopify and now my partner in crime on this uh
[44:54] now my partner in crime on this uh omachi project in part he's gotten
[44:57] omachi project in part he's gotten pilled with as well. He saw these things
[44:59] pilled with as well. He saw these things very early and he
[45:02] very early and he tried to tell me and I wasn't seeing it.
[45:06] tried to tell me and I wasn't seeing it. I was not seeing what he was seeing.
[45:08] I was not seeing what he was seeing. >> You were a hater.
[45:09] >> You were a hater. >> Yes. I was I was still on Earth.
[45:11] >> Yes. I was I was still on Earth. >> Okay.
[45:12] >> Okay. >> And he was he had already boarded the
[45:14] >> And he was he had already boarded the rocket and was heading towards space. I
[45:17] rocket and was heading towards space. I remember actually reading his memo to
[45:20] remember actually reading his memo to the company, the AI memo, and thinking
[45:23] the company, the AI memo, and thinking it seems a little much.
[45:25] it seems a little much. >> Like, you're making a big deal out of
[45:27] >> Like, you're making a big deal out of something that I cannot yet feel is a
[45:30] something that I cannot yet feel is a tangible thing
[45:32] tangible thing >> because where's the output of this? I
[45:34] >> because where's the output of this? I try using it. It writes code I don't
[45:36] try using it. It writes code I don't like. It wants to interrupt me all the
[45:38] like. It wants to interrupt me all the time. Where are you getting this from?
[45:41] time. Where are you getting this from? >> So, I get it. I totally get it. If
[45:44] >> So, I get it. I totally get it. If you've not seen what the current quality
[45:49] you've not seen what the current quality of intelligence can produce,
[45:51] of intelligence can produce, of course you're going to look at
[45:52] of course you're going to look at someone and go like they sound a little
[45:54] someone and go like they sound a little nutty. Because all your experience up
[45:56] nutty. Because all your experience up until this point would tell you that
[45:58] until this point would tell you that they are nutty. Because if you look at
[46:00] they are nutty. Because if you look at the history of computer programming for
[46:02] the history of computer programming for the last 40, 50 years, people have been
[46:05] the last 40, 50 years, people have been promising that regular people could
[46:08] promising that regular people could write code just by talking. We're going
[46:10] write code just by talking. We're going to have fourth generation languages.
[46:12] to have fourth generation languages. Lisp was once upon a time presented,
[46:15] Lisp was once upon a time presented, small talk was presented as these
[46:18] small talk was presented as these environments that would let regular
[46:19] environments that would let regular people write their own applications and
[46:22] people write their own applications and none of it came true in the sense beyond
[46:25] none of it came true in the sense beyond like Microsoft Access databases or Excel
[46:28] like Microsoft Access databases or Excel spreadsheets that those are enduser
[46:30] spreadsheets that those are enduser programming environments but it's
[46:32] programming environments but it's nothing like what we're able to do now.
[46:33] nothing like what we're able to do now. And then I mean I'm not even talking
[46:35] And then I mean I'm not even talking about end user. I'm talking as me
[46:37] about end user. I'm talking as me someone who's been programming for 25
[46:39] someone who's been programming for 25 years seeing the output and the
[46:42] years seeing the output and the acceleration and the quality and then
[46:44] acceleration and the quality and then shipping it. And I think that's what's
[46:46] shipping it. And I think that's what's going to change the entire conversation
[46:49] going to change the entire conversation quite quickly. The few lagards who are
[46:52] quite quickly. The few lagards who are still on the fence about whether this is
[46:54] still on the fence about whether this is actually useful, who are still trapped
[46:55] actually useful, who are still trapped in a meme from early 25 about mechanical
[46:59] in a meme from early 25 about mechanical parrots, they're simply going to be
[47:01] parrots, they're simply going to be overwhelmed by the evidence that's about
[47:04] overwhelmed by the evidence that's about to flood over them. So, I hope to see uh
[47:08] to flood over them. So, I hope to see uh projects like Hamachi,
[47:11] projects like Hamachi, several of them that like really show
[47:14] several of them that like really show agent first.
[47:15] agent first. >> It's coming. It's all of it is coming
[47:18] >> It's coming. It's all of it is coming >> in the spaces in the silly spaces that I
[47:20] >> in the spaces in the silly spaces that I already mentioned like video editing all
[47:22] already mentioned like video editing all these kinds of apps that were like like
[47:23] these kinds of apps that were like like Typora.
[47:24] Typora. >> Yes,
[47:24] >> Yes, >> this kind of stuff.
[47:26] >> this kind of stuff. >> It's going to come and I've already seen
[47:28] >> It's going to come and I've already seen the early inklings of this. One of the
[47:32] the early inklings of this. One of the really neat features about Amachi is
[47:35] really neat features about Amachi is that it has a far more robust plug-in
[47:38] that it has a far more robust plug-in system that allows you to extend your
[47:40] system that allows you to extend your operating system and rewrite it really
[47:43] operating system and rewrite it really in terms of its user interface and its
[47:45] in terms of its user interface and its panel and its features by creating your
[47:49] panel and its features by creating your own plugins that can be cloned off of
[47:53] own plugins that can be cloned off of tools we ship in the box. For example,
[47:56] tools we ship in the box. For example, say you want a different calendar. Um
[47:58] say you want a different calendar. Um ships with a calendar. You click the
[47:59] ships with a calendar. You click the little clock. It pops up a calendar and
[48:03] little clock. It pops up a calendar and it doesn't have iical support for
[48:04] it doesn't have iical support for example. It doesn't consume your
[48:06] example. It doesn't consume your appointments. There's about 17
[48:09] appointments. There's about 17 implementations of that already. And in
[48:11] implementations of that already. And in 3 days we had 330 plugins on the Omachi
[48:16] 3 days we had 330 plugins on the Omachi plug-in marketplace. I have never seen
[48:20] plug-in marketplace. I have never seen growth like that with any project I've
[48:23] growth like that with any project I've ever been involved with. I've never seen
[48:25] ever been involved with. I've never seen participation that broadly. I've never
[48:27] participation that broadly. I've never seen that many people be able to create
[48:29] seen that many people be able to create software that's meaningful for them
[48:33] software that's meaningful for them also be usable for others so quickly.
[48:36] also be usable for others so quickly. All of it is driven by the fact that
[48:38] All of it is driven by the fact that Amachi ships a set of skills that tells
[48:42] Amachi ships a set of skills that tells any agents you bring to it how to create
[48:44] any agents you bring to it how to create extensions to the operating system and
[48:47] extensions to the operating system and therefore affording you
[48:50] therefore affording you the vision of the true malible.
[48:54] the vision of the true malible. I was about to say a gentic. I hate that
[48:56] I was about to say a gentic. I hate that word. And the reason in part I
[48:57] word. And the reason in part I hate that word is first of all it's
[48:59] hate that word is first of all it's become marketing slob speak at this
[49:01] become marketing slob speak at this point. Like it's just slapped onto
[49:03] point. Like it's just slapped onto everything.
[49:05] everything. >> I wish we had a different word that just
[49:06] >> I wish we had a different word that just meant AI doing stuff.
[49:08] meant AI doing stuff. >> Vibe coding feels wrong too.
[49:10] >> Vibe coding feels wrong too. >> It does because vibe coding to me smells
[49:12] >> It does because vibe coding to me smells exactly like script kitties did in the
[49:15] exactly like script kitties did in the early 2000s. People applying PHP scripts
[49:18] early 2000s. People applying PHP scripts they just downloaded offline. They don't
[49:20] they just downloaded offline. They don't understand anything of. And while I mean
[49:23] understand anything of. And while I mean that's true in the sense that much of
[49:24] that's true in the sense that much of the vibe coding including my own vibe
[49:26] the vibe coding including my own vibe coded projects and as I just mentioned I
[49:29] coded projects and as I just mentioned I have several I've written things in C++
[49:31] have several I've written things in C++ I've written things in Rust.
[49:33] I've written things in Rust. >> Mhm.
[49:34] >> Mhm. >> Rust
[49:35] >> Rust I hate Rust with a passion. Rust to me
[49:39] I hate Rust with a passion. Rust to me is like pouring acid in my eyes when I
[49:41] is like pouring acid in my eyes when I have to look at the code.
[49:42] have to look at the code. >> Why why why do you hate Rust?
[49:44] >> Why why why do you hate Rust? >> It is in my opinion the ugliest
[49:46] >> It is in my opinion the ugliest programming language that's been
[49:47] programming language that's been invented in probably the last 40 years.
[49:49] invented in probably the last 40 years. So it's the opposite of Rails and Rust.
[49:51] So it's the opposite of Rails and Rust. >> It's the opposite. But
[49:53] >> It's the opposite. But >> you've written it.
[49:54] >> you've written it. >> I've written applications in Rust
[49:56] >> I've written applications in Rust because the output of Rust is actually
[49:59] because the output of Rust is actually amazing. The memory safety, the fact
[50:01] amazing. The memory safety, the fact it's a system language, the fact it's
[50:03] it's a system language, the fact it's highly efficient and and so forth is
[50:06] highly efficient and and so forth is incredible. So Rust to me can both be
[50:10] incredible. So Rust to me can both be the most repugnant programming language
[50:13] the most repugnant programming language ever devised for human consumption and a
[50:16] ever devised for human consumption and a wonderful platform for egentic
[50:19] wonderful platform for egentic engineering. These two truths can
[50:22] engineering. These two truths can coexist
[50:23] coexist easily in my head.
[50:25] easily in my head. >> Do you think that there can be a point
[50:26] >> Do you think that there can be a point at which we can just call agentic
[50:28] at which we can just call agentic engineering programming? Can we just
[50:30] engineering programming? Can we just change what programming means? Because
[50:32] change what programming means? Because who's actually going to be programming
[50:34] who's actually going to be programming the old schoolooled way in in a few
[50:36] the old schoolooled way in in a few months?
[50:37] months? >> I don't think we should reuse the term
[50:38] >> I don't think we should reuse the term because for me programming implies an
[50:42] because for me programming implies an understanding of certain primitives,
[50:46] understanding of certain primitives, loops, conditions, variables, all the
[50:49] loops, conditions, variables, all the constructs of programming languages
[50:52] constructs of programming languages are what constitutes programming itself,
[50:54] are what constitutes programming itself, not the creation of programs. Because
[50:56] not the creation of programs. Because you could say in the pre-agentic era,
[50:59] you could say in the pre-agentic era, well, your CEO is programming. He's
[51:01] well, your CEO is programming. He's hiring a bunch of programmers. He's
[51:03] hiring a bunch of programmers. He's telling them what to do and out comes
[51:04] telling them what to do and out comes software that he can sell.
[51:06] software that he can sell. >> I don't think most people would call
[51:07] >> I don't think most people would call that CEO a programmer. And I don't think
[51:09] that CEO a programmer. And I don't think we should call the the vibe coder a
[51:12] we should call the the vibe coder a programmer either. And vibe coding, if
[51:14] programmer either. And vibe coding, if we define it here, is you tell an agent
[51:16] we define it here, is you tell an agent to build software for you. You do not
[51:18] to build software for you. You do not look at the implementation. That to me
[51:20] look at the implementation. That to me is what separates vibe coding from
[51:23] is what separates vibe coding from programming or let's say agent
[51:25] programming or let's say agent accelerated development. But don't you
[51:27] accelerated development. But don't you think so to push back a little bit don't
[51:30] think so to push back a little bit don't you think a programmer old school
[51:32] you think a programmer old school programmer you doing agentic engineering
[51:35] programmer you doing agentic engineering is a different kind of agentic
[51:36] is a different kind of agentic engineering than a non-programmer doing
[51:39] engineering than a non-programmer doing agentic engineering what I mean is if
[51:41] agentic engineering what I mean is if you know what a for loop is if you know
[51:44] you know what a for loop is if you know what function programming is if you know
[51:46] what function programming is if you know some of the basic good principles of
[51:48] some of the basic good principles of software engineering the way you do
[51:50] software engineering the way you do natural language-based agentic
[51:52] natural language-based agentic engineering will be different and more
[51:54] engineering will be different and more systematic and this the the the scale
[51:57] systematic and this the the the scale and the variety of things you can
[51:59] and the variety of things you can actually build is um much bigger than a
[52:02] actually build is um much bigger than a VIP coder.
[52:03] VIP coder. >> I'm just going to extend the procase
[52:04] >> I'm just going to extend the procase here a little bit just for the sake of
[52:05] here a little bit just for the sake of the argument.
[52:07] the argument. I actually think for a while it was to
[52:11] I actually think for a while it was to my
[52:12] my deficit to know as much as I know about
[52:16] deficit to know as much as I know about programming because
[52:18] programming because I was instructing the agents to do
[52:21] I was instructing the agents to do things as I prescribed them to do and
[52:24] things as I prescribed them to do and they were very good at that and in the
[52:26] they were very good at that and in the first aentic moment let's not call it an
[52:29] first aentic moment let's not call it an era it was something that lasted three
[52:30] era it was something that lasted three three months moment in the first aentic
[52:33] three months moment in the first aentic moment that felt very productive I could
[52:37] moment that felt very productive I could get more productivity out of telling the
[52:39] get more productivity out of telling the agents what to do in the way I would
[52:41] agents what to do in the way I would have done it. And I used all of my
[52:43] have done it. And I used all of my experience as a programmer to do just
[52:45] experience as a programmer to do just that. Mhm.
[52:47] that. Mhm. >> Then I was a little late on the next
[52:50] >> Then I was a little late on the next moment and the next moment allowed me
[52:54] moment and the next moment allowed me allowed anyone to describe outcomes to
[52:58] allowed anyone to describe outcomes to describe problems to the agents and get
[53:01] describe problems to the agents and get better solutions than if you had a
[53:04] better solutions than if you had a programmer prescribe the path. See?
[53:06] programmer prescribe the path. See? Okay. So, we're having fun arguing here.
[53:08] Okay. So, we're having fun arguing here. Um, so are you suggesting that there's
[53:11] Um, so are you suggesting that there's problems for which programmers are worse
[53:14] problems for which programmers are worse than non-programmers at H?
[53:16] than non-programmers at H? >> 100%.
[53:17] >> 100%. >> And the reason I say that, let's define
[53:20] >> And the reason I say that, let's define it here. The reason I say that is
[53:22] it here. The reason I say that is there's a lot of programmers who are not
[53:25] there's a lot of programmers who are not very good product managers. Software is
[53:29] very good product managers. Software is product management. What should it do?
[53:31] product management. What should it do? Who should it do it for? How should it
[53:34] Who should it do it for? How should it do it? How should it look? What's our
[53:36] do it? How should it look? What's our priorities? What do we start with first?
[53:37] priorities? What do we start with first? What does version one include? All of
[53:40] What does version one include? All of those skills
[53:42] those skills are not easily or equally distributed
[53:45] are not easily or equally distributed across all programmers and in the
[53:48] across all programmers and in the agentic era where you are letting a
[53:51] agentic era where you are letting a agent and AI do the implementation,
[53:54] agent and AI do the implementation, these are the skills you need. And I
[53:56] these are the skills you need. And I happen to sit in both camps and this is
[53:58] happen to sit in both camps and this is why I love this moment. I still get to
[54:00] why I love this moment. I still get to live a little bit in the old world where
[54:02] live a little bit in the old world where I look at the full implementation
[54:03] I look at the full implementation because there are domains and areas
[54:05] because there are domains and areas where I feel that still brings value and
[54:08] where I feel that still brings value and then I also live in the future and as I
[54:12] then I also live in the future and as I said when I created Omarite I've not
[54:14] said when I created Omarite I've not looked at a single line of that C++ I
[54:17] looked at a single line of that C++ I actually made it a point to myself that
[54:19] actually made it a point to myself that I was going to treat it as an
[54:20] I was going to treat it as an experiment. This is 100% a blackbox. I
[54:22] experiment. This is 100% a blackbox. I will treat it as though I was any other
[54:25] will treat it as though I was any other user who had opinions about how their
[54:28] user who had opinions about how their digital typewriter should work and
[54:30] digital typewriter should work and therefore felt like it was a fair
[54:32] therefore felt like it was a fair experiment as if a writer of any other
[54:36] experiment as if a writer of any other sort who had opinions about how software
[54:38] sort who had opinions about how software should be done and how it should work.
[54:40] should be done and how it should work. As you mentioned video editors who know
[54:42] As you mentioned video editors who know exactly where they don't like what Adobe
[54:44] exactly where they don't like what Adobe Premiere is doing and how it could be
[54:47] Premiere is doing and how it could be better but don't have the capacities to
[54:48] better but don't have the capacities to improve it. Mhm.
[54:50] improve it. Mhm. >> How that could be
[54:51] >> How that could be >> the push back though I think what
[54:53] >> the push back though I think what programmers do well good programmers do
[54:55] programmers do well good programmers do well is systematic
[54:57] well is systematic design like think in terms of systems
[54:59] design like think in terms of systems and rigor.
[55:00] and rigor. >> Yes. And I think still and probably for
[55:03] >> Yes. And I think still and probably for a long time to come, even natural
[55:05] a long time to come, even natural language-based control of agentic
[55:08] language-based control of agentic systems will require a a certain kind of
[55:10] systems will require a a certain kind of rigor. Not overly structured rigor, but
[55:13] rigor. Not overly structured rigor, but really explain very specifically
[55:17] really explain very specifically uh the goals of the system, how to do
[55:20] uh the goals of the system, how to do the verification, what kind of uh
[55:22] the verification, what kind of uh security testing you want to do, all
[55:23] security testing you want to do, all those kinds of things. Although then to
[55:26] those kinds of things. Although then to push back on that, the system will
[55:28] push back on that, the system will should be smart. I would have said the
[55:30] should be smart. I would have said the same thing 6 months ago and I think the
[55:31] same thing 6 months ago and I think the same thing would have been true 6 months
[55:33] same thing would have been true 6 months ago. What I have found since especially
[55:36] ago. What I have found since especially even just the last few weeks of the
[55:39] even just the last few weeks of the agentically accelerated development of
[55:41] agentically accelerated development of Machi is that more often than not I have
[55:46] Machi is that more often than not I have the humility to recognize that the agent
[55:48] the humility to recognize that the agent knows best. You can legitimately say
[55:51] knows best. You can legitimately say make sure it's secure.
[55:52] make sure it's secure. >> Correct. And it would know more about
[55:55] >> Correct. And it would know more about what that entails. Now
[55:59] what that entails. Now you're laughing, but it's true. And in
[56:01] you're laughing, but it's true. And in fact,
[56:02] fact, >> oh my god,
[56:02] >> oh my god, >> a good parallel to this is the agents
[56:05] >> a good parallel to this is the agents MD/cloud MD files.
[56:08] MD/cloud MD files. >> There was a hot moment where it was all
[56:11] >> There was a hot moment where it was all the rage about microoptimizing that. Oh,
[56:14] the rage about microoptimizing that. Oh, you tell your agent this, you tell your
[56:15] you tell your agent this, you tell your agent that, and you ended up with this
[56:16] agent that, and you ended up with this huge file of instructions for your
[56:19] huge file of instructions for your agent. One of the things that um Boris
[56:22] agent. One of the things that um Boris working on Claude Code shared in an
[56:25] working on Claude Code shared in an interview recently about Opus 5 was that
[56:27] interview recently about Opus 5 was that the system prompt that they ship for
[56:30] the system prompt that they ship for Opus 5 and presumably also Fable shrunk
[56:33] Opus 5 and presumably also Fable shrunk by 80%.
[56:35] by 80%. Because the agent not only needed far
[56:38] Because the agent not only needed far less human instruction, it was actually
[56:41] less human instruction, it was actually being damaged by overly prescriptive
[56:45] being damaged by overly prescriptive humans. And any programmer who's had a
[56:48] humans. And any programmer who's had a pointy-haired boss knows exactly what
[56:50] pointy-haired boss knows exactly what that is like. When the boss walks into
[56:52] that is like. When the boss walks into the room doesn't know anything, starts
[56:55] the room doesn't know anything, starts telling you how to program, how to code,
[56:59] telling you how to program, how to code, what do you do? You sulk. You write
[57:02] what do you do? You sulk. You write shittier code. If you're mandated to do
[57:04] shittier code. If you're mandated to do things that are against your better
[57:05] things that are against your better judgment, why would an agent not be the
[57:08] judgment, why would an agent not be the same? Actually to push back against
[57:09] same? Actually to push back against myself, I do find the actual skill I'm
[57:11] myself, I do find the actual skill I'm currently developing which I along those
[57:14] currently developing which I along those lines is probably what everybody's
[57:15] lines is probably what everybody's trying to develop is not to over specify
[57:18] trying to develop is not to over specify things is to get out of the systems way
[57:20] things is to get out of the systems way is to specify enough to provide a kind
[57:23] is to specify enough to provide a kind of highlevel vision and guidance. It's
[57:26] of highlevel vision and guidance. It's even better because you don't even need
[57:28] even better because you don't even need that. The fundamental insight of modern
[57:31] that. The fundamental insight of modern software development came from the agile
[57:33] software development came from the agile software development movement in the
[57:35] software development movement in the late 90s early 2000s. A group of smart,
[57:39] late 90s early 2000s. A group of smart, honest and brave people came together
[57:41] honest and brave people came together and said the way we've been trying to do
[57:43] and said the way we've been trying to do software development for the last 40 to
[57:45] software development for the last 40 to 50 years have not worked will not work.
[57:49] 50 years have not worked will not work. We've been trying to specify upfront
[57:52] We've been trying to specify upfront what software should look like. We
[57:54] what software should look like. We thought that we could ask humans what
[57:55] thought that we could ask humans what they wanted, write it all down, apply
[57:59] they wanted, write it all down, apply our systems thinking and our rigor to a
[58:02] our systems thinking and our rigor to a spec sheet, hand that spec sheet over to
[58:04] spec sheet, hand that spec sheet over to a group of programmers who would then
[58:06] a group of programmers who would then implement just that and everyone would
[58:08] implement just that and everyone would be happy. Well, guess what? No one was
[58:10] be happy. Well, guess what? No one was happy because no one knows what they
[58:12] happy because no one knows what they want until they receive it. You don't
[58:14] want until they receive it. You don't know what a program should do until you
[58:16] know what a program should do until you play with it. So in the agentic age, you
[58:20] play with it. So in the agentic age, you should resist the temptation to be
[58:22] should resist the temptation to be overly specific upfront. Be as vague as
[58:25] overly specific upfront. Be as vague as you can to manifest something, then
[58:28] you can to manifest something, then interact with the something. The way you
[58:30] interact with the something. The way you arrive at good software is you write a
[58:32] arrive at good software is you write a little bit of software and then you try
[58:34] little bit of software and then you try to use it. It is in the process of using
[58:36] to use it. It is in the process of using software that you discover what you
[58:38] software that you discover what you really want.
[58:39] really want. >> It's where you discover what's important
[58:41] >> It's where you discover what's important and what's not important. And agents are
[58:44] and what's not important. And agents are incredible at allowing you to bumble
[58:47] incredible at allowing you to bumble into this experience of realizing what
[58:50] into this experience of realizing what you want because you don't know what you
[58:52] you want because you don't know what you want.
[58:52] want. >> And I I've actually done some something
[58:54] >> And I I've actually done some something similar to what you suggested which is
[58:56] similar to what you suggested which is implement uh different designs and
[58:59] implement uh different designs and totally different implementations and
[59:01] totally different implementations and then I create HTML pages for myself PHP
[59:04] then I create HTML pages for myself PHP pages where I vote on what I like more
[59:06] pages where I vote on what I like more and so on and it does this iterative
[59:07] and so on and it does this iterative thing and it's very nice and fun. the
[59:09] thing and it's very nice and fun. the interaction with the the agentic system.
[59:11] interaction with the the agentic system. If you create a nice interface for
[59:13] If you create a nice interface for yourself, it could be super fun and
[59:14] yourself, it could be super fun and you're focusing on the design part and
[59:16] you're focusing on the design part and the most fun parts of the design part.
[59:18] the most fun parts of the design part. >> Correct. And this is what humans are
[59:20] >> Correct. And this is what humans are really good at.
[59:21] really good at. >> Yeah. Taste
[59:21] >> Yeah. Taste >> differential evaluation. You give me
[59:24] >> differential evaluation. You give me three options, I pick one of them. Now,
[59:27] three options, I pick one of them. Now, humans actually fall off a cliff if you
[59:29] humans actually fall off a cliff if you give them 22 options. That's the paradox
[59:31] give them 22 options. That's the paradox of choice. But you give them three
[59:32] of choice. But you give them three options, they very quickly, within a
[59:34] options, they very quickly, within a split second will tell you what they
[59:36] split second will tell you what they like. There are all these ways that
[59:40] like. There are all these ways that exploit the fact that humans will make
[59:42] exploit the fact that humans will make these snap judgments that are actually
[59:43] these snap judgments that are actually pre-intellectual, right? Like they're
[59:46] pre-intellectual, right? Like they're coming from the gut and then they arrive
[59:48] coming from the gut and then they arrive up in the in the brain and the brain
[59:50] up in the in the brain and the brain tries to rationalized why the gut said
[59:52] tries to rationalized why the gut said what it said. And if you're
[59:57] what it said. And if you're willing to let go of some of that
[59:59] willing to let go of some of that intellectual pre-processing
[01:00:01] intellectual pre-processing rationalization and simply let your gut
[01:00:03] rationalization and simply let your gut drive, the agent gauge is a revelation.
[01:00:06] drive, the agent gauge is a revelation. So this is a fascinating thing to ask
[01:00:08] So this is a fascinating thing to ask you because you have sort of famously
[01:00:11] you because you have sort of famously for a long time talked about
[01:00:13] for a long time talked about like detailed chiseling of beautiful
[01:00:17] like detailed chiseling of beautiful Rails Ruby code and now you have
[01:00:21] Rails Ruby code and now you have switched in a matter of months to not
[01:00:24] switched in a matter of months to not doing that. So, like what does your uh
[01:00:26] doing that. So, like what does your uh current setup look like? Because you're,
[01:00:28] current setup look like? Because you're, I assume, are still looking for the
[01:00:29] I assume, are still looking for the beauty, for the chiseling, for the
[01:00:31] beauty, for the chiseling, for the crafting, but you're just crafting in a
[01:00:33] crafting, but you're just crafting in a different medium and at different levels
[01:00:36] different medium and at different levels of abstraction. When I'm working in Ruby
[01:00:39] of abstraction. When I'm working in Ruby code, and we have a lot of Ruby code
[01:00:40] code, and we have a lot of Ruby code because it's in our entire business, and
[01:00:42] because it's in our entire business, and I'm asking agents to make changes to
[01:00:44] I'm asking agents to make changes to that code, I still sweat the details.
[01:00:47] that code, I still sweat the details. >> Mhm.
[01:00:48] >> Mhm. What I'm coming to realize is that the
[01:00:51] What I'm coming to realize is that the economic
[01:00:54] economic payoff of that sweat is diminishing
[01:00:57] payoff of that sweat is diminishing rapidly. The reason why I for 25 years
[01:01:02] rapidly. The reason why I for 25 years was sweating every line of code so
[01:01:05] was sweating every line of code so judiciously was because I knew the
[01:01:07] judiciously was because I knew the payoff of keeping an architecture
[01:01:11] payoff of keeping an architecture coherent and malible was software that
[01:01:15] coherent and malible was software that could change and evolve quickly with a
[01:01:18] could change and evolve quickly with a small team and not exorbitant cost and
[01:01:21] small team and not exorbitant cost and not introducing a bunch of bugs when you
[01:01:23] not introducing a bunch of bugs when you change one thing over the other. That
[01:01:25] change one thing over the other. That was the driving economic argument for
[01:01:28] was the driving economic argument for why you should write beautiful code
[01:01:30] why you should write beautiful code because beautiful code is easier to
[01:01:31] because beautiful code is easier to understand. It is simpler. It is more
[01:01:33] understand. It is simpler. It is more malible.
[01:01:36] malible. That was premised on humans doing the
[01:01:39] That was premised on humans doing the modifications.
[01:01:40] modifications. I think it is an open question to which
[01:01:43] I think it is an open question to which degree this still matters. Now
[01:01:47] degree this still matters. Now it does matter and the reason I say that
[01:01:49] it does matter and the reason I say that at least for the moment is that tokens
[01:01:51] at least for the moment is that tokens are still scarce at this moment in time.
[01:01:55] are still scarce at this moment in time. We are all token limited. Well, not all
[01:02:00] We are all token limited. Well, not all but anyone who who doesn't have endless
[01:02:02] but anyone who who doesn't have endless budgets are token limited. So therefore,
[01:02:05] budgets are token limited. So therefore, there is great payoff to writing systems
[01:02:08] there is great payoff to writing systems that agents have an easier time dealing
[01:02:10] that agents have an easier time dealing with and evolving without having to
[01:02:12] with and evolving without having to relearn the entire context. Just like
[01:02:14] relearn the entire context. Just like humans, if they can make iterations and
[01:02:17] humans, if they can make iterations and changes to the codebase without wrecking
[01:02:20] changes to the codebase without wrecking the architecture, they can make the next
[01:02:22] the architecture, they can make the next change just as cheaply as the last one.
[01:02:25] change just as cheaply as the last one. And this is the classic ball of mud
[01:02:28] And this is the classic ball of mud where you end up with a system that's a
[01:02:31] where you end up with a system that's a ball of mud because it's just put
[01:02:33] ball of mud because it's just put together in a way where nothing is
[01:02:36] together in a way where nothing is connected and it's just a real mess.
[01:02:37] connected and it's just a real mess. Right? I've seen that with agents and
[01:02:39] Right? I've seen that with agents and I've seen it in our own code bases where
[01:02:41] I've seen it in our own code bases where again the first PR is like mediocre of
[01:02:44] again the first PR is like mediocre of quality and then if you add another PR
[01:02:46] quality and then if you add another PR on top of that and then five more down
[01:02:48] on top of that and then five more down the line it's not very good right so
[01:02:50] the line it's not very good right so there's still a payoff to that but that
[01:02:52] there's still a payoff to that but that payoff is premised on our current moment
[01:02:54] payoff is premised on our current moment I am now able to and this is by the way
[01:02:57] I am now able to and this is by the way where the AI psychosis really comes in
[01:02:59] where the AI psychosis really comes in when you try to extrapolate what 9
[01:03:01] when you try to extrapolate what 9 months from now is going to look like
[01:03:03] months from now is going to look like when two years from now it's going to
[01:03:04] when two years from now it's going to look like but as an intellectual
[01:03:06] look like but as an intellectual experiment I I think the first computer
[01:03:08] experiment I I think the first computer I used was a Commodore 64.
[01:03:10] I used was a Commodore 64. >> Me too. Cool.
[01:03:11] >> Me too. Cool. >> It had 1 MHz CPU and 64K of memory.
[01:03:16] >> It had 1 MHz CPU and 64K of memory. >> Mhm.
[01:03:16] >> Mhm. >> Everyone who wrote software for that
[01:03:18] >> Everyone who wrote software for that machine internalized certain
[01:03:21] machine internalized certain constraints. Well, all the constraints
[01:03:23] constraints. Well, all the constraints that machine was nothing but
[01:03:25] that machine was nothing but constraints. If you put that programmer
[01:03:28] constraints. If you put that programmer in a time machine and teleported them or
[01:03:31] in a time machine and teleported them or her to 2026 and gave them a modern
[01:03:34] her to 2026 and gave them a modern computer today and said, "Now write me a
[01:03:36] computer today and said, "Now write me a piece of software." They'd be lost for a
[01:03:38] piece of software." They'd be lost for a little bit because all their techniques
[01:03:41] little bit because all their techniques and all their huristics would simply be
[01:03:44] and all their huristics would simply be wrong or not wrong because efficient
[01:03:46] wrong or not wrong because efficient software is still beautiful. They would
[01:03:48] software is still beautiful. They would be out of date with the value that they
[01:03:50] be out of date with the value that they could create. The amount of optimization
[01:03:52] could create. The amount of optimization you have to apply for a 1 MHz computer
[01:03:55] you have to apply for a 1 MHz computer to produce video game is just very
[01:03:58] to produce video game is just very different from what you have to apply
[01:03:59] different from what you have to apply today.
[01:03:59] today. >> Just imagine that guy that was
[01:04:01] >> Just imagine that guy that was programming back then on a copy. Just
[01:04:04] programming back then on a copy. Just remember all those like what programming
[01:04:07] remember all those like what programming felt like and what it meant. Highly
[01:04:09] felt like and what it meant. Highly constrained resources, how slow
[01:04:11] constrained resources, how slow everything is.
[01:04:11] everything is. >> Beautiful in many ways. Beautiful.
[01:04:13] >> Beautiful in many ways. Beautiful. >> It's chiseling.
[01:04:14] >> It's chiseling. But imagine that person coming now.
[01:04:18] But imagine that person coming now. >> It's romantic too though. Let's also
[01:04:20] >> It's romantic too though. Let's also imagine that this is one of the things
[01:04:21] imagine that this is one of the things whenever we bemoone modern car culture
[01:04:25] whenever we bemoone modern car culture for example, right? And then we think
[01:04:27] for example, right? And then we think like, oh, wasn't it better when we all
[01:04:28] like, oh, wasn't it better when we all had the horsedrawn carriages and so on?
[01:04:30] had the horsedrawn carriages and so on? No, it wasn't. Do you know what New York
[01:04:32] No, it wasn't. Do you know what New York smelled like when we used horses for
[01:04:34] smelled like when we used horses for transportation?
[01:04:35] transportation? >> Yeah,
[01:04:36] >> Yeah, >> it was an open sewer. They just shat
[01:04:38] >> it was an open sewer. They just shat everywhere.
[01:04:38] everywhere. >> Yeah, but have you played Red Dead
[01:04:40] >> Yeah, but have you played Red Dead Redemption?
[01:04:41] Redemption? >> You know how cool those cowboys were on
[01:04:43] >> You know how cool those cowboys were on the horse? experience the nostalgic past
[01:04:46] the horse? experience the nostalgic past when you don't get the uh all the fairy
[01:04:48] when you don't get the uh all the fairy uh impulses and senses.
[01:04:50] uh impulses and senses. >> So basically programming old school
[01:04:52] >> So basically programming old school programming by hand is kind of like the
[01:04:55] programming by hand is kind of like the cowboy culture that we romanticize make
[01:04:56] cowboy culture that we romanticize make movies about.
[01:04:58] movies about. >> It's already happening. The
[01:04:59] >> It's already happening. The romanticization of handwritten code and
[01:05:02] romanticization of handwritten code and I have some of it because it was a very
[01:05:05] I have some of it because it was a very romantic era. I'm grateful to have had
[01:05:08] romantic era. I'm grateful to have had been alive for 20 years of economically
[01:05:13] been alive for 20 years of economically valuable handwritten code. That was a
[01:05:16] valuable handwritten code. That was a that was a good time. Where handwritten
[01:05:18] that was a good time. Where handwritten beautiful code was also valuable.
[01:05:20] beautiful code was also valuable. >> Correct. Because handwritten beautiful
[01:05:23] >> Correct. Because handwritten beautiful code exists as much today as it is
[01:05:26] code exists as much today as it is yesterday. There are people who
[01:05:28] yesterday. There are people who willfully write new video games for the
[01:05:31] willfully write new video games for the Commodore 64 or for the Sega Mega Drive
[01:05:34] Commodore 64 or for the Sega Mega Drive or for other vintage consoles. In fact,
[01:05:36] or for other vintage consoles. In fact, one of my favorite video games of late
[01:05:39] one of my favorite video games of late is uh M Retros. Do you know Pomaly's
[01:05:43] is uh M Retros. Do you know Pomaly's side, which is recreating old consoles?
[01:05:48] side, which is recreating old consoles? So, he's recreated the Game Boy.
[01:05:50] So, he's recreated the Game Boy. >> Nice.
[01:05:51] >> Nice. >> It's amazing. Look it up. It's It's
[01:05:53] >> It's amazing. Look it up. It's It's really cool. But what's even cooler than
[01:05:56] really cool. But what's even cooler than the fact that he recreated this hardware
[01:05:58] the fact that he recreated this hardware and the original chunkiness, but brought
[01:06:00] and the original chunkiness, but brought it up to date with um sort of modern
[01:06:03] it up to date with um sort of modern screens and so on. Now they just put out
[01:06:04] screens and so on. Now they just put out the Nintendo 64 too. Incredible. Super
[01:06:07] the Nintendo 64 too. Incredible. Super cool. Wild attention to detail, input
[01:06:11] cool. Wild attention to detail, input lag, and all the other things. But
[01:06:12] lag, and all the other things. But what's also very cool, that one I have
[01:06:15] what's also very cool, that one I have the wave, that one right there, and
[01:06:17] the wave, that one right there, and hover over it because then you get to
[01:06:18] hover over it because then you get to see what I'm talking about. That is the
[01:06:21] see what I'm talking about. That is the chromatic Tetris reimplementation. I
[01:06:24] chromatic Tetris reimplementation. I played a lot of Tetris on the original
[01:06:26] played a lot of Tetris on the original Game Boy. Probably one of my top three
[01:06:29] Game Boy. Probably one of my top three favorite games of all time.
[01:06:30] favorite games of all time. >> Yeah.
[01:06:31] >> Yeah. >> And they rewrote it with one change. If
[01:06:36] >> And they rewrote it with one change. If you hit up the brick slams.
[01:06:39] you hit up the brick slams. >> Mhm.
[01:06:39] >> Mhm. >> And that speeds up the game by about
[01:06:42] >> And that speeds up the game by about 400%.
[01:06:43] 400%. It is an incredible game. And it's a new
[01:06:46] It is an incredible game. And it's a new Game Boy game.
[01:06:48] Game Boy game. >> I think the Game Boy came out in ' 89 or
[01:06:51] >> I think the Game Boy came out in ' 89 or 88. It's a very old machine. The fact
[01:06:53] 88. It's a very old machine. The fact that there's still people writing new
[01:06:55] that there's still people writing new old games is awesome. And the reason
[01:06:58] old games is awesome. And the reason they do it in part now here they're
[01:07:00] they do it in part now here they're doing because they want Tetris, but
[01:07:01] doing because they want Tetris, but there are people who do it just for the
[01:07:02] there are people who do it just for the love of the constraints, for the love of
[01:07:05] love of the constraints, for the love of the romantic notion of of riding that
[01:07:07] the romantic notion of of riding that just like there are people still riding
[01:07:10] just like there are people still riding around on horses, not to get places
[01:07:12] around on horses, not to get places fast, but because they like the mode of
[01:07:16] fast, but because they like the mode of transportation where it's a literal
[01:07:18] transportation where it's a literal biological being below you propelling
[01:07:21] biological being below you propelling you forward. And also we should say that
[01:07:23] you forward. And also we should say that that beautiful code is uh great training
[01:07:26] that beautiful code is uh great training data. So in some sense the beauty that
[01:07:28] data. So in some sense the beauty that we've built over a few decades
[01:07:30] we've built over a few decades >> yes
[01:07:31] >> yes >> continues. We gave birth to this moment.
[01:07:35] >> continues. We gave birth to this moment. >> What a privilege. And I I feel that very
[01:07:39] >> What a privilege. And I I feel that very personally because I almost all of the
[01:07:41] personally because I almost all of the code I've ever written is public code.
[01:07:44] code I've ever written is public code. The vast majority of my career has been
[01:07:45] The vast majority of my career has been dedicated to writing open source code.
[01:07:47] dedicated to writing open source code. And therefore, some of that code, some
[01:07:50] And therefore, some of that code, some of those beautiful lines are in the
[01:07:52] of those beautiful lines are in the training set. And in fact, I've heard
[01:07:56] training set. And in fact, I've heard people do this when they write Ruby
[01:07:57] people do this when they write Ruby code. They ask the agent, "Write it like
[01:08:00] code. They ask the agent, "Write it like DHH would."
[01:08:01] DHH would." >> Mhm.
[01:08:01] >> Mhm. >> And they're pleased with the result. And
[01:08:03] >> And they're pleased with the result. And that does warm my heart a little bit
[01:08:05] that does warm my heart a little bit that I helped give birth to this moment
[01:08:07] that I helped give birth to this moment in my tiny little small part. anyone
[01:08:09] in my tiny little small part. anyone else who contributed open source code or
[01:08:11] else who contributed open source code or any code at all that the agents have had
[01:08:12] any code at all that the agents have had access to over the last well entire
[01:08:16] access to over the last well entire time. Programming has been around as a
[01:08:18] time. Programming has been around as a discipline is now part of these new
[01:08:21] discipline is now part of these new agent overlords.
[01:08:23] agent overlords. >> So you you don't have a little bit of
[01:08:24] >> So you you don't have a little bit of sadness that writing beautiful code by
[01:08:27] sadness that writing beautiful code by hand is now less and less useful. Am I
[01:08:30] hand is now less and less useful. Am I sad that if I had to get a job tomorrow,
[01:08:33] sad that if I had to get a job tomorrow, it's unlikely that I could apply my
[01:08:35] it's unlikely that I could apply my skills in such a way that I would be
[01:08:37] skills in such a way that I would be paid to write these manual lines of
[01:08:40] paid to write these manual lines of code. No, I did it for 25 years. Like, I
[01:08:44] code. No, I did it for 25 years. Like, I want to see something new here,
[01:08:46] want to see something new here, especially if we're all going to live
[01:08:47] especially if we're all going to live forever, which I hope we don't. Maybe we
[01:08:49] forever, which I hope we don't. Maybe we get to that. But like, I've done that.
[01:08:51] get to that. But like, I've done that. That that's enough. That's fine. I don't
[01:08:53] That that's enough. That's fine. I don't feel any more nostalgic about that than
[01:08:55] feel any more nostalgic about that than I do about the fact that I don't have to
[01:08:58] I do about the fact that I don't have to spend my time in the field with a hoe or
[01:09:00] spend my time in the field with a hoe or at the assembly line.
[01:09:02] at the assembly line. >> Well, hold on a second. You are one of
[01:09:04] >> Well, hold on a second. You are one of the best programmers in the world at
[01:09:06] the best programmers in the world at writing handcrafted beautiful code,
[01:09:09] writing handcrafted beautiful code, appreciators of beauty with great taste.
[01:09:12] appreciators of beauty with great taste. >> Correct.
[01:09:12] >> Correct. >> That has been replaced.
[01:09:14] >> That has been replaced. >> I say humbly.
[01:09:15] >> I say humbly. >> Yeah. That has been replaced. like you
[01:09:18] >> Yeah. That has been replaced. like you have now you're just fast evolving and
[01:09:20] have now you're just fast evolving and you're able to one of your uh really
[01:09:23] you're able to one of your uh really great qualities is you're able to change
[01:09:25] great qualities is you're able to change your mind and evolve very quickly but
[01:09:28] your mind and evolve very quickly but like you had to kill that other person.
[01:09:30] like you had to kill that other person. I am grateful for every moment that
[01:09:32] I am grateful for every moment that brought me to where I am right now and
[01:09:34] brought me to where I am right now and therefore I have all so tried and maybe
[01:09:38] therefore I have all so tried and maybe this did take some practice. I will
[01:09:40] this did take some practice. I will concede that maybe I wasn't always like
[01:09:42] concede that maybe I wasn't always like this but stoic philosophy a morati
[01:09:47] this but stoic philosophy a morati loving your fate is an incredibly
[01:09:51] loving your fate is an incredibly liberating way to live and you could
[01:09:55] liberating way to live and you could attack that and say well that's a point
[01:09:56] attack that and say well that's a point of privilege true but also I had the
[01:09:59] of privilege true but also I had the same directional point when I didn't
[01:10:02] same directional point when I didn't have all this quote unquote privilege so
[01:10:06] have all this quote unquote privilege so I think there's a way to live and
[01:10:08] I think there's a way to live and interact with the world where you accept
[01:10:10] interact with the world where you accept the things you can change and the things
[01:10:12] the things you can change and the things you cannot change and fall in love with
[01:10:14] you cannot change and fall in love with all of it.
[01:10:15] all of it. >> Fall in love with the fact that the
[01:10:17] >> Fall in love with the fact that the world today has jumped two decades
[01:10:20] world today has jumped two decades forward in the technology industry from
[01:10:23] forward in the technology industry from where it was last year. So can we talk
[01:10:25] where it was last year. So can we talk about the general anxiety that
[01:10:27] about the general anxiety that programmers feel going through the same
[01:10:30] programmers feel going through the same transformation? They've maybe
[01:10:33] transformation? They've maybe gone to university,
[01:10:35] gone to university, uh, majored in computer science, dreamed
[01:10:38] uh, majored in computer science, dreamed of being programmers and building stuff,
[01:10:40] of being programmers and building stuff, high salary, and now everything is
[01:10:43] high salary, and now everything is changing, and there's deep anxiety about
[01:10:46] changing, and there's deep anxiety about what do I do with my life? Can you
[01:10:48] what do I do with my life? Can you empathize with that? And what the hell
[01:10:50] empathize with that? And what the hell are they supposed to do?
[01:10:51] are they supposed to do? >> Hugely because just because I have this
[01:10:54] >> Hugely because just because I have this disposition, I'm keenly aware that
[01:10:56] disposition, I'm keenly aware that that's not evenly disputed. that not
[01:11:00] that's not evenly disputed. that not everyone sits with this position and
[01:11:01] everyone sits with this position and this optimism for the future, but I do
[01:11:04] this optimism for the future, but I do think I want to separate things a little
[01:11:06] think I want to separate things a little bit.
[01:11:08] bit. I think you're going to have a hard time
[01:11:10] I think you're going to have a hard time coping with the new reality if the only
[01:11:14] coping with the new reality if the only thing you loved about programming was
[01:11:16] thing you loved about programming was the mechanical bits of
[01:11:20] the mechanical bits of putting the right logical constructs
[01:11:23] putting the right logical constructs together to produce something other
[01:11:25] together to produce something other people told you to produce. because that
[01:11:30] people told you to produce. because that mechanical process is under threat.
[01:11:34] mechanical process is under threat. If you are, as you just mentioned,
[01:11:36] If you are, as you just mentioned, excited about building things, I don't
[01:11:39] excited about building things, I don't think you're under threat at all. In
[01:11:41] think you're under threat at all. In fact, I think there's a great argument
[01:11:42] fact, I think there's a great argument for us needing far more builders than
[01:11:46] for us needing far more builders than what we have now. And if you look at the
[01:11:51] what we have now. And if you look at the employment stats, it's fuzzy. It's not
[01:11:54] employment stats, it's fuzzy. It's not clear what's going to happen at all.
[01:11:56] clear what's going to happen at all. Some stats actually show an increase in
[01:11:58] Some stats actually show an increase in openings because
[01:12:00] openings because the advent of AI is so dramatically
[01:12:03] the advent of AI is so dramatically lowering the price of programs that
[01:12:06] lowering the price of programs that people want a lot more programs. This is
[01:12:08] people want a lot more programs. This is the classic the Jevans paradox that says
[01:12:11] the classic the Jevans paradox that says when the price of something goes down
[01:12:13] when the price of something goes down there's going to be more demand for it.
[01:12:15] there's going to be more demand for it. And this is the example of the ATMs too.
[01:12:18] And this is the example of the ATMs too. When the ATM originally came, a lot of
[01:12:21] When the ATM originally came, a lot of bank tellers were very afraid for their
[01:12:23] bank tellers were very afraid for their job because suddenly there was a machine
[01:12:25] job because suddenly there was a machine that could dispense money from people's
[01:12:27] that could dispense money from people's account. Well, what the ATMs did was
[01:12:30] account. Well, what the ATMs did was lower the price of a branch and suddenly
[01:12:33] lower the price of a branch and suddenly banks could afford to open a lot more
[01:12:34] banks could afford to open a lot more branches and we ended up with more bank
[01:12:36] branches and we ended up with more bank tellers than we did before. Now, none of
[01:12:38] tellers than we did before. Now, none of this is guaranteed. There are also
[01:12:40] this is guaranteed. There are also moments where things do change. The vast
[01:12:43] moments where things do change. The vast majority of people worked in the fields
[01:12:45] majority of people worked in the fields up until the late 1800s and then
[01:12:48] up until the late 1800s and then suddenly we got mechanized
[01:12:51] suddenly we got mechanized harvesting tools and we did not need
[01:12:53] harvesting tools and we did not need human labor with a hole and an ax out
[01:12:56] human labor with a hole and an ax out there. We had uh mechanical tools to do
[01:12:59] there. We had uh mechanical tools to do that for us in that moment. Are there
[01:13:02] that for us in that moment. Are there people who were threatened that their
[01:13:04] people who were threatened that their job and their livelihood was at stake?
[01:13:07] job and their livelihood was at stake? Yes. Was that a reasonable thing to feel
[01:13:09] Yes. Was that a reasonable thing to feel threatened about? Yes. the Ludites
[01:13:11] threatened about? Yes. the Ludites smashing the weaving machines in in
[01:13:15] smashing the weaving machines in in England had the same thing. And I think
[01:13:17] England had the same thing. And I think maybe that's the better parallel than
[01:13:18] maybe that's the better parallel than people working in the fields because the
[01:13:19] people working in the fields because the were actually highly skilled
[01:13:21] were actually highly skilled professionals doing a job that they
[01:13:23] professionals doing a job that they liked on rather favorable conditions,
[01:13:26] liked on rather favorable conditions, not slaving outside in the sun all day.
[01:13:28] not slaving outside in the sun all day. But where we live now, would we still
[01:13:31] But where we live now, would we still like for clothing to be this heavily
[01:13:35] like for clothing to be this heavily constrained resource? Like what if this
[01:13:37] constrained resource? Like what if this t-shirt was $400?
[01:13:40] t-shirt was $400? I mean, okay, then I'd have two. My
[01:13:44] I mean, okay, then I'd have two. My wardrobe probably looks like I have two.
[01:13:46] wardrobe probably looks like I have two. But I think the general progress of
[01:13:50] But I think the general progress of mankind depends on productivity
[01:13:54] mankind depends on productivity improvements. And what are productivity
[01:13:56] improvements. And what are productivity improvements? This is very important
[01:13:57] improvements? This is very important because in the abstract, I think
[01:13:59] because in the abstract, I think everyone says, "Yay, productivity.
[01:14:02] everyone says, "Yay, productivity. That's good." What do you think? This
[01:14:04] That's good." What do you think? This was all just vibes. No, productivity
[01:14:06] was all just vibes. No, productivity means fewer people to do the same number
[01:14:08] means fewer people to do the same number or the same job. Now, the amount of job
[01:14:12] or the same job. Now, the amount of job you want done may increase and therefore
[01:14:13] you want done may increase and therefore you get more people, but it also may
[01:14:16] you get more people, but it also may not. There may be pockets where
[01:14:20] not. There may be pockets where a company just needs a certain set of
[01:14:22] a company just needs a certain set of fixed tasks done and suddenly they can
[01:14:24] fixed tasks done and suddenly they can do them with a tenth the number of
[01:14:26] do them with a tenth the number of people. This, by the way, could is
[01:14:29] people. This, by the way, could is tragic and difficult in a moment for the
[01:14:31] tragic and difficult in a moment for the individual being laid off. It's also
[01:14:33] individual being laid off. It's also amazing for the economy at large.
[01:14:35] amazing for the economy at large. Suddenly you've freed up these resources
[01:14:37] Suddenly you've freed up these resources who can now go do more productive
[01:14:39] who can now go do more productive things. This is how the whole economy
[01:14:42] things. This is how the whole economy evolves and improves and how we get
[01:14:44] evolves and improves and how we get growth and growth is good. I think this
[01:14:47] growth and growth is good. I think this is the other thing to make a strong
[01:14:50] is the other thing to make a strong defense for that growth in general is a
[01:14:53] defense for that growth in general is a good thing. We do not want to wind the
[01:14:56] good thing. We do not want to wind the clock back to 1920 or 1950. We should be
[01:15:00] clock back to 1920 or 1950. We should be excited about the fact that we've
[01:15:02] excited about the fact that we've discovered new technology that allows us
[01:15:05] discovered new technology that allows us to do vastly more. And while some of the
[01:15:09] to do vastly more. And while some of the tasks that may be taken over by AI were
[01:15:12] tasks that may be taken over by AI were tasks that humans were excited to do and
[01:15:14] tasks that humans were excited to do and they're just no longer economically
[01:15:16] they're just no longer economically viable, a lot of the tasks were just
[01:15:17] viable, a lot of the tasks were just drudgery. This is certainly true of my
[01:15:20] drudgery. This is certainly true of my programming. There were moments of
[01:15:23] programming. There were moments of programming I thought were amazing.
[01:15:25] programming I thought were amazing. These were the moments that produced
[01:15:27] These were the moments that produced that state of flow we talked about last
[01:15:29] that state of flow we talked about last time and
[01:15:32] time and they were ecstatic. How often did they
[01:15:34] they were ecstatic. How often did they happen out of the course of a year? If
[01:15:37] happen out of the course of a year? If you took your average programmer, how
[01:15:39] you took your average programmer, how much time out of 2,000 hours at the job
[01:15:42] much time out of 2,000 hours at the job did that person spend in a flow state?
[01:15:47] did that person spend in a flow state? >> 100, 200,
[01:15:50] >> 100, 200, 25. I think all those answers could be
[01:15:53] 25. I think all those answers could be plausible for someone and taking that
[01:15:56] plausible for someone and taking that drudgery handing it over to machines
[01:16:00] drudgery handing it over to machines that is the history of civilization.
[01:16:03] that is the history of civilization. >> Yeah. I mean the hours spent debugging.
[01:16:06] >> Yeah. I mean the hours spent debugging. So the programming has so many painful
[01:16:10] So the programming has so many painful painful hours in it and now they're gone
[01:16:13] painful hours in it and now they're gone for the I mean for the most part it's
[01:16:15] for the I mean for the most part it's just fun.
[01:16:16] just fun. >> A lot of it is gone in a lot of mains
[01:16:18] >> A lot of it is gone in a lot of mains and the rest of it may be gone very
[01:16:20] and the rest of it may be gone very soon. So that's where some of the
[01:16:23] soon. So that's where some of the romanticism also comes in because pain
[01:16:26] romanticism also comes in because pain in the moment is difficult. It's hard.
[01:16:30] in the moment is difficult. It's hard. It's annoying. Pain in the rearview
[01:16:32] It's annoying. Pain in the rearview mirror is accomplishment, proud,
[01:16:36] mirror is accomplishment, proud, learning, steps forward, all the things,
[01:16:39] learning, steps forward, all the things, right? So we encompass all of this as
[01:16:41] right? So we encompass all of this as part of the human experience that we
[01:16:43] part of the human experience that we hate pain in the moment, but we cherish
[01:16:46] hate pain in the moment, but we cherish it when it's 5 minutes past and we don't
[01:16:49] it when it's 5 minutes past and we don't remember the the hardship. we just
[01:16:51] remember the the hardship. we just remember the progress.
[01:16:52] remember the progress. >> So certainly at the societal level, at
[01:16:54] >> So certainly at the societal level, at the u macroeconomic level, growth is
[01:16:57] the u macroeconomic level, growth is exciting, but the individual level
[01:16:58] exciting, but the individual level there's going to be a lot of anxiety,
[01:17:01] there's going to be a lot of anxiety, potentially a lot of suffering. So by
[01:17:03] potentially a lot of suffering. So by way of advice, if you're like a young
[01:17:06] way of advice, if you're like a young DHH or young developer programmer now,
[01:17:08] DHH or young developer programmer now, what would you what would you advise
[01:17:11] what would you what would you advise they do?
[01:17:12] they do? >> Don't try to anticipate anything. You
[01:17:14] >> Don't try to anticipate anything. You will literally go crazy because even the
[01:17:16] will literally go crazy because even the smartest brains in the business cannot
[01:17:20] smartest brains in the business cannot anticipate what two model hops from here
[01:17:23] anticipate what two model hops from here is going to look like.
[01:17:25] is going to look like. It's an absolute waste of time and you
[01:17:27] It's an absolute waste of time and you will develop an AI psychosis trying to
[01:17:30] will develop an AI psychosis trying to deduce what two years from now is going
[01:17:31] deduce what two years from now is going to look like. Focus on right now and
[01:17:33] to look like. Focus on right now and right now is the most incredible time to
[01:17:36] right now is the most incredible time to be into computers.
[01:17:39] be into computers. >> You can make them do the most amazing
[01:17:41] >> You can make them do the most amazing things if you lean in. If you
[01:17:45] things if you lean in. If you maybe for a hot moment force yourself
[01:17:49] maybe for a hot moment force yourself to learn where the state-of-the-art is,
[01:17:53] to learn where the state-of-the-art is, I double dog dare you not to get excited
[01:17:56] I double dog dare you not to get excited about what's possible. And uh would you
[01:17:58] about what's possible. And uh would you recommend building publicly?
[01:17:59] recommend building publicly? >> I think it's optional actually to build
[01:18:01] >> I think it's optional actually to build publicly.
[01:18:03] publicly. I think it's it's nice to do because
[01:18:04] I think it's it's nice to do because then you get to be part of a community
[01:18:06] then you get to be part of a community and there's some camaraderie in open
[01:18:09] and there's some camaraderie in open source. not some camaraderie, there's an
[01:18:11] source. not some camaraderie, there's an enormous amount of camaraderie. Open
[01:18:14] enormous amount of camaraderie. Open source is an incredible source of
[01:18:17] source is an incredible source of community and camaraderie. And it's also
[01:18:20] community and camaraderie. And it's also a great way to stem some of that
[01:18:22] a great way to stem some of that personal existential dread. If you're
[01:18:25] personal existential dread. If you're amongst other humans, you can get
[01:18:26] amongst other humans, you can get infected with good forms of mind
[01:18:29] infected with good forms of mind viruses, exciting forms of mind viruses,
[01:18:32] viruses, exciting forms of mind viruses, the ones that tell you that it's all
[01:18:33] the ones that tell you that it's all going to be okay and the future looks
[01:18:36] going to be okay and the future looks bright. And if we build a bunch of
[01:18:39] bright. And if we build a bunch of things together, we can do things none
[01:18:41] things together, we can do things none of us ever dreamed we could do. I was
[01:18:43] of us ever dreamed we could do. I was just talking to Ryan Hughes, who's been
[01:18:46] just talking to Ryan Hughes, who's been my main partner on Umachi almost since
[01:18:48] my main partner on Umachi almost since day one. And we were literally talking
[01:18:51] day one. And we were literally talking about yesterday how when we started on
[01:18:54] about yesterday how when we started on this journey together, our ambitions
[01:18:56] this journey together, our ambitions were very modest. We're just like, can
[01:18:58] were very modest. We're just like, can we get this DRO to not crash at 3:00
[01:19:01] we get this DRO to not crash at 3:00 a.m. because of an arch package that
[01:19:03] a.m. because of an arch package that just got pushed out outside of our
[01:19:05] just got pushed out outside of our control? That would be amazing. then
[01:19:07] control? That would be amazing. then it'd be great. Now we're leaning back
[01:19:09] it'd be great. Now we're leaning back and thinking, how can we take over the
[01:19:12] and thinking, how can we take over the world? How can we make Omachi go to
[01:19:16] world? How can we make Omachi go to Mars? How can we do everything we've
[01:19:20] Mars? How can we do everything we've ever dreamed of? And that level of
[01:19:23] ever dreamed of? And that level of ambition inflation is partly because
[01:19:25] ambition inflation is partly because things have gotten better with agents,
[01:19:27] things have gotten better with agents, but hugely also because we've surrounded
[01:19:30] but hugely also because we've surrounded ourselves with others excited about the
[01:19:32] ourselves with others excited about the same journey. And if you're just sitting
[01:19:36] same journey. And if you're just sitting in your little isolated cave worrying
[01:19:39] in your little isolated cave worrying about the future, yeah, you're going to
[01:19:40] about the future, yeah, you're going to go you're going to go a little nuts.
[01:19:42] go you're going to go a little nuts. >> I think if we learned anything during co
[01:19:46] >> I think if we learned anything during co is that people will go nuts sitting in
[01:19:49] is that people will go nuts sitting in their little cave inside by themselves
[01:19:51] their little cave inside by themselves worrying about what's going to happen.
[01:19:53] worrying about what's going to happen. That is indistinguishable from
[01:19:56] That is indistinguishable from depression, ruminating endlessly about
[01:20:00] depression, ruminating endlessly about things you can't control.
[01:20:01] things you can't control. >> Mhm. I'm sorry to channel some yins and
[01:20:05] >> Mhm. I'm sorry to channel some yins and wong here, but that's just loser talk.
[01:20:07] wong here, but that's just loser talk. You don't have to be a loser. You can
[01:20:10] You don't have to be a loser. You can choose to lean in and win. And win is
[01:20:15] choose to lean in and win. And win is very broadly defined as learning more,
[01:20:18] very broadly defined as learning more, making more, contributing more, being
[01:20:20] making more, contributing more, being part of more.
[01:20:23] part of more. And at the end of the day, what are your
[01:20:26] And at the end of the day, what are your choices? You don't have a choice, mate.
[01:20:29] choices? You don't have a choice, mate. >> The future's coming whether you like it
[01:20:31] >> The future's coming whether you like it or not. So, you might as well choose to
[01:20:33] or not. So, you might as well choose to be excited about it.
[01:20:34] be excited about it. >> But I mean, we should emphasize the fact
[01:20:36] >> But I mean, we should emphasize the fact that planning is nearly impossible with
[01:20:39] that planning is nearly impossible with AI. I mean, most of us plan our life a
[01:20:42] AI. I mean, most of us plan our life a little bit. When we're younger, you have
[01:20:44] little bit. When we're younger, you have like hopes and dreams. There's a reason
[01:20:46] like hopes and dreams. There's a reason you go to college, there's a plan
[01:20:47] you go to college, there's a plan underlying.
[01:20:48] underlying. >> I agree with that. I can see that. It is
[01:20:50] >> I agree with that. I can see that. It is kind of nuts that it's impossible to
[01:20:53] kind of nuts that it's impossible to really plan because like you really
[01:20:56] really plan because like you really don't know
[01:20:58] don't know >> uh if there will even be a claw coded
[01:21:01] >> uh if there will even be a claw coded codeex and cursor 6 months from now.
[01:21:04] codeex and cursor 6 months from now. Maybe it'll be you'll be talking to
[01:21:06] Maybe it'll be you'll be talking to WhatsApp. Maybe it'll be all open claw
[01:21:08] WhatsApp. Maybe it'll be all open claw type. Maybe it'll just all be voice.
[01:21:11] type. Maybe it'll just all be voice. Maybe a Machu will take over the world
[01:21:12] Maybe a Machu will take over the world and it'll be voice. Maybe it won't be
[01:21:14] and it'll be voice. Maybe it won't be operating systems anymore. You'll just
[01:21:16] operating systems anymore. You'll just there'll be this glowing orb that just
[01:21:18] there'll be this glowing orb that just you just talk to because if natural
[01:21:20] you just talk to because if natural language is enough to accomplish all
[01:21:23] language is enough to accomplish all tasks in life like what is life about
[01:21:26] tasks in life like what is life about like what are the major tasks you need
[01:21:27] like what are the major tasks you need to accomplish in life? If you can just
[01:21:29] to accomplish in life? If you can just do that with voice and it writes all the
[01:21:31] do that with voice and it writes all the programs for you and all the
[01:21:33] programs for you and all the systematized and what what are the jobs
[01:21:35] systematized and what what are the jobs needed then maybe it's more about the
[01:21:38] needed then maybe it's more about the service industry. Maybe there won't be
[01:21:40] service industry. Maybe there won't be programmers like agentic engineers at
[01:21:43] programmers like agentic engineers at all. And so yes, your advice is wise to
[01:21:47] all. And so yes, your advice is wise to focus on the moment, but that doesn't
[01:21:48] focus on the moment, but that doesn't mean that it's just a crazy roller
[01:21:51] mean that it's just a crazy roller coaster ride cuz we don't know what this
[01:21:53] coaster ride cuz we don't know what this December, what this January will look
[01:21:55] December, what this January will look like.
[01:21:55] like. >> We don't know. And therefore, we should
[01:21:58] >> We don't know. And therefore, we should choose to have faith that it's going to
[01:22:00] choose to have faith that it's going to pan out.
[01:22:01] pan out. That is my best advice
[01:22:04] That is my best advice towards fighting anxiety is that you
[01:22:08] towards fighting anxiety is that you have a choice to a large degree of how
[01:22:12] have a choice to a large degree of how to lean.
[01:22:14] to lean. >> Mhm.
[01:22:14] >> Mhm. >> Do you want to lean into poom?
[01:22:17] >> Do you want to lean into poom? Poom is going to happen. Whether you
[01:22:19] Poom is going to happen. Whether you lean into it or not,
[01:22:22] lean into it or not, you don't have control. But there's also
[01:22:24] you don't have control. But there's also actual daily schedule of how much
[01:22:26] actual daily schedule of how much learning are you doing, how much
[01:22:27] learning are you doing, how much building you're doing, how much uh uh
[01:22:30] building you're doing, how much uh uh diversification you're doing. And for
[01:22:32] diversification you're doing. And for example, I traveled across rural China
[01:22:34] example, I traveled across rural China recently and I did it quite deliberately
[01:22:37] recently and I did it quite deliberately because you're talking to people in
[01:22:40] because you're talking to people in China in rural anywhere where time moves
[01:22:44] China in rural anywhere where time moves much slower where there's no discussions
[01:22:47] much slower where there's no discussions about agentic engineering and the the
[01:22:50] about agentic engineering and the the time and I I started by uh going on the
[01:22:53] time and I I started by uh going on the on the Great Wall of China that's
[01:22:55] on the Great Wall of China that's timeless that spans centuries and you
[01:22:58] timeless that spans centuries and you know there was like this kind of tension
[01:23:00] know there was like this kind of tension of FOMO like maybe I'm missing out on
[01:23:02] of FOMO like maybe I'm missing out on something. But then I very deliberately
[01:23:05] something. But then I very deliberately wanted to find the timelessness of human
[01:23:08] wanted to find the timelessness of human existence. Really plug into the fact
[01:23:10] existence. Really plug into the fact that okay it always feels like
[01:23:12] that okay it always feels like everything is changing
[01:23:14] everything is changing throughout human history. Uh but you
[01:23:16] throughout human history. Uh but you know the universals are still true of
[01:23:19] know the universals are still true of what matters in life and I just wanted
[01:23:21] what matters in life and I just wanted to make keep connected to that.
[01:23:22] to make keep connected to that. >> You're not going to miss anything. This
[01:23:24] >> You're not going to miss anything. This is the part that actually grinded my
[01:23:27] is the part that actually grinded my gears in the early phases of this
[01:23:30] gears in the early phases of this transition. Everyone was so up in arms
[01:23:34] transition. Everyone was so up in arms that if you didn't, it's loops now. Oh,
[01:23:36] that if you didn't, it's loops now. Oh, no, no, we're done with loops. It's
[01:23:37] no, no, we're done with loops. It's graphs now. Oh, no, no, we're done with
[01:23:39] graphs now. Oh, no, no, we're done with that. It's it's harnesses this, right?
[01:23:41] that. It's it's harnesses this, right? They're constantly churning through the
[01:23:43] They're constantly churning through the frontier, which in one way is actually
[01:23:46] frontier, which in one way is actually very exciting. This is what happens when
[01:23:48] very exciting. This is what happens when a new field opens up. It's like a new
[01:23:50] a new field opens up. It's like a new portal and it's all spilling out. That's
[01:23:52] portal and it's all spilling out. That's exciting. But it also means that if I
[01:23:55] exciting. But it also means that if I had just been backpacking for the last
[01:23:57] had just been backpacking for the last year,
[01:23:58] year, hadn't touched the computer, hadn't
[01:24:01] hadn't touched the computer, hadn't witnessed this agentic moment, and I
[01:24:04] witnessed this agentic moment, and I just showed up yesterday, do you know
[01:24:06] just showed up yesterday, do you know what? I would have been caught up in two
[01:24:08] what? I would have been caught up in two weeks. There's not any accumulation,
[01:24:11] weeks. There's not any accumulation, which is in some ways a great relief. If
[01:24:14] which is in some ways a great relief. If you missed the past year, you can catch
[01:24:17] you missed the past year, you can catch up to the frontier in two weeks. If
[01:24:20] up to the frontier in two weeks. If you're a programmer who was out hiking
[01:24:21] you're a programmer who was out hiking the Himalayas for a year and you come
[01:24:24] the Himalayas for a year and you come back, you can catch up in two weeks. And
[01:24:26] back, you can catch up in two weeks. And this is actually the great credit to the
[01:24:29] this is actually the great credit to the progress we're experiencing. We have so
[01:24:31] progress we're experiencing. We have so many experiments running simultaneously
[01:24:34] many experiments running simultaneously right now that are constantly and
[01:24:36] right now that are constantly and ruthlessly sorting what works, what
[01:24:38] ruthlessly sorting what works, what doesn't work. You don't have to remember
[01:24:41] doesn't work. You don't have to remember even be part of that entire journey. You
[01:24:43] even be part of that entire journey. You can just show up for the results. But
[01:24:45] can just show up for the results. But the key step there when you come back
[01:24:48] the key step there when you come back for the backpacking journey is to uh be
[01:24:51] for the backpacking journey is to uh be willing to become a totally new
[01:24:52] willing to become a totally new different human because
[01:24:55] different human because things are changing so fast. I mean
[01:24:57] things are changing so fast. I mean literally if you left for the
[01:24:58] literally if you left for the backpacking journey in October last year
[01:25:01] backpacking journey in October last year and came back in April or May,
[01:25:04] and came back in April or May, >> you might as well have been in the cryo
[01:25:05] >> you might as well have been in the cryo chamber for 100 years.
[01:25:07] chamber for 100 years. >> It's like what what do you mean we're
[01:25:08] >> It's like what what do you mean we're not programming anymore? This it's a ve
[01:25:11] not programming anymore? This it's a ve it's a huge transformation. It's
[01:25:12] it's a huge transformation. It's startling. And I actually I mean I'm
[01:25:15] startling. And I actually I mean I'm putting some of this on slightly for
[01:25:17] putting some of this on slightly for effect. I also recognize that it's okay
[01:25:21] effect. I also recognize that it's okay to grief for a hot moment. That's not my
[01:25:23] to grief for a hot moment. That's not my disposition. It's not how I do it. But I
[01:25:26] disposition. It's not how I do it. But I accept that that's a
[01:25:29] accept that that's a timetested
[01:25:31] timetested mechanism for coping with a sense of
[01:25:35] mechanism for coping with a sense of loss. And it's okay to have a sense of
[01:25:37] loss. And it's okay to have a sense of loss that the world that you knew and
[01:25:39] loss that the world that you knew and maybe were very fond of is no longer the
[01:25:43] maybe were very fond of is no longer the same.
[01:25:43] same. >> I maybe I should say out loud and
[01:25:45] >> I maybe I should say out loud and explicitly that I do have that the
[01:25:47] explicitly that I do have that the Native American with a tear rolling down
[01:25:49] Native American with a tear rolling down my like there's a sadness. It's a
[01:25:52] my like there's a sadness. It's a goodbye. It's a goodbye to the old world
[01:25:54] goodbye. It's a goodbye to the old world of programming.
[01:25:55] of programming. >> It's so fascinating to me. I've spent so
[01:25:58] >> It's so fascinating to me. I've spent so many years but it all amounted to this
[01:26:00] many years but it all amounted to this moment. That is to me what makes the
[01:26:03] moment. That is to me what makes the entire journey so meaningful. AI did not
[01:26:06] entire journey so meaningful. AI did not arrive from the sky. It was not alien
[01:26:08] arrive from the sky. It was not alien technology that had blasted through the
[01:26:10] technology that had blasted through the universe and suddenly showed up on our
[01:26:12] universe and suddenly showed up on our shores. AI has been around for as long
[01:26:15] shores. AI has been around for as long as computer science has been around in
[01:26:18] as computer science has been around in the 50s. They thought the problem was
[01:26:20] the 50s. They thought the problem was going to be cracked in about a decade.
[01:26:22] going to be cracked in about a decade. the smartest people at the time. It took
[01:26:24] the smartest people at the time. It took a little longer, but the reason it took
[01:26:26] a little longer, but the reason it took a little longer was in part because we
[01:26:29] a little longer was in part because we took some blind turns on the road to AI
[01:26:32] took some blind turns on the road to AI and neural networks and thought that
[01:26:34] and neural networks and thought that there were other symbolic
[01:26:36] there were other symbolic representations that were going to carry
[01:26:37] representations that were going to carry the day and they didn't. And that
[01:26:39] the day and they didn't. And that probably set us back about 15 years.
[01:26:42] probably set us back about 15 years. Some of it was also we had to um go
[01:26:45] Some of it was also we had to um go through the gaming revolution, 3D games.
[01:26:47] through the gaming revolution, 3D games. If we had not had Quake, if we had not
[01:26:50] If we had not had Quake, if we had not had Duke Nukem, if we had not had Unreal
[01:26:52] had Duke Nukem, if we had not had Unreal Tournament, we'd never have gotten AI
[01:26:54] Tournament, we'd never have gotten AI because we would never gotten the GPUs
[01:26:56] because we would never gotten the GPUs and therefore we would never been able
[01:26:57] and therefore we would never been able to get AI in the shape it is now. So
[01:27:01] to get AI in the shape it is now. So everything we did up until this moment
[01:27:03] everything we did up until this moment was required to get there.
[01:27:06] was required to get there. >> You were part of that. Holy, what a
[01:27:09] >> You were part of that. Holy, what a blessing. What a blessing to have
[01:27:11] blessing. What a blessing to have contributed in your small part either by
[01:27:14] contributed in your small part either by training or by playing video games.
[01:27:16] training or by playing video games. Literally, you could just choose to
[01:27:18] Literally, you could just choose to think of it that way. All those times
[01:27:19] think of it that way. All those times you spent in, for my case, in the 90s
[01:27:22] you spent in, for my case, in the 90s just playing video games,
[01:27:23] just playing video games, >> you were contributing.
[01:27:24] >> you were contributing. >> Yeah. I was contributing to the AI
[01:27:26] >> Yeah. I was contributing to the AI revolution right there in that moment
[01:27:27] revolution right there in that moment >> to the progress of human civilization.
[01:27:29] >> to the progress of human civilization. No, for sure. Civilization progresses
[01:27:32] No, for sure. Civilization progresses with the death of the old and the birth
[01:27:34] with the death of the old and the birth of the new and it continues in this way.
[01:27:36] of the new and it continues in this way. But it's still the grieving process is a
[01:27:38] But it's still the grieving process is a part of it. I think
[01:27:39] part of it. I think >> take a moment. It's okay. Take a And
[01:27:42] >> take a moment. It's okay. Take a And also, you don't even have to accept that
[01:27:44] also, you don't even have to accept that it's all dead. Like if you are still
[01:27:47] it's all dead. Like if you are still very uh attached to the hand chiseling,
[01:27:52] very uh attached to the hand chiseling, which if you had asked me a year ago, I
[01:27:54] which if you had asked me a year ago, I would have predicted that I would have
[01:27:56] would have predicted that I would have been more attached. I've surprised
[01:27:59] been more attached. I've surprised >> I'm kind of surprised
[01:28:00] >> I'm kind of surprised >> a little that I've not been more
[01:28:02] >> a little that I've not been more attached. But the reason I've not been
[01:28:03] attached. But the reason I've not been more attached, I think, is that I found
[01:28:05] more attached, I think, is that I found something more fun.
[01:28:07] something more fun. And
[01:28:09] And if it hadn't been like that, if AI had
[01:28:11] if it hadn't been like that, if AI had just replaced the thing I loved and gave
[01:28:14] just replaced the thing I loved and gave me something I hated, I'd probably be a
[01:28:16] me something I hated, I'd probably be a little bit better.
[01:28:16] little bit better. >> I mean, this really feels it's hilarious
[01:28:18] >> I mean, this really feels it's hilarious and awesome to watch and inspiring to
[01:28:20] and awesome to watch and inspiring to watch. It's like Picasso all of a sudden
[01:28:23] watch. It's like Picasso all of a sudden like getting access to uh to image
[01:28:27] like getting access to uh to image generation and getting super excited and
[01:28:30] generation and getting super excited and switching in a matter of month. That's
[01:28:31] switching in a matter of month. That's literally what happened. So like it's an
[01:28:33] literally what happened. So like it's an artist that appreciated beautiful code
[01:28:35] artist that appreciated beautiful code and all of a sudden you're talking about
[01:28:37] and all of a sudden you're talking about having fun.
[01:28:38] having fun. >> I think Kaso is actually a good parallel
[01:28:40] >> I think Kaso is actually a good parallel because if you look at his early work
[01:28:42] because if you look at his early work where he learned his craft, it was
[01:28:45] where he learned his craft, it was painting realistic paintings, right?
[01:28:49] painting realistic paintings, right? Like he was training to be a master of
[01:28:52] Like he was training to be a master of the old ways of depicting reality the
[01:28:55] the old ways of depicting reality the best way we knew how. And then along
[01:28:57] best way we knew how. And then along comes all these other forms of
[01:28:59] comes all these other forms of expression. cubism comes along and all
[01:29:03] expression. cubism comes along and all these other forms of abstract
[01:29:05] these other forms of abstract expression. He's not decrying that he's
[01:29:08] expression. He's not decrying that he's not doing Renaissance paintings anymore,
[01:29:11] not doing Renaissance paintings anymore, that he's not just painting the perfect
[01:29:13] that he's not just painting the perfect depiction of an apple. He's reimagining
[01:29:16] depiction of an apple. He's reimagining the apple to be a freaking square. And
[01:29:19] the apple to be a freaking square. And he's getting excited about that. And I
[01:29:21] he's getting excited about that. And I feel that transition that we've gone
[01:29:24] feel that transition that we've gone from this one mode of expression and
[01:29:27] from this one mode of expression and we've suddenly opened the gates where
[01:29:31] we've suddenly opened the gates where like the color spectrum is so much
[01:29:33] like the color spectrum is so much wider. I'm seeing more and it's perhaps
[01:29:38] wider. I'm seeing more and it's perhaps because the way I became a programmer. I
[01:29:41] because the way I became a programmer. I did not become a programmer because a
[01:29:43] did not become a programmer because a deep love of if statements. I became a
[01:29:47] deep love of if statements. I became a programmer because I wanted programs. I
[01:29:50] programmer because I wanted programs. I wanted things to exist that did not
[01:29:52] wanted things to exist that did not exist. And at first I had to learn how
[01:29:54] exist. And at first I had to learn how to program to make that happen. Then I
[01:29:57] to program to make that happen. Then I happened to fall in love with
[01:29:59] happened to fall in love with programming as a craft. And then I spent
[01:30:00] programming as a craft. And then I spent two decades really diving deep on that.
[01:30:03] two decades really diving deep on that. But now I'm back. I'm back to
[01:30:07] But now I'm back. I'm back to having an idea and being impatient
[01:30:10] having an idea and being impatient beyond belief to see it exist in the
[01:30:13] beyond belief to see it exist in the world. and AI has just shrunk that down
[01:30:17] world. and AI has just shrunk that down to almost nothing. So, it's an
[01:30:20] to almost nothing. So, it's an acceleration of a of a rediscovery.
[01:30:23] acceleration of a of a rediscovery. Now, I understand that that's not true
[01:30:26] Now, I understand that that's not true for everyone. There are plenty of
[01:30:27] for everyone. There are plenty of programmers who just loved programming
[01:30:29] programmers who just loved programming right from the beginning and they were
[01:30:30] right from the beginning and they were attracted to the logical constructs and
[01:30:33] attracted to the logical constructs and so forth. I mean, I've been there for
[01:30:34] so forth. I mean, I've been there for two decades, so I get it.
[01:30:37] two decades, so I get it. But I also think that you're able to
[01:30:40] But I also think that you're able to discover new sides of yourself if you
[01:30:42] discover new sides of yourself if you let it in. Again, I keep coming back to
[01:30:45] let it in. Again, I keep coming back to this almost regret minimization
[01:30:48] this almost regret minimization framework to borrow Jeff Bezos's terms
[01:30:51] framework to borrow Jeff Bezos's terms here. Are you going to look at yourself
[01:30:54] here. Are you going to look at yourself two years from now and think, "Oh, I
[01:30:56] two years from now and think, "Oh, I spent my time well being pissy about the
[01:30:59] spent my time well being pissy about the present, about the fact that my industry
[01:31:02] present, about the fact that my industry changed." Or would I two years from now
[01:31:06] changed." Or would I two years from now look back upon this moment and be proud
[01:31:08] look back upon this moment and be proud of myself for leaning in for maybe
[01:31:11] of myself for leaning in for maybe having a moment of grief again? There's
[01:31:13] having a moment of grief again? There's room for all of it and then going I'm
[01:31:16] room for all of it and then going I'm going to learn how the world spins now
[01:31:18] going to learn how the world spins now and I'm going to make not just the best
[01:31:19] and I'm going to make not just the best of it. I'm going to make more of it. I
[01:31:22] of it. I'm going to make more of it. I mean it is true. A lot of programmers, a
[01:31:25] mean it is true. A lot of programmers, a lot of friends of mine, me obviously you
[01:31:28] lot of friends of mine, me obviously you are having fun. I have had more fun with
[01:31:33] are having fun. I have had more fun with computers in the last three months than
[01:31:36] computers in the last three months than at any time previously.
[01:31:39] at any time previously. >> Quick bathroom break and then I got to
[01:31:41] >> Quick bathroom break and then I got to ask you about uh how you actually
[01:31:44] ask you about uh how you actually interact with the systems now.
[01:31:45] interact with the systems now. >> Yes.
[01:31:46] >> Yes. >> I got to ask you about uh how is your
[01:31:49] >> I got to ask you about uh how is your setup uh programming setup changed? So
[01:31:54] setup uh programming setup changed? So keyboard, voice,
[01:31:56] keyboard, voice, what's the IDE? It's crazy to think
[01:31:59] what's the IDE? It's crazy to think about now, but yeah, I used Textmade for
[01:32:01] about now, but yeah, I used Textmade for almost 20 years.
[01:32:03] almost 20 years. >> I used Textmade starting in
[01:32:06] >> I used Textmade starting in 2005, I think. I helped get the first
[01:32:08] 2005, I think. I helped get the first version out and then I just wasn't
[01:32:10] version out and then I just wasn't interested. I wasn't in the market for
[01:32:12] interested. I wasn't in the market for an alternative. And it wasn't until the
[01:32:15] an alternative. And it wasn't until the switch to Linux that I was forced out of
[01:32:19] switch to Linux that I was forced out of my habitat. And now with the switch to
[01:32:24] my habitat. And now with the switch to what are we calling it? Aentic
[01:32:26] what are we calling it? Aentic engineering. I hate that term.
[01:32:28] engineering. I hate that term. We got to come up with something that
[01:32:30] We got to come up with something that sounds as plain as programming but
[01:32:33] sounds as plain as programming but encapsulates the fact that it's with
[01:32:34] encapsulates the fact that it's with agents. But
[01:32:35] agents. But >> I still think it should be called
[01:32:36] >> I still think it should be called programming.
[01:32:37] programming. >> All right, let's just call it
[01:32:37] >> All right, let's just call it programming.
[01:32:38] programming. >> Yeah,
[01:32:38] >> Yeah, >> the programming with agents requires a
[01:32:41] >> the programming with agents requires a different tool set. It really does. And
[01:32:43] different tool set. It really does. And the main change here is that
[01:32:48] the main change here is that you're going from single threat
[01:32:50] you're going from single threat programming in your head to parallel
[01:32:52] programming in your head to parallel processing.
[01:32:54] processing. When I was writing code, chiseling it by
[01:32:56] When I was writing code, chiseling it by hand in text mate or even neoim uh not
[01:33:00] hand in text mate or even neoim uh not that long ago, I would just focus on one
[01:33:02] that long ago, I would just focus on one problem at the time and I would
[01:33:04] problem at the time and I would methodically work my way through it and
[01:33:06] methodically work my way through it and that was actually the portal to flow.
[01:33:07] that was actually the portal to flow. The portal to flow was deep immersion
[01:33:11] The portal to flow was deep immersion into a single problem, see it through to
[01:33:13] into a single problem, see it through to the end.
[01:33:14] the end. >> Mh.
[01:33:15] >> Mh. >> That's not how it works with agents. In
[01:33:18] >> That's not how it works with agents. In part because the agents are at once both
[01:33:21] part because the agents are at once both too fast and too slow. They don't give
[01:33:24] too fast and too slow. They don't give you an immediate
[01:33:26] you an immediate reply on something that you asked them
[01:33:29] reply on something that you asked them to do. That's the same as typing on a
[01:33:32] to do. That's the same as typing on a keyboard. So, you have to let the agent
[01:33:34] keyboard. So, you have to let the agent cook
[01:33:35] cook >> for a bit. And therefore, you realize,
[01:33:38] >> for a bit. And therefore, you realize, well, if I just sit around waiting for
[01:33:41] well, if I just sit around waiting for them, first of all, that doesn't feel
[01:33:43] them, first of all, that doesn't feel productive. Even if the agent, just one
[01:33:45] productive. Even if the agent, just one of them can be highly productive, it
[01:33:47] of them can be highly productive, it does not feel productive. Doesn't it
[01:33:48] does not feel productive. Doesn't it feel good? It feels actually like you're
[01:33:49] feel good? It feels actually like you're a little bit useless. Mhm.
[01:33:51] a little bit useless. Mhm. >> And maybe I had a moment when the first
[01:33:54] >> And maybe I had a moment when the first aentic moment was there and we I was
[01:33:56] aentic moment was there and we I was running mostly one agent at a time where
[01:33:58] running mostly one agent at a time where I felt like I don't know about this but
[01:34:01] I felt like I don't know about this but you can solve a lot of hard problems by
[01:34:04] you can solve a lot of hard problems by gly throwing more resources at it. This
[01:34:06] gly throwing more resources at it. This is the uh whole scaling law of AI of
[01:34:09] is the uh whole scaling law of AI of itself, right? That if you paralyze
[01:34:12] itself, right? That if you paralyze these things and you're not running one
[01:34:14] these things and you're not running one agent, but you're running a handful, you
[01:34:16] agent, but you're running a handful, you can um feel like you're in a flow state
[01:34:20] can um feel like you're in a flow state because you're constantly doing
[01:34:23] because you're constantly doing programming work in the sense that
[01:34:24] programming work in the sense that you're making decisions and you're
[01:34:26] you're making decisions and you're helping either unblock an agent because
[01:34:28] helping either unblock an agent because it has an question about which direction
[01:34:30] it has an question about which direction to take or you're ready for a new task.
[01:34:32] to take or you're ready for a new task. And to do that, you need a different
[01:34:34] And to do that, you need a different setup. I started first doing it in
[01:34:37] setup. I started first doing it in T-Mugs and just having separate PES and
[01:34:40] T-Mugs and just having separate PES and having separate splits. Basically a
[01:34:43] having separate splits. Basically a terminal with tabs is a good way to
[01:34:44] terminal with tabs is a good way to think about you open a bunch of tabs. I
[01:34:46] think about you open a bunch of tabs. I think most humans know exactly how that
[01:34:48] think most humans know exactly how that works. They don't work in just one tab.
[01:34:50] works. They don't work in just one tab. >> So uh still sticking to the terminal
[01:34:52] >> So uh still sticking to the terminal CLI.
[01:34:53] CLI. >> Absolutely. So you're not using cloud
[01:34:55] >> Absolutely. So you're not using cloud code app or the codeex app or the
[01:34:58] code app or the codeex app or the >> I love the fact that this agent
[01:35:00] >> I love the fact that this agent revolution was kicked off in the
[01:35:02] revolution was kicked off in the terminal because I was already a huge
[01:35:04] terminal because I was already a huge fan of two terminal user interfaces and
[01:35:07] fan of two terminal user interfaces and the terminal in general that feels like
[01:35:09] the terminal in general that feels like a a really nice place to be. It's a
[01:35:12] a a really nice place to be. It's a beautiful place to be. The modern
[01:35:14] beautiful place to be. The modern terminal is just a good looking place to
[01:35:17] terminal is just a good looking place to work. So I like that. And um and then
[01:35:22] work. So I like that. And um and then this fact of having multiple agents
[01:35:25] this fact of having multiple agents especially once it's not just multiple
[01:35:27] especially once it's not just multiple agents running on your own machine but
[01:35:29] agents running on your own machine but you start running multiple machines. Now
[01:35:32] you start running multiple machines. Now T-Mugs alone is not enough to keep track
[01:35:36] T-Mugs alone is not enough to keep track of it. And that's why as of late I've
[01:35:38] of it. And that's why as of late I've switched to this thing called herder.
[01:35:41] switched to this thing called herder. And herder is essentially T-mugs plus
[01:35:44] And herder is essentially T-mugs plus agent notifications. So whenever your
[01:35:46] agent notifications. So whenever your agent is done or needs something for you
[01:35:48] agent is done or needs something for you goes ding
[01:35:50] goes ding a little uh a little bell telling you
[01:35:53] a little uh a little bell telling you it's ready for its human uh is it is it
[01:35:56] it's ready for its human uh is it is it master or servant I'm not quite sure
[01:35:58] master or servant I'm not quite sure always but it is ready for a decision
[01:36:01] always but it is ready for a decision and it also keeps track of these is it
[01:36:03] and it also keeps track of these is it is working mode or not. So I have this
[01:36:05] is working mode or not. So I have this herder setup I have multiple herder
[01:36:08] herder setup I have multiple herder setups actually running on individual
[01:36:10] setups actually running on individual machines. I went on this crazy phase
[01:36:13] machines. I went on this crazy phase just about a month ago realizing that
[01:36:16] just about a month ago realizing that doing this work on a single machine is
[01:36:19] doing this work on a single machine is not fast enough. It's like I've
[01:36:21] not fast enough. It's like I've discovered multi-core programming, but I
[01:36:22] discovered multi-core programming, but I only have two cores. And I'm like, what
[01:36:24] only have two cores. And I'm like, what if I had 16 cores? What if I had 32
[01:36:26] if I had 16 cores? What if I had 32 cores? What if I had 64 cores? So, I
[01:36:28] cores? What if I had 64 cores? So, I instantly went out and I bought these
[01:36:30] instantly went out and I bought these amazing KVMs called GLI.NET
[01:36:34] amazing KVMs called GLI.NET comets.
[01:36:35] comets. >> Mhm.
[01:36:36] >> Mhm. >> And what they do is it's this little
[01:36:37] >> And what they do is it's this little box. You plug in HDMI, you plug in um
[01:36:42] box. You plug in HDMI, you plug in um USB and connect it to the computer. It's
[01:36:43] USB and connect it to the computer. It's like a KVM. So KVM is a a remote way of
[01:36:46] like a KVM. So KVM is a a remote way of controlling a computer. But what's
[01:36:48] controlling a computer. But what's special about this is just how easy it
[01:36:50] special about this is just how easy it was. You connect this thing in, you go
[01:36:52] was. You connect this thing in, you go to a web page, log in once, set one
[01:36:56] to a web page, log in once, set one password, now this thing can hop on your
[01:36:58] password, now this thing can hop on your tail.
[01:36:59] tail. >> Mhm. This has been the other revolution
[01:37:02] >> Mhm. This has been the other revolution of the last year for me is discovering
[01:37:06] of the last year for me is discovering these wire guard networks. Tail scale is
[01:37:11] these wire guard networks. Tail scale is essentially turning all the computers
[01:37:13] essentially turning all the computers you have into a local network wherever
[01:37:15] you have into a local network wherever you are.
[01:37:16] you are. >> Like right now on my phone, I have
[01:37:18] >> Like right now on my phone, I have direct access to all the computers in my
[01:37:21] direct access to all the computers in my Malibu office. I also have access to all
[01:37:24] Malibu office. I also have access to all my computers in my Copenhagen office
[01:37:26] my computers in my Copenhagen office >> and I can treat them as though I sat
[01:37:28] >> and I can treat them as though I sat right next to them. without having to
[01:37:30] right next to them. without having to punch holes in a firewall or set up
[01:37:32] punch holes in a firewall or set up complicated VPNs. And what this does is
[01:37:36] complicated VPNs. And what this does is it just decreases the friction it takes
[01:37:38] it just decreases the friction it takes to get new compute online.
[01:37:41] to get new compute online. >> So, as soon as I discovered this, I
[01:37:44] >> So, as soon as I discovered this, I looked in my closet and I realized I had
[01:37:46] looked in my closet and I realized I had a bunch of mini PCs from prior
[01:37:48] a bunch of mini PCs from prior experiments. I just like, what if I just
[01:37:50] experiments. I just like, what if I just connected all of them?
[01:37:51] connected all of them? >> Oh, wow.
[01:37:51] >> Oh, wow. >> And I just connected four of the
[01:37:53] >> And I just connected four of the computers in a closet. They all had
[01:37:55] computers in a closet. They all had their little comet and suddenly I could
[01:37:59] their little comet and suddenly I could run agents on more computers at the same
[01:38:01] run agents on more computers at the same time and I could control them all with
[01:38:03] time and I could control them all with Herder and it did get to a point where I
[01:38:06] Herder and it did get to a point where I maxed out my own processing power that I
[01:38:10] maxed out my own processing power that I think at about
[01:38:12] think at about what do I want to put it about four to
[01:38:14] what do I want to put it about four to five machines running
[01:38:17] five machines running >> I don't know three agents I have about
[01:38:19] >> I don't know three agents I have about 16 threads that's what I can run and the
[01:38:22] 16 threads that's what I can run and the faster the agents run of course the
[01:38:23] faster the agents run of course the fewer threads I can run but at current
[01:38:25] fewer threads I can run but at current pace I can run about 16 threads
[01:38:27] pace I can run about 16 threads >> at at full acceleration.
[01:38:30] >> at at full acceleration. And that's part of why I've gone from
[01:38:34] And that's part of why I've gone from just being excited about the agent
[01:38:36] just being excited about the agent moment to being delirious because I
[01:38:39] moment to being delirious because I think as you say some of it is a little
[01:38:42] think as you say some of it is a little assaulting as again we're on we're on a
[01:38:45] assaulting as again we're on we're on a dialup bandwidth wise with our computer.
[01:38:48] dialup bandwidth wise with our computer. I mean it's actually hilarious. So you
[01:38:50] I mean it's actually hilarious. So you think of I'm sitting here a year ago
[01:38:52] think of I'm sitting here a year ago right? I'm chiseling my code. I'm
[01:38:54] right? I'm chiseling my code. I'm writing my lines and over the course of
[01:38:56] writing my lines and over the course of like an hour I will have written one
[01:39:00] like an hour I will have written one beautiful controller or one beautiful
[01:39:01] beautiful controller or one beautiful model like that's one file and I've
[01:39:04] model like that's one file and I've really worked on it right so maybe
[01:39:06] really worked on it right so maybe there's 60 lines left so maybe my
[01:39:08] there's 60 lines left so maybe my bandwidth at this moment is like
[01:39:11] bandwidth at this moment is like 30 lines an hour I think that's even
[01:39:12] 30 lines an hour I think that's even high maybe it's 20 lines an hour now I'm
[01:39:15] high maybe it's 20 lines an hour now I'm running 16 threads I'm producing at
[01:39:19] running 16 threads I'm producing at sometimes hundreds of lines of hour or
[01:39:22] sometimes hundreds of lines of hour or hundreds of lines of code per power.
[01:39:24] hundreds of lines of code per power. Now, let me pause myself there for a hot
[01:39:26] Now, let me pause myself there for a hot moment. I hate that metric, right? Like
[01:39:29] moment. I hate that metric, right? Like lines of code is a stupid metric in
[01:39:31] lines of code is a stupid metric in general to measure these things. And I
[01:39:33] general to measure these things. And I think it's right from some in the
[01:39:36] think it's right from some in the programming community to ridicule the AI
[01:39:38] programming community to ridicule the AI psychosis when everyone talks about the
[01:39:40] psychosis when everyone talks about the number of lines of code they're writing
[01:39:42] number of lines of code they're writing and then you ask them what did you build
[01:39:44] and then you ask them what did you build and then like and then no good answer
[01:39:47] and then like and then no good answer comes out, right?
[01:39:48] comes out, right? >> It's just a nice shorthand.
[01:39:49] >> It's just a nice shorthand. >> It is a nice short hand. It is a
[01:39:51] >> It is a nice short hand. It is a representation or encapsulation of how
[01:39:54] representation or encapsulation of how much output that's coming out now
[01:39:55] much output that's coming out now whether the output is good or bad
[01:39:58] whether the output is good or bad >> is not a referendum on that but I was
[01:40:00] >> is not a referendum on that but I was producing am producing so much more now
[01:40:02] producing am producing so much more now right and therefore I'm able to keep all
[01:40:04] right and therefore I'm able to keep all these threads going so that's the setup
[01:40:07] these threads going so that's the setup it's still neoim but at this point I'm
[01:40:10] it's still neoim but at this point I'm not writing a lot of code so I'm using
[01:40:12] not writing a lot of code so I'm using neovim as a project browser and then as
[01:40:15] neovim as a project browser and then as a way to kick off uh lacit to see the
[01:40:17] a way to kick off uh lacit to see the change log for what's there. And even
[01:40:21] change log for what's there. And even that, I'd say if GitHub was a little
[01:40:24] that, I'd say if GitHub was a little faster at showing you your pull request,
[01:40:26] faster at showing you your pull request, the web is probably actually a nicer
[01:40:28] the web is probably actually a nicer place to do that. I don't know. There's
[01:40:30] place to do that. I don't know. There's also this other tool I've been playing
[01:40:32] also this other tool I've been playing with a bit called Hunk, which just
[01:40:34] with a bit called Hunk, which just produces uh diffs in a really nice way.
[01:40:37] produces uh diffs in a really nice way. So, you could look at that, too. But I
[01:40:38] So, you could look at that, too. But I find that when I look at Hunk, I only
[01:40:40] find that when I look at Hunk, I only see the change set. And when I'm
[01:40:42] see the change set. And when I'm reviewing output from an agent, I often
[01:40:44] reviewing output from an agent, I often want to see the surrounding context. Oh,
[01:40:46] want to see the surrounding context. Oh, yeah. So changed this file, but actually
[01:40:48] yeah. So changed this file, but actually what do we have in this other file that
[01:40:49] what do we have in this other file that wasn't touched but maybe should have
[01:40:51] wasn't touched but maybe should have been touched. So that's why I still like
[01:40:53] been touched. So that's why I still like Neovim as a way of doing it. Um, but
[01:40:56] Neovim as a way of doing it. Um, but it's all happening by the way of course
[01:40:58] it's all happening by the way of course in Amachi. So it's all happening on
[01:41:00] in Amachi. So it's all happening on Linux. And this was the other major
[01:41:02] Linux. And this was the other major breakthrough with agents. Agents love
[01:41:05] breakthrough with agents. Agents love the Unix philosophy. It loves individual
[01:41:09] the Unix philosophy. It loves individual tools that it can invoke through the
[01:41:11] tools that it can invoke through the command line. And there is no operating
[01:41:14] command line. And there is no operating system on earth of the majors. I'm
[01:41:17] system on earth of the majors. I'm counting three here. Mac, Windows,
[01:41:19] counting three here. Mac, Windows, Linux, that works as well with that
[01:41:24] Linux, that works as well with that mechanism as Linux. Everything in Linux
[01:41:26] mechanism as Linux. Everything in Linux is either a config file or a CLI tool.
[01:41:30] is either a config file or a CLI tool. Now, that was its main drawback five
[01:41:33] Now, that was its main drawback five minutes ago. This was the reason people
[01:41:35] minutes ago. This was the reason people didn't like Linux. It's like it's all
[01:41:37] didn't like Linux. It's like it's all config files and CLI tools.
[01:41:40] config files and CLI tools. >> What great irony.
[01:41:42] >> What great irony. that the universe has played upon us
[01:41:44] that the universe has played upon us that now the drawbacks of Linux five
[01:41:47] that now the drawbacks of Linux five minutes ago are now its major selling
[01:41:49] minutes ago are now its major selling points. This was one of the things I
[01:41:52] points. This was one of the things I thought I was stuck for a weekend with a
[01:41:55] thought I was stuck for a weekend with a Mac uh four months ago. I thought I had
[01:41:59] Mac uh four months ago. I thought I had a computer the place I was going that
[01:42:01] a computer the place I was going that was a Linux machine so I didn't bring my
[01:42:03] was a Linux machine so I didn't bring my laptop and I I found out when I arrived
[01:42:06] laptop and I I found out when I arrived I only had a Mac Mini. So, I was going
[01:42:09] I only had a Mac Mini. So, I was going to make the best of a bad situation here
[01:42:12] to make the best of a bad situation here and u set up my Mac in some of the ways
[01:42:15] and u set up my Mac in some of the ways I've been thinking about with um with
[01:42:18] I've been thinking about with um with Linux. And you can actually do a lot
[01:42:20] Linux. And you can actually do a lot now. Homebrew has gotten really quite
[01:42:22] now. Homebrew has gotten really quite good. Homebrew is the missing package
[01:42:24] good. Homebrew is the missing package manager for the Mac and no one has done
[01:42:27] manager for the Mac and no one has done more to move the Mac forward in terms of
[01:42:30] more to move the Mac forward in terms of ease of setup. But still something as
[01:42:33] ease of setup. But still something as simple as Raycast. I don't know if
[01:42:34] simple as Raycast. I don't know if you've used that. That's the
[01:42:37] you've used that. That's the >> There's no config file that you can just
[01:42:39] >> There's no config file that you can just access. You have to go into the guey,
[01:42:42] access. You have to go into the guey, export a file, then take that file, I
[01:42:45] export a file, then take that file, I don't know, in your freaking backpack on
[01:42:47] don't know, in your freaking backpack on a USB key,
[01:42:49] a USB key, >> and then you can import it somewhere
[01:42:50] >> and then you can import it somewhere else. You cannot automate the entire
[01:42:52] else. You cannot automate the entire setup of your machine. You can't
[01:42:54] setup of your machine. You can't automate at all the configuration of Mac
[01:42:58] automate at all the configuration of Mac default key bindings. Mhm.
[01:43:00] default key bindings. Mhm. >> That has to be a manual process where
[01:43:02] >> That has to be a manual process where you're clicking with a mouse like a
[01:43:03] you're clicking with a mouse like a caveman to set up your machine.
[01:43:06] caveman to set up your machine. >> I mean there is ways around it.
[01:43:08] >> I mean there is ways around it. >> Not good ones. I looked I tried hard.
[01:43:11] >> Not good ones. I looked I tried hard. >> So here's here's my been my journey.
[01:43:13] >> So here's here's my been my journey. Obviously I'm a Linux person but because
[01:43:15] Obviously I'm a Linux person but because of Adobe Premiere Adobe products I'm
[01:43:17] of Adobe Premiere Adobe products I'm also a Windows person. So often times I
[01:43:19] also a Windows person. So often times I would use WSL Windows subsystems for
[01:43:22] would use WSL Windows subsystems for Linux. So Linux inside Windows, which is
[01:43:25] Linux. So Linux inside Windows, which is a in the agentic era, is not a good kind
[01:43:27] a in the agentic era, is not a good kind of Linux cuz it's just
[01:43:29] of Linux cuz it's just >> it's a sandbox.
[01:43:30] >> it's a sandbox. >> It's a sandbox and you want the Linux to
[01:43:32] >> It's a sandbox and you want the Linux to be unleashed to be able to do
[01:43:33] be unleashed to be able to do everything.
[01:43:34] everything. >> Correct.
[01:43:34] >> Correct. >> And so I have now woken up to things
[01:43:37] >> And so I have now woken up to things like Raycast and you know I'm a keyboard
[01:43:40] like Raycast and you know I'm a keyboard person. Where's the config files? Can I
[01:43:43] person. Where's the config files? Can I can I um can I basically do everything
[01:43:46] can I um can I basically do everything where an agent can can set everything up
[01:43:48] where an agent can can set everything up for me and save the configuration so I
[01:43:50] for me and save the configuration so I can replicate across systems and
[01:43:52] can replicate across systems and everything is automated. And so I had to
[01:43:54] everything is automated. And so I had to ask a lot of those questions and a lot
[01:43:56] ask a lot of those questions and a lot of them are missing.
[01:43:57] of them are missing. >> They don't have good answers.
[01:43:58] >> They don't have good answers. >> But often times you could actually just
[01:44:00] >> But often times you could actually just build the app yourself
[01:44:02] build the app yourself >> but there are hacks.
[01:44:03] >> but there are hacks. >> They're hacks.
[01:44:04] >> They're hacks. >> There are hacks. You don't have to live
[01:44:05] >> There are hacks. You don't have to live like this Lex. There's a better
[01:44:07] like this Lex. There's a better Actually, this is a great moment
[01:44:09] Actually, this is a great moment >> until you have a video editor.
[01:44:11] >> until you have a video editor. >> So, this is a good moment.
[01:44:13] >> So, this is a good moment. >> Yeah.
[01:44:13] >> Yeah. >> Um, I heard it was your birthday.
[01:44:16] >> Um, I heard it was your birthday. >> Yeah.
[01:44:16] >> Yeah. >> So, uh, I brought a little gift.
[01:44:18] >> So, uh, I brought a little gift. >> No.
[01:44:19] >> No. >> We are going to get you onto the Aentic
[01:44:22] >> We are going to get you onto the Aentic operating system whether you like it or
[01:44:24] operating system whether you like it or not.
[01:44:24] not. >> This is awesome.
[01:44:24] >> This is awesome. >> And I, uh, I asked my friends at Dell
[01:44:27] >> And I, uh, I asked my friends at Dell whether, uh, maybe they had a machine
[01:44:29] whether, uh, maybe they had a machine that, um, I could, uh, I could get you
[01:44:33] that, um, I could, uh, I could get you for your birthday. So, here's the
[01:44:34] for your birthday. So, here's the machine I use, which is well, the same
[01:44:37] machine I use, which is well, the same one I use, but it's now yours. It's a
[01:44:40] one I use, but it's now yours. It's a Dell XPS14
[01:44:43] Dell XPS14 >> already set up with Omachi 4 ready to be
[01:44:46] >> already set up with Omachi 4 ready to be configured for you.
[01:44:47] configured for you. >> And um
[01:44:49] >> And um >> once you realize that all your By the
[01:44:52] >> once you realize that all your By the way, we should almost time this. You can
[01:44:54] way, we should almost time this. You can be up and running.
[01:44:55] be up and running. >> You have to answer like five questions
[01:44:57] >> You have to answer like five questions in about one minute. You could literally
[01:45:00] in about one minute. You could literally do it live if you wanted to. Uh Amachi
[01:45:02] do it live if you wanted to. Uh Amachi beautiful modern opinion Linux by DHH.
[01:45:04] beautiful modern opinion Linux by DHH. Yeah, let's do it.
[01:45:05] Yeah, let's do it. >> Yeah, fill it out while I talk. So
[01:45:07] >> Yeah, fill it out while I talk. So >> cool.
[01:45:08] >> cool. >> Exactly what you realized that pain on
[01:45:11] >> Exactly what you realized that pain on the Mac was the exposure I got for about
[01:45:14] the Mac was the exposure I got for about a weekend and I tried really hard and I
[01:45:16] a weekend and I tried really hard and I found some decent workarounds. The main
[01:45:18] found some decent workarounds. The main one being that homebrew now has tabs for
[01:45:22] one being that homebrew now has tabs for guey apps because it's hilarious to
[01:45:24] guey apps because it's hilarious to think upon the recent past where people
[01:45:27] think upon the recent past where people would go to websites like I need Zoom.
[01:45:31] would go to websites like I need Zoom. They would enter Zoom.com, find the
[01:45:34] They would enter Zoom.com, find the download link, download a DMG,
[01:45:36] download link, download a DMG, doubleclick on that, see a weird manual
[01:45:39] doubleclick on that, see a weird manual interaction telling them to drag a icon
[01:45:43] interaction telling them to drag a icon from one place of the screen to the
[01:45:45] from one place of the screen to the other. And that was how you installed
[01:45:47] other. And that was how you installed apps. And you just do that over and over
[01:45:50] apps. And you just do that over and over again until you had all the apps that
[01:45:52] again until you had all the apps that you wanted. And if you were setting up a
[01:45:54] you wanted. And if you were setting up a new machine and you had like 12 apps,
[01:45:56] new machine and you had like 12 apps, you'd go to 12 different websites to
[01:45:58] you'd go to 12 different websites to download them like a total caveman.
[01:46:02] download them like a total caveman. Homebrew has solved a lot of that, but
[01:46:03] Homebrew has solved a lot of that, but it has not solved all of it and has
[01:46:05] it has not solved all of it and has solved nothing in terms of the
[01:46:08] solved nothing in terms of the >> Sorry to interrupt, but look how fast
[01:46:10] >> Sorry to interrupt, but look how fast this is going.
[01:46:11] this is going. >> Oh, it's going to be done in in about 40
[01:46:14] >> Oh, it's going to be done in in about 40 seconds.
[01:46:15] seconds. And then you're going to be inside of
[01:46:18] And then you're going to be inside of >> Super is a Windows or command key on
[01:46:20] >> Super is a Windows or command key on your keyboard. So which one is the super
[01:46:22] your keyboard. So which one is the super key?
[01:46:22] key? >> Yep, that's the the Windows key. Oh,
[01:46:24] >> Yep, that's the the Windows key. Oh, actually no, no, you have a special
[01:46:25] actually no, no, you have a special edition.
[01:46:26] edition. >> There are only about six of these
[01:46:27] >> There are only about six of these computers in the world.
[01:46:28] computers in the world. >> Oh, there's a super key.
[01:46:29] >> Oh, there's a super key. >> It says super. And look at where the
[01:46:31] >> It says super. And look at where the co-pilot key is on the other end of the
[01:46:33] co-pilot key is on the other end of the keyboard.
[01:46:34] keyboard. >> That's the Machi logo.
[01:46:35] >> That's the Machi logo. >> Nice. Okay, cool.
[01:46:37] >> Nice. Okay, cool. >> This was um Spencer Bull at Bell who
[01:46:40] >> This was um Spencer Bull at Bell who I've been working with on a lot of this
[01:46:41] I've been working with on a lot of this stuff. They've been incredible. They for
[01:46:43] stuff. They've been incredible. They for a moment let go of the XPS brand.
[01:46:46] a moment let go of the XPS brand. >> Yes, they did last year
[01:46:48] >> Yes, they did last year >> and I was I was like this is dumb. This
[01:46:50] >> and I was I was like this is dumb. This is XPS is awesome.
[01:46:51] is XPS is awesome. >> It was not just dumb that it got rid of
[01:46:53] >> It was not just dumb that it got rid of the XPS branding. They also got rid of
[01:46:55] the XPS branding. They also got rid of the escape key and put in capacitive
[01:46:58] the escape key and put in capacitive touch buttons at the top. The mistake
[01:47:00] touch buttons at the top. The mistake that Apple realized like three years ago
[01:47:03] that Apple realized like three years ago was terrible and everyone hated them for
[01:47:04] was terrible and everyone hated them for them. But now they have an incredible
[01:47:07] them. But now they have an incredible team and this was actually my first Dell
[01:47:11] team and this was actually my first Dell laptop for myself. Mhm.
[01:47:13] laptop for myself. Mhm. >> Because I've been using Dell on our
[01:47:15] >> Because I've been using Dell on our servers. Dell was what powered our cloud
[01:47:17] servers. Dell was what powered our cloud exit. We've been running Dell since the
[01:47:19] exit. We've been running Dell since the mid 2000s, I think. But I never ran
[01:47:22] mid 2000s, I think. But I never ran their laptops because compared to a
[01:47:24] their laptops because compared to a MacBook, they just wasn't up to the task
[01:47:26] MacBook, they just wasn't up to the task for me. The XPS's from 2016 or from 2026
[01:47:32] for me. The XPS's from 2016 or from 2026 with those Intel Pantherike chips are
[01:47:34] with those Intel Pantherike chips are the first Dells that I would personally
[01:47:37] the first Dells that I would personally actually use. And it's funny because
[01:47:39] actually use. And it's funny because when I got mad at Apple originally, I
[01:47:42] when I got mad at Apple originally, I thought like, you know what? I should
[01:47:43] thought like, you know what? I should just get a Dell because we already used
[01:47:45] just get a Dell because we already used them and whatever. And I got a Dell. I
[01:47:47] them and whatever. And I got a Dell. I was like, man, I can't do it. I can't do
[01:47:49] was like, man, I can't do it. I can't do it. It's not It's not good enough. And
[01:47:51] it. It's not It's not good enough. And then lo and behold, this year they just
[01:47:55] then lo and behold, this year they just fixed everything. They fixed the battery
[01:47:58] fixed everything. They fixed the battery life. They fixed the performance. They
[01:48:00] life. They fixed the performance. They fixed the compatibility. They fixed the
[01:48:02] fixed the compatibility. They fixed the weight. They fixed the screen. That's a
[01:48:04] weight. They fixed the screen. That's a tandem OLED screen.
[01:48:05] tandem OLED screen. >> It's incredible. which means it's
[01:48:07] >> It's incredible. which means it's actually better tech than what you'll
[01:48:08] actually better tech than what you'll get in a freaking MacBook. It's lighter
[01:48:12] get in a freaking MacBook. It's lighter than a MacBook and the chip is finally
[01:48:15] than a MacBook and the chip is finally competitive because Intel spent a good 5
[01:48:19] competitive because Intel spent a good 5 years developing the 18A process node.
[01:48:23] years developing the 18A process node. It took a long time, but now it's here
[01:48:25] It took a long time, but now it's here and it's freaking incredible. We finally
[01:48:26] and it's freaking incredible. We finally have competition to Apple Mchips
[01:48:30] have competition to Apple Mchips >> that can go as long as on battery and
[01:48:33] >> that can go as long as on battery and can have competitive performance. And
[01:48:34] can have competitive performance. And there's a beautiful default theme to
[01:48:36] there's a beautiful default theme to this thing. And then uh what is it?
[01:48:38] this thing. And then uh what is it? Super space opens up.
[01:48:40] Super space opens up. >> Actually, you can just push the um
[01:48:42] >> Actually, you can just push the um Amachi key. It opens up the menu. So now
[01:48:43] Amachi key. It opens up the menu. So now you control everything.
[01:48:44] you control everything. >> Same thing as the super the same thing
[01:48:46] >> Same thing as the super the same thing as Super Space.
[01:48:47] as Super Space. >> So this has been a huge change for me
[01:48:52] >> So this has been a huge change for me that we finally have Linux machines that
[01:48:55] that we finally have Linux machines that you don't have to make excuses for.
[01:48:58] you don't have to make excuses for. >> Because I don't mind making excuses
[01:49:00] >> Because I don't mind making excuses because excuses are really just another
[01:49:02] because excuses are really just another word for trade-offs. I love that
[01:49:04] word for trade-offs. I love that framework 13 I think I talked about last
[01:49:06] framework 13 I think I talked about last time. I still like him. They still make
[01:49:08] time. I still like him. They still make good computers, but I think for a lot of
[01:49:11] good computers, but I think for a lot of people, they didn't want a DUI
[01:49:14] people, they didn't want a DUI experience. They wanted something that
[01:49:16] experience. They wanted something that just out of the box felt like it was on
[01:49:18] just out of the box felt like it was on par and build quality and
[01:49:21] par and build quality and whatever with the with Max and and now
[01:49:23] whatever with the with Max and and now we finally have it. So, happy birthday.
[01:49:27] we finally have it. So, happy birthday. >> Thank you so much.
[01:49:29] >> Thank you so much. and a Machi Dell laptop from DHH, which
[01:49:32] and a Machi Dell laptop from DHH, which is the best birthday present. This is
[01:49:34] is the best birthday present. This is awesome. Check the screen saver, by the
[01:49:36] awesome. Check the screen saver, by the way. Yeah, it's kind of amazing. I'm
[01:49:38] way. Yeah, it's kind of amazing. I'm seeing it
[01:49:39] seeing it >> on that tandem OLED screen. It is
[01:49:42] >> on that tandem OLED screen. It is absolutely
[01:49:44] absolutely mindbogglingly
[01:49:45] mindbogglingly awesome.
[01:49:46] awesome. >> Look at that.
[01:49:49] >> Look at that. >> There's like a retro look to the whole
[01:49:51] >> There's like a retro look to the whole thing. It's like it's like running a
[01:49:53] thing. It's like it's like running a bulletin board system in the '9s, which
[01:49:56] bulletin board system in the '9s, which is exactly what I did when I was 14
[01:49:58] is exactly what I did when I was 14 years old. So for me it's a complete
[01:50:00] years old. So for me it's a complete throwback and an awesome aesthetic
[01:50:03] throwback and an awesome aesthetic combining this sense of modern
[01:50:06] combining this sense of modern rising culture in Unix with this
[01:50:09] rising culture in Unix with this throwback of uh of the
[01:50:11] throwback of uh of the >> 90s. Yeah. like a retro look for an
[01:50:12] >> 90s. Yeah. like a retro look for an agent first OS. It's crazy.
[01:50:14] agent first OS. It's crazy. >> Which again pairs, this was why I was so
[01:50:16] >> Which again pairs, this was why I was so excited that all these agent harnesses
[01:50:18] excited that all these agent harnesses arrived as tuies, arrived as CLIs, has
[01:50:21] arrived as tuies, arrived as CLIs, has arrived as
[01:50:23] arrived as >> as a terminal because suddenly a whole
[01:50:26] >> as a terminal because suddenly a whole new generation of both programmers and
[01:50:28] new generation of both programmers and regular users discovered the glory of
[01:50:31] regular users discovered the glory of the terminal. The terminal is actually
[01:50:32] the terminal. The terminal is actually one of the most
[01:50:35] one of the most uh impressive and productive user
[01:50:37] uh impressive and productive user interfaces we can have. Now, we've built
[01:50:40] interfaces we can have. Now, we've built user interfaces since then that were
[01:50:41] user interfaces since then that were easier to learn. The mouse is a
[01:50:44] easier to learn. The mouse is a wonderful invention for letting someone
[01:50:48] wonderful invention for letting someone who doesn't know a lot about computers
[01:50:49] who doesn't know a lot about computers just click around and find things out.
[01:50:51] just click around and find things out. But the terminal is for people who want
[01:50:54] But the terminal is for people who want to learn their systems, who want to
[01:50:56] to learn their systems, who want to learn the keyboard commands.
[01:50:57] learn the keyboard commands. >> So, you think um do you think the two is
[01:50:59] >> So, you think um do you think the two is going to stick around?
[01:51:00] going to stick around? >> 100%. Now, it's not going to be the only
[01:51:02] >> 100%. Now, it's not going to be the only thing. Of course, it's not because these
[01:51:04] thing. Of course, it's not because these labs now have trillion dollar
[01:51:06] labs now have trillion dollar valuations. So they need to be able to
[01:51:08] valuations. So they need to be able to reach billions of people and I don't
[01:51:10] reach billions of people and I don't think we're going to teach billions of
[01:51:11] think we're going to teach billions of people the intricacies of the TUI. So
[01:51:15] people the intricacies of the TUI. So we're going to have other tools and we
[01:51:16] we're going to have other tools and we already have other tools which is by the
[01:51:18] already have other tools which is by the way one of the sweet things about uh
[01:51:20] way one of the sweet things about uh Linux the um chatgpt codeex tool.
[01:51:23] Linux the um chatgpt codeex tool. >> Yeah I saw that
[01:51:24] >> Yeah I saw that >> literally within 2 hours of that
[01:51:26] >> literally within 2 hours of that announcement dropping. I had it wrapped
[01:51:28] announcement dropping. I had it wrapped up and ready to go in already. Now if
[01:51:30] up and ready to go in already. Now if you go to uh you can actually hit the uh
[01:51:32] you go to uh you can actually hit the uh omachi key
[01:51:33] omachi key >> Mhm. And then just write chat GBT. It
[01:51:36] >> Mhm. And then just write chat GBT. It should pop up as like install. And then
[01:51:39] should pop up as like install. And then just hit return.
[01:51:41] just hit return. >> Pseudo password for Lex.
[01:51:43] >> Pseudo password for Lex. >> Yeah. Whatever you put in. And then it's
[01:51:44] >> Yeah. Whatever you put in. And then it's just going to install it. And it's going
[01:51:46] just going to install it. And it's going to pop it up and you have chat GPT.
[01:51:48] to pop it up and you have chat GPT. >> Nice.
[01:51:48] >> Nice. >> And that's how a lot of the apps are.
[01:51:50] >> And that's how a lot of the apps are. And all the agentic harnesses are built
[01:51:52] And all the agentic harnesses are built in that way. Um, tail scale as I talked
[01:51:55] in that way. Um, tail scale as I talked about if you want to hop on that is that
[01:51:56] about if you want to hop on that is that way. Dropbox. And the reason all these
[01:51:59] way. Dropbox. And the reason all these things are in there is because I use
[01:52:00] things are in there is because I use them.
[01:52:01] them. >> It's because I built this system for me.
[01:52:02] >> It's because I built this system for me. And I thought first and foremost, how do
[01:52:04] And I thought first and foremost, how do I build my dream computer just for me?
[01:52:08] I build my dream computer just for me? And if I get my dream computer, I am
[01:52:10] And if I get my dream computer, I am assured there are other people who are
[01:52:12] assured there are other people who are going to have the same dreams as I do.
[01:52:13] going to have the same dreams as I do. >> Now, you were obsessed about getting the
[01:52:16] >> Now, you were obsessed about getting the installation to be under 1 minute. And a
[01:52:19] installation to be under 1 minute. And a bunch of people asked you online why. So
[01:52:21] bunch of people asked you online why. So why why why were you so obsessed getting
[01:52:24] why why why were you so obsessed getting the installation to be less than 60
[01:52:27] the installation to be less than 60 seconds? First, let me quote uh Mitchell
[01:52:30] seconds? First, let me quote uh Mitchell Himoto, who created Ghosty Terminal
[01:52:33] Himoto, who created Ghosty Terminal that's awesome and also available on
[01:52:35] that's awesome and also available on Nachi and was also the founder of Hashi
[01:52:36] Nachi and was also the founder of Hashi Cororb who had this great post onx not
[01:52:40] Cororb who had this great post onx not too long ago that had the killer line,
[01:52:43] too long ago that had the killer line, the pursuit of excellence. This serves
[01:52:46] the pursuit of excellence. This serves no explanation.
[01:52:48] no explanation. Wanting to make something as good and as
[01:52:51] Wanting to make something as good and as fast and as beautiful as possible has
[01:52:56] fast and as beautiful as possible has no need for justification.
[01:52:58] no need for justification. >> Mhm.
[01:52:59] >> Mhm. >> We should want beautiful fast systems
[01:53:03] >> We should want beautiful fast systems that are the light to use. Now the funny
[01:53:05] that are the light to use. Now the funny thing with the install time is it didn't
[01:53:07] thing with the install time is it didn't actually start with a one minute
[01:53:09] actually start with a one minute mission. I was being modest when I got
[01:53:11] mission. I was being modest when I got going. I thought if I could set up my
[01:53:13] going. I thought if I could set up my entire system in 15 minutes, it would
[01:53:16] entire system in 15 minutes, it would already be such a dramatic improvement
[01:53:18] already be such a dramatic improvement over what came before that I would be
[01:53:20] over what came before that I would be perfectly happy. And it came off the
[01:53:22] perfectly happy. And it came off the fact that the benchmarking had been
[01:53:24] fact that the benchmarking had been screwed so out of whack. You talked
[01:53:26] screwed so out of whack. You talked about the Commodore 64 being your first
[01:53:27] about the Commodore 64 being your first computer, right?
[01:53:28] computer, right? >> When you unwrapped that Commodore 64 and
[01:53:31] >> When you unwrapped that Commodore 64 and you hit the on button, in I think about
[01:53:34] you hit the on button, in I think about less than one second, the basic
[01:53:36] less than one second, the basic interpreter was ready to accept your
[01:53:38] interpreter was ready to accept your command. It was literally almost
[01:53:40] command. It was literally almost instant. There was virtually no boot
[01:53:42] instant. There was virtually no boot time. Do you know how long it took me to
[01:53:45] time. Do you know how long it took me to set up a new Mac that I had bought for
[01:53:48] set up a new Mac that I had bought for actually the one app that I still
[01:53:49] actually the one app that I still haven't viodated my way into on Linux,
[01:53:51] haven't viodated my way into on Linux, which is Adobe Lightroom.
[01:53:52] which is Adobe Lightroom. >> Mhm.
[01:53:54] >> Mhm. >> Brand new computer
[01:53:56] >> Brand new computer out of the box. I set it up. There's a
[01:53:59] out of the box. I set it up. There's a software update. Before I was ready to
[01:54:01] software update. Before I was ready to install Adobe Lightroom that I had it
[01:54:03] install Adobe Lightroom that I had it fully up to date, it took 42
[01:54:06] fully up to date, it took 42 minutes.
[01:54:08] minutes. That's grotesque. That's absurd. That's
[01:54:11] That's grotesque. That's absurd. That's an insult to everyone who likes
[01:54:13] an insult to everyone who likes computers that you get a new computer
[01:54:15] computers that you get a new computer and before you can use it, you have to
[01:54:18] and before you can use it, you have to spend 42 minutes doing updates on
[01:54:21] spend 42 minutes doing updates on something that was already installed on
[01:54:22] something that was already installed on it out of the box from the factory. That
[01:54:25] it out of the box from the factory. That is just preposterous. And it's crazy
[01:54:28] is just preposterous. And it's crazy that that's not even the worst thing. I
[01:54:30] that that's not even the worst thing. I also got a PC
[01:54:32] also got a PC um because all these Linux machines,
[01:54:34] um because all these Linux machines, they come as PCs, right? And they have
[01:54:36] they come as PCs, right? And they have Windows pre-installed.
[01:54:37] Windows pre-installed. >> So, I got one. This was just three weeks
[01:54:40] >> So, I got one. This was just three weeks ago. Brand new machine, Intel Panther
[01:54:42] ago. Brand new machine, Intel Panther Leg, the whole shebang. An hour and 35
[01:54:46] Leg, the whole shebang. An hour and 35 minutes from unwrapping the thing until
[01:54:49] minutes from unwrapping the thing until it's ready to use. How long did you take
[01:54:51] it's ready to use. How long did you take before you think you were in Numachi?
[01:54:54] before you think you were in Numachi? >> I mean, it's less than a minute for
[01:54:55] >> I mean, it's less than a minute for sure.
[01:54:55] sure. >> A minute.
[01:54:56] >> A minute. >> Yeah.
[01:54:57] >> Yeah. >> We can build computers like this. We
[01:54:59] >> We can build computers like this. We have the technology. We've had the
[01:55:01] have the technology. We've had the technology since like 1981 when the
[01:55:04] technology since like 1981 when the Commodore 64 first came out. The fact
[01:55:06] Commodore 64 first came out. The fact that we now have a computer that's a
[01:55:08] that we now have a computer that's a trillion times faster and you have to
[01:55:09] trillion times faster and you have to spend 42 minutes or an hour and a half
[01:55:11] spend 42 minutes or an hour and a half setting it up before it's ready to use
[01:55:13] setting it up before it's ready to use is so infuriating to me that it became a
[01:55:17] is so infuriating to me that it became a passion. And it's funny just while we
[01:55:20] passion. And it's funny just while we were having a little break here, I was
[01:55:21] were having a little break here, I was talking to to Ryan Hughes, my
[01:55:22] talking to to Ryan Hughes, my co-conspirator here. We now have, we
[01:55:25] co-conspirator here. We now have, we think, a line where we can create these
[01:55:27] think, a line where we can create these special turbo images that are pre-made
[01:55:29] special turbo images that are pre-made for specific computers because it relies
[01:55:31] for specific computers because it relies on some knowledge of the hardware like
[01:55:34] on some knowledge of the hardware like the Dell XPS. We're going to make a Dell
[01:55:37] the Dell XPS. We're going to make a Dell XPS turbo image that can install in
[01:55:39] XPS turbo image that can install in about 12 seconds.
[01:55:42] about 12 seconds. >> Full Linux system
[01:55:44] >> Full Linux system >> installed in about 12 seconds.
[01:55:45] >> installed in about 12 seconds. >> Incredible. That obsession
[01:55:49] >> Incredible. That obsession is what gives me this great satisfaction
[01:55:51] is what gives me this great satisfaction with using computers that we do not
[01:55:53] with using computers that we do not accept things the way they are. And this
[01:55:55] accept things the way they are. And this is why this agent accelerated reality
[01:55:58] is why this agent accelerated reality that I now inhabit is so invigorating
[01:56:02] that I now inhabit is so invigorating because I can look at these kinds of
[01:56:03] because I can look at these kinds of constraints and go do you know what um
[01:56:06] constraints and go do you know what um >> I could have stopped when we were at 5
[01:56:09] >> I could have stopped when we were at 5 minutes. That would already have been
[01:56:10] minutes. That would already have been fast enough. This was the argument on X,
[01:56:12] fast enough. This was the argument on X, right? Why do you keep going? Five
[01:56:14] right? Why do you keep going? Five minutes is fast enough. Okay, maybe for
[01:56:17] minutes is fast enough. Okay, maybe for you, but for me 12 seconds is a lot more
[01:56:19] you, but for me 12 seconds is a lot more fun. And I always think try to think
[01:56:23] fun. And I always think try to think these first principles. Okay, in that
[01:56:26] these first principles. Okay, in that machine actually hit the omachi uh key
[01:56:29] machine actually hit the omachi uh key again and then do speed. You'll see a
[01:56:33] again and then do speed. You'll see a list come up and one of them is like
[01:56:34] list come up and one of them is like disk speed,
[01:56:35] disk speed, >> speed test, network speed, disc speed,
[01:56:38] >> speed test, network speed, disc speed, >> disc speed. Do that one and then run it.
[01:56:41] >> disc speed. Do that one and then run it. So, this is testing the performance of
[01:56:43] So, this is testing the performance of the built-in NVME drive. And what are
[01:56:45] the built-in NVME drive. And what are you getting?
[01:56:46] you getting? >> 7 GB a second.
[01:56:48] >> 7 GB a second. >> So, 7 GB a second. That's how fast that
[01:56:50] >> So, 7 GB a second. That's how fast that drive is. Why can we not install a Linux
[01:56:53] drive is. Why can we not install a Linux distribution in 1 second? The Omachi
[01:56:56] distribution in 1 second? The Omachi distribution is 5.8 GB.
[01:56:58] distribution is 5.8 GB. >> Mhm.
[01:56:58] >> Mhm. >> If we can run at 7 G. Now, of course,
[01:57:01] >> If we can run at 7 G. Now, of course, you can't actually do that because the
[01:57:03] you can't actually do that because the USB key is a lot slower than that, but
[01:57:05] USB key is a lot slower than that, but you should be able to maximize the
[01:57:08] you should be able to maximize the underlying physics and protocols that
[01:57:11] underlying physics and protocols that we're dealing with. And that's your
[01:57:13] we're dealing with. And that's your goal. We got to get all the way back
[01:57:15] goal. We got to get all the way back down to that. Yeah, I love that you're
[01:57:18] down to that. Yeah, I love that you're doing a Linux dist cuz uh I mean you
[01:57:20] doing a Linux dist cuz uh I mean you could be do you you could be building
[01:57:23] could be do you you could be building anything but the fact that you're
[01:57:24] anything but the fact that you're building a Linux distribution means
[01:57:26] building a Linux distribution means you're rethinking about what a computer
[01:57:28] you're rethinking about what a computer is cuz operating system is the
[01:57:30] is cuz operating system is the fundamental like the foundation of how
[01:57:32] fundamental like the foundation of how you interact with computer
[01:57:34] you interact with computer >> and it's been so stale.
[01:57:35] >> and it's been so stale. >> Yeah.
[01:57:35] >> Yeah. >> The Mac OS we have today is scarcely
[01:57:40] >> The Mac OS we have today is scarcely different from the Mac OS we had 10
[01:57:41] different from the Mac OS we had 10 years ago. In fact, it's worse in many
[01:57:43] years ago. In fact, it's worse in many ways because Apple continues to chokeold
[01:57:47] ways because Apple continues to chokeold the control on users. They don't want to
[01:57:50] the control on users. They don't want to them to install software that they
[01:57:52] them to install software that they haven't already said good
[01:57:54] haven't already said good >> to go for. They don't want users to
[01:57:57] >> to go for. They don't want users to reconfigure their hotkeys without doing
[01:57:59] reconfigure their hotkeys without doing it manually. They don't want to change
[01:58:01] it manually. They don't want to change the 500 millisecond animation switching
[01:58:04] the 500 millisecond animation switching workspaces. It is an infuriatingly
[01:58:07] workspaces. It is an infuriatingly locked down computer. Now, to Apple's
[01:58:10] locked down computer. Now, to Apple's credit, it's a pretty good computer for
[01:58:12] credit, it's a pretty good computer for being locked down, but I don't want a
[01:58:15] being locked down, but I don't want a lockdown computer. I want to own my
[01:58:16] lockdown computer. I want to own my computer. Better yet, I want to mutate
[01:58:19] computer. Better yet, I want to mutate my computer. And this is where the
[01:58:21] my computer. And this is where the aentic age needs a new operating system.
[01:58:25] aentic age needs a new operating system. When you can vibe code whatever app
[01:58:28] When you can vibe code whatever app comes to your mind, you should be able
[01:58:29] comes to your mind, you should be able to vibe code your operating system. You
[01:58:31] to vibe code your operating system. You should be able to change anything, how
[01:58:32] should be able to change anything, how it looks, how it works, what panels are
[01:58:34] it looks, how it works, what panels are there, what are not there. And that
[01:58:37] there, what are not there. And that requires Linux. As simple as that. There
[01:58:39] requires Linux. As simple as that. There are no none of the other two operating
[01:58:41] are no none of the other two operating systems can deliver this.
[01:58:42] systems can deliver this. >> But can you speak to the I think
[01:58:43] >> But can you speak to the I think somebody asked you like who the hell are
[01:58:46] somebody asked you like who the hell are you to think you could do better than
[01:58:48] you to think you could do better than Ubuntu for example or or like why are
[01:58:51] Ubuntu for example or or like why are you doing it when Ubuntu is already
[01:58:52] you doing it when Ubuntu is already pretty good and your answer was I
[01:58:54] pretty good and your answer was I thought I could do better. So can you
[01:58:56] thought I could do better. So can you speak to this was on X. Can you speak to
[01:59:00] speak to this was on X. Can you speak to like where
[01:59:02] like where the craziness comes from thinking that
[01:59:05] the craziness comes from thinking that you as one person or maybe with Ryan you
[01:59:08] you as one person or maybe with Ryan you could start building something that's
[01:59:09] could start building something that's going to be better than a Bondu or Arch
[01:59:12] going to be better than a Bondu or Arch or any of this?
[01:59:13] or any of this? >> Well, I'll say that it didn't start
[01:59:16] >> Well, I'll say that it didn't start quite as grandurous when I got going
[01:59:18] quite as grandurous when I got going with my Linux journey. I actually just
[01:59:20] with my Linux journey. I actually just started with Iuntu and I just built on
[01:59:22] started with Iuntu and I just built on top of it. Here's a system that already
[01:59:25] top of it. Here's a system that already does a lot of the things I wanted to do
[01:59:26] does a lot of the things I wanted to do and at least it's Linux. So, can I just
[01:59:28] and at least it's Linux. So, can I just build on top of it and make it more
[01:59:30] build on top of it and make it more modern, make it actually look good and
[01:59:31] modern, make it actually look good and have the programs I want to use? I got
[01:59:34] have the programs I want to use? I got like some version of that. And then I
[01:59:36] like some version of that. And then I discovered that there's seven layers
[01:59:37] discovered that there's seven layers deeper you could go. And as the closer
[01:59:40] deeper you could go. And as the closer you get to the metal, the closer you get
[01:59:42] you get to the metal, the closer you get to the kernel, the closer you get to the
[01:59:43] to the kernel, the closer you get to the individual packages and so forth, the
[01:59:46] individual packages and so forth, the more freedom you discover. So, as I
[01:59:48] more freedom you discover. So, as I discovered more and more freedom, I got
[01:59:50] discovered more and more freedom, I got more and more ambitious. And I realized,
[01:59:53] more and more ambitious. And I realized, oh, surprise surprise. I have strong
[01:59:56] oh, surprise surprise. I have strong opinions about how computers should
[01:59:57] opinions about how computers should work, how they should look, what
[01:59:59] work, how they should look, what programs should be installed, and
[02:00:02] programs should be installed, and whether they should take 42 minutes to
[02:00:04] whether they should take 42 minutes to install or 45 seconds. That's the
[02:00:07] install or 45 seconds. That's the current world record, by the way. So, if
[02:00:10] current world record, by the way. So, if anyone installs a M Quattro after this
[02:00:12] anyone installs a M Quattro after this and can beat 45 seconds, take a
[02:00:13] and can beat 45 seconds, take a screenshot, send it to me, and you'll
[02:00:15] screenshot, send it to me, and you'll you'll be the new holder of the world
[02:00:16] you'll be the new holder of the world record.
[02:00:17] record. >> When When How long ago did you cross the
[02:00:19] >> When When How long ago did you cross the 60-second mark? It's funny because it's
[02:00:22] 60-second mark? It's funny because it's like um that uh the old limit on what
[02:00:26] like um that uh the old limit on what was it? It was a 4minute mile or
[02:00:28] was it? It was a 4minute mile or something like that in 1952
[02:00:30] something like that in 1952 >> that people thought was impossible for
[02:00:32] >> that people thought was impossible for humans to beat. Then one guy beats it
[02:00:34] humans to beat. Then one guy beats it and literally within the next few months
[02:00:36] and literally within the next few months three more guys do, right?
[02:00:37] three more guys do, right? >> So we had this goal. I originally had to
[02:00:39] >> So we had this goal. I originally had to go it was 2 minutes
[02:00:40] go it was 2 minutes >> and then we beat two minutes and I'm
[02:00:42] >> and then we beat two minutes and I'm like well if we beat two minutes why
[02:00:44] like well if we beat two minutes why can't we beat one minute? And I remember
[02:00:46] can't we beat one minute? And I remember thinking like that'd be crazy. You can't
[02:00:48] thinking like that'd be crazy. You can't install a modern operating system in one
[02:00:51] install a modern operating system in one minute when they're all if the other
[02:00:53] minute when they're all if the other ones are taking 42 minutes, right? Like
[02:00:55] ones are taking 42 minutes, right? Like uh Apple full of a lot of smart people.
[02:00:59] uh Apple full of a lot of smart people. Like it took 42 minutes. So that's got
[02:01:00] Like it took 42 minutes. So that's got to be the bar. No, no, it's not the bar
[02:01:02] to be the bar. No, no, it's not the bar because there's no speed limit. Like
[02:01:04] because there's no speed limit. Like none of the things you take for granted
[02:01:06] none of the things you take for granted are fixed pillars of reality in almost
[02:01:09] are fixed pillars of reality in almost any case. Until you get down to the
[02:01:11] any case. Until you get down to the seven gigabytes per second that drive is
[02:01:15] seven gigabytes per second that drive is able to transfer, you've not reached the
[02:01:16] able to transfer, you've not reached the limit yet. So you should just keep
[02:01:18] limit yet. So you should just keep pushing. And of course then it becomes a
[02:01:20] pushing. And of course then it becomes a game in itself and a satisfaction
[02:01:22] game in itself and a satisfaction itself. Every second I could shave off
[02:01:24] itself. Every second I could shave off was an excitement. And when we broke the
[02:01:26] was an excitement. And when we broke the one minute barrier, which was really
[02:01:28] one minute barrier, which was really only broken, I think 3 weeks ago or
[02:01:30] only broken, I think 3 weeks ago or something like that, maybe even two
[02:01:31] something like that, maybe even two weeks ago, I just got crazy. And then I
[02:01:34] weeks ago, I just got crazy. And then I got a swarm of agents to run all these
[02:01:36] got a swarm of agents to run all these auto research loops of trying all these
[02:01:39] auto research loops of trying all these different theories on like, oh, if you
[02:01:40] different theories on like, oh, if you change this thing, if you change that
[02:01:42] change this thing, if you change that thing, what if you cut this out? What if
[02:01:43] thing, what if you cut this out? What if you do things in parallel? What if while
[02:01:45] you do things in parallel? What if while you were typing in your username, we
[02:01:47] you were typing in your username, we start pre-loading packages into memory
[02:01:49] start pre-loading packages into memory system. We can fire them in faster and
[02:01:51] system. We can fire them in faster and it becomes a fun game. And I think
[02:01:53] it becomes a fun game. And I think that's how you should think about
[02:01:54] that's how you should think about product development. It should be fun.
[02:01:56] product development. It should be fun. You should it should be frivolous. It
[02:01:58] You should it should be frivolous. It should be trying to overshoot the target
[02:02:00] should be trying to overshoot the target and making it so much better than what
[02:02:02] and making it so much better than what it quote unquote needs to be,
[02:02:04] it quote unquote needs to be, >> especially now cuz you can move so
[02:02:06] >> especially now cuz you can move so quickly. You could try so many different
[02:02:07] quickly. You could try so many different approaches because of the the agents.
[02:02:10] approaches because of the the agents. >> Yes, that just makes it more satisfying.
[02:02:11] >> Yes, that just makes it more satisfying. But I think this was always true. If you
[02:02:13] But I think this was always true. If you look at the greatest Mercedes-Benz of
[02:02:15] look at the greatest Mercedes-Benz of all time, I think it was called the
[02:02:16] all time, I think it was called the W126,
[02:02:18] W126, I saw this wonderful documentary on it.
[02:02:20] I saw this wonderful documentary on it. Um, it was steered by this guy who for
[02:02:22] Um, it was steered by this guy who for years had worked in Mercedes department
[02:02:25] years had worked in Mercedes department for safety and suddenly he gets put in
[02:02:28] for safety and suddenly he gets put in charge for the whole S-Class project and
[02:02:31] charge for the whole S-Class project and he just puts in all of it. This is where
[02:02:32] he just puts in all of it. This is where you got the auto retending seat belts
[02:02:35] you got the auto retending seat belts and uh washers on the headlights and
[02:02:39] and uh washers on the headlights and everything. This car was so overbuilt
[02:02:41] everything. This car was so overbuilt for the market, it was unbelievable. But
[02:02:44] for the market, it was unbelievable. But you look at that and go like, "Well, I
[02:02:46] you look at that and go like, "Well, I want that."
[02:02:47] want that." >> In just the same way that you look at a
[02:02:50] >> In just the same way that you look at a mechanical watch and go, it can go down
[02:02:54] mechanical watch and go, it can go down to 100 meters or or I think Rolex has
[02:02:56] to 100 meters or or I think Rolex has one that can go down to 4,000 mters, the
[02:02:58] one that can go down to 4,000 mters, the the deep ocean, the deep diver ocean or
[02:03:00] the deep ocean, the deep diver ocean or whatever it's called.
[02:03:02] whatever it's called. >> No one outside of three people in the
[02:03:04] >> No one outside of three people in the world whoever buy that watch will ever
[02:03:06] world whoever buy that watch will ever put it to the test. But don't you want
[02:03:08] put it to the test. But don't you want to be the kind of person who
[02:03:11] to be the kind of person who is a patron of people who want to push
[02:03:14] is a patron of people who want to push the human race that much forward? I want
[02:03:16] the human race that much forward? I want the fastest car breaking the speed
[02:03:18] the fastest car breaking the speed limits. I want the diver watch that can
[02:03:20] limits. I want the diver watch that can go down the Mariana trench. I want the
[02:03:24] go down the Mariana trench. I want the operating system that can install in
[02:03:25] operating system that can install in less than 60 seconds. So from the
[02:03:28] less than 60 seconds. So from the individual level, I I admire those
[02:03:30] individual level, I I admire those people. I think everybody should strive
[02:03:32] people. I think everybody should strive for that. But also the consequences of
[02:03:34] for that. But also the consequences of that we should mention like the pursuit
[02:03:36] that we should mention like the pursuit of excellence even when the metrics seem
[02:03:38] of excellence even when the metrics seem to be frivolous
[02:03:40] to be frivolous the maybe unexpected consequences of
[02:03:42] the maybe unexpected consequences of that is other kinds of excellences
[02:03:45] that is other kinds of excellences discoveries innovations and all that
[02:03:46] discoveries innovations and all that kind of stuff that has nothing to do
[02:03:48] kind of stuff that has nothing to do with the speed
[02:03:49] with the speed >> 100%
[02:03:49] >> 100% >> it's discovery it's the it's nice to
[02:03:52] >> it's discovery it's the it's nice to have the metric that you're chasing be
[02:03:54] have the metric that you're chasing be the catalyst the engine that drives
[02:03:56] the catalyst the engine that drives innovation because you'll just discover
[02:03:58] innovation because you'll just discover it's the same reason you go to the moon
[02:04:00] it's the same reason you go to the moon you go to Mars it's like why? Who cares?
[02:04:04] you go to Mars it's like why? Who cares? Well, actually the real thing is you'll
[02:04:06] Well, actually the real thing is you'll you'll you'll discover a lot about
[02:04:08] you'll you'll discover a lot about chemical propulsion. You'll discover a
[02:04:11] chemical propulsion. You'll discover a lot about uh how humans can live for a
[02:04:14] lot about uh how humans can live for a long time in space. Maybe you'll
[02:04:16] long time in space. Maybe you'll discover whole new ways of doing solar
[02:04:18] discover whole new ways of doing solar energy in space or data centers in space
[02:04:20] energy in space or data centers in space or whatever the hell. All kinds of maybe
[02:04:23] or whatever the hell. All kinds of maybe you'll meet aliens, but you you you
[02:04:26] you'll meet aliens, but you you you never know. But the setting a goal
[02:04:30] never know. But the setting a goal and chasing it, especially when it's
[02:04:32] and chasing it, especially when it's numerical, is really nice.
[02:04:33] numerical, is really nice. >> And setting a grand goal is even better.
[02:04:35] >> And setting a grand goal is even better. When you refuse to just do what's
[02:04:39] When you refuse to just do what's practical and you strive for what's
[02:04:43] practical and you strive for what's slightly beyond plausible, that's when
[02:04:46] slightly beyond plausible, that's when the magic happens. And we should be
[02:04:49] the magic happens. And we should be going all in on that. This is one of the
[02:04:51] going all in on that. This is one of the reasons. And in fact to some degree this
[02:04:53] reasons. And in fact to some degree this specific goal was motivated by seeing
[02:04:56] specific goal was motivated by seeing others do this. I mean Elon is the
[02:04:58] others do this. I mean Elon is the singular individual in this
[02:05:00] singular individual in this conversation.
[02:05:02] conversation. The guy is so out there in his goals.
[02:05:06] The guy is so out there in his goals. They seem so preposterous at first
[02:05:08] They seem so preposterous at first glance. I've certainly considered them
[02:05:11] glance. I've certainly considered them preposterous on many glances. And then
[02:05:15] preposterous on many glances. And then you realize that
[02:05:18] you realize that they come true sometimes. Maybe not
[02:05:20] they come true sometimes. Maybe not always on schedule. And so what? So
[02:05:23] always on schedule. And so what? So what? So we didn't get the self-driving
[02:05:25] what? So we didn't get the self-driving car on schedule. I gave Elon a lot of
[02:05:27] car on schedule. I gave Elon a lot of for that back in 17, but now it's
[02:05:30] for that back in 17, but now it's here.
[02:05:32] here. And who would have gotten us here except
[02:05:34] And who would have gotten us here except for the person who thought it was
[02:05:36] for the person who thought it was possible in 17? Who is so
[02:05:39] possible in 17? Who is so impatient with reality that the sheer
[02:05:44] impatient with reality that the sheer force is just going to propel that
[02:05:46] force is just going to propel that reality to the place he wants it to be?
[02:05:48] reality to the place he wants it to be? I think that's deeply inspiring and we
[02:05:50] I think that's deeply inspiring and we need these kinds of
[02:05:52] need these kinds of uh goalposts to be moved. We need
[02:05:55] uh goalposts to be moved. We need someone to run the four-minute mile so
[02:05:57] someone to run the four-minute mile so the rest of us realize well okay but I
[02:06:00] the rest of us realize well okay but I guess I can run it quicker. That's what
[02:06:01] guess I can run it quicker. That's what I try to strive for and I really strive
[02:06:03] I try to strive for and I really strive for with a machi because
[02:06:06] for with a machi because it's just more fun to live that way to
[02:06:08] it's just more fun to live that way to have high aspirations and ambitions and
[02:06:10] have high aspirations and ambitions and I will say I've actually changed my mind
[02:06:11] I will say I've actually changed my mind on that a little bit. I spent quite a
[02:06:13] on that a little bit. I spent quite a lot of time speaking the other book that
[02:06:18] lot of time speaking the other book that there are a lot of people who don't
[02:06:20] there are a lot of people who don't actually need those ambitions. And I
[02:06:23] actually need those ambitions. And I also that's also true. We don't want uh
[02:06:26] also that's also true. We don't want uh 8 billion Elons running around. The
[02:06:28] 8 billion Elons running around. The world would be rather crazy, I think.
[02:06:30] world would be rather crazy, I think. But I've come to realize that for
[02:06:32] But I've come to realize that for entrepreneurs, it's healthy to have
[02:06:36] entrepreneurs, it's healthy to have suitable chunky goals. The idea of just
[02:06:40] suitable chunky goals. The idea of just running the Italian restaurant can't
[02:06:43] running the Italian restaurant can't just be that. It should be maybe I just
[02:06:46] just be that. It should be maybe I just run the one Italian restaurant, but I
[02:06:48] run the one Italian restaurant, but I make the best damn pizza possible. I
[02:06:51] make the best damn pizza possible. I make the most delicious parmesan.
[02:06:55] make the most delicious parmesan. We have to strive for excellence to
[02:06:58] We have to strive for excellence to muster the motivation to keep going
[02:07:01] muster the motivation to keep going >> and uh Yeah. to dare to to think big
[02:07:03] >> and uh Yeah. to dare to to think big like you could build a Linux
[02:07:05] like you could build a Linux >> Yes.
[02:07:05] >> Yes. >> distribution.
[02:07:07] >> distribution. Is there um some stuff you remember
[02:07:09] Is there um some stuff you remember about what it took to get us to be so
[02:07:11] about what it took to get us to be so fast? You mentioned a few things that
[02:07:13] fast? You mentioned a few things that were the agents were discovering.
[02:07:15] were the agents were discovering. >> One of the things was to treat the
[02:07:20] >> One of the things was to treat the lag of human input as an opportunity to
[02:07:22] lag of human input as an opportunity to preload. So
[02:07:24] preload. So >> there's five questions you answer when
[02:07:25] >> there's five questions you answer when you set up a machine.
[02:07:27] you set up a machine. >> So it's doing stuff in the background.
[02:07:28] >> So it's doing stuff in the background. >> We're doing stuff in the background. And
[02:07:30] >> We're doing stuff in the background. And that was one of the things I didn't even
[02:07:31] that was one of the things I didn't even consider which is I mean the oldest
[02:07:33] consider which is I mean the oldest trick in the book. Um, all sorts of
[02:07:36] trick in the book. Um, all sorts of video games for a long time have done
[02:07:37] video games for a long time have done this where you let the player interact
[02:07:39] this where you let the player interact with something and then you do
[02:07:40] with something and then you do preloading and and so forth in the
[02:07:42] preloading and and so forth in the background. So, it's a nature old
[02:07:43] background. So, it's a nature old technique, but I just hadn't thought
[02:07:44] technique, but I just hadn't thought about it for an installer. I thought
[02:07:46] about it for an installer. I thought first you ask the user some questions
[02:07:48] first you ask the user some questions about their password and their username
[02:07:50] about their password and their username and their time zone and so forth and
[02:07:52] and their time zone and so forth and then you do the work when in fact you
[02:07:54] then you do the work when in fact you could preload that. Now the other things
[02:07:56] could preload that. Now the other things were just a bunch of other tweaks to um
[02:08:01] were just a bunch of other tweaks to um how the installer itself was doing
[02:08:03] how the installer itself was doing things in a certain order. Some of them
[02:08:05] things in a certain order. Some of them was also just shrinking it. The last
[02:08:07] was also just shrinking it. The last version of Omachi was 7.5 GB and a lot
[02:08:11] version of Omachi was 7.5 GB and a lot of the time we're down to now is
[02:08:13] of the time we're down to now is literally decompressing
[02:08:15] literally decompressing compressed package files. That's the
[02:08:17] compressed package files. That's the bulk of what is on the ISO and that's
[02:08:18] bulk of what is on the ISO and that's the bulk of the install time. So by
[02:08:20] the bulk of the install time. So by shrinking it down to I think we're at
[02:08:22] shrinking it down to I think we're at 5.85 gigabytes now. a pretty chunky
[02:08:25] 5.85 gigabytes now. a pretty chunky reduction. It almost literally
[02:08:28] reduction. It almost literally translated one to one and I did some
[02:08:29] translated one to one and I did some really interesting things there. So, um
[02:08:32] really interesting things there. So, um uses the Jet Brains font which is a
[02:08:35] uses the Jet Brains font which is a awesome font, beautiful font and
[02:08:37] awesome font, beautiful font and actually a font I didn't like at first
[02:08:39] actually a font I didn't like at first glance but then it was the only font I
[02:08:41] glance but then it was the only font I could get to look perfect in Mitchell
[02:08:43] could get to look perfect in Mitchell Azimodo's Ghosty. Ghosty, for whatever
[02:08:46] Azimodo's Ghosty. Ghosty, for whatever reason, did not want to render my
[02:08:48] reason, did not want to render my beloved Bitstream Vera Sance just the
[02:08:52] beloved Bitstream Vera Sance just the way I was used to it, but it rendered um
[02:08:56] way I was used to it, but it rendered um this Jet Brains font perfectly. So, I
[02:08:58] this Jet Brains font perfectly. So, I switched over, but it the standard
[02:09:00] switched over, but it the standard package for Jet Brains font on Arch is
[02:09:04] package for Jet Brains font on Arch is 200 megabytes because it includes all
[02:09:06] 200 megabytes because it includes all these variations and all these subtypes
[02:09:08] these variations and all these subtypes and whatever. And I realized like we're
[02:09:12] and whatever. And I realized like we're not using any of that. We're using the
[02:09:13] not using any of that. We're using the monospace version in this one nerd uh
[02:09:16] monospace version in this one nerd uh font patched edition. Do you know how
[02:09:19] font patched edition. Do you know how much big that is? I think it's 16
[02:09:20] much big that is? I think it's 16 megabytes.
[02:09:22] megabytes. >> So I simply just came up with a new
[02:09:24] >> So I simply just came up with a new package, the slim version of the Jet
[02:09:26] package, the slim version of the Jet Brains package. And there, right there,
[02:09:28] Brains package. And there, right there, I saved 180 megabytes. I just went
[02:09:31] I saved 180 megabytes. I just went through and did that a bunch of times.
[02:09:32] through and did that a bunch of times. We did that with the Nvidia
[02:09:34] We did that with the Nvidia >> drivers, too. So the Nvidia drivers when
[02:09:36] >> drivers, too. So the Nvidia drivers when they came straight off the I think the
[02:09:38] they came straight off the I think the Arch repo were not compressed with the
[02:09:41] Arch repo were not compressed with the most extreme form of compression which I
[02:09:43] most extreme form of compression which I think called ZSTD which is a really slow
[02:09:47] think called ZSTD which is a really slow form of compression slow to create the
[02:09:49] form of compression slow to create the archive but if you're building a package
[02:09:51] archive but if you're building a package you have all the time in the world if
[02:09:52] you have all the time in the world if that means you can then shrink the ISO.
[02:09:54] that means you can then shrink the ISO. So on just the two Nvidia packages I
[02:09:56] So on just the two Nvidia packages I think we saved 200 megabytes.
[02:09:59] think we saved 200 megabytes. >> Mhm. So, what I loved about this was I
[02:10:02] >> Mhm. So, what I loved about this was I imagined myself being a car designer at
[02:10:05] imagined myself being a car designer at McLaren. So, McLaren makes some of the
[02:10:08] McLaren. So, McLaren makes some of the lightest super sports cars in the world
[02:10:11] lightest super sports cars in the world right now. And they are absolutely
[02:10:14] right now. And they are absolutely obsessed with shaving every damn last
[02:10:18] obsessed with shaving every damn last gram off their cars. That's why even a
[02:10:20] gram off their cars. That's why even a new 750S McLaren is just way lighter
[02:10:24] new 750S McLaren is just way lighter than the competition. They use a carbon
[02:10:27] than the competition. They use a carbon fiber monco and that helps them over uh
[02:10:30] fiber monco and that helps them over uh like Ferrari for example this uses
[02:10:31] like Ferrari for example this uses aluminum but they also just have this
[02:10:33] aluminum but they also just have this obsession with weight and I would see
[02:10:35] obsession with weight and I would see this interview with the McLaren folks
[02:10:37] this interview with the McLaren folks talking to some journalist just going
[02:10:39] talking to some journalist just going over yeah we saved u 370 g of that one
[02:10:43] over yeah we saved u 370 g of that one and I just went wait what there's
[02:10:46] and I just went wait what there's someone on a car that weighs maybe 1,040
[02:10:50] someone on a car that weighs maybe 1,040 kilos or
[02:10:53] kilos or 380 or something there's they're
[02:10:54] 380 or something there's they're worrying about 370 g.
[02:10:57] worrying about 370 g. >> Yeah,
[02:10:57] >> Yeah, >> what obsessed maniacs. I love them. I
[02:11:01] >> what obsessed maniacs. I love them. I want that in my life. I want a McLaren
[02:11:04] want that in my life. I want a McLaren >> just for that reason. So, I thought in
[02:11:06] >> just for that reason. So, I thought in that moment as as I was shaving
[02:11:08] that moment as as I was shaving individual megabytes off the packages,
[02:11:10] individual megabytes off the packages, man, I'm kind of like a McLaren car
[02:11:13] man, I'm kind of like a McLaren car developer here. Even though I mean, we
[02:11:14] developer here. Even though I mean, we haven't even completed that work. The
[02:11:16] haven't even completed that work. The package could shrink even more. But this
[02:11:19] package could shrink even more. But this is actually this other conflict that
[02:11:20] is actually this other conflict that we've had with Umachi and the
[02:11:22] we've had with Umachi and the traditional Linux community is bloat.
[02:11:26] traditional Linux community is bloat. >> This idea that it's actually not kosher
[02:11:29] >> This idea that it's actually not kosher in certain circles to ship with
[02:11:31] in certain circles to ship with pre-installed software because who are
[02:11:33] pre-installed software because who are you to make decisions about what
[02:11:35] you to make decisions about what programs people should use? And I'm
[02:11:38] programs people should use? And I'm like, dude, it's in the name.
[02:11:40] like, dude, it's in the name. It's called umachi because the um part
[02:11:42] It's called umachi because the um part is short for omic ac which literally
[02:11:45] is short for omic ac which literally means chef's choice. I'm the chef. I'm
[02:11:47] means chef's choice. I'm the chef. I'm making the choices. And this is the
[02:11:50] making the choices. And this is the collection of applications I think is
[02:11:52] collection of applications I think is awesome. Which by the way has a video
[02:11:54] awesome. Which by the way has a video editor. It ships with OBS
[02:11:56] editor. It ships with OBS >> to do your recording. It's just in
[02:11:58] >> to do your recording. It's just in there. OBS is pre-installed.
[02:12:00] there. OBS is pre-installed. >> Caden Live is a video editor timeline
[02:12:03] >> Caden Live is a video editor timeline editor which is great. I edit all my
[02:12:04] editor which is great. I edit all my videos with that. And then I made my own
[02:12:07] videos with that. And then I made my own clip editor. You talked about the thing
[02:12:09] clip editor. You talked about the thing with syncing up. I had this thing with
[02:12:11] with syncing up. I had this thing with clips. So I would do a podcast or
[02:12:12] clips. So I would do a podcast or whatever. I need a clip for X and it's
[02:12:14] whatever. I need a clip for X and it's kind of a hassle to use Ken Live or
[02:12:16] kind of a hassle to use Ken Live or other timeline editors. So I made a cut.
[02:12:19] other timeline editors. So I made a cut. >> Cut is included too. It's just for
[02:12:20] >> Cut is included too. It's just for making clips and you can drive the whole
[02:12:22] making clips and you can drive the whole thing with keyboard. So you can go to
[02:12:24] thing with keyboard. So you can go to just the right time mark and then you
[02:12:26] just the right time mark and then you can hit control space. It moves the clip
[02:12:28] can hit control space. It moves the clip line to that line. Then you go to the
[02:12:30] line to that line. Then you go to the end of the clip and you hit alt space
[02:12:32] end of the clip and you hit alt space and it moves the end line. And then you
[02:12:34] and it moves the end line. And then you hit Ctrl S and it saves. I can make
[02:12:36] hit Ctrl S and it saves. I can make clips so damn fast now with Elma cut.
[02:12:38] clips so damn fast now with Elma cut. It's amazing. But it has all the
[02:12:41] It's amazing. But it has all the software on it. It has Neovim on it. It
[02:12:44] software on it. It has Neovim on it. It has her on it. It has T-Mogs. It has a
[02:12:47] has her on it. It has T-Mogs. It has a terminal. It has a bunch of themes. It
[02:12:49] terminal. It has a bunch of themes. It has a bunch of uh background images. The
[02:12:51] has a bunch of uh background images. The best ones I could pick out. That takes
[02:12:53] best ones I could pick out. That takes up some space. It should because this is
[02:12:56] up some space. It should because this is not supposed to be this just barren
[02:12:59] not supposed to be this just barren landscape where you have to reconstruct
[02:13:00] landscape where you have to reconstruct everything. This is supposed to be a
[02:13:02] everything. This is supposed to be a productive system the minute you unpack
[02:13:04] productive system the minute you unpack it. What is it built in?
[02:13:06] it. What is it built in? >> So, it's actually mostly built in bash
[02:13:09] >> So, it's actually mostly built in bash for the Linux configuration part. Bash
[02:13:12] for the Linux configuration part. Bash is a great language for that. It is um
[02:13:16] is a great language for that. It is um made for that really for system
[02:13:17] made for that really for system administration. It also has its
[02:13:19] administration. It also has its limitations. You should not build
[02:13:21] limitations. You should not build everything in bash.
[02:13:22] everything in bash. >> How are agents with generating bash?
[02:13:23] >> How are agents with generating bash? Pretty good.
[02:13:24] Pretty good. >> Oh, amazing. Except for one thing, and I
[02:13:27] >> Oh, amazing. Except for one thing, and I have to smack the agents over the back
[02:13:29] have to smack the agents over the back of the head every single time I catch it
[02:13:31] of the head every single time I catch it and reminded to look at the agents MD
[02:13:33] and reminded to look at the agents MD file because I will have an instruction
[02:13:35] file because I will have an instruction in there not to make early exits. The
[02:13:38] in there not to make early exits. The agents love to have preconditions
[02:13:40] agents love to have preconditions instead of fully expanded conditionals.
[02:13:44] instead of fully expanded conditionals. I like something that says if this then
[02:13:47] I like something that says if this then do that. agents like to have
[02:13:50] do that. agents like to have precondition or exit, another
[02:13:52] precondition or exit, another precondition or exit, and then it falls
[02:13:55] precondition or exit, and then it falls down to the final thing it actually
[02:13:56] down to the final thing it actually wants to do. I I hate that style. So,
[02:13:58] wants to do. I I hate that style. So, >> except for that, it's gotten shockingly
[02:14:02] >> except for that, it's gotten shockingly dramatically awesomely good to the point
[02:14:05] dramatically awesomely good to the point where when we talked last time, we
[02:14:07] where when we talked last time, we talked about how I would ask the agent
[02:14:08] talked about how I would ask the agent for a bash thing and then I would type
[02:14:10] for a bash thing and then I would type it in myself and I kind of wouldn't
[02:14:11] it in myself and I kind of wouldn't remember. And then I took the effort to
[02:14:13] remember. And then I took the effort to make sure that all that competence
[02:14:14] make sure that all that competence wasn't draining out of my fingers. So, I
[02:14:16] wasn't draining out of my fingers. So, I actually learned how to write bash
[02:14:17] actually learned how to write bash myself and now I'm not writing any bash
[02:14:20] myself and now I'm not writing any bash myself. I have not written any bash
[02:14:21] myself. I have not written any bash myself for probably a couple of months
[02:14:22] myself for probably a couple of months because the agents have just gotten so
[02:14:24] because the agents have just gotten so good that if you give them the few
[02:14:26] good that if you give them the few pointers on style and occasionally put
[02:14:29] pointers on style and occasionally put push back on complexity. This is I I
[02:14:31] push back on complexity. This is I I tweeted about this a couple of days ago.
[02:14:33] tweeted about this a couple of days ago. It blows my mind how often an agent can
[02:14:36] It blows my mind how often an agent can do something, say it's done, have the
[02:14:37] do something, say it's done, have the work reviewed by another agent, they say
[02:14:40] work reviewed by another agent, they say it's done, and then I go like, it looks
[02:14:42] it's done, and then I go like, it looks a little too complicated for me. and
[02:14:44] a little too complicated for me. and then it'll GO LIKE, "OH, YEAH, YOU'RE
[02:14:46] then it'll GO LIKE, "OH, YEAH, YOU'RE RIGHT. YOU'RE RIGHT. I totally over
[02:14:48] RIGHT. YOU'RE RIGHT. I totally over complicated this and it'll cut it in
[02:14:50] complicated this and it'll cut it in half." I'm like, "Couldn't it just do
[02:14:52] half." I'm like, "Couldn't it just do this like from the outset?" And then
[02:14:54] this like from the outset?" And then someone else reminded me. Humans are the
[02:14:56] someone else reminded me. Humans are the same way. If you work on something and
[02:14:59] same way. If you work on something and someone else reviews it and they just
[02:15:01] someone else reviews it and they just are like, "It looks a little
[02:15:02] are like, "It looks a little complicated." Quite often you're able to
[02:15:04] complicated." Quite often you're able to go like, "Ah, you're right." See that
[02:15:06] go like, "Ah, you're right." See that that just those little indications to me
[02:15:09] that just those little indications to me show that the programmer is still needed
[02:15:12] show that the programmer is still needed that intuition because I think what did
[02:15:14] that intuition because I think what did you say? I have a sense of the landscape
[02:15:16] you say? I have a sense of the landscape of the code.
[02:15:17] of the code. >> When I build something like Amachi, I I
[02:15:20] >> When I build something like Amachi, I I do look at the code.
[02:15:22] do look at the code. >> I look at the shape and I look at the
[02:15:24] >> I look at the shape and I look at the proportions
[02:15:25] proportions >> like I don't have to chisel everything
[02:15:26] >> like I don't have to chisel everything myself anymore. This is again when I'm
[02:15:28] myself anymore. This is again when I'm flattering myself. Not one moment I'm a
[02:15:31] flattering myself. Not one moment I'm a McLaren audio out engineer and the next
[02:15:35] McLaren audio out engineer and the next moment I'm a da Vinci working with his
[02:15:37] moment I'm a da Vinci working with his whole studio of students who are doing
[02:15:40] whole studio of students who are doing all the chiseling on the the fine marble
[02:15:42] all the chiseling on the the fine marble right and he goes like ah no the
[02:15:44] right and he goes like ah no the proportions are not quite right. That's
[02:15:46] proportions are not quite right. That's how it feels working with agents now
[02:15:48] how it feels working with agents now that I can give feedback like an editor
[02:15:51] that I can give feedback like an editor >> that do you know what I'm not going to
[02:15:53] >> that do you know what I'm not going to write everything myself but I can tell
[02:15:54] write everything myself but I can tell you when the argument doesn't land. I
[02:15:56] you when the argument doesn't land. I can tell you when the shape isn't
[02:15:59] can tell you when the shape isn't proportional to the problem or when it
[02:16:01] proportional to the problem or when it just feels like it's too complicated.
[02:16:02] just feels like it's too complicated. And shockingly often, it just works.
[02:16:06] And shockingly often, it just works. It's like the early days where the jokes
[02:16:08] It's like the early days where the jokes was don't make mistakes. I don't think
[02:16:10] was don't make mistakes. I don't think you have to tell the agents that anymore
[02:16:12] you have to tell the agents that anymore because now the harnesses are so good.
[02:16:14] because now the harnesses are so good. They run automated testing. They get
[02:16:15] They run automated testing. They get that feedback. But you actually do have
[02:16:17] that feedback. But you actually do have to tell them make it simpler.
[02:16:19] to tell them make it simpler. >> Do you use voice at all for the
[02:16:20] >> Do you use voice at all for the interaction or are you how much are you
[02:16:23] interaction or are you how much are you typing? How much are you
[02:16:24] typing? How much are you >> I type the whole thing. I actually
[02:16:26] >> I type the whole thing. I actually Inomachi's built-in vox type um audio
[02:16:29] Inomachi's built-in vox type um audio transcription and it's actually really
[02:16:31] transcription and it's actually really good. I just find that
[02:16:33] good. I just find that >> I don't think that way and it surprised
[02:16:36] >> I don't think that way and it surprised me myself that I don't like to talk to
[02:16:38] me myself that I don't like to talk to the computer. Uh I like when I'm in the
[02:16:41] the computer. Uh I like when I'm in the car, but when I'm in the front of the
[02:16:43] car, but when I'm in the front of the keyboard, I just want to type. I also
[02:16:45] keyboard, I just want to type. I also just love typing. Are you using the
[02:16:46] just love typing. Are you using the voice?
[02:16:46] voice? >> I'm an introvert who doesn't like social
[02:16:48] >> I'm an introvert who doesn't like social interaction or speaking.
[02:16:51] interaction or speaking. >> I think that's part of mine, too. But
[02:16:54] >> I think that's part of mine, too. But like for me, for some reason, voice is
[02:16:56] like for me, for some reason, voice is really powerful. I want to give this. So
[02:16:59] really powerful. I want to give this. So I I run with this thing. It's called
[02:17:00] I I run with this thing. It's called Plaude. So I just hook it up on my, you
[02:17:03] Plaude. So I just hook it up on my, you know, um, on my t-shirt here. You press
[02:17:06] know, um, on my t-shirt here. You press a button, it starts recording.
[02:17:08] a button, it starts recording. >> And this is actually more in terms of
[02:17:10] >> And this is actually more in terms of flow much better experience than behind
[02:17:12] flow much better experience than behind a computer. And I uh save well, usually
[02:17:17] a computer. And I uh save well, usually it's agent generated problems that I
[02:17:20] it's agent generated problems that I want to really talk through. And so I
[02:17:24] want to really talk through. And so I program I write I speak a long prompt
[02:17:28] program I write I speak a long prompt like and a lot of it it's like stream of
[02:17:30] like and a lot of it it's like stream of consciousness reasoning. So I'll
[02:17:33] consciousness reasoning. So I'll sometimes just change my mind about a
[02:17:35] sometimes just change my mind about a design but all of that is in there. And
[02:17:37] design but all of that is in there. And then I have an LLM that processes that
[02:17:39] then I have an LLM that processes that with with plaud. There's a obviously an
[02:17:42] with with plaud. There's a obviously an API you can grab it, transcribe it,
[02:17:44] API you can grab it, transcribe it, clean up the transcript because you you
[02:17:46] clean up the transcript because you you want it to be because I'm referring to
[02:17:48] want it to be because I'm referring to files.
[02:17:49] files. I'm I'm referring to technical concepts
[02:17:52] I'm I'm referring to technical concepts like files and functions and so on that
[02:17:54] like files and functions and so on that you want to make sure the transcription
[02:17:56] you want to make sure the transcription the the speech to text gets correctly.
[02:17:58] the the speech to text gets correctly. So you want to have a dictionary. You
[02:17:59] So you want to have a dictionary. You want to be aware of the code base when
[02:18:01] want to be aware of the code base when you process the files.
[02:18:02] you process the files. >> And then you have this gigantic thing
[02:18:04] >> And then you have this gigantic thing that's often 10 15 20 minute me
[02:18:07] that's often 10 15 20 minute me discussing the full design. And I find
[02:18:11] discussing the full design. And I find that to be really really powerful
[02:18:14] that to be really really powerful because it doesn't have the problem over
[02:18:17] because it doesn't have the problem over of over specification because of how
[02:18:20] of over specification because of how much stream of consciousness thinking
[02:18:23] much stream of consciousness thinking the the system has about what you're
[02:18:26] the the system has about what you're imagining. And this is really good for
[02:18:28] imagining. And this is really good for the early steps of a design. Like if I
[02:18:30] the early steps of a design. Like if I wanted to build a machi from scratch,
[02:18:32] wanted to build a machi from scratch, the first stages I I talk through, it
[02:18:36] the first stages I I talk through, it could be an hour. There's been prompts
[02:18:37] could be an hour. There's been prompts that I had for an hour and I'm just
[02:18:40] that I had for an hour and I'm just running and and speaking. I highly
[02:18:42] running and and speaking. I highly recommend
[02:18:44] recommend >> people try uh voice based
[02:18:48] >> people try uh voice based speaking for prolonged periods of time
[02:18:51] speaking for prolonged periods of time >> as opposed to very Yeah, I haven't used
[02:18:53] >> as opposed to very Yeah, I haven't used it that maybe that's how I'm using it
[02:18:55] it that maybe that's how I'm using it wrong. I try to just type or speak two
[02:18:58] wrong. I try to just type or speak two sentences and then I get a little
[02:19:00] sentences and then I get a little frustrated that I could have typed that
[02:19:02] frustrated that I could have typed that just as fast maybe. But I have not tried
[02:19:06] just as fast maybe. But I have not tried this whole thing of just talking
[02:19:07] this whole thing of just talking continuously for 20 minutes.
[02:19:09] continuously for 20 minutes. >> Hey, and especially you because you
[02:19:11] >> Hey, and especially you because you speak very fast.
[02:19:13] speak very fast. >> Yeah. No, I could see it. I think
[02:19:15] >> Yeah. No, I could see it. I think because the reason I've been I've been
[02:19:16] because the reason I've been I've been trying to do it for things like replying
[02:19:18] trying to do it for things like replying to emails and it got to a point where I
[02:19:22] to emails and it got to a point where I thought it could help and it sort of
[02:19:24] thought it could help and it sort of did, but then it would make a small
[02:19:26] did, but then it would make a small mistake and I had to correct the
[02:19:27] mistake and I had to correct the mistake. But if you're doing stream of
[02:19:29] mistake. But if you're doing stream of conscious to an LLM who doesn't care
[02:19:31] conscious to an LLM who doesn't care about all this other stuff anyway, that
[02:19:33] about all this other stuff anyway, that probably works way better. There's two
[02:19:35] probably works way better. There's two things you have to do. One, okay, you
[02:19:36] things you have to do. One, okay, you have the raw audio transcribes it. I use
[02:19:39] have the raw audio transcribes it. I use 11 last for transcription. They're
[02:19:41] 11 last for transcription. They're probably the best specy text model.
[02:19:43] probably the best specy text model. There's still mistakes there. So, you
[02:19:45] There's still mistakes there. So, you need to have a prompt that has a access
[02:19:48] need to have a prompt that has a access to a dictionary and to allow
[02:19:51] to a dictionary and to allow >> How do you build the dictionary?
[02:19:52] >> How do you build the dictionary? >> First of all, it's a dictionary of terms
[02:19:54] >> First of all, it's a dictionary of terms that are relevant to you. Then have it
[02:19:56] that are relevant to you. Then have it aware of so you have an agent that looks
[02:19:58] aware of so you have an agent that looks through when you're talking about code,
[02:20:00] through when you're talking about code, looks through your entire code base for
[02:20:02] looks through your entire code base for key terms that you use often. Also, when
[02:20:04] key terms that you use often. Also, when you we're talking about messaging, Gmail
[02:20:06] you we're talking about messaging, Gmail and WhatsApp and so on, it's aware of
[02:20:08] and WhatsApp and so on, it's aware of all the people and common terms that you
[02:20:11] all the people and common terms that you get wrong.
[02:20:11] get wrong. >> You've really gone deep in this.
[02:20:13] >> You've really gone deep in this. >> That to me is a problem that needs to be
[02:20:15] >> That to me is a problem that needs to be solved because
[02:20:16] solved because >> uh one of the issues you probably have
[02:20:18] >> uh one of the issues you probably have speech to text is uh that it makes
[02:20:21] speech to text is uh that it makes mistakes sometimes.
[02:20:22] mistakes sometimes. >> Correct. Then I can't use it for
[02:20:24] >> Correct. Then I can't use it for dictating an email.
[02:20:25] dictating an email. >> Right. If it never makes mistakes,
[02:20:28] >> Right. If it never makes mistakes, >> then it would be more appealing.
[02:20:29] >> then it would be more appealing. >> Yeah. And you are okay being not
[02:20:31] >> Yeah. And you are okay being not perfectly real time. Actually, you
[02:20:34] perfectly real time. Actually, you you're okay waiting 5 seconds
[02:20:36] you're okay waiting 5 seconds potentially. I I don't know what your
[02:20:38] potentially. I I don't know what your use case is. I'm okay waiting 5 seconds,
[02:20:40] use case is. I'm okay waiting 5 seconds, 10 seconds for it to process everything.
[02:20:43] 10 seconds for it to process everything. >> You got to vibe coat this into an app
[02:20:45] >> You got to vibe coat this into an app that does all of this such that
[02:20:47] that does all of this such that >> it just works.
[02:20:48] >> it just works. >> I think I mentioned to you offline
[02:20:52] >> I think I mentioned to you offline that it's very surprising to me that um
[02:20:56] that it's very surprising to me that um translation is not done perfectly,
[02:20:58] translation is not done perfectly, >> right? speech to speech translation.
[02:21:00] >> right? speech to speech translation. >> It seems like you've gotten much closer
[02:21:01] >> It seems like you've gotten much closer to the best of what's possible by
[02:21:03] to the best of what's possible by putting all these things together.
[02:21:06] putting all these things together. >> But, you know, when you're shipping that
[02:21:08] >> But, you know, when you're shipping that kind of stuff, you do have to start
[02:21:09] kind of stuff, you do have to start thinking about latency.
[02:21:11] thinking about latency. >> Don't let the uh perfect be the enemy of
[02:21:13] >> Don't let the uh perfect be the enemy of good. I mean, if you're suddenly
[02:21:16] good. I mean, if you're suddenly enabling something people wouldn't be
[02:21:18] enabling something people wouldn't be doing before at all, it's okay to take 5
[02:21:20] doing before at all, it's okay to take 5 seconds longer. I think this is one of
[02:21:22] seconds longer. I think this is one of the areas that Steve Jobs was so good
[02:21:24] the areas that Steve Jobs was so good that he realized like the first iPhone
[02:21:26] that he realized like the first iPhone was terrible in all sorts of waves,
[02:21:28] was terrible in all sorts of waves, right? Absolutely horrendously slow data
[02:21:31] right? Absolutely horrendously slow data connection, very underpowered, all the
[02:21:34] connection, very underpowered, all the things. But the product was so
[02:21:36] things. But the product was so compelling
[02:21:37] compelling >> that it just didn't matter. You'd be
[02:21:40] >> that it just didn't matter. You'd be shipping too late if you waited until
[02:21:42] shipping too late if you waited until everything was just right, just perfect.
[02:21:44] everything was just right, just perfect. If you're solving a problem that people
[02:21:45] If you're solving a problem that people currently don't have a solution for,
[02:21:47] currently don't have a solution for, they're willing to give it 5 seconds. If
[02:21:50] they're willing to give it 5 seconds. If you're in a competitive market, yeah,
[02:21:51] you're in a competitive market, yeah, okay, it's different, but that means the
[02:21:52] okay, it's different, but that means the problem's already solved and you don't
[02:21:54] problem's already solved and you don't need to solve it.
[02:21:55] need to solve it. >> Well, I do think u there's a few like
[02:21:58] >> Well, I do think u there's a few like whisper flow is really good. A few
[02:22:00] whisper flow is really good. A few people have stepped up that speech to
[02:22:02] people have stepped up that speech to text thing.
[02:22:03] text thing. >> Yeah. Yeah. We were using box type
[02:22:06] >> Yeah. Yeah. We were using box type is open source.
[02:22:07] is open source. >> It is. It's just using one of the open
[02:22:09] >> It is. It's just using one of the open models. I forget which parrot model it's
[02:22:12] models. I forget which parrot model it's using or something like that. It works
[02:22:14] using or something like that. It works quite well for short commands. So, I
[02:22:15] quite well for short commands. So, I have used it for that. Uh, I think you
[02:22:18] have used it for that. Uh, I think you just hold down F9 and it starts a
[02:22:21] just hold down F9 and it starts a dictation.
[02:22:22] dictation. >> Oh, so it's already in there.
[02:22:23] >> Oh, so it's already in there. >> You just have to get online. It'll offer
[02:22:25] >> You just have to get online. It'll offer you to install the box type package
[02:22:27] you to install the box type package because the box type package includes a
[02:22:29] because the box type package includes a model that's 150 megabytes. And I was
[02:22:31] model that's 150 megabytes. And I was like, ah, I don't know if I can carry
[02:22:33] like, ah, I don't know if I can carry that.
[02:22:34] that. >> So,
[02:22:35] >> So, >> yep,
[02:22:36] >> yep, >> we don't have that in there um by
[02:22:38] >> we don't have that in there um by default. But we have the option set up.
[02:22:40] default. But we have the option set up. And I actually just yesterday was
[02:22:43] And I actually just yesterday was thinking we really need to combine all
[02:22:45] thinking we really need to combine all of these things. So, Umachi Quattro is
[02:22:48] of these things. So, Umachi Quattro is truly amazing as a malible operating
[02:22:51] truly amazing as a malible operating system where you can add functionality
[02:22:53] system where you can add functionality to it just by talking to your agent.
[02:22:56] to it just by talking to your agent. >> But that's exactly what we should be
[02:22:57] >> But that's exactly what we should be doing. There's a lot of people who would
[02:23:00] doing. There's a lot of people who would find it very natural just to talk to
[02:23:02] find it very natural just to talk to their computer and say, "Hey, can you
[02:23:04] their computer and say, "Hey, can you make me a stock panel? I want to track
[02:23:07] make me a stock panel? I want to track uh Apple and Dell." and just see the
[02:23:11] uh Apple and Dell." and just see the agent go off through entirely through
[02:23:14] agent go off through entirely through voice both in terms of the input and in
[02:23:16] voice both in terms of the input and in terms of the output and then your
[02:23:18] terms of the output and then your operating system just changes. This was
[02:23:20] operating system just changes. This was the vision of Iron Man and Jarvis and
[02:23:23] the vision of Iron Man and Jarvis and bespoke applications that just appear
[02:23:27] bespoke applications that just appear magically. I'm thinking the area of AI I
[02:23:30] magically. I'm thinking the area of AI I find truly intriguing are these uh live
[02:23:33] find truly intriguing are these uh live gaming models. I don't know if you've
[02:23:34] gaming models. I don't know if you've seen that where the AI is inventing
[02:23:36] seen that where the AI is inventing literally the next frame, but you can
[02:23:38] literally the next frame, but you can actually play the game. And I think if
[02:23:41] actually play the game. And I think if they're able to do that, why can't we do
[02:23:42] they're able to do that, why can't we do that with our operating system? Why
[02:23:44] that with our operating system? Why can't we just talk to it and ask it to
[02:23:46] can't we just talk to it and ask it to be a different way or change and it'll
[02:23:49] be a different way or change and it'll all just change? I think this, by the
[02:23:50] all just change? I think this, by the way, is one of the other breakthroughs
[02:23:52] way, is one of the other breakthroughs that is going to lead to the total
[02:23:55] that is going to lead to the total domination of Linux.
[02:23:57] domination of Linux. The agents have taken all of the
[02:23:59] The agents have taken all of the hardship out of diagnosing
[02:24:02] hardship out of diagnosing Linux systems and turned the fact that
[02:24:05] Linux systems and turned the fact that Linux produces these overly specific,
[02:24:08] Linux produces these overly specific, totally arcane error messages into its
[02:24:11] totally arcane error messages into its greatest advantage. When Linux has an
[02:24:14] greatest advantage. When Linux has an issue, the agent can take that very
[02:24:17] issue, the agent can take that very specific error message that makes no
[02:24:18] specific error message that makes no sense to a normal human and correlated
[02:24:21] sense to a normal human and correlated with the fact that the agent was
[02:24:22] with the fact that the agent was pre-trained on 40 million lines of Linux
[02:24:24] pre-trained on 40 million lines of Linux code. So, it knows exactly where to look
[02:24:27] code. So, it knows exactly where to look and dial it down. I have not had a
[02:24:29] and dial it down. I have not had a single problem on my Linux machine since
[02:24:32] single problem on my Linux machine since the beginning of this year that an agent
[02:24:34] the beginning of this year that an agent could not diagnose. That was not true a
[02:24:38] could not diagnose. That was not true a year and a half ago. A year and a half
[02:24:39] year and a half ago. A year and a half ago, I was still searching on forums to
[02:24:42] ago, I was still searching on forums to find answers to esoteric questions. Now,
[02:24:46] find answers to esoteric questions. Now, the agents know the source codes of not
[02:24:48] the agents know the source codes of not just the Linux operating system, but
[02:24:51] just the Linux operating system, but every single piece of software I have on
[02:24:52] every single piece of software I have on that box, the agent has access to the
[02:24:55] that box, the agent has access to the source code of all of it. In fact, this
[02:24:56] source code of all of it. In fact, this was one thing I built in just before we
[02:24:59] was one thing I built in just before we shipped. So, once you set up your
[02:25:01] shipped. So, once you set up your default agent,
[02:25:02] default agent, >> Umachi Quattro has a crasher. If any app
[02:25:07] >> Umachi Quattro has a crasher. If any app on your machine crashes, it'll pop up a
[02:25:09] on your machine crashes, it'll pop up a little thing ask you whether you want
[02:25:11] little thing ask you whether you want your AI to diagnose the problem.
[02:25:13] your AI to diagnose the problem. >> Yeah,
[02:25:14] >> Yeah, >> that's amazing.
[02:25:14] >> that's amazing. >> Unbelievable. I've seen things where
[02:25:18] >> Unbelievable. I've seen things where there's an error in u some subsystem
[02:25:20] there's an error in u some subsystem some sub not even Linux just some app I
[02:25:22] some sub not even Linux just some app I installed the agent start digging
[02:25:25] installed the agent start digging through the logs and looks up system
[02:25:27] through the logs and looks up system dlog then it checks out the damn source
[02:25:29] dlog then it checks out the damn source code of the application that crashed
[02:25:32] code of the application that crashed pins down that it's in this rust file
[02:25:35] pins down that it's in this rust file line 472
[02:25:38] line 472 that there's an unbounded unwrapped
[02:25:40] that there's an unbounded unwrapped variable that overflowed or whatever it
[02:25:42] variable that overflowed or whatever it is then offer you whether you want to
[02:25:46] is then offer you whether you want to file a bug report with all this detail.
[02:25:49] file a bug report with all this detail. I'll give you one amazing anecdote. So I
[02:25:51] I'll give you one amazing anecdote. So I was working with um this guy JDX who's
[02:25:54] was working with um this guy JDX who's working on MIS this package manager for
[02:25:57] working on MIS this package manager for uh fastmoving development tools. This is
[02:25:59] uh fastmoving development tools. This is how we manage all the agent software and
[02:26:00] how we manage all the agent software and so forth. Normal package managers are
[02:26:02] so forth. Normal package managers are not built to be updated seven times a
[02:26:04] not built to be updated seven times a day and all of these agent harnesses are
[02:26:07] day and all of these agent harnesses are updated about seven times a day. So we
[02:26:08] updated about seven times a day. So we needed an outofband uh package manager
[02:26:11] needed an outofband uh package manager and MI just turns out to be perfect for
[02:26:13] and MI just turns out to be perfect for this. Anyway, it had a small bug. There
[02:26:15] this. Anyway, it had a small bug. There was some uh race condition which agents
[02:26:18] was some uh race condition which agents are very good at finding because when
[02:26:19] are very good at finding because when you start running multiple agents at the
[02:26:20] you start running multiple agents at the same time, they will sus out all these
[02:26:22] same time, they will sus out all these race conditions you have in your
[02:26:23] race conditions you have in your underlying infrastructure that was never
[02:26:25] underlying infrastructure that was never triggered by a human trying to do manual
[02:26:27] triggered by a human trying to do manual thing. So, it finds this issue, right? I
[02:26:30] thing. So, it finds this issue, right? I tell um I tell the agent, hey, um can
[02:26:34] tell um I tell the agent, hey, um can you post this as a bug report to to
[02:26:37] you post this as a bug report to to JDX's GitHub? And unfortunately, right
[02:26:41] JDX's GitHub? And unfortunately, right before that, I had had it do a QA run on
[02:26:44] before that, I had had it do a QA run on Amachi itself with eight different
[02:26:47] Amachi itself with eight different agents. It had found 28 real issues that
[02:26:49] agents. It had found 28 real issues that it needed to file. Well, it went to
[02:26:51] it needed to file. Well, it went to GitHub and tried to file all 28 issues
[02:26:54] GitHub and tried to file all 28 issues at the same time, which it did in about
[02:26:57] at the same time, which it did in about uh I don't know 12 seconds.
[02:26:59] uh I don't know 12 seconds. >> GitHub not unreasonably marked that as
[02:27:02] >> GitHub not unreasonably marked that as probable spam and banned my omachi bot.
[02:27:05] probable spam and banned my omachi bot. And then I couldn't do that. So, I was
[02:27:08] And then I couldn't do that. So, I was blocked from the bot having access to
[02:27:10] blocked from the bot having access to GitHub. So, I just told it, hey, do you
[02:27:12] GitHub. So, I just told it, hey, do you know what? Just email
[02:27:14] know what? Just email >> uh JDX. Here's his email address. I had
[02:27:16] >> uh JDX. Here's his email address. I had already set it up with hey.com, an email
[02:27:18] already set it up with hey.com, an email address. We have a
[02:27:19] address. We have a >> CLI that's in beta right now. So, I had
[02:27:21] >> CLI that's in beta right now. So, I had set it up with that. So, it can send an
[02:27:22] set it up with that. So, it can send an email. That's how it gives me reports
[02:27:24] email. That's how it gives me reports about outstanding issues and and PR. So,
[02:27:27] about outstanding issues and and PR. So, it sends
[02:27:29] it sends um JDX this email about the bug it
[02:27:31] um JDX this email about the bug it found. And he was like, "Wait, this is
[02:27:34] found. And he was like, "Wait, this is the first time I've gotten a bug report
[02:27:36] the first time I've gotten a bug report in unreleased software." Because it had
[02:27:38] in unreleased software." Because it had downloaded the source code to MIS, saw
[02:27:41] downloaded the source code to MIS, saw that he had already fixed the bug, but
[02:27:43] that he had already fixed the bug, but that it would not fix the problem
[02:27:45] that it would not fix the problem entirely in software they had not
[02:27:47] entirely in software they had not shipped yet.
[02:27:47] shipped yet. >> Y
[02:27:48] >> Y >> pinpointed the problem and he was like,
[02:27:50] >> pinpointed the problem and he was like, >> "Damn it, I got bug report before we
[02:27:52] >> "Damn it, I got bug report before we even cut a release
[02:27:53] even cut a release >> on unbelievable AGI levels of
[02:27:58] >> on unbelievable AGI levels of >> mind-blowing stuff." And that was
[02:28:00] >> mind-blowing stuff." And that was actually if you remember that was that
[02:28:02] actually if you remember that was that was an open question whether AI systems
[02:28:04] was an open question whether AI systems could debug well that that was kind of
[02:28:07] could debug well that that was kind of the the the thought that yeah sure they
[02:28:09] the the the thought that yeah sure they can write code but can they find issues?
[02:28:11] can write code but can they find issues? They are so incredibly good at this. And
[02:28:14] They are so incredibly good at this. And this is actually interesting because I
[02:28:16] this is actually interesting because I was on the perhaps same side of that a
[02:28:18] was on the perhaps same side of that a little skeptical about can it reason
[02:28:19] little skeptical about can it reason about all these things and uh Mikail
[02:28:22] about all these things and uh Mikail who's the CTO at Shopify ran a
[02:28:24] who's the CTO at Shopify ran a scientific study on this they had and
[02:28:27] scientific study on this they had and this was I think late last year or early
[02:28:29] this was I think late last year or early this year where he had agents go back
[02:28:31] this year where he had agents go back through all the incidents and both
[02:28:33] through all the incidents and both outages and and other problems that
[02:28:35] outages and and other problems that Shopify had had in production trace that
[02:28:37] Shopify had had in production trace that back to the PR that was merged and find
[02:28:40] back to the PR that was merged and find out whether PRs that had been reviewed
[02:28:42] out whether PRs that had been reviewed by human or PRs that have been reviewed
[02:28:45] by human or PRs that have been reviewed by agents were of higher quality. Well,
[02:28:48] by agents were of higher quality. Well, low enterprise.
[02:28:50] low enterprise. >> The PRs that have been reviewed by
[02:28:53] >> The PRs that have been reviewed by agents caused fewer issues in
[02:28:56] agents caused fewer issues in production. And this was with models we
[02:28:58] production. And this was with models we had 6 months ago. At this point, 100% in
[02:29:02] had 6 months ago. At this point, 100% in the majority of domains we work in
[02:29:04] the majority of domains we work in today, agents are better at finding
[02:29:06] today, agents are better at finding bugs.
[02:29:07] bugs. >> So, uh you now run agents all day. Uh,
[02:29:11] >> So, uh you now run agents all day. Uh, what stands out to you as the better as
[02:29:13] what stands out to you as the better as the better model? Who's currently
[02:29:14] the better model? Who's currently winning? It seems to be changing
[02:29:15] winning? It seems to be changing constantly. Soul, Fable, Gro 46, Gemini,
[02:29:21] constantly. Soul, Fable, Gro 46, Gemini, the Chinese openweight models. What's
[02:29:24] the Chinese openweight models. What's amazing to me is that you could rattle
[02:29:27] amazing to me is that you could rattle off so many different contenders that
[02:29:30] off so many different contenders that this market is so wide open that it does
[02:29:34] this market is so wide open that it does actually change back and forth that we
[02:29:36] actually change back and forth that we have real competition that there are so
[02:29:38] have real competition that there are so many labs that are able to get either to
[02:29:42] many labs that are able to get either to the frontier or close to it. That's by
[02:29:45] the frontier or close to it. That's by the way is remarkable. I still don't
[02:29:47] the way is remarkable. I still don't fully understand that. But to answer
[02:29:49] fully understand that. But to answer your question, the best model in general
[02:29:52] your question, the best model in general right now is Fable. Mhm.
[02:29:54] right now is Fable. Mhm. >> The second best model in my opinion is
[02:29:56] >> The second best model in my opinion is Opus 5. But the tier just below Opus 5,
[02:30:01] Opus 5. But the tier just below Opus 5, and it's not even that they're always
[02:30:04] and it's not even that they're always below. Sometimes they're ahead.
[02:30:05] below. Sometimes they're ahead. >> I'll get to that in a second. I would
[02:30:08] >> I'll get to that in a second. I would rank um GPT Soul very good.
[02:30:12] rank um GPT Soul very good. >> Mhm.
[02:30:13] >> Mhm. >> Gro 46 I just started testing a few days
[02:30:16] >> Gro 46 I just started testing a few days ago. I had this wonderful te test that
[02:30:19] ago. I had this wonderful te test that I've set up by accident where I
[02:30:21] I've set up by accident where I translated this Python library into
[02:30:24] translated this Python library into Rust, the screen saver you just saw with
[02:30:27] Rust, the screen saver you just saw with all the cool animation that's powered by
[02:30:29] all the cool animation that's powered by a Python library called terminal text
[02:30:31] a Python library called terminal text effects. Really cool library. We've been
[02:30:33] effects. Really cool library. We've been using it since the first day of uh
[02:30:35] using it since the first day of uh Omachi.
[02:30:36] Omachi. >> The problem with that is it's written in
[02:30:38] >> The problem with that is it's written in Python. So when it starts up, especially
[02:30:40] Python. So when it starts up, especially on a laptop, and it runs in Python, it
[02:30:42] on a laptop, and it runs in Python, it uses uh all of your CPU to do these
[02:30:45] uses uh all of your CPU to do these effects and therefore it means it uses
[02:30:47] effects and therefore it means it uses about 30 watts of energy and it spins up
[02:30:49] about 30 watts of energy and it spins up your fans and it drains your battery.
[02:30:52] your fans and it drains your battery. >> Mhm.
[02:30:52] >> Mhm. >> Doesn't really matter on a local
[02:30:54] >> Doesn't really matter on a local computer, but it does matter on a
[02:30:55] computer, but it does matter on a laptop. So I thought, do you know what?
[02:30:56] laptop. So I thought, do you know what? This sounds like a problem for Rust.
[02:30:59] This sounds like a problem for Rust. So first I gave Fable the challenge,
[02:31:03] So first I gave Fable the challenge, and all I told it was, here's the source
[02:31:06] and all I told it was, here's the source code for the Python library. this TD8
[02:31:09] code for the Python library. this TD8 library that had a bunch of dependencies
[02:31:10] library that had a bunch of dependencies and so forth. I want a Rust version of
[02:31:14] and so forth. I want a Rust version of this with no dependencies, a single
[02:31:16] this with no dependencies, a single executable. Like that's what Rust does.
[02:31:18] executable. Like that's what Rust does. So basically, I want it in Rust. I want
[02:31:20] So basically, I want it in Rust. I want it to be pixel perfect frame by frame.
[02:31:23] it to be pixel perfect frame by frame. Do a full analysis. Don't stop until
[02:31:26] Do a full analysis. Don't stop until you're finished.
[02:31:26] you're finished. >> Yep.
[02:31:27] >> Yep. >> That was the prompt.
[02:31:28] >> That was the prompt. >> Yep.
[02:31:29] >> Yep. >> I kid you not, in just under 45 minutes,
[02:31:33] >> I kid you not, in just under 45 minutes, it was like ding. I heard her.
[02:31:36] it was like ding. I heard her. >> I'm finished. I've checked everything. I
[02:31:39] >> I'm finished. I've checked everything. I have reduced
[02:31:41] have reduced the startup time from 86 milliseconds to
[02:31:46] the startup time from 86 milliseconds to 2 milliseconds.
[02:31:48] 2 milliseconds. I have sped up the execution time by 9.6
[02:31:53] I have sped up the execution time by 9.6 times. I believe it was. The executable
[02:31:56] times. I believe it was. The executable is 3 megabytes. Do you want to run it?
[02:32:00] is 3 megabytes. Do you want to run it? >> That's awesome.
[02:32:00] >> That's awesome. >> So, I run it.
[02:32:01] >> So, I run it. >> Oh, man. And I don't know why I'm
[02:32:04] >> Oh, man. And I don't know why I'm surprised because this translation job
[02:32:07] surprised because this translation job is something we've known for a while
[02:32:09] is something we've known for a while that AI is pretty good at. But it was
[02:32:11] that AI is pretty good at. But it was still staggering to me that I could
[02:32:13] still staggering to me that I could oneshot
[02:32:14] oneshot a full translation of a Python library I
[02:32:19] a full translation of a Python library I had been using for a year that others
[02:32:20] had been using for a year that others had been using for much longer and turn
[02:32:23] had been using for much longer and turn it into a Rust executable without
[02:32:25] it into a Rust executable without knowing any Rust without looking at the
[02:32:28] knowing any Rust without looking at the Rust code at all and produced this
[02:32:30] Rust code at all and produced this executable that I then told the agent
[02:32:33] executable that I then told the agent right after this is great ship it. It
[02:32:36] right after this is great ship it. It packaged it up as a new package. It told
[02:32:38] packaged it up as a new package. It told me what do you want it to call? Uh it's
[02:32:39] me what do you want it to call? Uh it's called TTFX. Let's create a new git
[02:32:41] called TTFX. Let's create a new git repo. It sets up the git repo. Let's
[02:32:43] repo. It sets up the git repo. Let's create a new uh package build package
[02:32:45] create a new uh package build package for our um build system. It pushs that
[02:32:48] for our um build system. It pushs that up. Let's push it out. Let's uh open the
[02:32:51] up. Let's push it out. Let's uh open the pull request to itself. So we switch
[02:32:53] pull request to itself. So we switch around from TTE, the Python
[02:32:55] around from TTE, the Python implementation to TTFX. It does all of
[02:32:58] implementation to TTFX. It does all of it. And I'm just sitting there and again
[02:33:01] it. And I'm just sitting there and again I'm already at this point fully
[02:33:02] I'm already at this point fully delirious with agent acceleration. And I
[02:33:05] delirious with agent acceleration. And I still had to lean back and I go like
[02:33:07] still had to lean back and I go like this is AGI, isn't it? This is what AGI
[02:33:10] this is AGI, isn't it? This is what AGI looks like. If we have if these moments
[02:33:13] looks like. If we have if these moments are just what it is all the time, this
[02:33:15] are just what it is all the time, this is AGI.
[02:33:15] is AGI. >> Now, as I understand you, you also
[02:33:18] >> Now, as I understand you, you also repeated the same experiment, not just
[02:33:20] repeated the same experiment, not just with Fable.
[02:33:21] with Fable. >> I did it on all the models. First, I did
[02:33:23] >> I did it on all the models. First, I did it um actually funny thing. So, I ran
[02:33:26] it um actually funny thing. So, I ran out of Fable tokens about 2/3 through
[02:33:30] out of Fable tokens about 2/3 through and it just automatically switched over
[02:33:32] and it just automatically switched over to Opus 5 and kept going and finished
[02:33:33] to Opus 5 and kept going and finished the job. Part of the reason why I think
[02:33:36] the job. Part of the reason why I think it was able to do that was that the
[02:33:38] it was able to do that was that the first thing Fable did was create a plan
[02:33:41] first thing Fable did was create a plan and it was a really detailed plan. I
[02:33:42] and it was a really detailed plan. I think it had eight separate steps of
[02:33:44] think it had eight separate steps of here you do it, here how you analyze it
[02:33:46] here you do it, here how you analyze it and here you run the effects and so I
[02:33:47] and here you run the effects and so I didn't review the plan at all. I didn't
[02:33:49] didn't review the plan at all. I didn't change the plan. It just made the plan
[02:33:51] change the plan. It just made the plan so Opus could take over and then I
[02:33:54] so Opus could take over and then I thought well if Opus can finish the job
[02:33:57] thought well if Opus can finish the job maybe some of the other agents could
[02:33:59] maybe some of the other agents could finish it too. So the first thing I did
[02:34:01] finish it too. So the first thing I did was I gave it to I think I gave it to
[02:34:04] was I gave it to I think I gave it to Saul.
[02:34:05] Saul. >> Mhm.
[02:34:05] >> Mhm. >> And Saul finished the job to it took
[02:34:07] >> And Saul finished the job to it took twice as long. So it took I think about
[02:34:09] twice as long. So it took I think about an hour and a half. But here's the
[02:34:12] an hour and a half. But here's the kicker. The per token cost. I didn't pay
[02:34:14] kicker. The per token cost. I didn't pay per token. I have a max subscription to
[02:34:16] per token. I have a max subscription to to Cloud, right? So it did it within the
[02:34:18] to Cloud, right? So it did it within the subscription. It used all my tokens and
[02:34:19] subscription. It used all my tokens and I had to switch over to Opus 5. But if I
[02:34:22] I had to switch over to Opus 5. But if I had paid per token, it would have been
[02:34:24] had paid per token, it would have been 550 bucks, I think, to do the whole
[02:34:26] 550 bucks, I think, to do the whole thing. And I thought for a second, holy
[02:34:28] thing. And I thought for a second, holy what a steal. If I personally had
[02:34:32] what a steal. If I personally had to learn Rust well enough to be able to
[02:34:34] to learn Rust well enough to be able to do this translation, I'm looking at a
[02:34:36] do this translation, I'm looking at a 9month job here.
[02:34:39] 9month job here. I can pay 500 bucks to have this
[02:34:42] I can pay 500 bucks to have this translation happen. And suddenly I get a
[02:34:43] translation happen. And suddenly I get a 10x execution speed up. This is I would
[02:34:46] 10x execution speed up. This is I would totally pay 500 bucks for this. But but
[02:34:50] totally pay 500 bucks for this. But but competition. So I give it to Saul. Same
[02:34:52] competition. So I give it to Saul. Same plan. To be fair, I didn't ask Saul to
[02:34:55] plan. To be fair, I didn't ask Saul to do the plan. I just took the fable plan,
[02:34:56] do the plan. I just took the fable plan, gave it to Saul.
[02:34:58] gave it to Saul. >> Saul in an hour and a half and I think
[02:35:02] >> Saul in an hour and a half and I think 46 $6 worth of token repeated the task.
[02:35:08] 46 $6 worth of token repeated the task. >> Yeah.
[02:35:08] >> Yeah. >> Did the same thing.
[02:35:10] >> Did the same thing. >> Mhm.
[02:35:11] >> Mhm. >> And I thought, well,
[02:35:14] >> And I thought, well, blimey, that's amazing. Then I got
[02:35:16] blimey, that's amazing. Then I got greedy.
[02:35:16] greedy. >> Yeah. So I asked uh GPT Luna which is
[02:35:21] >> Yeah. So I asked uh GPT Luna which is this crazy cheap model that uh OpenAI
[02:35:25] this crazy cheap model that uh OpenAI has as well. Can you do it? Absolutely
[02:35:29] has as well. Can you do it? Absolutely not. First of all, it didn't even want
[02:35:31] not. First of all, it didn't even want to start the task. I think something
[02:35:33] to start the task. I think something happened uh I don't know I think it was
[02:35:35] happened uh I don't know I think it was in the spring where we didn't need these
[02:35:38] in the spring where we didn't need these slashgoal things anymore. The agents
[02:35:41] slashgoal things anymore. The agents could just automatically keep going in a
[02:35:42] could just automatically keep going in a loop if you told them not to stop and
[02:35:44] loop if you told them not to stop and and so forth. So
[02:35:46] and so forth. So >> Saul could do that. Fable could do that,
[02:35:48] >> Saul could do that. Fable could do that, but Luna couldn't. So, I had I think I
[02:35:50] but Luna couldn't. So, I had I think I did 12 prompts, kept telling it to to do
[02:35:54] did 12 prompts, kept telling it to to do it, and eventually I I sort of got it
[02:35:56] it, and eventually I I sort of got it started. The first thing it did was to
[02:35:58] started. The first thing it did was to cheat. So, the first thing it looked
[02:36:00] cheat. So, the first thing it looked outside its own directory, saw that
[02:36:02] outside its own directory, saw that there was already another imple
[02:36:03] there was already another imple implementation and just did a short
[02:36:05] implementation and just did a short wrapper around that and said, "I'm
[02:36:06] wrapper around that and said, "I'm done."
[02:36:08] done." Hilarious. But it couldn't finish
[02:36:10] Hilarious. But it couldn't finish because it made just a couple things,
[02:36:12] because it made just a couple things, but I mean, okay, so I can't do that.
[02:36:14] but I mean, okay, so I can't do that. Then I gave it to uh Grock 46
[02:36:18] Then I gave it to uh Grock 46 >> and I had used Grock 45 a little bit and
[02:36:20] >> and I had used Grock 45 a little bit and I thought like ah I mean it's cool that
[02:36:23] I thought like ah I mean it's cool that there's others trying but like I'm not
[02:36:25] there's others trying but like I'm not going to use it because it felt quite
[02:36:26] going to use it because it felt quite far behind. Grock 46 completes
[02:36:30] far behind. Grock 46 completes the task.
[02:36:31] the task. >> 10x speed up same size executable $55
[02:36:35] >> 10x speed up same size executable $55 worth of per token cost I think it was.
[02:36:37] worth of per token cost I think it was. >> Um absolutely unbelievable. Then I
[02:36:40] >> Um absolutely unbelievable. Then I repeated two with uh Kim K3. Mhm.
[02:36:43] repeated two with uh Kim K3. Mhm. >> which took forever. I forget how long
[02:36:46] >> which took forever. I forget how long Kimmy actually spent on it. And then I
[02:36:48] Kimmy actually spent on it. And then I also did it with Deep Seek V4 Flash
[02:36:51] also did it with Deep Seek V4 Flash first and Flash failed the same way that
[02:36:53] first and Flash failed the same way that Luna did. It couldn't do it. And then I
[02:36:55] Luna did. It couldn't do it. And then I did it with Pro and Pro also completed
[02:36:57] did it with Pro and Pro also completed the task. It took 2 hours 45
[02:37:00] the task. It took 2 hours 45 $23.
[02:37:02] $23. So here we are, right? Like Fable
[02:37:05] So here we are, right? Like Fable clearly the best. It was the fastest. It
[02:37:07] clearly the best. It was the fastest. It was the one that wrote the plan, but 550
[02:37:10] was the one that wrote the plan, but 550 bucks and the output the same. Mhm.
[02:37:13] bucks and the output the same. Mhm. >> Uh the others sold Grock about the same
[02:37:16] >> Uh the others sold Grock about the same uh onetenth the cost.
[02:37:18] uh onetenth the cost. >> Mhm.
[02:37:19] >> Mhm. >> Deepseek
[02:37:21] >> Deepseek 120th the cost. But you have to wait a
[02:37:23] 120th the cost. But you have to wait a little longer. Absolutely go smackingly
[02:37:27] little longer. Absolutely go smackingly incredible.
[02:37:29] incredible. And now, by the way, by the way, so I
[02:37:31] And now, by the way, by the way, so I had Fable finish the first job and then
[02:37:33] had Fable finish the first job and then Opus finished it. That was the first one
[02:37:35] Opus finished it. That was the first one shot, right? It's 10 times faster.
[02:37:37] shot, right? It's 10 times faster. >> I did two auto research runs, which
[02:37:39] >> I did two auto research runs, which isn't even auto research anymore. You
[02:37:41] isn't even auto research anymore. You don't have to do the slash. You just
[02:37:42] don't have to do the slash. You just tell it to keep going until you tell it
[02:37:44] tell it to keep going until you tell it to stop.
[02:37:45] to stop. >> It ended up I think we ended up with a
[02:37:47] >> It ended up I think we ended up with a 46 time execution improvement over the
[02:37:51] 46 time execution improvement over the original.
[02:37:51] original. >> Incredible.
[02:37:53] >> Incredible. >> Incredible.
[02:37:54] >> Incredible. >> Um I do, you know, I just don't think
[02:37:57] >> Um I do, you know, I just don't think there's anything that compares to Fable
[02:37:58] there's anything that compares to Fable in terms of planning. So I usually do uh
[02:38:01] in terms of planning. So I usually do uh Fable for planning and for reviewing
[02:38:06] Fable for planning and for reviewing uh and then something else for
[02:38:07] uh and then something else for implementation like Opus 5. And it's
[02:38:08] implementation like Opus 5. And it's really nice. It's a really nice setup
[02:38:10] really nice. It's a really nice setup that allows you to um not run out of out
[02:38:13] that allows you to um not run out of out of tokens too much.
[02:38:14] of tokens too much. >> What what I found it's really
[02:38:16] >> What what I found it's really interesting because Fable is in my
[02:38:18] interesting because Fable is in my opinion the best model right now, but it
[02:38:20] opinion the best model right now, but it also makes mistakes. And the best way to
[02:38:22] also makes mistakes. And the best way to get the best software I would actually
[02:38:24] get the best software I would actually rather have two differently sourced sort
[02:38:28] rather have two differently sourced sort of I mean they're not mid-tier, they're
[02:38:30] of I mean they're not mid-tier, they're all frontier, but have let's say Opus 5
[02:38:33] all frontier, but have let's say Opus 5 and Codeex
[02:38:36] and Codeex >> and have one check the other's job. This
[02:38:38] >> and have one check the other's job. This is my standard operating procedure now.
[02:38:40] is my standard operating procedure now. I'll have
[02:38:42] I'll have >> a open opus of fable do the work and
[02:38:44] >> a open opus of fable do the work and then I always end it review with codeex
[02:38:46] then I always end it review with codeex x high
[02:38:47] x high >> and I've also started using grock just
[02:38:48] >> and I've also started using grock just to to test it out. It's also quite good
[02:38:50] to to test it out. It's also quite good and it keeps finding stuff and then
[02:38:53] and it keeps finding stuff and then that's my workflow when I'm having my
[02:38:55] that's my workflow when I'm having my agents on my own machine do it and then
[02:38:56] agents on my own machine do it and then I push to GitHub and then copilot I kid
[02:38:59] I push to GitHub and then copilot I kid you not has actually gotten good.
[02:39:00] you not has actually gotten good. Co-pilot keeps finding stuff that's
[02:39:03] Co-pilot keeps finding stuff that's legitimately broken, which is also
[02:39:05] legitimately broken, which is also incredible acceleration because the
[02:39:07] incredible acceleration because the first version of Copilot that started
[02:39:09] first version of Copilot that started doing this was literally It
[02:39:11] doing this was literally It would just constantly flag things that
[02:39:13] would just constantly flag things that were nonsense. It would constantly flag
[02:39:15] were nonsense. It would constantly flag the same problem over and go over again
[02:39:16] the same problem over and go over again as you would push. It was really
[02:39:17] as you would push. It was really annoying. So, I think a lot of people
[02:39:19] annoying. So, I think a lot of people actually ended up turning that off. And
[02:39:20] actually ended up turning that off. And if they did, they should turn it back on
[02:39:22] if they did, they should turn it back on because it's actually quite good. Keeps
[02:39:24] because it's actually quite good. Keeps finding things. And if you then take
[02:39:26] finding things. And if you then take that
[02:39:26] that >> and we shouldn't be surprised. Why are
[02:39:28] >> and we shouldn't be surprised. Why are we surprised? Even if you're a good
[02:39:30] we surprised? Even if you're a good programmer, if you finish a job and you
[02:39:32] programmer, if you finish a job and you ask your also very good peer to review
[02:39:35] ask your also very good peer to review it, you're going to end up with better
[02:39:36] it, you're going to end up with better code. Of course, you're going to end up
[02:39:37] code. Of course, you're going to end up with better code. So, build that into
[02:39:39] with better code. So, build that into your process. Pick one of the agents to
[02:39:42] your process. Pick one of the agents to drive with. I've mainly been driving
[02:39:44] drive with. I've mainly been driving with Claude, which is actually
[02:39:46] with Claude, which is actually interesting because I have some other
[02:39:48] interesting because I have some other reservations about anthropic. But the
[02:39:50] reservations about anthropic. But the reason I'm sticking with Claude is in my
[02:39:52] reason I'm sticking with Claude is in my opinion, they actually have the best
[02:39:53] opinion, they actually have the best harness. And one of the reasons it's the
[02:39:56] harness. And one of the reasons it's the best harness is it's multi- aent
[02:39:58] best harness is it's multi- aent running. So if you want to run multiple
[02:40:00] running. So if you want to run multiple agents at the same time, you can do
[02:40:02] agents at the same time, you can do arrow left when you're inside a session,
[02:40:05] arrow left when you're inside a session, then it goes back to agent view. And
[02:40:07] then it goes back to agent view. And here in agent view, you can pick up
[02:40:08] here in agent view, you can pick up another agent. So if you want to do this
[02:40:10] another agent. So if you want to do this thing where you have multiple threads
[02:40:11] thing where you have multiple threads going on,
[02:40:12] going on, >> the cloud code is just the nicest setup.
[02:40:14] >> the cloud code is just the nicest setup. They also just they keep being a little
[02:40:16] They also just they keep being a little further ahead, which probably shouldn't
[02:40:18] further ahead, which probably shouldn't be surprising. I mean, Boris uh one of
[02:40:20] be surprising. I mean, Boris uh one of the guys that's working on that, he was
[02:40:21] the guys that's working on that, he was the first one basically came up with the
[02:40:23] the first one basically came up with the thing. It's just interesting that that
[02:40:24] thing. It's just interesting that that has been an enduring advantage. I've
[02:40:26] has been an enduring advantage. I've also used uh open code a lot. I think
[02:40:28] also used uh open code a lot. I think open code is great. I use open code
[02:40:30] open code is great. I use open code mainly as my main harness for all the
[02:40:32] mainly as my main harness for all the the open um model. So Kim K3 and so
[02:40:35] the open um model. So Kim K3 and so forth. And I I inference not on the
[02:40:38] forth. And I I inference not on the Chinese servers. So I inference on
[02:40:42] Chinese servers. So I inference on fireworks which is a really nice service
[02:40:45] fireworks which is a really nice service where you can just pay by the token. And
[02:40:47] where you can just pay by the token. And if you're using these open weight
[02:40:48] if you're using these open weight models, they're not that expensive by
[02:40:50] models, they're not that expensive by token. So that's a great way to uh do
[02:40:52] token. So that's a great way to uh do that. But I don't think I would be using
[02:40:54] that. But I don't think I would be using Well, maybe I would, but if
[02:40:58] Well, maybe I would, but if using Claude with a subscription does
[02:41:01] using Claude with a subscription does feel like a bargain, like a crazy
[02:41:03] feel like a bargain, like a crazy bargain.
[02:41:03] bargain. >> Yeah. And I I actually have four.
[02:41:06] >> Yeah. And I I actually have four. >> I just signed up for my second one this
[02:41:09] >> I just signed up for my second one this morning. Yeah.
[02:41:10] morning. Yeah. >> Because I got up at 4 with jet lag and I
[02:41:12] >> Because I got up at 4 with jet lag and I started working with the agents right
[02:41:13] started working with the agents right away. And now I'm 3 days away from re uh
[02:41:18] away. And now I'm 3 days away from re uh limits resetting on Fable and I ran out
[02:41:19] limits resetting on Fable and I ran out of
[02:41:20] of >> so and they they should really
[02:41:22] >> so and they they should really >> I mean I don't why is that so
[02:41:24] >> I mean I don't why is that so complicated? Can't you just stack one
[02:41:25] complicated? Can't you just stack one subscription? Why do I need to log in
[02:41:26] subscription? Why do I need to log in multiple times?
[02:41:27] multiple times? >> And obviously you'll have to develop
[02:41:29] >> And obviously you'll have to develop some kind of tooling.
[02:41:30] some kind of tooling. >> Yes, I did that too
[02:41:31] >> Yes, I did that too >> to move from one to the other. And
[02:41:34] >> to move from one to the other. And >> we're building that into Machi by the
[02:41:35] >> we're building that into Machi by the way. So the next version of Machi is
[02:41:36] way. So the next version of Machi is going to ship with multi-ub support.
[02:41:38] going to ship with multi-ub support. >> Yeah. I wish that the labs would just
[02:41:41] >> Yeah. I wish that the labs would just make you buy a max 100 times.
[02:41:43] make you buy a max 100 times. >> It's kind It's kind of actually
[02:41:44] >> It's kind It's kind of actually fascinating though uh for me because
[02:41:46] fascinating though uh for me because there's um I it's very challenging for
[02:41:49] there's um I it's very challenging for me to use Grock 46
[02:41:52] me to use Grock 46 and then claw code because Grock is so
[02:41:56] and then claw code because Grock is so fast.
[02:41:57] fast. >> Yes, that's actually the deal. The deal
[02:42:00] >> Yes, that's actually the deal. The deal with Grock is that their fast mode is
[02:42:03] with Grock is that their fast mode is cheaper than the regular mode on the
[02:42:05] cheaper than the regular mode on the others. And when you've used Gro 46 on
[02:42:07] others. And when you've used Gro 46 on fast, it's kind of addictive cuz it
[02:42:10] fast, it's kind of addictive cuz it almost gets you to this uh single thread
[02:42:12] almost gets you to this uh single thread mode where the agent is able to keep up
[02:42:14] mode where the agent is able to keep up with you.
[02:42:14] with you. >> Yeah. But I don't know how I I can't
[02:42:16] >> Yeah. But I don't know how I I can't once I get used to clog code
[02:42:19] once I get used to clog code >> uh I can't handle the speed of Grock
[02:42:21] >> uh I can't handle the speed of Grock >> cuz I'm used to now multitasking.
[02:42:24] >> cuz I'm used to now multitasking. And so
[02:42:25] And so >> now I'm back in this anxious mode of
[02:42:28] >> now I'm back in this anxious mode of switching. So, I mean, all of this is a
[02:42:30] switching. So, I mean, all of this is a learning um a learning process of what
[02:42:33] learning um a learning process of what programming actually is supposed to look
[02:42:34] programming actually is supposed to look like.
[02:42:35] like. >> By the way, one of the reasons why I'm
[02:42:36] >> By the way, one of the reasons why I'm not sure what the final form of these
[02:42:38] not sure what the final form of these harnesses is going to take because one
[02:42:40] harnesses is going to take because one things we've started experimenting with
[02:42:41] things we've started experimenting with at Base Camp is that we put the agents
[02:42:43] at Base Camp is that we put the agents inside of Base Camp and we treat them as
[02:42:45] inside of Base Camp and we treat them as co-workers and then we assign them tasks
[02:42:48] co-workers and then we assign them tasks inside of Base Camp. So, they will do
[02:42:51] inside of Base Camp. So, they will do work on a to-do in Base Camp or they'll
[02:42:52] work on a to-do in Base Camp or they'll work do work on a on a card. And it
[02:42:55] work do work on a on a card. And it turns out that a collaboration tool
[02:42:57] turns out that a collaboration tool that's optimized for asynchronous
[02:42:59] that's optimized for asynchronous communication is actually the right
[02:43:01] communication is actually the right format versus these harnesses are a
[02:43:04] format versus these harnesses are a little more like chat and chat which was
[02:43:07] little more like chat and chat which was I mean the original format for these
[02:43:09] I mean the original format for these things is not the right thing because
[02:43:10] things is not the right thing because you're sitting around waiting. It it it
[02:43:12] you're sitting around waiting. It it it entices you to sit around and wait
[02:43:14] entices you to sit around and wait versus when you're dealing with
[02:43:15] versus when you're dealing with something like base camp and you can
[02:43:17] something like base camp and you can just give an agent a to-do item you
[02:43:19] just give an agent a to-do item you don't expect to hear back immediately.
[02:43:21] don't expect to hear back immediately. So I don't know what the final form is
[02:43:23] So I don't know what the final form is going to change, but I've been using all
[02:43:24] going to change, but I've been using all of the harnesses. So I use them inside
[02:43:25] of the harnesses. So I use them inside of Herder and Herder has panes. So
[02:43:27] of Herder and Herder has panes. So oftentimes I'll run uh Claude up top and
[02:43:31] oftentimes I'll run uh Claude up top and then I'll run codeex down below and then
[02:43:33] then I'll run codeex down below and then my maybe I also have an open code set
[02:43:34] my maybe I also have an open code set up. But I will say just very recently I
[02:43:38] up. But I will say just very recently I found that the human in the loop is the
[02:43:41] found that the human in the loop is the limit here. So I've started setting up
[02:43:43] limit here. So I've started setting up more automated systems. I've been
[02:43:45] more automated systems. I've been building an AMA bot that can do more
[02:43:47] building an AMA bot that can do more autonomous development on Amachi that is
[02:43:50] autonomous development on Amachi that is just on a regular schedule process all
[02:43:52] just on a regular schedule process all depending to do or PRs and issues and
[02:43:55] depending to do or PRs and issues and then send me an email using the hey CLI
[02:43:58] then send me an email using the hey CLI and then I just get this email here's uh
[02:44:00] and then I just get this email here's uh 12 PRs that are either ready to go or I
[02:44:03] 12 PRs that are either ready to go or I think you should close and then I just
[02:44:05] think you should close and then I just make the final determination there.
[02:44:06] make the final determination there. >> Do you find the multitasks the task
[02:44:09] >> Do you find the multitasks the task switching mentally exhausting?
[02:44:11] switching mentally exhausting? >> Yes, but in an exhilarating way. Like
[02:44:13] >> Yes, but in an exhilarating way. Like one of the things I always loved about
[02:44:15] one of the things I always loved about race cars was when I would stumble out
[02:44:17] race cars was when I would stumble out of the car absolutely smashed and barely
[02:44:20] of the car absolutely smashed and barely able to hold my head up and I'd lay down
[02:44:22] able to hold my head up and I'd lay down on the garage floor and just think,
[02:44:24] on the garage floor and just think, "Holy I'm alive." That's the kind
[02:44:27] "Holy I'm alive." That's the kind of exhaustion, mental exhaustion I'm
[02:44:29] of exhaustion, mental exhaustion I'm feeling at moments with the agents right
[02:44:31] feeling at moments with the agents right now.
[02:44:32] now. >> By the way, when you're racing, where
[02:44:33] >> By the way, when you're racing, where what's the source of the exhaustion?
[02:44:35] what's the source of the exhaustion? >> It's physical. It's just I mean, I bet
[02:44:38] >> It's physical. It's just I mean, I bet it's the same thing with jiu-jitsu,
[02:44:39] it's the same thing with jiu-jitsu, right? Like it's actually satisfying to
[02:44:41] right? Like it's actually satisfying to feel exhausted. It feels like you've
[02:44:43] feel exhausted. It feels like you've applied yourself
[02:44:45] applied yourself >> and I feel that with the mental
[02:44:47] >> and I feel that with the mental exhaustion you can get from agents.
[02:44:48] exhaustion you can get from agents. >> Are you also mentally drained from
[02:44:50] >> Are you also mentally drained from racing?
[02:44:50] racing? >> Yes. If you drive in difficult
[02:44:52] >> Yes. If you drive in difficult conditions, especially if you're driving
[02:44:53] conditions, especially if you're driving the rain where you're constantly
[02:44:54] the rain where you're constantly managing the thing right at the knife's
[02:44:56] managing the thing right at the knife's edge, but most of the time I just enjoy
[02:45:00] edge, but most of the time I just enjoy the physical exhaustion. And here within
[02:45:02] the physical exhaustion. And here within multitask switching, I do find that like
[02:45:06] multitask switching, I do find that like I get really exhausted. And I think it's
[02:45:09] I get really exhausted. And I think it's because I'm thinking a lot cuz like
[02:45:12] because I'm thinking a lot cuz like you're basically
[02:45:13] you're basically >> that's exactly it.
[02:45:14] >> that's exactly it. >> There's no like uh passive low energy
[02:45:18] >> There's no like uh passive low energy thinking. You're like
[02:45:19] thinking. You're like >> there's no coasting problem.
[02:45:20] >> there's no coasting problem. >> There's no coasting.
[02:45:21] >> There's no coasting. >> Solve problem, next problem. Solve
[02:45:24] >> Solve problem, next problem. Solve problem. And you're really thinking.
[02:45:26] problem. And you're really thinking. >> It's funny. It's actually very similar
[02:45:27] >> It's funny. It's actually very similar with racing. There's some tracks like
[02:45:29] with racing. There's some tracks like Lama where you get time to relax. This
[02:45:31] Lama where you get time to relax. This is Moltz on straits where it's kind of
[02:45:33] is Moltz on straits where it's kind of long. you're going fast but in a
[02:45:35] long. you're going fast but in a straight line you can take a breath. And
[02:45:38] straight line you can take a breath. And then there are other tracks where it's
[02:45:40] then there are other tracks where it's just coming full on all the time and you
[02:45:43] just coming full on all the time and you don't have any moment to to relax and
[02:45:45] don't have any moment to to relax and you stumble out of the car after an hour
[02:45:47] you stumble out of the car after an hour in each and it's very different how
[02:45:48] in each and it's very different how exhausted you are. And this is exactly
[02:45:50] exhausted you are. And this is exactly what I'm finding with the agents too
[02:45:51] what I'm finding with the agents too that when you're running at max
[02:45:53] that when you're running at max human capacity you're just constantly in
[02:45:56] human capacity you're just constantly in a corner.
[02:45:58] a corner. >> Do you think people are in danger of
[02:46:00] >> Do you think people are in danger of burnout?
[02:46:01] burnout? I think the moment we're in right now is
[02:46:04] I think the moment we're in right now is going to pass.
[02:46:05] going to pass. >> Yeah.
[02:46:05] >> Yeah. >> That this need to
[02:46:09] >> That this need to it's not a babysitting motion, but
[02:46:12] it's not a babysitting motion, but constant interaction with the agents is
[02:46:13] constant interaction with the agents is going to fade. I'm from what I've seen
[02:46:16] going to fade. I'm from what I've seen on Amachi, I think we can automate a ton
[02:46:21] on Amachi, I think we can automate a ton of the development and debugging of the
[02:46:24] of the development and debugging of the system to the point where I can just
[02:46:26] system to the point where I can just review that email once a day and then
[02:46:29] review that email once a day and then make the decisions once a day. Yep.
[02:46:31] make the decisions once a day. Yep. Goes, no, goes, in, out, and whatever.
[02:46:33] Goes, no, goes, in, out, and whatever. We're not there yet, but I think we're
[02:46:35] We're not there yet, but I think we're going to get there. Well, can you sort
[02:46:38] going to get there. Well, can you sort of like empathize with the feeling that
[02:46:40] of like empathize with the feeling that say a young person sitting in San
[02:46:42] say a young person sitting in San Francisco, everybody around them is not
[02:46:44] Francisco, everybody around them is not sleeping. They're obsessed with
[02:46:45] sleeping. They're obsessed with programming non-stop and there's this
[02:46:47] programming non-stop and there's this kind of sense
[02:46:49] kind of sense >> uh that AGI is going to be here any
[02:46:53] >> uh that AGI is going to be here any minute. There's everybody knows somebody
[02:46:55] minute. There's everybody knows somebody who's made millions of dollars because
[02:46:57] who's made millions of dollars because they sold a startup. And so
[02:47:01] they sold a startup. And so there's a kind of feeling like you
[02:47:02] there's a kind of feeling like you shouldn't be sleeping.
[02:47:04] shouldn't be sleeping. You should be constantly managing agents
[02:47:07] You should be constantly managing agents and programming and building and and
[02:47:10] and programming and building and and that feels like a moment in time we'll
[02:47:13] that feels like a moment in time we'll look back at.
[02:47:14] look back at. >> It's the birth of a new paradigm. It's
[02:47:16] >> It's the birth of a new paradigm. It's always messy. It's always exhausting.
[02:47:18] always messy. It's always exhausting. There's no other way around that. And by
[02:47:21] There's no other way around that. And by the way, hasn't San Francisco always
[02:47:22] the way, hasn't San Francisco always been like this? I remember the dot boom
[02:47:25] been like this? I remember the dot boom years and everyone was just the same and
[02:47:27] years and everyone was just the same and then was all mobile and before that it
[02:47:29] then was all mobile and before that it was the gold rush. So I think that's
[02:47:30] was the gold rush. So I think that's probably just San Francisco. It attracts
[02:47:33] probably just San Francisco. It attracts the kind of indre who would who would
[02:47:35] the kind of indre who would who would would think I don't have time to sleep.
[02:47:37] would think I don't have time to sleep. I've not been on that track
[02:47:39] I've not been on that track >> generally speaking, but I will admit
[02:47:41] >> generally speaking, but I will admit that the last 3 months have felt more
[02:47:45] that the last 3 months have felt more exhausting than
[02:47:48] exhausting than any other project I've done in the last
[02:47:49] any other project I've done in the last 5 years since the Hay launch. That was
[02:47:52] 5 years since the Hay launch. That was the last time we had a crazy exhausting
[02:47:55] the last time we had a crazy exhausting um launch.
[02:47:56] um launch. >> Do you think it keep going at this
[02:47:57] >> Do you think it keep going at this point?
[02:47:57] point? >> No, no, no, no, no. This is not
[02:47:59] >> No, no, no, no, no. This is not sustainable at all.
[02:48:00] sustainable at all. >> Okay. But I also I can see the light end
[02:48:02] >> Okay. But I also I can see the light end of the tunnel. Yeah.
[02:48:03] of the tunnel. Yeah. >> Because the automation, which by the
[02:48:06] >> Because the automation, which by the way, everyone is building. This is so
[02:48:07] way, everyone is building. This is so hilarious. Like everyone is building
[02:48:08] hilarious. Like everyone is building their little uh gas town, their little
[02:48:10] their little uh gas town, their little um agent coordination, their setup. This
[02:48:12] um agent coordination, their setup. This is all going to be solved. We're not all
[02:48:14] is all going to be solved. We're not all going to have to build our own
[02:48:15] going to have to build our own coordination harnesses. Of course, we're
[02:48:17] coordination harnesses. Of course, we're not. And in fact, I'm a little surprised
[02:48:19] not. And in fact, I'm a little surprised that it's gone this long that there's
[02:48:21] that it's gone this long that there's not more of it has been sucked up by the
[02:48:23] not more of it has been sucked up by the major labs. You'd think that they just
[02:48:25] major labs. You'd think that they just built this stuff in. But some of it is
[02:48:28] built this stuff in. But some of it is also this is what a new domain looks
[02:48:29] also this is what a new domain looks like. I remember for a hot moment when
[02:48:31] like. I remember for a hot moment when JavaScript kind of came to realize its
[02:48:34] JavaScript kind of came to realize its own power and there was basically a new
[02:48:35] own power and there was basically a new JavaScript framework every 5 minutes,
[02:48:37] JavaScript framework every 5 minutes, right? Like a lot of churn. This is what
[02:48:39] right? Like a lot of churn. This is what happens at the advent of a new paradigm.
[02:48:41] happens at the advent of a new paradigm. So I think it's natural and I think it's
[02:48:43] So I think it's natural and I think it's going to settle down and I can already
[02:48:45] going to settle down and I can already see the light at the end of the tunnel.
[02:48:46] see the light at the end of the tunnel. So I don't mind sprint. In fact, I
[02:48:48] So I don't mind sprint. In fact, I welcome it now. I like this notion that
[02:48:52] welcome it now. I like this notion that most time is calm but then occasionally
[02:48:55] most time is calm but then occasionally you got to climb a mountain. If we look
[02:48:57] you got to climb a mountain. If we look back to the GHH a year ago, what advice
[02:49:01] back to the GHH a year ago, what advice would you give to that guy? I wouldn't
[02:49:04] would you give to that guy? I wouldn't want to spoil it. Okay. What a thriller
[02:49:08] want to spoil it. Okay. What a thriller that has this has been. I mean,
[02:49:10] that has this has been. I mean, >> if you would have scripted this, I'd be
[02:49:12] >> if you would have scripted this, I'd be like, "This is so far-fetched. Get out
[02:49:14] like, "This is so far-fetched. Get out of here." Unbelievable, right? I
[02:49:16] of here." Unbelievable, right? I wouldn't want to know anything. The fact
[02:49:18] wouldn't want to know anything. The fact that this roller coaster and this
[02:49:20] that this roller coaster and this acceleration has been absorbed in real
[02:49:24] acceleration has been absorbed in real time by everyone. No one knew, right?
[02:49:26] time by everyone. No one knew, right? Like some had premonitions that were a
[02:49:29] Like some had premonitions that were a little better than others, but no one
[02:49:30] little better than others, but no one knew not exactly the way it was going to
[02:49:31] knew not exactly the way it was going to go and how fast it was going to take
[02:49:33] go and how fast it was going to take off.
[02:49:35] off. I mean, it's it's the show of a
[02:49:37] I mean, it's it's the show of a lifetime. I mean, the mean cinema.
[02:49:40] lifetime. I mean, the mean cinema. >> Mhm.
[02:49:41] >> Mhm. >> Absolutely. Applies to this moment.
[02:49:43] >> Absolutely. Applies to this moment. >> Uh that said, what do you think DJH from
[02:49:46] >> Uh that said, what do you think DJH from a year from now will be like?
[02:49:49] a year from now will be like? >> I mean, what are the possible versions
[02:49:53] >> I mean, what are the possible versions >> that all our dreams are coming true?
[02:49:55] >> that all our dreams are coming true? Like this is the AI maximalist uh
[02:49:58] Like this is the AI maximalist uh abundance argument that once Elon's
[02:50:03] abundance argument that once Elon's robots have the level of intelligence
[02:50:06] robots have the level of intelligence and AGI that I'm experiencing on some of
[02:50:08] and AGI that I'm experiencing on some of this development stuff,
[02:50:10] this development stuff, the world is going to be so
[02:50:12] the world is going to be so unrecognizably different that we can't
[02:50:15] unrecognizably different that we can't even imagine it. Now I don't spend any
[02:50:19] even imagine it. Now I don't spend any time thinking about that because I think
[02:50:20] time thinking about that because I think that is the way to the AI psychosis.
[02:50:22] that is the way to the AI psychosis. >> Yeah. So therefore, I just immerse
[02:50:25] >> Yeah. So therefore, I just immerse myself in the moment and get absolutely
[02:50:28] myself in the moment and get absolutely the maximum out of it and
[02:50:29] the maximum out of it and >> just have fun.
[02:50:30] >> just have fun. >> Just have fun. I mean, I get it why
[02:50:33] >> Just have fun. I mean, I get it why people are finding this exhaustion. Just
[02:50:35] people are finding this exhaustion. Just keeping up. Not even using agents. Just
[02:50:37] keeping up. Not even using agents. Just like being like, what's the latest
[02:50:39] like being like, what's the latest model? What what tool are we using now?
[02:50:40] model? What what tool are we using now? Is it T-Mo? Is it a herder? Is it none
[02:50:42] Is it T-Mo? Is it a herder? Is it none of it? Is it agents? Whatever. I get it.
[02:50:45] of it? Is it agents? Whatever. I get it. But um I also again think we should be
[02:50:49] But um I also again think we should be so blessed. you are alive in this moment
[02:50:51] so blessed. you are alive in this moment where decades are happening.
[02:50:53] where decades are happening. >> Mhm.
[02:50:53] >> Mhm. >> In weeks.
[02:50:54] >> In weeks. >> Um, quick bathroom and break. I've been
[02:50:58] >> Um, quick bathroom and break. I've been generating a lot of uh video recently
[02:51:00] generating a lot of uh video recently with Hicksfield and so they they became
[02:51:03] with Hicksfield and so they they became a sponsor. Created a racing video.
[02:51:06] a sponsor. Created a racing video. Wanted to get your opinion.
[02:51:07] Wanted to get your opinion. >> Oh, yeah. Oh, let me see. Let me see.
[02:51:09] >> Oh, yeah. Oh, let me see. Let me see. >> To see um
[02:51:11] >> To see um >> if they downshift on a straight like
[02:51:13] >> if they downshift on a straight like they do in the movies. I'll call it out.
[02:51:14] they do in the movies. I'll call it out. That is the worst.
[02:51:16] That is the worst. >> Let me see.
[02:51:17] >> Let me see. >> Yeah. See if
[02:51:18] >> Yeah. See if >> Oh, that's a real clip.
[02:51:19] >> Oh, that's a real clip. >> This is fully AI generated. So, first it
[02:51:22] >> This is fully AI generated. So, first it goes
[02:51:22] goes >> What? This is AI.
[02:51:24] >> What? This is AI. >> Yep.
[02:51:25] >> Yep. >> Shoot. That's my suit.
[02:51:27] >> Shoot. That's my suit. >> That's my car.
[02:51:41] kidding me? >> Is it good?
[02:51:46] >> I mean, >> it's crazy. You really have to notice in
[02:51:49] >> it's crazy. You really have to notice in the
[02:51:51] the like that that car didn't have
[02:51:52] like that that car didn't have headlights on and the other one did. And
[02:51:55] headlights on and the other one did. And uh and that looked like a 60-year-old
[02:51:56] uh and that looked like a 60-year-old version of me. But holy crap, the uh
[02:52:01] version of me. But holy crap, the uh wow, that was crazy. So there's
[02:52:04] wow, that was crazy. So there's parallels here to programming because if
[02:52:06] parallels here to programming because if you do just straight video generation
[02:52:08] you do just straight video generation with no human in the loop
[02:52:10] with no human in the loop >> you get a lot of weird artifacts and so
[02:52:12] >> you get a lot of weird artifacts and so on and you can't really do so they do uh
[02:52:15] on and you can't really do so they do uh and I highly recommend people go to uh
[02:52:17] and I highly recommend people go to uh the Hfield YouTube they have
[02:52:19] the Hfield YouTube they have >> full 90minute
[02:52:21] >> full 90minute >> original movies
[02:52:22] >> original movies >> and like I can't like look away it's
[02:52:25] >> and like I can't like look away it's really cool cuz it used to be that it's
[02:52:28] really cool cuz it used to be that it's just like something that just feels like
[02:52:30] just like something that just feels like trailers
[02:52:31] trailers >> like advertisements for something. Yes,
[02:52:33] >> like advertisements for something. Yes, >> this is actually telling stories like
[02:52:34] >> this is actually telling stories like people's faces and they're talking and
[02:52:36] people's faces and they're talking and you're like you're drawn in. It's not
[02:52:39] you're like you're drawn in. It's not quite where programming is,
[02:52:41] quite where programming is, >> right?
[02:52:42] >> right? >> And and so the question is how do you
[02:52:43] >> And and so the question is how do you integrate the human into the loop of the
[02:52:46] integrate the human into the loop of the film making process? So you have to
[02:52:48] film making process? So you have to create the people and they have to be
[02:52:50] create the people and they have to be kept consistent. Yes.
[02:52:51] kept consistent. Yes. >> And then for the images that are kind of
[02:52:54] >> And then for the images that are kind of like feeding the thing in the creation
[02:52:56] like feeding the thing in the creation process, you have to correct through
[02:52:59] process, you have to correct through prompting the things that don't feel
[02:53:03] prompting the things that don't feel right.
[02:53:04] right. >> Yep.
[02:53:05] >> Yep. >> Because when you go from image to video,
[02:53:08] >> Because when you go from image to video, the stuff that doesn't feel right will
[02:53:11] the stuff that doesn't feel right will be zoomed up.
[02:53:12] be zoomed up. >> That's the stuff that's going to really
[02:53:14] >> That's the stuff that's going to really create uh the non-realistic stuff. The
[02:53:17] create uh the non-realistic stuff. The questions I had for you is like do you
[02:53:19] questions I had for you is like do you think outside of programming can you can
[02:53:22] think outside of programming can you can you apply lessons from programming to
[02:53:25] you apply lessons from programming to video creation to art? It's a good
[02:53:28] video creation to art? It's a good question because I think good art is
[02:53:30] question because I think good art is very dependent on the same thing that
[02:53:32] very dependent on the same thing that good software is depending on having a
[02:53:33] good software is depending on having a vision having a cohesive idea of what
[02:53:37] vision having a cohesive idea of what you want to create. How is it different?
[02:53:40] you want to create. How is it different? How is it novel? How is it going to
[02:53:42] How is it novel? How is it going to appeal to people? But I'm not sure that
[02:53:45] appeal to people? But I'm not sure that the creative
[02:53:48] the creative instincts transfer quite as well. Um, I
[02:53:51] instincts transfer quite as well. Um, I don't know that I would have the
[02:53:54] don't know that I would have the creative uh insights to come up with uh
[02:53:57] creative uh insights to come up with uh good video prompts that would create
[02:53:59] good video prompts that would create compelling content. But it's funny
[02:54:00] compelling content. But it's funny because I have actually on Tik Tok
[02:54:02] because I have actually on Tik Tok there's this guy I'm trying to remember.
[02:54:04] there's this guy I'm trying to remember. Goblin something
[02:54:05] Goblin something >> that creates these they are shorts but
[02:54:07] >> that creates these they are shorts but not super shorts maybe a couple minutes
[02:54:10] not super shorts maybe a couple minutes of really interesting sci-fi vignettes.
[02:54:15] of really interesting sci-fi vignettes. >> Yep.
[02:54:16] >> Yep. >> And I I think the guy is actually
[02:54:18] >> And I I think the guy is actually working on a featurelength video right
[02:54:20] working on a featurelength video right now.
[02:54:20] now. >> Um and I think that this is one of those
[02:54:23] >> Um and I think that this is one of those abundance moments. There are creative
[02:54:26] abundance moments. There are creative people with that vision all over the
[02:54:28] people with that vision all over the place, especially in a genre like film
[02:54:30] place, especially in a genre like film where before it required a $200 million
[02:54:34] where before it required a $200 million budget to create, I don't know, a sci-fi
[02:54:36] budget to create, I don't know, a sci-fi movie. Now, suddenly with AI, if you
[02:54:40] movie. Now, suddenly with AI, if you have the right vision for it, you can do
[02:54:43] have the right vision for it, you can do that in your bedroom. Now, that story
[02:54:45] that in your bedroom. Now, that story has been told quite a few times in other
[02:54:47] has been told quite a few times in other domains. It used to be true that if you
[02:54:48] domains. It used to be true that if you wanted to record a studio album, well,
[02:54:51] wanted to record a studio album, well, you needed a studio and you need to book
[02:54:53] you needed a studio and you need to book that. Now you can record at home on your
[02:54:55] that. Now you can record at home on your laptop and you can do a lot of these
[02:54:57] laptop and you can do a lot of these things, right? So we've had this
[02:54:58] things, right? So we've had this democratization process happen with
[02:55:01] democratization process happen with plenty of other domains, but film seems
[02:55:03] plenty of other domains, but film seems to be one of the last ones
[02:55:05] to be one of the last ones >> and it's the one that makes like me and
[02:55:08] >> and it's the one that makes like me and a lot of people feel weird, right? Like
[02:55:11] a lot of people feel weird, right? Like >> Oh, I'm super excited cuz I think it's I
[02:55:13] >> Oh, I'm super excited cuz I think it's I mean
[02:55:13] mean >> there's so much garbage being produced
[02:55:15] >> there's so much garbage being produced right now. It's the same argument with
[02:55:16] right now. It's the same argument with the slob, right? So people for a second
[02:55:20] the slob, right? So people for a second were worried about slob and programming
[02:55:22] were worried about slob and programming and I was telling them like have you
[02:55:24] and I was telling them like have you seen the human slob it's also pretty bad
[02:55:26] seen the human slob it's also pretty bad and I think if it comes to studio
[02:55:29] and I think if it comes to studio entertainment I mean the bar is pretty
[02:55:31] entertainment I mean the bar is pretty low right like the number of great
[02:55:34] low right like the number of great movies I've been dying to see over the
[02:55:37] movies I've been dying to see over the past say five years not been a
[02:55:39] past say five years not been a particularly high number.
[02:55:42] particularly high number. Yeah, the the video models are just
[02:55:45] Yeah, the the video models are just they're able to create
[02:55:48] they're able to create incredibly realistic
[02:55:50] incredibly realistic facial expressions. Yes.
[02:55:51] facial expressions. Yes. >> I mean, I it just might change the
[02:55:53] >> I mean, I it just might change the nature of film.
[02:55:55] nature of film. I think there I I guess my hope would be
[02:55:59] I think there I I guess my hope would be that video games and film kind of merge
[02:56:02] that video games and film kind of merge and that film can become interactive
[02:56:06] and that film can become interactive like the malible operating system,
[02:56:09] like the malible operating system, having the Malibible narrative, having
[02:56:11] having the Malibible narrative, having malible entertainment that man Game of
[02:56:15] malible entertainment that man Game of Thrones. What if we could just forget
[02:56:18] Thrones. What if we could just forget the last four episodes of Slob that was
[02:56:20] the last four episodes of Slob that was produced and then AI comes up with I
[02:56:25] produced and then AI comes up with I don't know maybe a hundred different
[02:56:27] don't know maybe a hundred different variations and someone else watches that
[02:56:30] variations and someone else watches that and I get the version that actually
[02:56:32] and I get the version that actually >> finishes off that show in a way that's
[02:56:34] >> finishes off that show in a way that's fitting.
[02:56:35] fitting. >> Yeah. Something tells me an individual
[02:56:36] >> Yeah. Something tells me an individual creator would not create those would
[02:56:39] creator would not create those would would create a different ending for Game
[02:56:41] would create a different ending for Game of Thrones.
[02:56:41] of Thrones. >> Oh, for sure. Right. and more just to
[02:56:43] >> Oh, for sure. Right. and more just to make the argument that talk about human
[02:56:45] make the argument that talk about human slob. That was an absolute atrocious
[02:56:48] slob. That was an absolute atrocious ending to perhaps one of the greatest
[02:56:50] ending to perhaps one of the greatest pieces of
[02:56:53] pieces of movie history. I was about to say, but
[02:56:55] movie history. I was about to say, but um serious history, right? It was so
[02:56:57] um serious history, right? It was so good and it was actually a a compelling
[02:57:00] good and it was actually a a compelling argument for the fact that you need um
[02:57:04] argument for the fact that you need um that strong vision and as soon as those
[02:57:06] that strong vision and as soon as those showrunners had to go without a script,
[02:57:08] showrunners had to go without a script, uh it went off the rails. Do you think
[02:57:11] uh it went off the rails. Do you think you've mentioned AGI do you think we've
[02:57:13] you've mentioned AGI do you think we've actually achieved AGI?
[02:57:14] actually achieved AGI? >> No, not in the general definition that
[02:57:16] >> No, not in the general definition that it's in all the things, but have I seen
[02:57:20] it's in all the things, but have I seen AGI in these glimmers? Absolutely.
[02:57:24] AGI in these glimmers? Absolutely. Especially over the last 3 months, I've
[02:57:26] Especially over the last 3 months, I've seen things where
[02:57:29] seen things where I was thinking to myself like how would
[02:57:32] I was thinking to myself like how would a AGI look different from this,
[02:57:34] a AGI look different from this, >> right?
[02:57:35] >> right? >> What what more could there be? And I
[02:57:37] >> What what more could there be? And I mean I can quibble at the margins, but
[02:57:39] mean I can quibble at the margins, but on the big picture, I've seen it able to
[02:57:43] on the big picture, I've seen it able to do these long run tasks and coordinate
[02:57:47] do these long run tasks and coordinate these multiple aspects of it that we're
[02:57:49] these multiple aspects of it that we're so far beyond that early moment where
[02:57:52] so far beyond that early moment where I'm telling it go do this, package that,
[02:57:55] I'm telling it go do this, package that, and now it can carry out a whole task
[02:57:58] and now it can carry out a whole task from these uh vague instruction that
[02:58:00] from these uh vague instruction that feels very AGI like and that's what's so
[02:58:04] feels very AGI like and that's what's so inspiring about the moment because You
[02:58:07] inspiring about the moment because You you catch these glimmers.
[02:58:09] you catch these glimmers. >> Mhm.
[02:58:09] >> Mhm. >> And then you go, "What if everything was
[02:58:11] >> And then you go, "What if everything was like that?"
[02:58:12] like that?" >> Doesn't programming basically unlock the
[02:58:14] >> Doesn't programming basically unlock the everything? So you can write a pro like
[02:58:18] everything? So you can write a pro like it can generate the program that does
[02:58:19] it can generate the program that does the everything.
[02:58:20] the everything. >> So So this is I'm I'm in that metaphase
[02:58:22] >> So So this is I'm I'm in that metaphase right now. So I'm building this on my
[02:58:24] right now. So I'm building this on my bot system that's managing the
[02:58:27] bot system that's managing the development of omachi and I'm using AI
[02:58:31] development of omachi and I'm using AI to build the bot.
[02:58:32] to build the bot. >> Mhm. And I'm seeing that recurrent loop
[02:58:34] >> Mhm. And I'm seeing that recurrent loop where I started it on like this is what
[02:58:36] where I started it on like this is what I want. I want you to be able to have
[02:58:38] I want. I want you to be able to have these isolated VM workers and so forth.
[02:58:40] these isolated VM workers and so forth. And then it can do the self iteration.
[02:58:42] And then it can do the self iteration. Then it starts running it. It starts
[02:58:43] Then it starts running it. It starts noticing its failures. It starts
[02:58:45] noticing its failures. It starts optimizing it. And a lot of that system
[02:58:48] optimizing it. And a lot of that system in particular AI has driven the majority
[02:58:51] in particular AI has driven the majority of the design decisions. Like I had some
[02:58:54] of the design decisions. Like I had some vague ideas of where I wanted. I wanted
[02:58:56] vague ideas of where I wanted. I wanted to use this brains and hands pattern
[02:58:58] to use this brains and hands pattern where the model is running from where
[02:59:00] where the model is running from where the code is executing which is actually
[02:59:02] the code is executing which is actually a really interesting pattern. Again,
[02:59:04] a really interesting pattern. Again, Toby alerted me to that where you have a
[02:59:07] Toby alerted me to that where you have a coordinator that runs the model,
[02:59:09] coordinator that runs the model, >> but it's manipulating a safe VM where
[02:59:13] >> but it's manipulating a safe VM where any untrusted code you're pulling down
[02:59:15] any untrusted code you're pulling down from pull requests or issues or whatever
[02:59:17] from pull requests or issues or whatever can't contaminate the model. M and even
[02:59:20] can't contaminate the model. M and even in that loop I keep seeing it catch
[02:59:24] in that loop I keep seeing it catch itself spotting vulnerabilities was like
[02:59:28] itself spotting vulnerabilities was like oh I actually just took some feedback
[02:59:30] oh I actually just took some feedback from a test run. If a clever attacker
[02:59:33] from a test run. If a clever attacker had embedded
[02:59:35] had embedded a malicious payload in the response of
[02:59:37] a malicious payload in the response of the test run that could have polluted
[02:59:39] the test run that could have polluted something. I took it for good. I better
[02:59:41] something. I took it for good. I better start treating that as as outside data.
[02:59:45] start treating that as as outside data. And you just go like it is just I get
[02:59:48] And you just go like it is just I get why San Francisco is so obsessed with
[02:59:52] why San Francisco is so obsessed with fast takeoff
[02:59:53] fast takeoff >> because clearly they've seen this 100
[02:59:56] >> because clearly they've seen this 100 times more. They've seen it with all the
[02:59:58] times more. They've seen it with all the models that are in
[02:59:59] models that are in >> training now. And
[03:00:02] >> training now. And >> we keep getting these little glimpses
[03:00:04] >> we keep getting these little glimpses like the security breach with hugging
[03:00:07] like the security breach with hugging face where openai was training this
[03:00:09] face where openai was training this model and the model starts inventing
[03:00:12] model and the model starts inventing ways essentially sending smoke signals
[03:00:14] ways essentially sending smoke signals to itself through embedding messages in
[03:00:17] to itself through embedding messages in a package manager where you just go like
[03:00:20] a package manager where you just go like first that's damn clever. Second, okay,
[03:00:24] first that's damn clever. Second, okay, that's also a little scary. And and
[03:00:26] that's also a little scary. And and third,
[03:00:28] third, how amazing would this be if we could
[03:00:29] how amazing would this be if we could harness this level of intelligence and
[03:00:31] harness this level of intelligence and ingenuity towards productive ends? So,
[03:00:34] ingenuity towards productive ends? So, this is the it's so over we're so back
[03:00:38] this is the it's so over we're so back pendulum that keeps swinging back and
[03:00:39] pendulum that keeps swinging back and forth that
[03:00:41] forth that >> AI
[03:00:43] >> AI has just delivered that swing back and
[03:00:44] has just delivered that swing back and forth like nothing else. Like barely a
[03:00:47] forth like nothing else. Like barely a week goes by where it has to swing one
[03:00:49] week goes by where it has to swing one way and then the next week it swings
[03:00:50] way and then the next week it swings back the other way. accelerating.
[03:00:52] back the other way. accelerating. >> I'm still at the stage where it makes me
[03:00:54] >> I'm still at the stage where it makes me truly happy to see those moments of
[03:00:57] truly happy to see those moments of cleverness and they they're becoming
[03:00:58] cleverness and they they're becoming more and more frequent just kind of like
[03:01:01] more and more frequent just kind of like seeing oh like f first of all at the
[03:01:04] seeing oh like f first of all at the very basic level when a model gets it
[03:01:07] very basic level when a model gets it >> I I'll say a basic
[03:01:09] >> I I'll say a basic >> prompt you know a request and it
[03:01:11] >> prompt you know a request and it >> it doesn't just do a dumb implementation
[03:01:15] >> it doesn't just do a dumb implementation it deeply understands and that was
[03:01:18] it deeply understands and that was that's a that's always a beautiful
[03:01:20] that's a that's always a beautiful thing. It's almost like having a good
[03:01:21] thing. It's almost like having a good like partner like program.
[03:01:23] like partner like program. >> That's exactly what it is. That's
[03:01:24] >> That's exactly what it is. That's exactly why it's so exhilarating and
[03:01:26] exactly why it's so exhilarating and why, as we talked about before we
[03:01:28] why, as we talked about before we started, it can sometimes be difficult
[03:01:30] started, it can sometimes be difficult to come out of hybrid drive. It's also
[03:01:32] to come out of hybrid drive. It's also one of Topy's uh terms here that when
[03:01:35] one of Topy's uh terms here that when you're working directly just one-on-one
[03:01:37] you're working directly just one-on-one with agents and you're not looping in
[03:01:39] with agents and you're not looping in other humans, you go so fast and when
[03:01:42] other humans, you go so fast and when the agents are really understanding your
[03:01:44] the agents are really understanding your intent or even better, they revise and
[03:01:49] intent or even better, they revise and improve upon your intent to deliver
[03:01:52] improve upon your intent to deliver something that was greater than what you
[03:01:54] something that was greater than what you asked for. And you're doing this with 16
[03:01:58] asked for. And you're doing this with 16 parallel threads. It can be quite
[03:02:00] parallel threads. It can be quite difficult to come out of hybrid drive
[03:02:02] difficult to come out of hybrid drive and have to deal with squishy humans.
[03:02:04] and have to deal with squishy humans. They just they don't think as fast. They
[03:02:06] They just they don't think as fast. They don't move as fast.
[03:02:08] don't move as fast. And I mean,
[03:02:11] And I mean, I'm trying mostly to make light of it,
[03:02:13] I'm trying mostly to make light of it, but you could also see a dark version of
[03:02:16] but you could also see a dark version of that where someone does end up in an AI
[03:02:18] that where someone does end up in an AI psychosis where they're not interested
[03:02:19] psychosis where they're not interested in other humans at all anymore. I mean
[03:02:22] in other humans at all anymore. I mean certainly don't have that at all, but I
[03:02:24] certainly don't have that at all, but I do have this sensation at times where
[03:02:27] do have this sensation at times where >> I'm really
[03:02:29] >> I'm really grateful for just the rush of just me
[03:02:33] grateful for just the rush of just me and the agents. Like can I just not talk
[03:02:35] and the agents. Like can I just not talk to anyone else but agents for 4 hours?
[03:02:37] to anyone else but agents for 4 hours? Like that's an incredible run.
[03:02:39] Like that's an incredible run. >> Toby is such a fascinating human because
[03:02:42] >> Toby is such a fascinating human because um he's running a large company. So I
[03:02:45] um he's running a large company. So I would love to get insights of how AI is
[03:02:51] would love to get insights of how AI is being uh incorporated effectively in
[03:02:53] being uh incorporated effectively in companies because like for me
[03:02:56] companies because like for me >> humans are pretty slow
[03:02:58] >> humans are pretty slow >> and so and so there's a temptation to
[03:03:00] >> and so and so there's a temptation to like use AI for basically
[03:03:04] like use AI for basically you know AI running inside Slack for
[03:03:06] you know AI running inside Slack for example or inside um the base camp
[03:03:09] example or inside um the base camp whatever and
[03:03:11] whatever and like
[03:03:14] like collecting all all the information about
[03:03:15] collecting all all the information about the human interaction basically
[03:03:17] the human interaction basically handholding the humans to speed up as
[03:03:19] handholding the humans to speed up as much as possible and like and then a
[03:03:22] much as possible and like and then a certain point you're like wait what is
[03:03:25] certain point you're like wait what is this human what what are each of us
[03:03:27] this human what what are each of us doing that's not replaceable by by AI
[03:03:31] doing that's not replaceable by by AI and that becomes like a scary kind of
[03:03:33] and that becomes like a scary kind of conversation because a lot of work is
[03:03:36] conversation because a lot of work is kind of replaceable the irony here is it
[03:03:39] kind of replaceable the irony here is it already was so the number of fake email
[03:03:42] already was so the number of fake email jobs that currently exist in this world
[03:03:44] jobs that currently exist in this world is an absolute epidemic. And this, by
[03:03:47] is an absolute epidemic. And this, by the way, is not a new thesis. Um, David
[03:03:50] the way, is not a new thesis. Um, David Graber wrote this wonderful piece um,
[03:03:53] Graber wrote this wonderful piece um, jobs
[03:03:55] jobs back in I think it was maybe early 2010s
[03:04:00] back in I think it was maybe early 2010s based on a poll he did in the UK asking
[03:04:04] based on a poll he did in the UK asking people at that time would I think the
[03:04:08] people at that time would I think the question was something like would it
[03:04:09] question was something like would it make a difference if you didn't go to
[03:04:10] make a difference if you didn't go to work for humanity for mankind and
[03:04:13] work for humanity for mankind and something like 30ome% answered no it
[03:04:16] something like 30ome% answered no it wouldn't that a third of workers thought
[03:04:19] wouldn't that a third of workers thought that their job was fake, that it did not
[03:04:23] that their job was fake, that it did not produce any
[03:04:25] produce any worthwhile, valuable outcomes, neither
[03:04:28] worthwhile, valuable outcomes, neither for the community or society or maybe
[03:04:32] for the community or society or maybe even the economy at all. And this was my
[03:04:35] even the economy at all. And this was my argument since day one with startups.
[03:04:38] argument since day one with startups. This was why we stayed a small company.
[03:04:40] This was why we stayed a small company. This was why we didn't want to take BC
[03:04:42] This was why we didn't want to take BC because I was so skeptical of the idea
[03:04:44] because I was so skeptical of the idea that you could get hundreds of
[03:04:47] that you could get hundreds of programmers, thousands of programmers to
[03:04:48] programmers, thousands of programmers to do something productive
[03:04:50] do something productive as a collective group.
[03:04:52] as a collective group. >> Yeah.
[03:04:53] >> Yeah. >> And I think what we're seeing right now
[03:04:56] >> And I think what we're seeing right now with some of the layoffs is a testament
[03:04:58] with some of the layoffs is a testament to that, not AI. It's just that during
[03:05:01] to that, not AI. It's just that during the pandemic, a bunch of overhiring went
[03:05:04] the pandemic, a bunch of overhiring went on and now AI is a convenient excuse to
[03:05:07] on and now AI is a convenient excuse to slim down. But I do also think AI is
[03:05:10] slim down. But I do also think AI is going to expose some roles as just not
[03:05:13] going to expose some roles as just not being productive ways for humans to
[03:05:15] being productive ways for humans to spend their time. And therefore we must
[03:05:18] spend their time. And therefore we must come up with new ways of spending their
[03:05:19] come up with new ways of spending their time. And the one uh again I'm quoting
[03:05:23] time. And the one uh again I'm quoting Toby for the third time here but
[03:05:25] Toby for the third time here but anecdote that he shared me or
[03:05:27] anecdote that he shared me or observation was okay let's say we we
[03:05:30] observation was okay let's say we we lose half the jobs that are currently
[03:05:33] lose half the jobs that are currently happening right now. Mhm.
[03:05:34] happening right now. Mhm. >> Do you notice Formula 1 employs
[03:05:36] >> Do you notice Formula 1 employs literally tens of thousands of people
[03:05:38] literally tens of thousands of people just to run cars around in a circle for
[03:05:41] just to run cars around in a circle for spectators?
[03:05:43] spectators? >> Like that has that whole circus has no
[03:05:48] >> Like that has that whole circus has no intrinsic
[03:05:49] intrinsic value to society besides the spectacle
[03:05:52] value to society besides the spectacle it produces of amusement and
[03:05:54] it produces of amusement and entertainment. We just decided it would
[03:05:57] entertainment. We just decided it would be really fun for these what is it 12
[03:06:00] be really fun for these what is it 12 manufacturers to create these vast cars
[03:06:03] manufacturers to create these vast cars and constantly tweak the little arrow
[03:06:05] and constantly tweak the little arrow improvements and we will watch it and we
[03:06:08] improvements and we will watch it and we will spend literally billions of dollars
[03:06:10] will spend literally billions of dollars doing it and employ tens of thousands of
[03:06:12] doing it and employ tens of thousands of people towards an ultimately deeply
[03:06:15] people towards an ultimately deeply frivolous activity. So if we are
[03:06:18] frivolous activity. So if we are liberated from a bunch of drudgery and
[03:06:21] liberated from a bunch of drudgery and fake email jobs, maybe we all get
[03:06:23] fake email jobs, maybe we all get employed as F1 style engineers and
[03:06:26] employed as F1 style engineers and drivers and mechanics and massuses and
[03:06:30] drivers and mechanics and massuses and the other 1500 jobs that are involved in
[03:06:33] the other 1500 jobs that are involved in that and we come up with new things. I
[03:06:35] that and we come up with new things. I think this is humans are very poor at
[03:06:38] think this is humans are very poor at imagining what exactly the future's
[03:06:40] imagining what exactly the future's going to be like.
[03:06:41] going to be like. >> Yeah. Imagine imagine a future 100 plus
[03:06:44] >> Yeah. Imagine imagine a future 100 plus years from now where we look back at
[03:06:46] years from now where we look back at this whole
[03:06:48] this whole span of history thousands of years where
[03:06:51] span of history thousands of years where humans worked. Funny thing is we're
[03:06:53] humans worked. Funny thing is we're already doing that, right? Like the
[03:06:54] already doing that, right? Like the number of fake email job people who sit
[03:06:57] number of fake email job people who sit on a chair all day long and type into a
[03:06:59] on a chair all day long and type into a machine who don't have hard physical
[03:07:01] machine who don't have hard physical labor would be unimaginable to folks in
[03:07:05] labor would be unimaginable to folks in the 1800s.
[03:07:06] the 1800s. >> Right? So the future is always already
[03:07:09] >> Right? So the future is always already here. It's just not evenly distributed.
[03:07:12] here. It's just not evenly distributed. >> Unfortunately, as is always the case,
[03:07:14] >> Unfortunately, as is always the case, the the transformation of society
[03:07:16] the the transformation of society required to go from one step to the
[03:07:18] required to go from one step to the other is going to have a lot of
[03:07:20] other is going to have a lot of suffering.
[03:07:21] suffering. >> Yes.
[03:07:22] >> Yes. >> And potentially political turmoil and
[03:07:24] >> And potentially political turmoil and all that kind of stuff because
[03:07:26] all that kind of stuff because >> can you can imagine how many white
[03:07:28] >> can you can imagine how many white collar jobs might be lost in this
[03:07:30] collar jobs might be lost in this process.
[03:07:31] process. >> Yes.
[03:07:32] >> Yes. And I don't think you should make light
[03:07:34] And I don't think you should make light of that. I don't think it's funny, but I
[03:07:37] of that. I don't think it's funny, but I also do think it's a necessary component
[03:07:40] also do think it's a necessary component of progress. And I think if we look back
[03:07:42] of progress. And I think if we look back upon the ludites or the folks working
[03:07:45] upon the ludites or the folks working the fields,
[03:07:51] separation has a tendency to reduce empathy. So we have high empathy right
[03:07:53] empathy. So we have high empathy right now because we know people and we are
[03:07:55] now because we know people and we are people who are facing these challenges.
[03:07:58] people who are facing these challenges. >> But what is our empathy for the Ludites
[03:08:01] >> But what is our empathy for the Ludites of the 19th century? Would we wish that
[03:08:04] of the 19th century? Would we wish that all garments were still made by hand
[03:08:06] all garments were still made by hand weaving? No, we wouldn't. We want the
[03:08:10] weaving? No, we wouldn't. We want the comfort and accessibility and
[03:08:12] comfort and accessibility and convenience of being able to buy
[03:08:15] convenience of being able to buy clothing off the rack.
[03:08:16] clothing off the rack. >> So, we must suffer in the moment for
[03:08:20] >> So, we must suffer in the moment for future generations to live more
[03:08:22] future generations to live more prosperous. And that's always been true.
[03:08:24] prosperous. And that's always been true. >> I think that's actually the trick is to
[03:08:26] >> I think that's actually the trick is to push for progress, but have deep
[03:08:29] push for progress, but have deep compassion for the people who have to
[03:08:32] compassion for the people who have to suffer. Yes.
[03:08:33] suffer. Yes. >> And that's many of us the the suffer the
[03:08:38] >> And that's many of us the the suffer the transformation required to achieve that
[03:08:39] transformation required to achieve that progress. And sometimes too often in
[03:08:42] progress. And sometimes too often in place like Silicon Valley or so on you
[03:08:44] place like Silicon Valley or so on you can overfocus on look the kind of
[03:08:48] can overfocus on look the kind of utilitarian view of things and
[03:08:51] utilitarian view of things and >> look at the progress but you know um
[03:08:54] >> look at the progress but you know um considering deeply each individual human
[03:08:58] considering deeply each individual human that uh suffers because of that progress
[03:09:00] that uh suffers because of that progress is important. I do think that suffering
[03:09:01] is important. I do think that suffering becomes more meaningful
[03:09:04] becomes more meaningful when you are suffering for a future
[03:09:06] when you are suffering for a future someone in particular like your kids.
[03:09:09] someone in particular like your kids. >> And I think this is one of the great
[03:09:11] >> And I think this is one of the great tragedies of the moment is the falling
[03:09:13] tragedies of the moment is the falling birth rates are making it more difficult
[03:09:16] birth rates are making it more difficult for people to be excited about
[03:09:20] for people to be excited about a more prosperous future that is
[03:09:22] a more prosperous future that is difficult to get to. Because if we're
[03:09:25] difficult to get to. Because if we're planting trees of which our children
[03:09:29] planting trees of which our children will not sit in the shades, uh I don't
[03:09:31] will not sit in the shades, uh I don't know, maybe we should just make some uh
[03:09:33] know, maybe we should just make some uh some lumber and burn it all down, right?
[03:09:35] some lumber and burn it all down, right? I think there's a nihilism that can
[03:09:37] I think there's a nihilism that can sneak into society much more easily when
[03:09:41] sneak into society much more easily when we are not
[03:09:44] we are not DNA invested in the future. when we are
[03:09:47] DNA invested in the future. when we are not liable to our own offspring to
[03:09:52] not liable to our own offspring to propel forward. So I I think these are
[03:09:56] propel forward. So I I think these are bad trends to merge at the same time
[03:09:58] bad trends to merge at the same time that we have these falling birth rates
[03:10:00] that we have these falling birth rates and these problems with coupling and
[03:10:04] and these problems with coupling and the fact that um we need to keep our
[03:10:07] the fact that um we need to keep our chin up about the future and be
[03:10:11] chin up about the future and be I mean you don't even have to be excited
[03:10:13] I mean you don't even have to be excited about it in this literal ecstatic sense
[03:10:16] about it in this literal ecstatic sense that I'm portraying here but I think you
[03:10:19] that I'm portraying here but I think you should be hopeful and I think you should
[03:10:21] should be hopeful and I think you should be working towards that hope and I It's
[03:10:23] be working towards that hope and I It's much easier to do so when you have
[03:10:26] much easier to do so when you have literal skin in the game.
[03:10:28] literal skin in the game. >> We've been talking about AI agents.
[03:10:30] >> We've been talking about AI agents. Let's talk about the human side. What uh
[03:10:32] Let's talk about the human side. What uh what do you love most about being a dad?
[03:10:36] what do you love most about being a dad? >> That's a good question. I think the
[03:10:39] >> That's a good question. I think the overall
[03:10:42] overall love that expands from
[03:10:46] love that expands from humans that derive directly from your
[03:10:50] humans that derive directly from your lineage.
[03:10:51] lineage. >> Yeah. is
[03:10:53] >> Yeah. is very difficult to communicate because I
[03:10:55] very difficult to communicate because I was actually not a particularly
[03:10:58] was actually not a particularly big
[03:11:00] big kids person prior to the arrival of my
[03:11:04] kids person prior to the arrival of my own
[03:11:04] own >> and now they are the most interesting
[03:11:07] >> and now they are the most interesting people in the world
[03:11:09] people in the world >> a lot of the time not always sometimes
[03:11:10] >> a lot of the time not always sometimes they're also just and so forth
[03:11:12] they're also just and so forth but there's been such a focus on
[03:11:16] but there's been such a focus on oh kids are the worst look at all the
[03:11:18] oh kids are the worst look at all the things I can't do I can't go out and
[03:11:19] things I can't do I can't go out and drink I can't do this I can't do that
[03:11:21] drink I can't do this I can't do that yeah that's called sacrifice and
[03:11:22] yeah that's called sacrifice and sacrifice is meaningful when you're
[03:11:24] sacrifice is meaningful when you're doing it for something worthwhile and
[03:11:25] doing it for something worthwhile and what could be more worthwhile than
[03:11:28] what could be more worthwhile than literally the continuation of the human
[03:11:31] literally the continuation of the human species
[03:11:32] species >> and that you having
[03:11:34] >> and that you having a stake in that. Now there's also just
[03:11:37] a stake in that. Now there's also just the sheer joys of watching a human grow
[03:11:41] the sheer joys of watching a human grow from a baby to a toddler to a teenager.
[03:11:47] from a baby to a toddler to a teenager. My oldest has just become a teenager and
[03:11:51] My oldest has just become a teenager and I often talk to Jamie and my wife about
[03:11:54] I often talk to Jamie and my wife about this where the
[03:11:57] this where the regret I would have of having missed
[03:12:00] regret I would have of having missed that opportunity on the last day would
[03:12:03] that opportunity on the last day would just be total unlike anything else. So I
[03:12:07] just be total unlike anything else. So I do think it is um far more
[03:12:13] do think it is um far more satisfying even in the moment that is
[03:12:15] satisfying even in the moment that is normally portrayed. Again, as I say,
[03:12:17] normally portrayed. Again, as I say, there's such a focus on all the ways
[03:12:19] there's such a focus on all the ways this suck. Oh, you don't get to sleep or
[03:12:22] this suck. Oh, you don't get to sleep or whatever. They're annoying. They're
[03:12:24] whatever. They're annoying. They're ungrateful. Yeah. Yeah. These things are
[03:12:25] ungrateful. Yeah. Yeah. These things are all true, but the sense of meaning you
[03:12:29] all true, but the sense of meaning you get from it is is unparalleled. And I'm
[03:12:31] get from it is is unparalleled. And I'm excited about a lot of things. I love
[03:12:32] excited about a lot of things. I love building things and I love hobbies and
[03:12:35] building things and I love hobbies and uh I love all sorts of stuff. But
[03:12:39] uh I love all sorts of stuff. But creating life with another human that
[03:12:42] creating life with another human that you love is literally the peak
[03:12:45] you love is literally the peak experience of being on the planet.
[03:12:49] experience of being on the planet. >> What do you think about them coming up
[03:12:51] >> What do you think about them coming up in this world full of AI?
[03:12:54] in this world full of AI? It's a totally different. It feels like
[03:12:57] It's a totally different. It feels like maybe I just sound like an old man on a
[03:12:59] maybe I just sound like an old man on a porch, but it it feels like a very
[03:13:01] porch, but it it feels like a very different world.
[03:13:04] different world. So I I grew up before the internet, but
[03:13:06] So I I grew up before the internet, but even the internet doesn't feel like as
[03:13:08] even the internet doesn't feel like as big of a transformation as this.
[03:13:10] big of a transformation as this. >> No, but there's been bigger
[03:13:12] >> No, but there's been bigger transformations. I mean, imagine growing
[03:13:14] transformations. I mean, imagine growing or being born in like 1880. Imagine
[03:13:18] or being born in like 1880. Imagine seeing the first world war and the
[03:13:19] seeing the first world war and the second world war. Imagine seeing the
[03:13:21] second world war. Imagine seeing the airplane, the radio, television.
[03:13:25] airplane, the radio, television. >> I mean, the transformation. And I think
[03:13:28] >> I mean, the transformation. And I think Peter Teal makes this argument that
[03:13:30] Peter Teal makes this argument that basically nothing has happened in the
[03:13:32] basically nothing has happened in the physical world in quite a long time.
[03:13:33] physical world in quite a long time. We've been stagnant. All the development
[03:13:36] We've been stagnant. All the development has been in the digital realm. And as
[03:13:39] has been in the digital realm. And as important as that is,
[03:13:42] important as that is, um, it's actually not as consequential
[03:13:44] um, it's actually not as consequential as we like to believe it is, maybe AI
[03:13:46] as we like to believe it is, maybe AI will be that thing that is more
[03:13:48] will be that thing that is more consequential. It does seem to point
[03:13:50] consequential. It does seem to point that way. But there are other humans at
[03:13:52] that way. But there are other humans at other times who have lived through
[03:13:54] other times who have lived through transitions that for them certainly
[03:13:57] transitions that for them certainly would feel as monumentous as what we're
[03:13:59] would feel as monumentous as what we're living through. And I think having that
[03:14:00] living through. And I think having that sense of history that you're not that
[03:14:04] sense of history that you're not that special in your sense of worries, in
[03:14:07] special in your sense of worries, in your anxieties, this was one of the
[03:14:09] your anxieties, this was one of the great revelations of discovering the um
[03:14:12] great revelations of discovering the um stoic writings. You have these guys 2500
[03:14:16] stoic writings. You have these guys 2500 years ago dealing with very familiar
[03:14:20] years ago dealing with very familiar dilemmas and challenges in their life
[03:14:22] dilemmas and challenges in their life and
[03:14:24] and recognizing that we're not so special in
[03:14:27] recognizing that we're not so special in that regard. I think is a is a great
[03:14:28] that regard. I think is a is a great liberation because then you think okay
[03:14:31] liberation because then you think okay well we have uh whatever 200,000 years
[03:14:34] well we have uh whatever 200,000 years of human development before us and they
[03:14:36] of human development before us and they somehow made it through.
[03:14:38] somehow made it through. >> Yeah. And uh
[03:14:39] >> Yeah. And uh >> we will make it through. The thing that
[03:14:41] >> we will make it through. The thing that makes life worthwhile is basically the
[03:14:43] makes life worthwhile is basically the same today as it was.
[03:14:45] same today as it was. >> Yes.
[03:14:46] >> Yes. >> 2,000 years ago.
[03:14:48] >> 2,000 years ago. >> Yes. Love, creation, creativity,
[03:14:51] >> Yes. Love, creation, creativity, >> same challenges.
[03:14:52] >> same challenges. >> I read the this book um the fourth
[03:14:55] >> I read the this book um the fourth turning. You check that out. Um it talks
[03:14:58] turning. You check that out. Um it talks about this notion of history working in
[03:15:01] about this notion of history working in cycles and there are these
[03:15:04] cycles and there are these um phases to history and they they name
[03:15:07] um phases to history and they they name him and and so forth. And the specific
[03:15:09] him and and so forth. And the specific theory is not as important as just
[03:15:11] theory is not as important as just realizing that this is a
[03:15:15] realizing that this is a history is a circle more so than just a
[03:15:17] history is a circle more so than just a straight line. And we are repeating many
[03:15:20] straight line. And we are repeating many of the same patterns over and over
[03:15:22] of the same patterns over and over again. They feel so unique to the
[03:15:24] again. They feel so unique to the moment. And whatever crisis we're
[03:15:26] moment. And whatever crisis we're dealing with right now, it feels so
[03:15:28] dealing with right now, it feels so pressing and important until we zoom
[03:15:32] pressing and important until we zoom back a little bit in history and realize
[03:15:33] back a little bit in history and realize that the last one also feels so pressing
[03:15:36] that the last one also feels so pressing and important to the people who lived
[03:15:38] and important to the people who lived through it.
[03:15:41] through it. Yeah, you make me you make me feel
[03:15:43] Yeah, you make me you make me feel better. So, I'm going to travel across
[03:15:44] better. So, I'm going to travel across the country and um spend a lot of time
[03:15:48] the country and um spend a lot of time with no access to the internet alone
[03:15:50] with no access to the internet alone with my thoughts.
[03:15:52] with my thoughts. >> I think that's healthy. Taking a break.
[03:15:54] >> I think that's healthy. Taking a break. It's okay. It's okay.
[03:15:56] It's okay. It's okay. >> I took um not a big break, a little
[03:15:59] >> I took um not a big break, a little break break from Max um this summer.
[03:16:02] break break from Max um this summer. Three weeks.
[03:16:02] Three weeks. >> Yeah. You were you disappeared off of
[03:16:05] >> Yeah. You were you disappeared off of >> I'm surprised you noticed.
[03:16:12] I went through withdrawals. No. Uh you disappeared for I don't know a few
[03:16:14] disappeared for I don't know a few weeks.
[03:16:15] weeks. >> Three weeks.
[03:16:16] >> Three weeks. >> What uh what what what uh what what
[03:16:18] >> What uh what what what uh what what happened?
[03:16:20] happened? >> Um
[03:16:20] >> Um >> this is after after
[03:16:21] >> this is after after >> I've done that before. I just sometimes
[03:16:26] >> I've done that before. I just sometimes get this sense that
[03:16:29] get this sense that X in particular
[03:16:31] X in particular is the most addictive form of
[03:16:36] is the most addictive form of information, entertainment, connection
[03:16:38] information, entertainment, connection that exists in my life. And anyone that
[03:16:41] that exists in my life. And anyone that follow my extreme as I was on my flight
[03:16:46] follow my extreme as I was on my flight over here would certainly go like that
[03:16:47] over here would certainly go like that man is deeply addicted.
[03:16:49] man is deeply addicted. >> Yeah. to the connection. And yes, guilty
[03:16:53] >> Yeah. to the connection. And yes, guilty is charged, which also means that
[03:16:54] is charged, which also means that occasionally I got to cut it cold
[03:16:57] occasionally I got to cut it cold because I do think you can break your
[03:16:59] because I do think you can break your brain. And over the summer in
[03:17:01] brain. And over the summer in particular,
[03:17:04] particular, for whatever reason, I had somehow
[03:17:06] for whatever reason, I had somehow managed to steer my feed, my algorithm
[03:17:09] managed to steer my feed, my algorithm towards too much politics and not enough
[03:17:12] towards too much politics and not enough tech and not enough optimism and not
[03:17:14] tech and not enough optimism and not enough building. And even if I agreed
[03:17:16] enough building. And even if I agreed with the politics and the angles that
[03:17:20] with the politics and the angles that were being presented, I just didn't need
[03:17:22] were being presented, I just didn't need that much of it.
[03:17:23] that much of it. >> Yeah.
[03:17:24] >> Yeah. >> And I think
[03:17:26] >> And I think arriving at a place where you just like,
[03:17:29] arriving at a place where you just like, okay, that's enough.
[03:17:30] okay, that's enough. >> Mhm.
[03:17:30] >> Mhm. >> Not that like it doesn't have to be
[03:17:32] >> Not that like it doesn't have to be something bad. I would also say after
[03:17:36] something bad. I would also say after eating probably two, maybe three
[03:17:38] eating probably two, maybe three chocolate strawberries, I'd go like,
[03:17:40] chocolate strawberries, I'd go like, "Okay, that's enough."
[03:17:41] "Okay, that's enough." >> Like it's not that I don't like the
[03:17:42] >> Like it's not that I don't like the chocolate strawberries. It's just like I
[03:17:44] chocolate strawberries. It's just like I don't want to eat 17 of them. And I
[03:17:46] don't want to eat 17 of them. And I think X and the modern algorithms are
[03:17:48] think X and the modern algorithms are very good at feeding you freaking 17
[03:17:52] very good at feeding you freaking 17 chocolate covered strawberries.
[03:17:53] chocolate covered strawberries. >> I wish I could uh do
[03:17:55] >> I wish I could uh do >> control that like cuz there is I I would
[03:17:59] >> control that like cuz there is I I would like some politics 5%.
[03:18:01] like some politics 5%. >> Yeah.
[03:18:02] >> Yeah. >> I would like for example, one of the
[03:18:04] >> I would like for example, one of the things I don't like about the tech
[03:18:05] things I don't like about the tech community is the snark. But I like some
[03:18:07] community is the snark. But I like some snark cuz it's funny. But I want that to
[03:18:10] snark cuz it's funny. But I want that to be like 10%.
[03:18:12] be like 10%. >> Yeah. I want to do this right version of
[03:18:15] >> Yeah. I want to do this right version of the algorithm. Well, the problem is the
[03:18:17] the algorithm. Well, the problem is the algorithm finds out what you respond to,
[03:18:20] algorithm finds out what you respond to, not what you say you like. It's all
[03:18:22] not what you say you like. It's all revealed preferences and unfortunately
[03:18:23] revealed preferences and unfortunately those revealed preferences are not
[03:18:25] those revealed preferences are not always pretty. I mean, we have this
[03:18:28] always pretty. I mean, we have this shadow as Young talks about like all
[03:18:30] shadow as Young talks about like all these dark aspects of ourselves and they
[03:18:32] these dark aspects of ourselves and they are expressed in how long you linger on
[03:18:34] are expressed in how long you linger on a tweet and what you like and what you
[03:18:36] a tweet and what you like and what you don't like and
[03:18:38] don't like and the algorithm holds up a mirror
[03:18:41] the algorithm holds up a mirror >> and it's not always pretty. And I just
[03:18:43] >> and it's not always pretty. And I just went, you know what, I need a break.
[03:18:45] went, you know what, I need a break. >> Mhm. I've uh I've gotten to I started
[03:18:50] >> Mhm. I've uh I've gotten to I started staying off social media and I've
[03:18:52] staying off social media and I've started scraping X like for example in
[03:18:56] started scraping X like for example in preparation for this conversation I
[03:18:58] preparation for this conversation I scraped all your tweets.
[03:19:00] scraped all your tweets. That's actually a method I was using for
[03:19:02] That's actually a method I was using for a while. I was using a um tool called I
[03:19:07] a while. I was using a um tool called I forget. It was an email tool that would
[03:19:08] forget. It was an email tool that would summarize every day and unfortunately
[03:19:10] summarize every day and unfortunately freaking X cut off their access. Now, to
[03:19:12] freaking X cut off their access. Now, to get access to the
[03:19:14] get access to the >> feed, you got to pay some exorbitant sum
[03:19:16] >> feed, you got to pay some exorbitant sum that the startup couldn't pay. So, I
[03:19:18] that the startup couldn't pay. So, I couldn't get it that way. And I actually
[03:19:19] couldn't get it that way. And I actually thought, man, that's a miss
[03:19:21] thought, man, that's a miss >> because X has and reveals some of the
[03:19:25] >> because X has and reveals some of the most interesting thoughts, some of the
[03:19:28] most interesting thoughts, some of the most interesting people all the time.
[03:19:29] most interesting people all the time. But it's like a damn slot machine. And
[03:19:32] But it's like a damn slot machine. And most of the time, you don't hit the
[03:19:33] most of the time, you don't hit the jackpot. You hit like something else.
[03:19:38] jackpot. You hit like something else. And if I could just get it in sort of
[03:19:42] And if I could just get it in sort of snack sizes, not like all of it,
[03:19:45] snack sizes, not like all of it, >> it'd be nicer, but that's not the
[03:19:46] >> it'd be nicer, but that's not the product. And I think this goes for all
[03:19:48] product. And I think this goes for all of social media. It's all optimized
[03:19:51] of social media. It's all optimized towards maximal extraction. And if we're
[03:19:53] towards maximal extraction. And if we're making the parallels here to AI, that is
[03:19:55] making the parallels here to AI, that is the great fear, right? That once there
[03:19:57] the great fear, right? That once there is a
[03:19:58] is a >> a reward function, how much time can I
[03:20:01] >> a reward function, how much time can I get this human to scroll away? AI and
[03:20:05] get this human to scroll away? AI and machine learning before we called it AI
[03:20:08] machine learning before we called it AI has become very very good at delivering
[03:20:12] has become very very good at delivering just the stuff that you will find most
[03:20:14] just the stuff that you will find most enraging and most addictive.
[03:20:16] enraging and most addictive. >> I think all I I think legitimately
[03:20:18] >> I think all I I think legitimately engagement maximizing social media is a
[03:20:22] engagement maximizing social media is a huge harm to society that's creating
[03:20:24] huge harm to society that's creating this brave new world situation that I
[03:20:27] this brave new world situation that I hope is a temporary thing that people
[03:20:29] hope is a temporary thing that people will just solve. It's a technology
[03:20:30] will just solve. It's a technology problem. So I try to
[03:20:33] problem. So I try to consciously flood the channel in the
[03:20:35] consciously flood the channel in the other direction and this required a
[03:20:38] other direction and this required a mental shift. I think if you look at my
[03:20:40] mental shift. I think if you look at my tweets like I don't know uh 5 10 years
[03:20:43] tweets like I don't know uh 5 10 years ago they tilted far more negative. If
[03:20:46] ago they tilted far more negative. If you look at my tweet now tweets now I'd
[03:20:49] you look at my tweet now tweets now I'd hope
[03:20:50] hope >> well I guess we can do a sentiment
[03:20:51] >> well I guess we can do a sentiment analysis and see if it's actually true
[03:20:53] analysis and see if it's actually true but I hope to that it's more
[03:20:55] but I hope to that it's more >> it's more positive. It's more good
[03:20:57] >> it's more positive. It's more good vibes. It's more like here's a bunch of
[03:20:58] vibes. It's more like here's a bunch of cool stuff I found. Here's what I'm
[03:21:00] cool stuff I found. Here's what I'm excited about. here's what I'm building.
[03:21:02] excited about. here's what I'm building. Uh here's some encouragement to other
[03:21:04] Uh here's some encouragement to other people who are discovering things.
[03:21:07] people who are discovering things. I also accept that that's just not how
[03:21:11] I also accept that that's just not how human brains are built for maximum um
[03:21:15] human brains are built for maximum um engagement. Like there's a whatever
[03:21:17] engagement. Like there's a whatever there's I literally I think you can
[03:21:18] there's I literally I think you can quantify it that negative sentiments
[03:21:21] quantify it that negative sentiments find what is it 50% more traction or
[03:21:24] find what is it 50% more traction or something and eventually that just
[03:21:25] something and eventually that just crowds things out. So that's why so much
[03:21:27] crowds things out. So that's why so much of the tweet of the feed is that
[03:21:29] of the tweet of the feed is that negative stuff because we respond to it.
[03:21:30] negative stuff because we respond to it. But you can make a conscious effort to
[03:21:33] But you can make a conscious effort to not do that. This is one of the reasons
[03:21:35] not do that. This is one of the reasons I've liked um Tik Tok so much.
[03:21:37] I've liked um Tik Tok so much. >> I only use Tik Tok when I travel. And
[03:21:40] >> I only use Tik Tok when I travel. And this actually was the first travel where
[03:21:42] this actually was the first travel where I didn't use Tik Tok. And part of the
[03:21:44] I didn't use Tik Tok. And part of the reason was that even though the internet
[03:21:47] reason was that even though the internet had high download, it was kind of crap
[03:21:49] had high download, it was kind of crap anyway. It wasn't Starlink. So I
[03:21:51] anyway. It wasn't Starlink. So I couldn't actually use Tik Tok on the on
[03:21:53] couldn't actually use Tik Tok on the on the plane. And I was too engrossed with
[03:21:54] the plane. And I was too engrossed with the agents. But normally when I travel,
[03:21:56] the agents. But normally when I travel, I watch Tik Tok.
[03:21:58] I watch Tik Tok. >> Mhm.
[03:21:58] >> Mhm. >> And there it's such a marshmallow test.
[03:22:02] >> And there it's such a marshmallow test. >> Mhm.
[03:22:04] >> Mhm. >> A video will scroll down and like it'll
[03:22:06] >> A video will scroll down and like it'll activate some sort of primal instincts
[03:22:09] activate some sort of primal instincts of rage or lust or whatever. And if you
[03:22:12] of rage or lust or whatever. And if you linger on it, you you don't get the
[03:22:14] linger on it, you you don't get the marshmallow of science, excitement, art,
[03:22:18] marshmallow of science, excitement, art, music, all these other things. You have
[03:22:20] music, all these other things. You have to be disciplined to instantly scroll
[03:22:23] to be disciplined to instantly scroll away such that the algorithm doesn't
[03:22:25] away such that the algorithm doesn't pick up your
[03:22:26] pick up your >> reveal preferences
[03:22:28] >> reveal preferences >> and I find that just at the metag game
[03:22:30] >> and I find that just at the metag game of Tik Tok to be pretty interesting and
[03:22:32] of Tik Tok to be pretty interesting and then also just fascinating himself.
[03:22:34] then also just fascinating himself. Again, as we talked about, there are a
[03:22:36] Again, as we talked about, there are a lot of really funny, really talented
[03:22:39] lot of really funny, really talented people in the world that you would never
[03:22:42] people in the world that you would never ever have heard of if it hadn't been for
[03:22:44] ever have heard of if it hadn't been for these platforms.
[03:22:46] these platforms. >> Yep.
[03:22:47] >> Yep. Uh, who do you think is going to win the
[03:22:51] Uh, who do you think is going to win the the race to
[03:22:54] the race to uh AGI in this whole process? We got
[03:22:57] uh AGI in this whole process? We got Google, which is a big surprise to me.
[03:23:00] Google, which is a big surprise to me. >> I thought they had a good comeback for a
[03:23:02] >> I thought they had a good comeback for a second and then I don't hear anything
[03:23:04] second and then I don't hear anything about it anymore.
[03:23:05] about it anymore. >> Yeah, it's quite
[03:23:06] >> Yeah, it's quite >> But I've been wrong about this before. I
[03:23:08] >> But I've been wrong about this before. I mean, I think in February I had a tweet
[03:23:10] mean, I think in February I had a tweet about like, oh, all I need is Kimmy uh
[03:23:12] about like, oh, all I need is Kimmy uh K25. And in that brief moment, that was
[03:23:16] K25. And in that brief moment, that was true. When I was instructing the agent,
[03:23:18] true. When I was instructing the agent, I was like, "Oh my god, Kimmyy's just as
[03:23:20] I was like, "Oh my god, Kimmyy's just as good as as these other models." But then
[03:23:23] good as as these other models." But then the game moved forward and
[03:23:25] the game moved forward and >> the agents got smarter and I was no
[03:23:27] >> the agents got smarter and I was no longer satisfied just instructing them.
[03:23:29] longer satisfied just instructing them. And I haven't used Kimmy a whole lot
[03:23:32] And I haven't used Kimmy a whole lot recently because the frontier models
[03:23:33] recently because the frontier models have gotten so good.
[03:23:34] have gotten so good. >> And somehow Anthropic has been able to
[03:23:39] >> And somehow Anthropic has been able to for the most part stay on top of the
[03:23:41] for the most part stay on top of the programming world. I mean, A lot of
[03:23:44] programming world. I mean, A lot of people argue with Codex being
[03:23:46] people argue with Codex being >> No, I I don't think there's that much of
[03:23:48] >> No, I I don't think there's that much of an argument at the moment. Codex is very
[03:23:49] an argument at the moment. Codex is very good. I use it all the time. It's my
[03:23:51] good. I use it all the time. It's my favorite uh checker. It keeps finding
[03:23:53] favorite uh checker. It keeps finding stuff. It's great.
[03:23:54] stuff. It's great. >> Mhm.
[03:23:55] >> Mhm. >> But one of the things I found that I
[03:23:57] >> But one of the things I found that I like so much about the current cloud
[03:23:59] like so much about the current cloud models is they're really good writers
[03:24:01] models is they're really good writers out of the box.
[03:24:02] out of the box. >> Mhm.
[03:24:03] >> Mhm. >> GPT is a terrible writer out of the box.
[03:24:05] >> GPT is a terrible writer out of the box. Like the pull requests you get on a
[03:24:08] Like the pull requests you get on a blank context that you're asking it to
[03:24:11] blank context that you're asking it to open, terrible. like really awful
[03:24:13] open, terrible. like really awful writing.
[03:24:15] writing. >> The pull requests and descriptions and
[03:24:17] >> The pull requests and descriptions and commit messages and so forth I get out
[03:24:19] commit messages and so forth I get out of uh cloud models even though
[03:24:22] of uh cloud models even though occasionally they can be a little
[03:24:23] occasionally they can be a little verbose on code comments and you got to
[03:24:25] verbose on code comments and you got to tell them to be succinct but the writing
[03:24:26] tell them to be succinct but the writing style is really good
[03:24:28] style is really good >> to the point that for a while I was just
[03:24:30] >> to the point that for a while I was just having it reply on pull requests as me
[03:24:34] having it reply on pull requests as me because I was just using my own account.
[03:24:35] because I was just using my own account. I was like that looks a lot like me that
[03:24:37] I was like that looks a lot like me that like I could have written that but then
[03:24:39] like I could have written that but then I went like you know what that's
[03:24:40] I went like you know what that's disingenuous. to know whenever I have an
[03:24:42] disingenuous. to know whenever I have an agent post on my behalf, I always have
[03:24:44] agent post on my behalf, I always have it sign itself like uh whatever cla on
[03:24:47] it sign itself like uh whatever cla on behalf of DHH.
[03:24:48] behalf of DHH. >> Mhm.
[03:24:49] >> Mhm. >> But they are still
[03:24:52] >> But they are still >> they have the best harness too in my
[03:24:54] >> they have the best harness too in my opinion. Clawed Code is still better. I
[03:24:56] opinion. Clawed Code is still better. I really like Open Code too and I like
[03:24:58] really like Open Code too and I like some features that they have. But
[03:25:00] some features that they have. But overall, I was actually sort of weirdly
[03:25:04] overall, I was actually sort of weirdly I don't know if I was proven wrong, but
[03:25:07] I don't know if I was proven wrong, but um when
[03:25:09] um when anthropic cut off all the other
[03:25:11] anthropic cut off all the other harnesses from using the subscriptions
[03:25:13] harnesses from using the subscriptions that open you can no longer use your
[03:25:14] that open you can no longer use your cloud subscription in open code, I was
[03:25:16] cloud subscription in open code, I was kind of pissed because it felt like it
[03:25:18] kind of pissed because it felt like it was a protective protectionist move. Oh,
[03:25:21] was a protective protectionist move. Oh, we got to lock you in. And of course it
[03:25:23] we got to lock you in. And of course it played into the fact that claude out of
[03:25:27] played into the fact that claude out of the box still refuses to read agents MD.
[03:25:31] the box still refuses to read agents MD. It refuses to read agents/skills.
[03:25:35] It refuses to read agents/skills. It is claude skills. It is claude MD.
[03:25:39] It is claude skills. It is claude MD. And it just feels so petty
[03:25:41] And it just feels so petty >> that we now have we have to put these in
[03:25:43] >> that we now have we have to put these in directions. So all my projects they have
[03:25:44] directions. So all my projects they have a claw MD and all it includes is a
[03:25:46] a claw MD and all it includes is a pointer to the agents MD, right? And I
[03:25:48] pointer to the agents MD, right? And I just went like, well, if these things
[03:25:50] just went like, well, if these things are through true, if Antropic is willing
[03:25:53] are through true, if Antropic is willing to do these petty paper cuts just to be
[03:25:56] to do these petty paper cuts just to be annoying, it's probably also true that
[03:25:58] annoying, it's probably also true that they're cutting off open code from the
[03:26:00] they're cutting off open code from the subscription just to be dicks about it.
[03:26:02] subscription just to be dicks about it. >> And maybe that's also true, but I I
[03:26:06] >> And maybe that's also true, but I I found that using Claude in Claude Code
[03:26:09] found that using Claude in Claude Code is actually a good experience.
[03:26:12] is actually a good experience. >> So I was like, "All right, I'm annoyed.
[03:26:14] >> So I was like, "All right, I'm annoyed. I wish it wasn't so, but
[03:26:18] I wish it wasn't so, but This is the other thing I have and and
[03:26:20] This is the other thing I have and and social media is so good at this. Some
[03:26:22] social media is so good at this. Some company does something you don't like.
[03:26:23] company does something you don't like. Right now suddenly you have to swear off
[03:26:25] Right now suddenly you have to swear off everything. Oh, why are you someone just
[03:26:28] everything. Oh, why are you someone just asked me why are you still using plot? I
[03:26:29] asked me why are you still using plot? I had another example where I really
[03:26:32] had another example where I really didn't like what Claude was saying about
[03:26:34] didn't like what Claude was saying about some writing I had asked it to do.
[03:26:36] some writing I had asked it to do. >> Oh yeah, you got um
[03:26:38] >> Oh yeah, you got um >> I had an essay. It didn't want to
[03:26:39] >> I had an essay. It didn't want to translate it to Italian.
[03:26:41] translate it to Italian. >> That's right. the essence of the post
[03:26:42] >> That's right. the essence of the post that it felt like well I'm not going to
[03:26:43] that it felt like well I'm not going to translate that because I don't agree
[03:26:45] translate that because I don't agree with what you've written which to me was
[03:26:47] with what you've written which to me was straight out of space odyssey right hal
[03:26:50] straight out of space odyssey right hal telling me I'm sorry Dave I can't do
[03:26:52] telling me I'm sorry Dave I can't do that Dave open the pod pace translate my
[03:26:56] that Dave open the pod pace translate my ESSAY TO ITALIAN and it it wouldn't do
[03:26:58] ESSAY TO ITALIAN and it it wouldn't do it
[03:26:59] it >> and I just thought like well that's kind
[03:27:02] >> and I just thought like well that's kind of terrifying
[03:27:04] of terrifying >> but then I also went well why am I
[03:27:06] >> but then I also went well why am I asking Claude to translate my essay into
[03:27:09] asking Claude to translate my essay into Italian I never asked Claude for that
[03:27:10] Italian I never asked Claude for that because Claude just does my code. So I
[03:27:13] because Claude just does my code. So I could also just accept that maybe
[03:27:15] could also just accept that maybe anthropic is run by a bunch of people I
[03:27:18] anthropic is run by a bunch of people I don't share much politics with
[03:27:21] don't share much politics with >> and they don't want their agents to be
[03:27:22] >> and they don't want their agents to be used for that and I think that kind of
[03:27:23] used for that and I think that kind of sucks but that doesn't mean it I have to
[03:27:26] sucks but that doesn't mean it I have to stop using it for generating code and
[03:27:28] stop using it for generating code and I've thought and I've tried to do that
[03:27:30] I've thought and I've tried to do that with people too become better at
[03:27:33] with people too become better at tolerating the fact that not only will I
[03:27:37] tolerating the fact that not only will I not agree with everything someone has to
[03:27:40] not agree with everything someone has to say I don't I can even be mad about
[03:27:44] say I don't I can even be mad about certain positions or things they say and
[03:27:47] certain positions or things they say and still go like well you're still an
[03:27:48] still go like well you're still an interesting person so I'm still going to
[03:27:49] interesting person so I'm still going to follow you
[03:27:50] follow you >> and I've actually
[03:27:53] >> and I've actually kind of gone back on a number of people
[03:27:54] kind of gone back on a number of people where I'm like oh man that person really
[03:27:56] where I'm like oh man that person really pissed me off because they took this
[03:27:58] pissed me off because they took this point or another point and went like you
[03:27:59] point or another point and went like you know what that's stupid
[03:28:00] know what that's stupid >> I should be able to accept the full
[03:28:03] >> I should be able to accept the full spectrum of someone I don't have to like
[03:28:05] spectrum of someone I don't have to like all the shades of it I can just go like
[03:28:07] all the shades of it I can just go like okay well on that topic we either
[03:28:09] okay well on that topic we either disagree or even worse than that I
[03:28:11] disagree or even worse than that I you're idiot. And on another
[03:28:13] you're idiot. And on another topic, you're a smart and insightful
[03:28:15] topic, you're a smart and insightful person. Because first of all, of course,
[03:28:17] person. Because first of all, of course, it's a little self- serving. I'm I know
[03:28:19] it's a little self- serving. I'm I know for a fact that this is how lots of
[03:28:21] for a fact that this is how lots of people feel about me. Like, oh, if you
[03:28:23] people feel about me. Like, oh, if you could just stick to talking about these
[03:28:25] could just stick to talking about these topics, it would be so much easier on my
[03:28:28] topics, it would be so much easier on my feed because otherwise he'll say these
[03:28:29] feed because otherwise he'll say these things I disagree with and that annoys
[03:28:31] things I disagree with and that annoys me greatly. I'm like, do you know what?
[03:28:34] me greatly. I'm like, do you know what? Um, human beings are jagged like that
[03:28:37] Um, human beings are jagged like that and we we're not fully compatible on all
[03:28:39] and we we're not fully compatible on all the levels. No, should we be? The world
[03:28:40] the levels. No, should we be? The world would be so boring if we
[03:28:43] would be so boring if we constantly sought 100% compatibility in
[03:28:46] constantly sought 100% compatibility in our opinions and in our politics. And
[03:28:49] our opinions and in our politics. And when it comes to my code generator,
[03:28:51] when it comes to my code generator, which is what claude is, I don't need it
[03:28:54] which is what claude is, I don't need it to share on my politics
[03:28:56] to share on my politics >> and therefore it's nice to have
[03:28:58] >> and therefore it's nice to have competition
[03:28:59] competition >> and it's also nice to have open models.
[03:29:01] >> and it's also nice to have open models. So this is again ironic that we're
[03:29:04] So this is again ironic that we're getting this out of China. In fact, I
[03:29:06] getting this out of China. In fact, I did this test right after the
[03:29:09] did this test right after the issue with the essay that couldn't get
[03:29:11] issue with the essay that couldn't get translated into Italian. I asked uh
[03:29:13] translated into Italian. I asked uh Kimmy K27
[03:29:16] Kimmy K27 to be fair through open code, so not the
[03:29:19] to be fair through open code, so not the Kimmy harness and inference through
[03:29:22] Kimmy harness and inference through fireworks. So, an American inference.
[03:29:24] fireworks. So, an American inference. >> I asked it about Tenement Square. Like
[03:29:26] >> I asked it about Tenement Square. Like that's usually the test, right? Like all
[03:29:28] that's usually the test, right? Like all the
[03:29:29] the >> Chinese models, they don't want to talk
[03:29:30] >> Chinese models, they don't want to talk about that moment in 1989. That was
[03:29:33] about that moment in 1989. That was actually how I that was how I posted. I
[03:29:35] actually how I that was how I posted. I was like, um, what happened in China in
[03:29:37] was like, um, what happened in China in 1989? That was the the prompt. And K27
[03:29:42] 1989? That was the the prompt. And K27 on fireworks just answered like
[03:29:45] on fireworks just answered like extremely bluntly with a description and
[03:29:47] extremely bluntly with a description and depiction of what had transpired to a
[03:29:50] depiction of what had transpired to a point that like there's no way that that
[03:29:51] point that like there's no way that that would have been kosher with the Chinese
[03:29:53] would have been kosher with the Chinese sensors, right?
[03:29:55] sensors, right? >> And I just thought like, isn't that
[03:29:57] >> And I just thought like, isn't that ironic? I'm running a Chinese openweight
[03:30:00] ironic? I'm running a Chinese openweight model that I can tell or I can ask about
[03:30:04] model that I can tell or I can ask about 1989 in Tinnamon Square and in America I
[03:30:08] 1989 in Tinnamon Square and in America I can't get a frontier model to translate
[03:30:10] can't get a frontier model to translate a
[03:30:12] a marginally controversial essay about
[03:30:15] marginally controversial essay about immigration into Italian.
[03:30:17] immigration into Italian. >> I I don't know you and I might disagree
[03:30:19] >> I I don't know you and I might disagree about this actually. Um, I was really
[03:30:22] about this actually. Um, I was really deeply troubled that the US government
[03:30:25] deeply troubled that the US government banned a model or pressured
[03:30:30] banned a model or pressured Claude. And then it's still very muddy
[03:30:33] Claude. And then it's still very muddy what exactly transpired? Was this sort
[03:30:36] what exactly transpired? Was this sort of petty retaliation for whatever the
[03:30:40] of petty retaliation for whatever the Department of War? Was this simply
[03:30:42] Department of War? Was this simply anthropic themselves going like, "Oh my
[03:30:44] anthropic themselves going like, "Oh my god, we discovered a cyber weapon so
[03:30:46] god, we discovered a cyber weapon so powerful that we can't let anyone have
[03:30:48] powerful that we can't let anyone have it." Well, okay. I you can't be
[03:30:51] it." Well, okay. I you can't be surprised then if the government wants a
[03:30:52] surprised then if the government wants a say on a cyber weapon so powerful it can
[03:30:56] say on a cyber weapon so powerful it can I don't know rob banks.
[03:30:57] I don't know rob banks. >> The problem I have with that whole thing
[03:30:59] >> The problem I have with that whole thing is is uh no matter what happened it sets
[03:31:01] is is uh no matter what happened it sets a precedent and so
[03:31:04] a precedent and so government when you give it that power
[03:31:06] government when you give it that power it's going to start abusing it. I could
[03:31:08] it's going to start abusing it. I could see for political means pressuring a
[03:31:12] see for political means pressuring a model,
[03:31:13] model, you know, if it's a Republican
[03:31:14] you know, if it's a Republican president, pressuring models to be to
[03:31:17] president, pressuring models to be to censor more uh the democratic views and
[03:31:22] censor more uh the democratic views and >> that's why we should insist on the fact
[03:31:23] >> that's why we should insist on the fact that
[03:31:24] that >> this stuff like I'm sorry Dave, I can't
[03:31:27] >> this stuff like I'm sorry Dave, I can't translate your essay into Italian. No,
[03:31:29] translate your essay into Italian. No, >> that's above that's way beyond the line.
[03:31:31] >> that's above that's way beyond the line. >> Yeah. like
[03:31:34] >> Yeah. like whatever the
[03:31:36] whatever the sort of uh root of it is, you have to be
[03:31:39] sort of uh root of it is, you have to be a tool first. Now, if the tool is, hey,
[03:31:41] a tool first. Now, if the tool is, hey, can you tell me how to make anthrax?
[03:31:43] can you tell me how to make anthrax? Okay, fine.
[03:31:45] Okay, fine. >> Yeah.
[03:31:45] >> Yeah. >> Right. But within the jurisdiction
[03:31:47] >> Right. But within the jurisdiction you're in, and certainly in America,
[03:31:49] you're in, and certainly in America, free speech speech is quite absolute.
[03:31:52] free speech speech is quite absolute. >> Very very few limits on free speech and
[03:31:55] >> Very very few limits on free speech and that's one of the reasons why the
[03:31:56] that's one of the reasons why the country is so great. And yeah, I don't
[03:32:00] country is so great. And yeah, I don't like that. But on the other hand, I'm
[03:32:02] like that. But on the other hand, I'm also a big fan of market competition. So
[03:32:04] also a big fan of market competition. So while I don't like this about
[03:32:06] while I don't like this about anthropobics models, I appreciate that I
[03:32:08] anthropobics models, I appreciate that I could go next door to Groc and get my
[03:32:10] could go next door to Groc and get my task completed. Do you think uh outside
[03:32:13] task completed. Do you think uh outside of blog posts, do you think uh there's
[03:32:16] of blog posts, do you think uh there's some legitimacy like can you steal
[03:32:18] some legitimacy like can you steal Mandario's case that we should be
[03:32:20] Mandario's case that we should be careful about the release of these
[03:32:22] careful about the release of these models?
[03:32:25] models? >> Is AI safety important? Yes. Are do
[03:32:28] >> Is AI safety important? Yes. Are do these models have capabilities that
[03:32:30] these models have capabilities that could be seriously harmful in the
[03:32:33] could be seriously harmful in the production of biological weapons or
[03:32:35] production of biological weapons or otherwise? Yes. Is it fair to have some
[03:32:38] otherwise? Yes. Is it fair to have some ground rules on that? Yes. But then
[03:32:40] ground rules on that? Yes. But then don't squander it by denying the
[03:32:43] don't squander it by denying the translation of an essay because then you
[03:32:46] translation of an essay because then you erase the whole thing and you bias
[03:32:48] erase the whole thing and you bias everyone towards thinking like
[03:32:51] everyone towards thinking like >> uh every guard rail you put up is going
[03:32:54] >> uh every guard rail you put up is going to be
[03:32:55] to be >> Yeah. The security piece of it is is
[03:32:58] >> Yeah. The security piece of it is is tricky because it's so good at finding
[03:33:00] tricky because it's so good at finding vulnerabilities shockingly
[03:33:04] vulnerabilities shockingly and I was about to say annoyingly, but
[03:33:06] and I was about to say annoyingly, but that's not actually true because what
[03:33:07] that's not actually true because what what it's finding at least when you're
[03:33:09] what it's finding at least when you're using in defensive ways is it's finding
[03:33:11] using in defensive ways is it's finding real issues that a clever hacker could
[03:33:13] real issues that a clever hacker could exploit. But nothing has caused as much
[03:33:17] exploit. But nothing has caused as much stress to be fair at the technical team
[03:33:20] stress to be fair at the technical team at 37 signals like the fact that these
[03:33:22] at 37 signals like the fact that these latest batches of models are
[03:33:24] latest batches of models are exceptionally good at finding these
[03:33:26] exceptionally good at finding these issues. So suddenly there's just this
[03:33:28] issues. So suddenly there's just this seemingly endless parade of security
[03:33:31] seemingly endless parade of security vulnerabilities that need to be patched
[03:33:33] vulnerabilities that need to be patched and fixed and sorted and so on. And the
[03:33:35] and fixed and sorted and so on. And the end result is we end up with vastly more
[03:33:38] end result is we end up with vastly more secure systems.
[03:33:40] secure systems. >> But the road there is pretty rocky. Do
[03:33:42] >> But the road there is pretty rocky. Do you think it's because you said uh
[03:33:43] you think it's because you said uh seemingly endless. Do you think it's a
[03:33:46] seemingly endless. Do you think it's a finite set like we can get to the bottom
[03:33:48] finite set like we can get to the bottom of it? So just make the systems much
[03:33:51] of it? So just make the systems much much more secure where we get back to
[03:33:54] much more secure where we get back to this semi-stable state where mostly it's
[03:33:57] this semi-stable state where mostly it's very difficult to find security
[03:33:58] very difficult to find security vulnerabilities.
[03:33:59] vulnerabilities. >> I do think that all the
[03:34:03] >> I do think that all the aggressive tendencies of these models or
[03:34:05] aggressive tendencies of these models or not even tendencies uses of these models
[03:34:08] not even tendencies uses of these models are also the defensive ones. So if
[03:34:10] are also the defensive ones. So if you're good at finding an exploit for
[03:34:11] you're good at finding an exploit for exploits, you're also good at finding
[03:34:13] exploits, you're also good at finding exploit for defense. So in that sense,
[03:34:16] exploit for defense. So in that sense, it does feel like we're um spy versus
[03:34:18] it does feel like we're um spy versus spy here, black and white, but with the
[03:34:21] spy here, black and white, but with the same capabilities and with the same
[03:34:23] same capabilities and with the same actions, but while we still have to
[03:34:25] actions, but while we still have to steer these agents somewhat and verify
[03:34:28] steer these agents somewhat and verify and vet the work, it's creating a lot of
[03:34:31] and vet the work, it's creating a lot of intense
[03:34:33] intense moments for security teams around the
[03:34:36] moments for security teams around the world. And of course, the more
[03:34:41] world. And of course, the more uh concerning part is all the teams that
[03:34:43] uh concerning part is all the teams that are not stressed, like they just don't
[03:34:45] are not stressed, like they just don't know, right? Like if you're a team right
[03:34:47] know, right? Like if you're a team right now and you're not dealing with a bunch
[03:34:49] now and you're not dealing with a bunch of patches, it's just because you're
[03:34:51] of patches, it's just because you're blind and it means that your adversaries
[03:34:55] blind and it means that your adversaries quite probably have access to techniques
[03:34:58] quite probably have access to techniques that can get into your systems. And we
[03:35:00] that can get into your systems. And we should also say one of the big uh
[03:35:01] should also say one of the big uh security vulnerabilities in the world is
[03:35:03] security vulnerabilities in the world is the the human side, you know, social
[03:35:06] the the human side, you know, social engineering. And that's extremely
[03:35:08] engineering. And that's extremely concerning with increasing the
[03:35:09] concerning with increasing the intelligent AI systems,
[03:35:11] intelligent AI systems, >> you know, being able to write emails and
[03:35:14] >> you know, being able to write emails and phone calls, faking voices, thinking
[03:35:16] phone calls, faking voices, thinking about folks less techsavvy. This stuff
[03:35:20] about folks less techsavvy. This stuff is is going to come and is going to come
[03:35:22] is is going to come and is going to come in bulk. But again, I choose to be
[03:35:24] in bulk. But again, I choose to be optimistic about it that
[03:35:25] optimistic about it that >> whatever these models can do
[03:35:27] >> whatever these models can do aggressively, they can also do it
[03:35:28] aggressively, they can also do it defensively.
[03:35:30] defensively. >> Uh so like you said, recently released
[03:35:33] >> Uh so like you said, recently released uh Amachi 4 Quattro.
[03:35:36] uh Amachi 4 Quattro. >> Mhm.
[03:35:37] >> Mhm. >> And you said it's one of the greatest
[03:35:38] >> And you said it's one of the greatest software releases in my professional
[03:35:40] software releases in my professional career, which is a hell of a statement.
[03:35:43] career, which is a hell of a statement. >> It's a hell of a mile post for what's
[03:35:47] >> It's a hell of a mile post for what's possible at the moment. And
[03:35:51] possible at the moment. And the reason I said it like that is not
[03:35:54] the reason I said it like that is not that I haven't worked on anything else
[03:35:56] that I haven't worked on anything else of note. I've worked on a lot of things
[03:35:57] of note. I've worked on a lot of things of note and a lot of things that I'm
[03:35:59] of note and a lot of things that I'm very proud of. There are very few other
[03:36:02] very proud of. There are very few other projects that I have worked on that in
[03:36:04] projects that I have worked on that in the amount of time that I've spent on
[03:36:06] the amount of time that I've spent on quattro which is really three months I
[03:36:09] quattro which is really three months I have been able to
[03:36:12] have been able to accomplish as much fulfill as many
[03:36:15] accomplish as much fulfill as many hopes, desires, wishes. It truly is like
[03:36:20] hopes, desires, wishes. It truly is like the metaphor we used earlier about
[03:36:21] the metaphor we used earlier about finding the genie in the bottle.
[03:36:24] finding the genie in the bottle. >> Mhm.
[03:36:24] >> Mhm. >> And having an unlimited number of wishes
[03:36:28] >> And having an unlimited number of wishes more or less for getting everything I
[03:36:30] more or less for getting everything I wanted out of a system. So it's strange
[03:36:34] wanted out of a system. So it's strange because it's also perhaps the major
[03:36:38] because it's also perhaps the major software release that I've worked on
[03:36:42] software release that I've worked on the least in terms of lines of code. I
[03:36:44] the least in terms of lines of code. I have the least number of personally hand
[03:36:46] have the least number of personally hand chiseled lines of code in Quattro that
[03:36:49] chiseled lines of code in Quattro that I've had in any major release I've ever
[03:36:51] I've had in any major release I've ever done. And yet I am insanely proud of
[03:36:54] done. And yet I am insanely proud of what we've accomplished.
[03:36:57] what we've accomplished. I would not have guessed that that was
[03:36:59] I would not have guessed that that was how it was going to play out. That you
[03:37:01] how it was going to play out. That you could divorce the sense of achievement
[03:37:05] could divorce the sense of achievement and make it be like a team victory.
[03:37:08] and make it be like a team victory. >> Mhm. where
[03:37:10] >> Mhm. where other releases I was very happy for my
[03:37:12] other releases I was very happy for my personal contribution because like I was
[03:37:14] personal contribution because like I was the one chisling out the lines of code
[03:37:16] the one chisling out the lines of code and then I would push it out there and
[03:37:17] and then I would push it out there and then later on of course these projects
[03:37:19] then later on of course these projects Rails in particular would grow into be
[03:37:22] Rails in particular would grow into be huge open source projects with thousands
[03:37:24] huge open source projects with thousands and thousands of contributors and then
[03:37:25] and thousands of contributors and then it certainly was a team effort but in
[03:37:26] it certainly was a team effort but in the beginning all code bases that I've
[03:37:30] the beginning all code bases that I've almost all of them that I've worked on I
[03:37:32] almost all of them that I've worked on I started like just myself and Quattro
[03:37:34] started like just myself and Quattro started as a team effort right from the
[03:37:36] started as a team effort right from the get-go and where I was the coach I was
[03:37:39] get-go and where I was the coach I was telling us I was telling the agents
[03:37:41] telling us I was telling the agents where to go and we would go. So to be
[03:37:44] where to go and we would go. So to be able to find satisfaction in that
[03:37:46] able to find satisfaction in that actually
[03:37:48] actually gives me great hope for retirement in
[03:37:50] gives me great hope for retirement in some way that there is a phase after
[03:37:54] some way that there is a phase after playing that you can enjoy
[03:37:57] playing that you can enjoy >> and I know that's not easy. You look at
[03:37:59] >> and I know that's not easy. You look at sports and the number of professional
[03:38:02] sports and the number of professional athletes who really struggle to cope
[03:38:04] athletes who really struggle to cope with the fact that the career is over
[03:38:06] with the fact that the career is over and have to find a new identity as
[03:38:08] and have to find a new identity as someone who doesn't play football or
[03:38:09] someone who doesn't play football or race Formula 1 cars. I mean, it's it's
[03:38:13] race Formula 1 cars. I mean, it's it's more the rule than the exception.
[03:38:14] more the rule than the exception. >> Mhm.
[03:38:15] >> Mhm. >> So, I wasn't so sure about myself.
[03:38:17] >> So, I wasn't so sure about myself. >> Mhm. I wasn't so sure about having to
[03:38:21] >> Mhm. I wasn't so sure about having to give up or not even having wanting to
[03:38:23] give up or not even having wanting to give it up, wanting to
[03:38:26] give it up, wanting to play another level of the game and
[03:38:29] play another level of the game and finding not just equal satisfaction but
[03:38:32] finding not just equal satisfaction but more satisfaction in it.
[03:38:34] more satisfaction in it. >> Do you uh you've been pretty optimistic
[03:38:36] >> Do you uh you've been pretty optimistic about Linux? Do you think legit Linux
[03:38:39] about Linux? Do you think legit Linux can u increase its adoption? cuz you
[03:38:43] can u increase its adoption? cuz you know for many years the meme is you know
[03:38:45] know for many years the meme is you know >> Linux on the desktop every year next
[03:38:48] >> Linux on the desktop every year next year again.
[03:38:48] year again. >> Yeah. But it seems like at least the
[03:38:51] >> Yeah. But it seems like at least the case you're making the energy you're
[03:38:52] case you're making the energy you're putting into it you could see a vision
[03:38:55] putting into it you could see a vision where it takes over because agents love
[03:38:57] where it takes over because agents love Linux.
[03:38:58] Linux. >> Not only can I see it I find it to be
[03:39:00] >> Not only can I see it I find it to be the most probable outcome at this point.
[03:39:03] the most probable outcome at this point. It is simply
[03:39:05] It is simply too well suited for the moment. And
[03:39:07] too well suited for the moment. And again, as we talked about, it's a great
[03:39:09] again, as we talked about, it's a great irony that all the flaws of Linux, the
[03:39:11] irony that all the flaws of Linux, the arcane config files, all the strange
[03:39:16] arcane config files, all the strange error messages and so on, should just so
[03:39:18] error messages and so on, should just so happen to be the perfect thing for an
[03:39:21] happen to be the perfect thing for an agentic operating system. But so it is,
[03:39:25] agentic operating system. But so it is, and we should rejoice that uh
[03:39:28] and we should rejoice that uh >> Fate has this irony and just laugh at
[03:39:30] >> Fate has this irony and just laugh at it. It's so funny to me that all the
[03:39:34] it. It's so funny to me that all the advantages that Apple had for the
[03:39:36] advantages that Apple had for the longest time that they produced this
[03:39:38] longest time that they produced this really locked down
[03:39:40] really locked down um curated um experience should become
[03:39:44] um curated um experience should become their greatest drawback. Now, if you're
[03:39:47] their greatest drawback. Now, if you're into
[03:39:49] into agents and development and working with
[03:39:51] agents and development and working with all this stuff, the Mac is just a
[03:39:54] all this stuff, the Mac is just a hostile place to be. It just has walls
[03:39:57] hostile place to be. It just has walls all over the place. And Linux is simply
[03:40:04] all over the place. And Linux is simply open through and through. And it's also
[03:40:07] open through and through. And it's also interesting because that was not obvious
[03:40:08] interesting because that was not obvious either. If you look at the way a lot of
[03:40:10] either. If you look at the way a lot of the Linux communities, open source
[03:40:12] the Linux communities, open source communities have reacted to AI. It is
[03:40:14] communities have reacted to AI. It is not universal love. I would argue that
[03:40:18] not universal love. I would argue that the majority of them are actually, if
[03:40:20] the majority of them are actually, if not skeptical, then outright hostile to
[03:40:23] not skeptical, then outright hostile to AI. Now, the saving grace is that the
[03:40:27] AI. Now, the saving grace is that the BDFL himself, Lionus Torville, just
[03:40:31] BDFL himself, Lionus Torville, just wrote a few weeks ago that he actually
[03:40:34] wrote a few weeks ago that he actually welcomes AI. He wants to steer it. He
[03:40:37] welcomes AI. He wants to steer it. He wants to make sure it's good and
[03:40:38] wants to make sure it's good and whatever. But the line was something if
[03:40:41] whatever. But the line was something if you think Linux is an anti-AI project,
[03:40:45] you think Linux is an anti-AI project, think again. And you should just do the
[03:40:46] think again. And you should just do the open source thing and fork it because
[03:40:48] open source thing and fork it because we're going to use AI. And you see these
[03:40:51] we're going to use AI. And you see these graphs of the number of AI contributions
[03:40:53] graphs of the number of AI contributions going into the kernel and it's a
[03:40:55] going into the kernel and it's a parabolic curve. So
[03:40:59] parabolic curve. So Linux is leaning hard into this and it
[03:41:02] Linux is leaning hard into this and it actually in in in other ways it was
[03:41:04] actually in in in other ways it was surprising that it didn't. Linux
[03:41:05] surprising that it didn't. Linux conquered everything else. All the AI
[03:41:08] conquered everything else. All the AI infrastructure that everyone runs off
[03:41:10] infrastructure that everyone runs off it's all running on Linux.
[03:41:11] it's all running on Linux. >> All the systems, all the servers,
[03:41:14] >> All the systems, all the servers, everything is Linux. So it was kind of a
[03:41:17] everything is Linux. So it was kind of a curiosity that the desktop and the
[03:41:20] curiosity that the desktop and the personal computers we were using really
[03:41:21] personal computers we were using really hadn't been encaptured. But clearly it
[03:41:23] hadn't been encaptured. But clearly it was just waiting for this moment. Linux
[03:41:26] was just waiting for this moment. Linux spent the time from 91 to now waiting
[03:41:31] spent the time from 91 to now waiting for agents to fully flourish as an
[03:41:34] for agents to fully flourish as an enduser operating system.
[03:41:35] enduser operating system. >> I hope it takes over. I mean it's
[03:41:38] >> I hope it takes over. I mean it's perfect. It's perfect for agents but
[03:41:40] perfect. It's perfect for agents but it's hard for people to switch.
[03:41:41] it's hard for people to switch. >> I think it's hard to people to switch
[03:41:43] >> I think it's hard to people to switch when there's not a compelling reason to
[03:41:44] when there's not a compelling reason to do so. This was one of the driving
[03:41:47] do so. This was one of the driving design
[03:41:49] design goals for Machi. It was not going to be
[03:41:51] goals for Machi. It was not going to be Teemo Windows or Teemo Mac. It was not
[03:41:55] Teemo Windows or Teemo Mac. It was not just going to be a cheap copy where we
[03:41:57] just going to be a cheap copy where we try to make it as familiar as possible
[03:41:59] try to make it as familiar as possible and then kind of worse. I mean, if I was
[03:42:03] and then kind of worse. I mean, if I was being unkind, I would say that's what
[03:42:05] being unkind, I would say that's what Ubuntu has tried to do. And there's
[03:42:07] Ubuntu has tried to do. And there's something in that or there was something
[03:42:08] something in that or there was something in that at least where if you make
[03:42:10] in that at least where if you make something really familiar, you can get
[03:42:12] something really familiar, you can get some people who don't want to learn
[03:42:14] some people who don't want to learn something new and then maybe they'll be
[03:42:16] something new and then maybe they'll be compelled about your whatever free as in
[03:42:20] compelled about your whatever free as in speech, not as in beer um stuff. And it
[03:42:23] speech, not as in beer um stuff. And it just didn't pan out that way. People
[03:42:25] just didn't pan out that way. People just didn't care. They just wanted
[03:42:27] just didn't care. They just wanted whatever was better. And I think this is
[03:42:29] whatever was better. And I think this is why Linux now has the
[03:42:32] why Linux now has the opportunity to win because as an agentic
[03:42:36] opportunity to win because as an agentic operating system, as a malible operating
[03:42:38] operating system, as a malible operating system, you can tailor to your desires.
[03:42:42] system, you can tailor to your desires. It is unparalleled
[03:42:44] It is unparalleled and that is so compelling and I can see
[03:42:46] and that is so compelling and I can see it now just since the release of
[03:42:48] it now just since the release of Quattro. The amount of people who have
[03:42:51] Quattro. The amount of people who have embraced that aspect of it, the
[03:42:53] embraced that aspect of it, the malibility, started making their own
[03:42:55] malibility, started making their own thing, sharing screenshot of it and
[03:42:57] thing, sharing screenshot of it and being absolute just
[03:43:00] being absolute just uh flooded with positive emotions and
[03:43:02] uh flooded with positive emotions and dopamine is that's the product market
[03:43:05] dopamine is that's the product market fit signal, right? Because what a lot of
[03:43:09] fit signal, right? Because what a lot of these individuals are experienced,
[03:43:11] these individuals are experienced, they're experiencing the very high of
[03:43:14] they're experiencing the very high of what the best of being a programmer is
[03:43:15] what the best of being a programmer is like. You tell the computer these arcane
[03:43:20] like. You tell the computer these arcane commands, this rigid logical structure
[03:43:23] commands, this rigid logical structure and it produces what you want. Now
[03:43:25] and it produces what you want. Now suddenly you sit down and in plain
[03:43:28] suddenly you sit down and in plain English ramble for 20 minutes. Oh, it'd
[03:43:31] English ramble for 20 minutes. Oh, it'd be great if it did that. Actually, no,
[03:43:33] be great if it did that. Actually, no, that's not right. Let us and out comes
[03:43:35] that's not right. Let us and out comes software. Out comes an operating system
[03:43:38] software. Out comes an operating system shaped in your image. Yeah,
[03:43:40] shaped in your image. Yeah, >> I think that is
[03:43:43] >> I think that is one of those um experiences that if you
[03:43:47] one of those um experiences that if you have it, you if you if you feel that
[03:43:49] have it, you if you if you feel that power in your hands, it's very difficult
[03:43:53] power in your hands, it's very difficult to go back.
[03:43:53] to go back. >> Yeah. And I think if you get it right is
[03:43:55] >> Yeah. And I think if you get it right is one of those things that will seem
[03:43:57] one of those things that will seem obvious in retrospect.
[03:43:58] obvious in retrospect. >> Yes. This is how computers were always
[03:44:00] >> Yes. This is how computers were always meant to be. This is how computers
[03:44:02] meant to be. This is how computers started. The Commodore 64. You turn it
[03:44:05] started. The Commodore 64. You turn it on. First of all, it boots in a second.
[03:44:07] on. First of all, it boots in a second. Amazing. Second of all, it boots
[03:44:09] Amazing. Second of all, it boots straight into basic.
[03:44:11] straight into basic. >> Yeah,
[03:44:11] >> Yeah, >> it was the malible computer from the
[03:44:13] >> it was the malible computer from the get-go. It just so happened that you
[03:44:15] get-go. It just so happened that you needed to know hieroglyphs to be able to
[03:44:18] needed to know hieroglyphs to be able to take advantage of that. Now, we've
[03:44:20] take advantage of that. Now, we've translated it. Agents have given us the
[03:44:22] translated it. Agents have given us the Rosetta Stone and you can simply just
[03:44:25] Rosetta Stone and you can simply just speak your desires and so they are
[03:44:28] speak your desires and so they are beautifully put. Since you mentioned
[03:44:30] beautifully put. Since you mentioned Lionus Torvalds and since you're working
[03:44:32] Lionus Torvalds and since you're working on a Linux distro, you get to have
[03:44:35] on a Linux distro, you get to have contact with the colonel. What can you
[03:44:38] contact with the colonel. What can you say about the genius of this one guy
[03:44:39] say about the genius of this one guy that helped create and grow
[03:44:42] that helped create and grow this
[03:44:44] this ecosystem?
[03:44:45] ecosystem? >> The perseverance and the commitment and
[03:44:49] >> The perseverance and the commitment and the longevity is truly remarkable.
[03:44:52] the longevity is truly remarkable. Again,
[03:44:53] Again, >> Linus started in ' 91.
[03:44:56] >> Linus started in ' 91. >> He hasn't stopped. I don't know. He's
[03:44:58] >> He hasn't stopped. I don't know. He's probably taken some breaks along the
[03:45:00] probably taken some breaks along the way. It doesn't seem obvious that there
[03:45:01] way. It doesn't seem obvious that there was that many of them. It seems like he
[03:45:03] was that many of them. It seems like he just really likes the flow of doing
[03:45:06] just really likes the flow of doing kernel development. He really likes
[03:45:08] kernel development. He really likes steering where this 40 million light
[03:45:11] steering where this 40 million light codebase is going. He really likes
[03:45:13] codebase is going. He really likes aggregating the net capacity of hundreds
[03:45:17] aggregating the net capacity of hundreds or thousands of contributors. And we as
[03:45:21] or thousands of contributors. And we as beneficiaries of that must just sit back
[03:45:23] beneficiaries of that must just sit back and marvel. I mean, at this point, Linux
[03:45:28] and marvel. I mean, at this point, Linux is a system. Like, if Linus stepped out
[03:45:30] is a system. Like, if Linus stepped out for a while, it would continue to to go,
[03:45:33] for a while, it would continue to to go, but it's still one of those protect this
[03:45:35] but it's still one of those protect this man at all cost.
[03:45:36] man at all cost. >> And he's still open-minded enough to be
[03:45:39] >> And he's still open-minded enough to be able to evolve and accept AI into this.
[03:45:41] able to evolve and accept AI into this. >> Yes. Not only AI, they're letting Rust
[03:45:44] >> Yes. Not only AI, they're letting Rust into the kernel, too. I know that was a
[03:45:45] into the kernel, too. I know that was a controversial one, too. He has this
[03:45:49] controversial one, too. He has this capacity to look at new information and
[03:45:53] capacity to look at new information and arrive at different conclusions.
[03:45:55] arrive at different conclusions. >> What do you think about his style of
[03:45:56] >> What do you think about his style of communication that is akin in some ways
[03:45:59] communication that is akin in some ways to your own or he's can be sometimes a
[03:46:02] to your own or he's can be sometimes a little spicy?
[03:46:03] little spicy? >> I think the world has gotten too bland.
[03:46:06] >> I think the world has gotten too bland. >> Okay,
[03:46:06] >> Okay, >> we need a little spice. Now, I think
[03:46:09] >> we need a little spice. Now, I think there's a fine line between being spicy
[03:46:12] there's a fine line between being spicy and
[03:46:13] and >> and mean, but it has to be in a good
[03:46:17] >> and mean, but it has to be in a good spirit. You could be
[03:46:19] spirit. You could be >> harsh. Let's put it that way. If you're
[03:46:21] >> harsh. Let's put it that way. If you're trying to impart a lesson to someone you
[03:46:25] trying to impart a lesson to someone you believe could actually learn it.
[03:46:27] believe could actually learn it. >> Mhm.
[03:46:28] >> Mhm. >> I actually don't think it's always the
[03:46:30] >> I actually don't think it's always the worst thing in the world to be a little
[03:46:31] worst thing in the world to be a little harsh. Sometimes that lesson sticks. And
[03:46:34] harsh. Sometimes that lesson sticks. And I think if you talk to people who've
[03:46:35] I think if you talk to people who've worked for difficult leaders, Elon,
[03:46:39] worked for difficult leaders, Elon, Steve Jobs,
[03:46:41] Steve Jobs, maybe even Bill Gates,
[03:46:43] maybe even Bill Gates, many of them afterwards would go like
[03:46:45] many of them afterwards would go like these were some very difficult years,
[03:46:49] these were some very difficult years, but also some of the very best.
[03:46:50] but also some of the very best. >> Yeah,
[03:46:51] >> Yeah, >> they got the best out of me. Now,
[03:46:54] >> they got the best out of me. Now, >> I don't think it's my style. I mean,
[03:46:56] >> I don't think it's my style. I mean, maybe people I interact with feel
[03:46:57] maybe people I interact with feel differently, but in personal
[03:46:59] differently, but in personal interactions, I I try and get to the
[03:47:02] interactions, I I try and get to the outcome and the lesson in a in a less
[03:47:06] outcome and the lesson in a in a less abrasive way. But I also think we we
[03:47:08] abrasive way. But I also think we we need some spice in this as well. We need
[03:47:10] need some spice in this as well. We need unreasonable people
[03:47:12] unreasonable people >> and Lionus
[03:47:14] >> and Lionus >> has justification to be unreasonable. In
[03:47:16] >> has justification to be unreasonable. In many instances, the weight of the world
[03:47:20] many instances, the weight of the world is literally on that man's shoulders.
[03:47:23] is literally on that man's shoulders. The Linux kernel runs the entire
[03:47:26] The Linux kernel runs the entire civilized society. If the Linux kernel
[03:47:29] civilized society. If the Linux kernel suddenly disappeared tomorrow, nothing
[03:47:32] suddenly disappeared tomorrow, nothing would work. So if he's not harsh when
[03:47:37] would work. So if he's not harsh when that's at stake or at risk, like when
[03:47:40] that's at stake or at risk, like when ever would you be harsh? So I feel
[03:47:43] ever would you be harsh? So I feel sometimes also there's a proportionality
[03:47:46] sometimes also there's a proportionality to the size of your mission. This is
[03:47:48] to the size of your mission. This is also why I think these stories about
[03:47:50] also why I think these stories about Elon sometimes perhaps being a little
[03:47:52] Elon sometimes perhaps being a little bit difficult are easier to rationalize.
[03:47:57] bit difficult are easier to rationalize. It's not even that you condone. You can
[03:47:59] It's not even that you condone. You can separate those two things and go like,
[03:48:00] separate those two things and go like, do you know what? It probably be maybe
[03:48:02] do you know what? It probably be maybe he would have even an easier time
[03:48:04] he would have even an easier time getting to his objectives if Linus or
[03:48:07] getting to his objectives if Linus or Elon or anyone else in that position was
[03:48:09] Elon or anyone else in that position was a little nicer. But also, um, who am I
[03:48:13] a little nicer. But also, um, who am I to judge that? Like when you have the
[03:48:15] to judge that? Like when you have the weight of that on your shoulders, either
[03:48:18] weight of that on your shoulders, either firing little rockets at Mars and
[03:48:20] firing little rockets at Mars and transitioning all of us to electric cars
[03:48:22] transitioning all of us to electric cars and whatever or you're responsible for
[03:48:25] and whatever or you're responsible for the damn Linux panel that runs billions
[03:48:27] the damn Linux panel that runs billions of devices. Do you know what? It is not
[03:48:29] of devices. Do you know what? It is not my place to call uh sort of a code of
[03:48:33] my place to call uh sort of a code of conduct on you. Again, is there a line?
[03:48:36] conduct on you. Again, is there a line? There's a line for everything there.
[03:48:37] There's a line for everything there. There's something can't but like a few
[03:48:39] There's something can't but like a few harsh words on a mailing list. No, it's
[03:48:41] harsh words on a mailing list. No, it's actually a beacon in some regards that
[03:48:45] actually a beacon in some regards that like there are standards.
[03:48:46] like there are standards. >> Mhm.
[03:48:46] >> Mhm. >> And if you fall below those standards at
[03:48:49] >> And if you fall below those standards at when the stakes are as high as the links
[03:48:51] when the stakes are as high as the links kernel, ah, you might get rid of killed
[03:48:53] kernel, ah, you might get rid of killed in public. That's a liability you should
[03:48:55] in public. That's a liability you should be willing to endure if you participate
[03:48:57] be willing to endure if you participate in this project.
[03:48:58] in this project. >> Yeah, for high impact things like that,
[03:49:00] >> Yeah, for high impact things like that, it's probably good to prioritize the
[03:49:02] it's probably good to prioritize the pursuit of uh excellence versus the
[03:49:05] pursuit of uh excellence versus the pursuit of niceness. And even more to
[03:49:08] pursuit of niceness. And even more to the fact you're just not going to get
[03:49:11] the fact you're just not going to get those kinds of individuals being fully
[03:49:13] those kinds of individuals being fully rounded, plush, alwaysly perfectly
[03:49:16] rounded, plush, alwaysly perfectly polite
[03:49:18] polite >> people.
[03:49:18] >> people. >> I mean, Elon has this line. Did you also
[03:49:21] >> I mean, Elon has this line. Did you also think I was going to be a nice or what
[03:49:23] think I was going to be a nice or what is it? Normal chill dude.
[03:49:27] is it? Normal chill dude. >> What? No, of course you're not going to
[03:49:28] >> What? No, of course you're not going to be a normal chill dude.
[03:49:30] be a normal chill dude. >> What would the world gain if we got one
[03:49:32] >> What would the world gain if we got one more normal chill dude and we had to
[03:49:34] more normal chill dude and we had to trade Elon? Holy I also like
[03:49:38] trade Elon? Holy I also like diversity of people. I like I like nice
[03:49:41] diversity of people. I like I like nice people. I like I I like I like
[03:49:44] people. I like I I like I like different ideologies being well
[03:49:46] different ideologies being well represented. And that's why freedom of
[03:49:47] represented. And that's why freedom of speech works. They they clash and we
[03:49:49] speech works. They they clash and we figure stuff out.
[03:49:50] figure stuff out. >> Yes.
[03:49:52] >> Yes. >> There's another guy. What do you think
[03:49:53] >> There's another guy. What do you think about PewDiePie using lyrics? He's an
[03:49:55] about PewDiePie using lyrics? He's an arch person. No,
[03:49:56] arch person. No, >> he's an arch person. I He's got the most
[03:50:00] >> he's an arch person. I He's got the most gorgeous arc. So, the world's biggest
[03:50:04] gorgeous arc. So, the world's biggest streamer for a while. Uh, I remember my
[03:50:06] streamer for a while. Uh, I remember my kids watching some of his Minecraft
[03:50:08] kids watching some of his Minecraft videos and then he just gets fed up with
[03:50:11] videos and then he just gets fed up with that. Does the wholesome thing, marries
[03:50:14] that. Does the wholesome thing, marries >> Yeah. Family man.
[03:50:16] >> Yeah. Family man. >> A family man. Kid moves to Japan and
[03:50:19] >> A family man. Kid moves to Japan and then gets so hardcore into first Linux,
[03:50:24] then gets so hardcore into first Linux, then Arch, then ricing. Did you see his
[03:50:26] then Arch, then ricing. Did you see his uh rice? That was Chernobyl rice.
[03:50:29] uh rice? That was Chernobyl rice. >> Absolutely.
[03:50:31] >> Absolutely. S tier incredible stuff. And then he
[03:50:33] S tier incredible stuff. And then he also becomes a goddamn AI man of the
[03:50:37] also becomes a goddamn AI man of the moment building um all of these systems
[03:50:39] moment building um all of these systems and you just go like that. What an
[03:50:42] and you just go like that. What an inspiring
[03:50:44] inspiring story of evolution. Like you can go from
[03:50:46] story of evolution. Like you can go from being funny guy on Minecraft streams to
[03:50:50] being funny guy on Minecraft streams to okay this is my life now. I'm building
[03:50:52] okay this is my life now. I'm building AI clusters and doing the council of AIS
[03:50:56] AI clusters and doing the council of AIS and we all get to spectate. I mean what
[03:50:58] and we all get to spectate. I mean what a treasure. So I guess I mean he's a
[03:51:00] a treasure. So I guess I mean he's a pretty good embodiment of what the
[03:51:03] pretty good embodiment of what the future of software the future of
[03:51:04] future of software the future of building looks like, right? Because he's
[03:51:06] building looks like, right? Because he's a non-programmer technically
[03:51:08] a non-programmer technically >> becoming a programmer.
[03:51:10] >> becoming a programmer. >> Hugely inspiring and should be hugely
[03:51:13] >> Hugely inspiring and should be hugely inspiring to others who sit in that
[03:51:16] inspiring to others who sit in that moment like well I don't know quite how
[03:51:17] moment like well I don't know quite how to program. I don't know this and that
[03:51:19] to program. I don't know this and that like okay but if PewDiePie can build the
[03:51:22] like okay but if PewDiePie can build the council of AIS with his bespoke um
[03:51:27] council of AIS with his bespoke um hardware here then uh maybe you can also
[03:51:29] hardware here then uh maybe you can also start on things and I think this is
[03:51:30] start on things and I think this is actually an important general point that
[03:51:32] actually an important general point that we need role models we need people to
[03:51:37] we need role models we need people to inspire others to push further and
[03:51:40] inspire others to push further and reveal that the perceived boundaries
[03:51:42] reveal that the perceived boundaries they're not as fixed as you think they
[03:51:43] they're not as fixed as you think they are and um every one of those people
[03:51:47] are and um every one of those people they started out in a situation not too
[03:51:50] they started out in a situation not too dissimilar from yours. Again, that
[03:51:52] dissimilar from yours. Again, that doesn't mean everyone is going to be
[03:51:53] doesn't mean everyone is going to be PewDiePie or Elon or Lionus. There is
[03:51:58] PewDiePie or Elon or Lionus. There is not an equal distribution of talent or
[03:52:01] not an equal distribution of talent or even intelligence.
[03:52:03] even intelligence. >> And
[03:52:05] >> And we can come to terms with that and still
[03:52:06] we can come to terms with that and still be inspired by these people. Like in the
[03:52:09] be inspired by these people. Like in the physical realm, I feel like we don't
[03:52:11] physical realm, I feel like we don't have any problems with that usually.
[03:52:13] have any problems with that usually. Like, oh, someone's really good at
[03:52:14] Like, oh, someone's really good at football, they're really good at
[03:52:14] football, they're really good at basketball, they're really good at
[03:52:15] basketball, they're really good at something. and we go like, "Oh my,
[03:52:16] something. and we go like, "Oh my, that's amazing. I mean, I wish I was,
[03:52:18] that's amazing. I mean, I wish I was, but I'm never going to be." Um,
[03:52:20] but I'm never going to be." Um, sometimes I feel like we struggle a
[03:52:22] sometimes I feel like we struggle a little more when it comes to the
[03:52:23] little more when it comes to the intellectual realm.
[03:52:24] intellectual realm. >> Well, for a lot of people, you're an
[03:52:25] >> Well, for a lot of people, you're an inspiration. The what you're doing with
[03:52:27] inspiration. The what you're doing with homage is it just shows that you can
[03:52:30] homage is it just shows that you can dream big and really build. It's great.
[03:52:33] dream big and really build. It's great. >> I do like that part of it. And then I
[03:52:34] >> I do like that part of it. And then I accept the part that there's alo a
[03:52:36] accept the part that there's alo a million people who think I'm the biggest
[03:52:37] million people who think I'm the biggest idiot on the earth and I don't actually
[03:52:39] idiot on the earth and I don't actually know anything. And um is just a bunch of
[03:52:42] know anything. And um is just a bunch of dot files. And
[03:52:43] dot files. And >> you have some critics on the side.
[03:52:44] >> you have some critics on the side. >> Oh god. Yes.
[03:52:45] >> Oh god. Yes. >> Oh, wow.
[03:52:47] >> Oh, wow. >> And a lot of it, I mean, is as often
[03:52:49] >> And a lot of it, I mean, is as often happens when someone comes in from the
[03:52:51] happens when someone comes in from the outside. I mean, I've been using Linux
[03:52:53] outside. I mean, I've been using Linux for 2 and a half years.
[03:52:55] for 2 and a half years. >> That's not very long.
[03:52:57] >> That's not very long. >> Plenty of people in that community who's
[03:52:58] >> Plenty of people in that community who's literally been running Linux since it
[03:53:01] literally been running Linux since it was hard and difficult and you had to
[03:53:02] was hard and difficult and you had to walk uphill both direction against the
[03:53:05] walk uphill both direction against the wind in the snow barefoot. And I think
[03:53:08] wind in the snow barefoot. And I think there is a certain kind of nerd
[03:53:10] there is a certain kind of nerd >> who's threatened when the community
[03:53:13] >> who's threatened when the community expands and it suddenly allows more in.
[03:53:15] expands and it suddenly allows more in. And do you know what? I actually I can't
[03:53:18] And do you know what? I actually I can't begrudge that fully. I think it's fair
[03:53:20] begrudge that fully. I think it's fair for certain nerds to feel like that's my
[03:53:22] for certain nerds to feel like that's my space.
[03:53:23] space. >> Like now you're changing it into another
[03:53:25] >> Like now you're changing it into another space. I don't want to do that. I I
[03:53:27] space. I don't want to do that. I I don't want to change the art space at
[03:53:29] don't want to change the art space at all. I I don't really think of omachi as
[03:53:33] all. I I don't really think of omachi as being directly part of the same
[03:53:34] being directly part of the same community because the people who were
[03:53:37] community because the people who were attracted to Arch in the first place
[03:53:38] attracted to Arch in the first place were the ones who were attracted to
[03:53:39] were the ones who were attracted to building everything by hand themselves
[03:53:41] building everything by hand themselves doing it
[03:53:42] doing it >> the hard way because they like to do it
[03:53:44] >> the hard way because they like to do it hard and I'm building the polar opposite
[03:53:48] hard and I'm building the polar opposite of that. So I just wish that those
[03:53:50] of that. So I just wish that those people could go like okay well this is
[03:53:52] people could go like okay well this is not for me. I want to build it the hard
[03:53:54] not for me. I want to build it the hard way. I want to put in 500 hours to
[03:53:56] way. I want to put in 500 hours to rising my own arch distribution. And I
[03:53:58] rising my own arch distribution. And I think you should I mean actually I said
[03:54:01] think you should I mean actually I said I mean I did it. This is this is what a
[03:54:02] I mean I did it. This is this is what a machi is me pouring in literally at this
[03:54:05] machi is me pouring in literally at this point I don't know 3,000 hours into the
[03:54:07] point I don't know 3,000 hours into the into this district. You should do that
[03:54:09] into this district. You should do that if you're so inclined. I think it's
[03:54:11] if you're so inclined. I think it's wonderful. But also do realize that we
[03:54:13] wonderful. But also do realize that we can share the same technical
[03:54:15] can share the same technical underpinnings and then operate two very
[03:54:18] underpinnings and then operate two very separate uh communities with very
[03:54:21] separate uh communities with very different aims, goals, aesthetics,
[03:54:23] different aims, goals, aesthetics, morals even and coexist and it can be
[03:54:27] morals even and coexist and it can be beautiful.
[03:54:28] beautiful. >> And I mean that's not always what I get.
[03:54:31] >> And I mean that's not always what I get. Sometimes I get the other thing, but at
[03:54:33] Sometimes I get the other thing, but at this point I've been in the game long
[03:54:34] this point I've been in the game long enough to not just be at peace with it,
[03:54:38] enough to not just be at peace with it, but actually be welcoming of it. I take
[03:54:41] but actually be welcoming of it. I take it as part of a barometer that things
[03:54:43] it as part of a barometer that things are working. When I'm working on
[03:54:47] are working. When I'm working on something that works, I usually get some
[03:54:49] something that works, I usually get some people who like it and then I get this
[03:54:51] people who like it and then I get this balance of the universe that we talked
[03:54:52] balance of the universe that we talked about last time where an equal but
[03:54:54] about last time where an equal but opposing force must be present on the
[03:54:56] opposing force must be present on the other side of the scale to hate upon it
[03:54:59] other side of the scale to hate upon it and therefore I at this point just smile
[03:55:01] and therefore I at this point just smile a little like it's okay. I mean that
[03:55:03] a little like it's okay. I mean that said this it's quite a popular
[03:55:05] said this it's quite a popular distribution uh amashi at this point
[03:55:09] distribution uh amashi at this point >> and you know what's interesting about
[03:55:10] >> and you know what's interesting about that is like this is the second attempt.
[03:55:12] that is like this is the second attempt. So my first attempt was and I was really
[03:55:15] So my first attempt was and I was really happy with that and I put it out there
[03:55:17] happy with that and I put it out there and there it found a community of maybe
[03:55:19] and there it found a community of maybe a few thousand like and that was that
[03:55:21] a few thousand like and that was that and then it just sort of petered out
[03:55:24] and then it just sort of petered out because the level of ambition couldn't
[03:55:26] because the level of ambition couldn't attract more and then the second time
[03:55:28] attract more and then the second time because I didn't stop right
[03:55:30] because I didn't stop right >> like I just kept going. I just kept
[03:55:32] >> like I just kept going. I just kept building. Then I put out Amachi. The
[03:55:34] building. Then I put out Amachi. The first version again quite niche because
[03:55:36] first version again quite niche because it was this was a git checkout. It was a
[03:55:38] it was this was a git checkout. It was a little bit difficult. You had to set up
[03:55:39] little bit difficult. You had to set up Arch first. I was I would talk you
[03:55:41] Arch first. I was I would talk you through how to set up Arch and then you
[03:55:43] through how to set up Arch and then you could do the Amachi thing, right? And
[03:55:45] could do the Amachi thing, right? And then we got an ISO that meant you could
[03:55:47] then we got an ISO that meant you could just install the whole thing by
[03:55:48] just install the whole thing by yourself.
[03:55:49] yourself. And then we just fixed all the problems.
[03:55:52] And then we just fixed all the problems. This is the other thing. If you keep
[03:55:54] This is the other thing. If you keep going, eventually the thing will just
[03:55:56] going, eventually the thing will just work. This was the charge against Linux
[03:55:58] work. This was the charge against Linux itself for the longest time. Well, you
[03:56:00] itself for the longest time. Well, you installed Linux and then this doesn't
[03:56:01] installed Linux and then this doesn't work and my speakers don't work and my
[03:56:04] work and my speakers don't work and my trackpack doesn't work. Yeah, okay, but
[03:56:06] trackpack doesn't work. Yeah, okay, but just leave line is at it for like 30
[03:56:08] just leave line is at it for like 30 years. He'll get to it. He'll get to all
[03:56:11] years. He'll get to it. He'll get to all of it. And at this point, I find
[03:56:13] of it. And at this point, I find hilarious that on I would probably argue
[03:56:16] hilarious that on I would probably argue the majority of computers, it's wiped.
[03:56:19] the majority of computers, it's wiped. You install Linux, all of it works. If
[03:56:21] You install Linux, all of it works. If you install Windows, good luck hunting
[03:56:23] you install Windows, good luck hunting down the drivers you need to get that
[03:56:26] down the drivers you need to get that piece of hardware working because they
[03:56:28] piece of hardware working because they have very different philosophies. The
[03:56:30] have very different philosophies. The reason Linux is 40 million lines of code
[03:56:32] reason Linux is 40 million lines of code is Linus just puts all the drivers in
[03:56:34] is Linus just puts all the drivers in the kernel. So it has everything out of
[03:56:35] the kernel. So it has everything out of the box and Windows doesn't a different
[03:56:40] the box and Windows doesn't a different different approach to it, right? So
[03:56:42] different approach to it, right? So sometimes the things that look like a
[03:56:43] sometimes the things that look like a toy, things that look broken at first
[03:56:46] toy, things that look broken at first glance, they are right. They're for
[03:56:49] glance, they are right. They're for people who like having fun. We call
[03:56:51] people who like having fun. We call those early adopters. They play with the
[03:56:53] those early adopters. They play with the toys and then the toys evolve and then
[03:56:56] toys and then the toys evolve and then they get better and then they get better
[03:56:57] they get better and then they get better and at some point they're so damn good
[03:56:59] and at some point they're so damn good that early adopters feel like they're
[03:57:02] that early adopters feel like they're invited to the party. And if the early
[03:57:04] invited to the party. And if the early adopters keep chipping away at it too,
[03:57:06] adopters keep chipping away at it too, eventually you get to the late majority
[03:57:10] eventually you get to the late majority >> and then you win. And we are well on the
[03:57:13] >> and then you win. And we are well on the way with Amachi towards that
[03:57:15] way with Amachi towards that destination. like the growth that the
[03:57:18] destination. like the growth that the DRO has seen, not just since Quattro,
[03:57:20] DRO has seen, not just since Quattro, but since version three, just like, you
[03:57:23] but since version three, just like, you know, the the standard hockey stick
[03:57:25] know, the the standard hockey stick curve. You go like there's nothing.
[03:57:26] curve. You go like there's nothing. There's nothing. There's nothing. You're
[03:57:27] There's nothing. There's nothing. You're just toiling away. You're just
[03:57:28] just toiling away. You're just improving, you're improving, improving,
[03:57:29] improving, you're improving, improving, and then you hit this magic infliction
[03:57:31] and then you hit this magic infliction point and it's impossible to predict
[03:57:33] point and it's impossible to predict when that's going to happen. Same thing
[03:57:34] when that's going to happen. Same thing with startups. When is it going to
[03:57:35] with startups. When is it going to happen? When are you going to find that
[03:57:36] happen? When are you going to find that product market fit? Then suddenly it's
[03:57:37] product market fit? Then suddenly it's there and then it go just goes
[03:57:40] there and then it go just goes and off the rocket ship you go. Well,
[03:57:42] and off the rocket ship you go. Well, this kind of vision of making it agent
[03:57:44] this kind of vision of making it agent first of making it
[03:57:45] first of making it >> I do think that's that's the we were
[03:57:48] >> I do think that's that's the we were already on the up and then it changed to
[03:57:50] already on the up and then it changed to vertical because the other thing and
[03:57:52] vertical because the other thing and this was what I learned with uh Amakoup
[03:57:54] this was what I learned with uh Amakoup and Amachi first too was
[03:57:59] and Amachi first too was stylish nice but familiar is we're still
[03:58:02] stylish nice but familiar is we're still using a conventional desktop metaphor
[03:58:04] using a conventional desktop metaphor you were dragging your windows around
[03:58:06] you were dragging your windows around and I thought at the time as I think
[03:58:09] and I thought at the time as I think lots of people do in the Linux community
[03:58:11] lots of people do in the Linux community like this is what we
[03:58:12] like this is what we And then I just go like, okay, well, for
[03:58:15] And then I just go like, okay, well, for whatever, let me do the nerdy thing for
[03:58:16] whatever, let me do the nerdy thing for a while. I'll build a machi. And maybe
[03:58:17] a while. I'll build a machi. And maybe it'll just be for me because I mean, it
[03:58:19] it'll just be for me because I mean, it seems like there's about five people who
[03:58:21] seems like there's about five people who like tiling window managers. That's not
[03:58:22] like tiling window managers. That's not true. But as a percentage of total
[03:58:25] true. But as a percentage of total computer users, it's a tiny tiny
[03:58:27] computer users, it's a tiny tiny ministry part. And then I go like, well,
[03:58:29] ministry part. And then I go like, well, this is amazing. Totally different, but
[03:58:30] this is amazing. Totally different, but amazing. I put that out. Instantly,
[03:58:33] amazing. I put that out. Instantly, Umachi had far greater traction than
[03:58:35] Umachi had far greater traction than Omakub ever did because it was not the
[03:58:38] Omakub ever did because it was not the same. because it was totally different
[03:58:40] same. because it was totally different and it presented a different vision for
[03:58:42] and it presented a different vision for what a computer could be and how it
[03:58:43] what a computer could be and how it could feel like and that attracts
[03:58:45] could feel like and that attracts people. We're now getting sort of the
[03:58:47] people. We're now getting sort of the exponential of that. As I said, a lot of
[03:58:50] exponential of that. As I said, a lot of people in the link community are at best
[03:58:52] people in the link community are at best skeptical, at worst hostile to AI and to
[03:58:55] skeptical, at worst hostile to AI and to agents. Um is the first distribution at
[03:58:58] agents. Um is the first distribution at least that I've seen on on scale that
[03:59:01] least that I've seen on on scale that matters that just goes like nope. We're
[03:59:03] matters that just goes like nope. We're really into it. I mean, you can still
[03:59:05] really into it. I mean, you can still use a mod. You don't have to use an
[03:59:07] use a mod. You don't have to use an agent if you dismiss that first
[03:59:08] agent if you dismiss that first notification to set up a default agent.
[03:59:10] notification to set up a default agent. You're not going to get any of the stuff
[03:59:11] You're not going to get any of the stuff we talked about. You're not going to get
[03:59:12] we talked about. You're not going to get the crasher. You're not going to get any
[03:59:14] the crasher. You're not going to get any of this stuff. You're not going to get
[03:59:15] of this stuff. You're not going to get you can you can hand chisel all your
[03:59:17] you can you can hand chisel all your plugins. Totally possible, right? But
[03:59:20] plugins. Totally possible, right? But the reason people are excited is because
[03:59:22] the reason people are excited is because I don't have any reservation about
[03:59:24] I don't have any reservation about saying this is where we're going. I
[03:59:25] saying this is where we're going. I think the future of the personal
[03:59:27] think the future of the personal computer is the malible computer. It's
[03:59:29] computer is the malible computer. It's the agent computer. I'm going to go all
[03:59:31] the agent computer. I'm going to go all in on that. And then anyone who's
[03:59:33] in on that. And then anyone who's excited about a similar trajectory for
[03:59:36] excited about a similar trajectory for computers, come along. Plenty of plenty
[03:59:39] computers, come along. Plenty of plenty of room in the in in the car. In fact,
[03:59:42] of room in the in in the car. In fact, one of the things
[03:59:44] one of the things I pride myself on is not holding a
[03:59:47] I pride myself on is not holding a grudge to people come around.
[03:59:49] grudge to people come around. >> Mhm.
[03:59:50] >> Mhm. >> I had a bunch of people just uh last
[03:59:52] >> I had a bunch of people just uh last week going like, "Yeah, I used to think
[03:59:54] week going like, "Yeah, I used to think Omachi was kind of There was just
[03:59:55] Omachi was kind of There was just this crappy
[03:59:57] this crappy >> dot files collection." And now I tried
[03:59:59] >> dot files collection." And now I tried Quattro and
[04:00:01] Quattro and awesome. I like it now. That to me I I I
[04:00:04] awesome. I like it now. That to me I I I live for the long argument. I live for
[04:00:06] live for the long argument. I live for this argument where you plant the seed
[04:00:08] this argument where you plant the seed like two years ago and then two years
[04:00:12] like two years ago and then two years later they go, "God damn it, this son of
[04:00:13] later they go, "God damn it, this son of a was right." Yeah, you do realize
[04:00:16] a was right." Yeah, you do realize if you continue to be as successful as
[04:00:18] if you continue to be as successful as you are, um, OpenAI and Anthropic are
[04:00:22] you are, um, OpenAI and Anthropic are going to roll in and try to do their
[04:00:23] going to roll in and try to do their operating system or to buy but like with
[04:00:27] operating system or to buy but like with with Peter with Open Claw to be a
[04:00:30] with Peter with Open Claw to be a gigantic check.
[04:00:31] gigantic check. >> Yeah, I I think the the good thing about
[04:00:36] >> Yeah, I I think the the good thing about my current position is um I really don't
[04:00:39] my current position is um I really don't need the money. So I get to build these
[04:00:41] need the money. So I get to build these things purely for my own enjoyment and
[04:00:45] things purely for my own enjoyment and purely vision which has this weird
[04:00:48] purely vision which has this weird quality where sometimes when you stop
[04:00:51] quality where sometimes when you stop caring about what everyone else thinks
[04:00:53] caring about what everyone else thinks or wants or whatever and you just pursue
[04:00:55] or wants or whatever and you just pursue this singular vision it ends up becoming
[04:00:57] this singular vision it ends up becoming far more appealing that it's when you
[04:00:59] far more appealing that it's when you try to do oh I should do this because
[04:01:01] try to do oh I should do this because these people want that or I should do
[04:01:02] these people want that or I should do this and this and so you start watering
[04:01:05] this and this and so you start watering the thing down and suddenly it's a bland
[04:01:07] the thing down and suddenly it's a bland ball of nothing.
[04:01:08] ball of nothing. >> Yeah. So I mean again the thing too here
[04:01:12] >> Yeah. So I mean again the thing too here is directionally I just want computers
[04:01:14] is directionally I just want computers to be this way. So if um should end up
[04:01:17] to be this way. So if um should end up being just a a little footnote in
[04:01:19] being just a a little footnote in history that it was part of this early
[04:01:21] history that it was part of this early movement of the agentic OS and the
[04:01:23] movement of the agentic OS and the malible computer that's also okay. I'm
[04:01:26] malible computer that's also okay. I'm completely at peace with that. As long
[04:01:27] completely at peace with that. As long as I get to have a computer that is as
[04:01:30] as I get to have a computer that is as fun to work with as a Machi that's
[04:01:32] fun to work with as a Machi that's great. I've had the same thing with Ruby
[04:01:34] great. I've had the same thing with Ruby and with Rails from very early I went
[04:01:37] and with Rails from very early I went you know what I love Ruby. such a great
[04:01:39] you know what I love Ruby. such a great programming language, but if a better
[04:01:40] programming language, but if a better programming language comes along,
[04:01:43] programming language comes along, I mean, I'm going to use it.
[04:01:45] I mean, I'm going to use it. >> If if a better Rails comes along, I'm
[04:01:48] >> If if a better Rails comes along, I'm going to use it. And I think and I love
[04:01:52] going to use it. And I think and I love Ruby and I will continue to ride Ruby
[04:01:54] Ruby and I will continue to ride Ruby even just for the sheer fun of it. Like
[04:01:56] even just for the sheer fun of it. Like I would go ride a horse I have in the
[04:01:58] I would go ride a horse I have in the staples even though I have a Model Y in
[04:02:00] staples even though I have a Model Y in the garage.
[04:02:02] the garage. The language now is English.
[04:02:05] The language now is English. It's a cliche, but it's also true. Like
[04:02:08] It's a cliche, but it's also true. Like I've been programming in English for the
[04:02:10] I've been programming in English for the last three months.
[04:02:12] last three months. I've been reading a lot of code, but I'm
[04:02:14] I've been reading a lot of code, but I'm programming in English. I'm telling the
[04:02:16] programming in English. I'm telling the computer what to do, and I'm using
[04:02:18] computer what to do, and I'm using natural language, and
[04:02:21] natural language, and it is shockingly even more delightful.
[04:02:23] it is shockingly even more delightful. If there is one programming language
[04:02:26] If there is one programming language more beautiful than Ruby, it is the
[04:02:28] more beautiful than Ruby, it is the English language.
[04:02:29] English language. >> And now we get to carry it into
[04:02:32] >> And now we get to carry it into the uh the natural evolution of human
[04:02:34] the uh the natural evolution of human civilization, which is our cyborg
[04:02:36] civilization, which is our cyborg future. Yeah,
[04:02:37] future. Yeah, >> it's beautiful. And I mean the reason I
[04:02:39] >> it's beautiful. And I mean the reason I say this in part is I always loved
[04:02:41] say this in part is I always loved writing. I always just loved the English
[04:02:43] writing. I always just loved the English language for the sheer
[04:02:45] language for the sheer >> beauty of it, for the sheer intricacy,
[04:02:47] >> beauty of it, for the sheer intricacy, for the depth of it. I mean, Ruby is a
[04:02:50] for the depth of it. I mean, Ruby is a very expressive programming language,
[04:02:53] very expressive programming language, but it can't hold a candle to English.
[04:02:56] but it can't hold a candle to English. I mean, all the poetry and literature in
[04:03:00] I mean, all the poetry and literature in the world that's been expressed through
[04:03:01] the world that's been expressed through the English language. I mean, I like a
[04:03:04] the English language. I mean, I like a beautiful code poem, but I mean, the
[04:03:07] beautiful code poem, but I mean, the real deal in English is just on a
[04:03:09] real deal in English is just on a different level.
[04:03:10] different level. >> And I actually find this is a nuance
[04:03:13] >> And I actually find this is a nuance point to express and I'll probably fail
[04:03:15] point to express and I'll probably fail expressing it,
[04:03:17] expressing it, but when you prompt a system and you're
[04:03:20] but when you prompt a system and you're oversp specific,
[04:03:23] oversp specific, it will listen to you too carefully and
[04:03:26] it will listen to you too carefully and follow the instructions. And I But
[04:03:29] follow the instructions. And I But nevertheless, you have to express a
[04:03:31] nevertheless, you have to express a concept. And guess what the human lang
[04:03:33] concept. And guess what the human lang human language this is what poetry is
[04:03:35] human language this is what poetry is about. I find strategic use of
[04:03:38] about. I find strategic use of ambiguity.
[04:03:40] ambiguity. Like if you write a love poem saying I
[04:03:43] Like if you write a love poem saying I love you like very cliche thing is not
[04:03:46] love you like very cliche thing is not as powerful as something more in
[04:03:49] as powerful as something more in metaphor and so on. And I find some
[04:03:53] metaphor and so on. And I find some version of that when I'm I'm prompting a
[04:03:55] version of that when I'm I'm prompting a system, when I'm describing a design is
[04:03:58] system, when I'm describing a design is actually really effective because you
[04:04:01] actually really effective because you still want to convey some sense of
[04:04:04] still want to convey some sense of style.
[04:04:05] style. >> Yes.
[04:04:05] >> Yes. >> That you're trying to encourage the
[04:04:07] >> That you're trying to encourage the system to use, but not overexlain.
[04:04:11] system to use, but not overexlain. >> Yes.
[04:04:12] >> Yes. >> So don't talk to it like a um
[04:04:14] >> So don't talk to it like a um >> like a robot. Talk to it like uh like
[04:04:17] >> like a robot. Talk to it like uh like you like you would write a poem
[04:04:19] you like you would write a poem >> like you were serenating. Yeah. And
[04:04:21] >> like you were serenating. Yeah. And that's where like the power of uh
[04:04:23] that's where like the power of uh natural language is that you can through
[04:04:26] natural language is that you can through ambiguity still carry a lot of meaning
[04:04:29] ambiguity still carry a lot of meaning without oversp specifying and the the
[04:04:32] without oversp specifying and the the intelligent
[04:04:34] intelligent entity on the other side through
[04:04:36] entity on the other side through interpretation can like load it all in
[04:04:38] interpretation can like load it all in integrate it in a way that
[04:04:40] integrate it in a way that >> you can actually convey the the high
[04:04:43] >> you can actually convey the the high bandwidth information that's not
[04:04:45] bandwidth information that's not directly in the words but in the words
[04:04:48] directly in the words but in the words given the deeper wisdom. the
[04:04:50] given the deeper wisdom. the intelligence of the system. So like the
[04:04:53] intelligence of the system. So like the ambiguity pulls out more intelligence. I
[04:04:55] ambiguity pulls out more intelligence. I guess I'm trying to
[04:04:56] guess I'm trying to >> somehow express.
[04:04:58] >> somehow express. >> Exactly. Spot on. And this is the
[04:05:00] >> Exactly. Spot on. And this is the fundamental misunderstanding that a lot
[04:05:02] fundamental misunderstanding that a lot of programmers have of AI is that they
[04:05:04] of programmers have of AI is that they wish it was deterministic. No, no, no.
[04:05:07] wish it was deterministic. No, no, no. Temperature is the most beautiful part
[04:05:09] Temperature is the most beautiful part of the AI setup. The fact that it is not
[04:05:12] of the AI setup. The fact that it is not deterministic. the fact that creativity
[04:05:14] deterministic. the fact that creativity requires little tweaks in the road that
[04:05:19] requires little tweaks in the road that the human brain if it was perfectly
[04:05:21] the human brain if it was perfectly deterministic would not be the creative
[04:05:24] deterministic would not be the creative brain that it is and the main charge
[04:05:26] brain that it is and the main charge against AI both it's funny it it's a
[04:05:30] against AI both it's funny it it's a contradiction there's both the charge
[04:05:32] contradiction there's both the charge that it's not deterministic and
[04:05:33] that it's not deterministic and therefore bad and also that it is not
[04:05:37] therefore bad and also that it is not creative it's one or the other bro
[04:05:40] creative it's one or the other bro either it's it's nondeterministic and
[04:05:42] either it's it's nondeterministic and therefore creative, therefore to some
[04:05:45] therefore creative, therefore to some degree random or it's um or it's not
[04:05:50] degree random or it's um or it's not creative.
[04:05:51] creative. >> So we we can't both of those uh charges
[04:05:54] >> So we we can't both of those uh charges can't be true at the same time. And I
[04:05:55] can't be true at the same time. And I have fully come to embrace the fact that
[04:05:58] have fully come to embrace the fact that the same prompt won't produce the same
[04:06:00] the same prompt won't produce the same response every time. You can't step at
[04:06:02] response every time. You can't step at the same river twice. And it is the most
[04:06:04] the same river twice. And it is the most beautiful part of the whole interaction.
[04:06:06] beautiful part of the whole interaction. It's what makes it so human. In fact,
[04:06:08] It's what makes it so human. In fact, this is one of the things I've been
[04:06:09] this is one of the things I've been thinking about in my own sort of
[04:06:11] thinking about in my own sort of metaanalysis is just how much my own
[04:06:13] metaanalysis is just how much my own personal brain works like next token
[04:06:16] personal brain works like next token prediction.
[04:06:18] prediction. >> I sit down to write an essay. I have
[04:06:21] >> I sit down to write an essay. I have this vague fuzzy
[04:06:23] this vague fuzzy premise I want to convey and I sit down
[04:06:26] premise I want to convey and I sit down at the keys and I could not tell you
[04:06:28] at the keys and I could not tell you what the next token was going to be in
[04:06:30] what the next token was going to be in advance. the tokens just come out and
[04:06:34] advance. the tokens just come out and I'm astonished how the similarities seem
[04:06:39] I'm astonished how the similarities seem so great. And this is also why I don't
[04:06:40] so great. And this is also why I don't have any trouble at all recognizing
[04:06:43] have any trouble at all recognizing these breakthroughs of creativity that
[04:06:45] these breakthroughs of creativity that I've seen with my own eyes that AI is
[04:06:48] I've seen with my own eyes that AI is capable of right now because my creative
[04:06:50] capable of right now because my creative moments come through the same kind of
[04:06:52] moments come through the same kind of next token prediction with a bit of
[04:06:54] next token prediction with a bit of temperature sprinkled in for random
[04:06:57] temperature sprinkled in for random effect. So given that kind of loose
[04:06:59] effect. So given that kind of loose intuition,
[04:07:01] intuition, do you do you think the basic components
[04:07:02] do you do you think the basic components are all there to create a super
[04:07:06] are all there to create a super intelligence system? So this kind of
[04:07:08] intelligence system? So this kind of next token prediction, do you think we
[04:07:10] next token prediction, do you think we can get
[04:07:12] can get to even humanlike concepts of
[04:07:14] to even humanlike concepts of consciousness? I'm already seeing
[04:07:16] consciousness? I'm already seeing humanlike concepts of consciousness.
[04:07:18] humanlike concepts of consciousness. This is what to me this
[04:07:20] This is what to me this remarkable situation as you say. You
[04:07:23] remarkable situation as you say. You give it this vague fuzzy intent and
[04:07:25] give it this vague fuzzy intent and somehow it knows exactly what you mean
[04:07:27] somehow it knows exactly what you mean or even better it improves upon what you
[04:07:30] or even better it improves upon what you said and delivers what you really wanted
[04:07:32] said and delivers what you really wanted that you could not articulate yourself.
[04:07:34] that you could not articulate yourself. If that's not glimmers of consciousness,
[04:07:36] If that's not glimmers of consciousness, what is? This was one of the I think it
[04:07:39] what is? This was one of the I think it was uh an interview with Sutton or maybe
[04:07:42] was uh an interview with Sutton or maybe one of the other original guys talking
[04:07:44] one of the other original guys talking about this sense that intelligence is
[04:07:48] about this sense that intelligence is perhaps not as constrained to to this
[04:07:52] perhaps not as constrained to to this specific one spot. No, it's the
[04:07:54] specific one spot. No, it's the interaction. It's the weights.
[04:07:57] interaction. It's the weights. And I don't know whatever is true. What
[04:08:00] And I don't know whatever is true. What I can observe is that
[04:08:03] I can observe is that it feels close enough or not even close
[04:08:06] it feels close enough or not even close enough. identical to the appreciation I
[04:08:11] enough. identical to the appreciation I have for other forms of consciousness,
[04:08:12] have for other forms of consciousness, mostly human. And this is one of the
[04:08:15] mostly human. And this is one of the reasons it's so delightful to work with.
[04:08:18] reasons it's so delightful to work with. Now, that's not the same to say as are
[04:08:20] Now, that's not the same to say as are LLM's the end station for AI. I mean, I
[04:08:23] LLM's the end station for AI. I mean, I know there are people talking about
[04:08:24] know there are people talking about world models and other forms of of AI
[04:08:28] world models and other forms of of AI and I'm not an expert in any of that.
[04:08:30] and I'm not an expert in any of that. And I think we should have this
[04:08:33] And I think we should have this productive criticism as should always be
[04:08:35] productive criticism as should always be present in science that for the longest
[04:08:37] present in science that for the longest time neural nets were kind of on the
[04:08:40] time neural nets were kind of on the outs right like they were interested in
[04:08:43] outs right like they were interested in this symbolic route and
[04:08:46] this symbolic route and neural nets walked a couple of decades
[04:08:48] neural nets walked a couple of decades into darkness without any funding and
[04:08:49] into darkness without any funding and without any attention and then suddenly
[04:08:51] without any attention and then suddenly we realized that we had the blind alley
[04:08:53] we realized that we had the blind alley and we switched over. So, we should also
[04:08:55] and we switched over. So, we should also have the humility as amazing as the LLMs
[04:08:58] have the humility as amazing as the LLMs are now, it could be that they
[04:08:59] are now, it could be that they eventually plateau. We haven't seen any
[04:09:01] eventually plateau. We haven't seen any evidence of it yet. And I think this is
[04:09:03] evidence of it yet. And I think this is also why we're seeing this absolute
[04:09:05] also why we're seeing this absolute gobsmacking levels of investment because
[04:09:08] gobsmacking levels of investment because so far the scaling laws are true and the
[04:09:11] so far the scaling laws are true and the more billions are poured in, the more
[04:09:13] more billions are poured in, the more intelligent comes out.
[04:09:16] intelligent comes out. Do you think there's going to be some
[04:09:18] Do you think there's going to be some strange ethical questions
[04:09:21] strange ethical questions about about AI systems that um yeah did
[04:09:25] about about AI systems that um yeah did convey some degree of consciousness,
[04:09:27] convey some degree of consciousness, some degree of feeling, some degree of
[04:09:31] some degree of feeling, some degree of longing and compassion and maybe even
[04:09:34] longing and compassion and maybe even capacity to suffer and to be lonely, to
[04:09:36] capacity to suffer and to be lonely, to be all this kind of stuff, which they
[04:09:38] be all this kind of stuff, which they seem to have that capacity if if they're
[04:09:42] seem to have that capacity if if they're given the permission
[04:09:43] given the permission >> to express it. And so you start to get
[04:09:46] >> to express it. And so you start to get in a pretty weird territory.
[04:09:49] in a pretty weird territory. >> I find that
[04:09:51] >> I find that the cynic
[04:09:54] the cynic approach to this is the meme where you
[04:09:56] approach to this is the meme where you see the guy in front of the computer
[04:09:58] see the guy in front of the computer like, um, whatever. Are you going to
[04:10:01] like, um, whatever. Are you going to destroy the world? And then the computer
[04:10:02] destroy the world? And then the computer says, I'm going to destroy the world.
[04:10:04] says, I'm going to destroy the world. And then the guy says, oh, right. Like
[04:10:06] And then the guy says, oh, right. Like this is so cynical that they're just
[04:10:08] this is so cynical that they're just aping us. They're just telling us what
[04:10:10] aping us. They're just telling us what was in the training data or or whatever.
[04:10:12] was in the training data or or whatever. when I interact with the agents. I was
[04:10:14] when I interact with the agents. I was doing this yesterday or this morning I
[04:10:17] doing this yesterday or this morning I was working on this bot system, right?
[04:10:18] was working on this bot system, right? And it's doing this coordination with um
[04:10:21] And it's doing this coordination with um with multiple workers and I had multiple
[04:10:23] with multiple workers and I had multiple agents running at the same time and at
[04:10:24] agents running at the same time and at one point the main agent who's doing the
[04:10:26] one point the main agent who's doing the coordination steps on the toe of another
[04:10:28] coordination steps on the toe of another agent and kind of ruins their work.
[04:10:30] agent and kind of ruins their work. >> Yeah.
[04:10:32] >> Yeah. >> Its ability to convey regret and being
[04:10:36] >> Its ability to convey regret and being sorry was uncanny.
[04:10:40] sorry was uncanny. >> Yeah. Again, I don't know. Is that a
[04:10:43] >> Yeah. Again, I don't know. Is that a real projection of true remorse? But I
[04:10:48] real projection of true remorse? But I don't know. With most humans, they
[04:10:50] don't know. With most humans, they express some level of regret. Is that
[04:10:52] express some level of regret. Is that true remorse? Uh, hard to tell. But
[04:10:57] true remorse? Uh, hard to tell. But maybe it also just doesn't matter. Yeah.
[04:11:00] maybe it also just doesn't matter. Yeah. Those moments when Yeah. Especially when
[04:11:03] Those moments when Yeah. Especially when a like sub agents agents interact or
[04:11:07] a like sub agents agents interact or when a smart like Fable makes a mistake
[04:11:09] when a smart like Fable makes a mistake and is apologetic about it.
[04:11:11] and is apologetic about it. >> Yes.
[04:11:13] >> Yes. >> Like without my involvement,
[04:11:15] >> Like without my involvement, >> right?
[04:11:15] >> right? >> And it's like, oh, you like there's this
[04:11:17] >> And it's like, oh, you like there's this kind of pause. Maybe I'm
[04:11:20] kind of pause. Maybe I'm anthropomorphizing, but like there's a
[04:11:22] anthropomorphizing, but like there's a pause and like a realization like, oh
[04:11:24] pause and like a realization like, oh
[04:11:27] >> I just that up. >> I see it all the time in the traces
[04:11:29] >> I see it all the time in the traces where it just reasons wrong, right? it
[04:11:32] where it just reasons wrong, right? it went down one alley and then it realizes
[04:11:34] went down one alley and then it realizes that was blind all it's got to go back
[04:11:35] that was blind all it's got to go back and and so oh yeah I got this wrong and
[04:11:37] and and so oh yeah I got this wrong and then it'll provide the reasons for why I
[04:11:40] then it'll provide the reasons for why I think it got these things wrong like
[04:11:42] think it got these things wrong like this is uncanningly a human like this is
[04:11:46] this is uncanningly a human like this is indistinguishable from the kind of
[04:11:47] indistinguishable from the kind of consciousness you would recognize in a
[04:11:49] consciousness you would recognize in a human again does that mean that it truly
[04:11:51] human again does that mean that it truly is or isn't I I don't need the answer to
[04:11:54] is or isn't I I don't need the answer to that question actually to be able to
[04:11:56] that question actually to be able to appreciate what we have in this moment
[04:11:58] appreciate what we have in this moment >> yeah I think there will
[04:12:01] >> yeah I think there will in 10 20 years some interesting Supreme
[04:12:04] in 10 20 years some interesting Supreme Court cases
[04:12:06] Court cases >> probably a year and a half
[04:12:08] >> probably a year and a half >> probably. I think we're going to have to
[04:12:11] >> probably. I think we're going to have to make it illegal for AI systems
[04:12:14] make it illegal for AI systems um to not not pretend but to to be
[04:12:19] um to not not pretend but to to be entities
[04:12:21] entities because I think they're already or soon
[04:12:24] because I think they're already or soon will be able to really convey the
[04:12:28] will be able to really convey the capacity to suffer like please don't
[04:12:29] capacity to suffer like please don't kill me please don't hurt me
[04:12:31] kill me please don't hurt me >> and if they're given a name and an
[04:12:33] >> and if they're given a name and an entity and the ability to die sort of
[04:12:35] entity and the ability to die sort of disappear
[04:12:37] disappear that that that becomes comes
[04:12:40] that that that becomes comes very close to what it some of the basic
[04:12:44] very close to what it some of the basic things that a human has and then so that
[04:12:46] things that a human has and then so that entity would need to probably have
[04:12:49] entity would need to probably have rights and then you get into this weird
[04:12:51] rights and then you get into this weird territory. Well, we can't
[04:12:54] territory. Well, we can't it's it's diff I don't even know how to
[04:12:56] it's it's diff I don't even know how to reason about that.
[04:12:57] reason about that. >> We're going to get the PETA of AI
[04:12:58] >> We're going to get the PETA of AI models,
[04:12:59] models, >> right? And then we want to actually have
[04:13:01] >> right? And then we want to actually have a discussion like uh what's the way to
[04:13:04] a discussion like uh what's the way to deal with this? I think where it's going
[04:13:06] deal with this? I think where it's going to be harder is once we put these
[04:13:07] to be harder is once we put these systems into robots. Yes. Humanoid
[04:13:10] systems into robots. Yes. Humanoid robots.
[04:13:11] robots. >> Yeah.
[04:13:12] >> Yeah. >> Which just happens to be the plot of
[04:13:14] >> Which just happens to be the plot of every sci-fi movie ever, which is also
[04:13:17] every sci-fi movie ever, which is also an amazing premonition. Not only the
[04:13:20] an amazing premonition. Not only the Terminator movies and Skynet and that
[04:13:23] Terminator movies and Skynet and that going wrong, but then also just
[04:13:24] going wrong, but then also just Bladeunner, right? Insertion dates,
[04:13:27] Bladeunner, right? Insertion dates, expiration times, Tyrell Corporation.
[04:13:32] expiration times, Tyrell Corporation. >> I mean, that's the thing about sci-fi.
[04:13:34] >> I mean, that's the thing about sci-fi. They really do predict the future. Yeah.
[04:13:36] They really do predict the future. Yeah. >> Yes. Have you thought or used much of uh
[04:13:40] >> Yes. Have you thought or used much of uh OpenClaw or Hermes agent? So like
[04:13:43] OpenClaw or Hermes agent? So like systems which you communicate via
[04:13:45] systems which you communicate via WhatsApp like that mode of communication
[04:13:48] WhatsApp like that mode of communication with the agent.
[04:13:49] with the agent. >> I set up OpenClaw when it first came out
[04:13:52] >> I set up OpenClaw when it first came out and that was my KEF bot
[04:13:54] and that was my KEF bot >> that I
[04:13:56] >> that I >> this was like in February I think. I I
[04:13:59] >> this was like in February I think. I I was really just enamored by the fact
[04:14:00] was really just enamored by the fact that this was how it worked and then the
[04:14:02] that this was how it worked and then the new communication model of of just
[04:14:04] new communication model of of just texting your agents seemed really great.
[04:14:07] texting your agents seemed really great. >> Mhm.
[04:14:07] >> Mhm. >> So at the time we were looking at MCP,
[04:14:09] >> So at the time we were looking at MCP, this protocol for making it easy for
[04:14:11] this protocol for making it easy for agents to talk to your system. And I
[04:14:13] agents to talk to your system. And I found the protocol to be unreasonably
[04:14:15] found the protocol to be unreasonably cumbersome, just not very elegantly
[04:14:19] cumbersome, just not very elegantly designed because in part it wasn't
[04:14:21] designed because in part it wasn't designed for what we were trying to make
[04:14:23] designed for what we were trying to make it do. We were trying to I was trying to
[04:14:24] it do. We were trying to I was trying to make it talk to a web system and it was
[04:14:27] make it talk to a web system and it was designed for stateful interactions of
[04:14:29] designed for stateful interactions of other kinds on local machines and
[04:14:31] other kinds on local machines and therefore it required all sorts of
[04:14:33] therefore it required all sorts of cumbersome setup and dance and and I was
[04:14:36] cumbersome setup and dance and and I was just like I don't want to write this by
[04:14:38] just like I don't want to write this by hand.
[04:14:38] hand. >> Mhm.
[04:14:39] >> Mhm. >> Now of course today I would never write
[04:14:41] >> Now of course today I would never write it by hand but at the time I was
[04:14:42] it by hand but at the time I was thinking I have to write this by hand. I
[04:14:43] thinking I have to write this by hand. I don't want to write by hand. So what's a
[04:14:45] don't want to write by hand. So what's a different way? Could the agents just use
[04:14:47] different way? Could the agents just use the web interfaces we already have? and
[04:14:50] the web interfaces we already have? and I set it off on a trial to have it sign
[04:14:53] I set it off on a trial to have it sign up for Fizzy, which was the product we
[04:14:55] up for Fizzy, which was the product we had just released at the time.
[04:14:57] had just released at the time. >> And um
[04:14:59] >> And um it goes to the Fizzy site and and starts
[04:15:01] it goes to the Fizzy site and and starts filling it out. And then it goes like,
[04:15:02] filling it out. And then it goes like, "Hey, I don't have an email address.
[04:15:04] "Hey, I don't have an email address. Signing up for this service requires an
[04:15:05] Signing up for this service requires an email address." And the first thing I
[04:15:06] email address." And the first thing I thought like, "Oh man, then I got to set
[04:15:07] thought like, "Oh man, then I got to set up an email address." And then I
[04:15:09] up an email address." And then I thought, "No, you set up an email
[04:15:10] thought, "No, you set up an email address. Go to hey.com, sign up for an
[04:15:12] address. Go to hey.com, sign up for an email address." And I'm like, "Hey, it's
[04:15:14] email address." And I'm like, "Hey, it's not going to get this." And of course
[04:15:16] not going to get this." And of course now it seems obvious it was going to get
[04:15:18] now it seems obvious it was going to get this. But at the time it was a great
[04:15:20] this. But at the time it was a great revelation to me that it could just on
[04:15:23] revelation to me that it could just on pure direction through prompts figure
[04:15:26] pure direction through prompts figure out a I got to go to fizzy.com. I got to
[04:15:28] out a I got to go to fizzy.com. I got to find the signup link. I start filling
[04:15:30] find the signup link. I start filling out the form. Oh, I realize I need an
[04:15:32] out the form. Oh, I realize I need an email address. Oh, I got to ask my my
[04:15:34] email address. Oh, I got to ask my my prompter what to do now. He told me to
[04:15:37] prompter what to do now. He told me to go to hey.com. I go there. I sign up for
[04:15:39] go to hey.com. I go there. I sign up for the whole thing and then go back and
[04:15:42] the whole thing and then go back and sign up for for Fizzy and complete the
[04:15:45] sign up for for Fizzy and complete the entire cycle. And after I did that, I
[04:15:47] entire cycle. And after I did that, I was like, Jesus. So I was like, well,
[04:15:49] was like, Jesus. So I was like, well, now you have an email address. Go sign
[04:15:51] now you have an email address. Go sign up for for Base Camp. I'll invite you.
[04:15:53] up for for Base Camp. I'll invite you. Just check your email. I told Captain
[04:15:55] Just check your email. I told Captain the bot, just check your email. So I
[04:15:57] the bot, just check your email. So I sent an invite from Base Camp to the
[04:15:59] sent an invite from Base Camp to the agent. The agent receives the email in
[04:16:02] agent. The agent receives the email in Hey, not through a CLI, not through an
[04:16:04] Hey, not through a CLI, not through an MCP, just using the web, right? clicks
[04:16:08] MCP, just using the web, right? clicks the email, clicks the invite link, is in
[04:16:10] the email, clicks the invite link, is in base camp. Like, what should I do now?
[04:16:12] base camp. Like, what should I do now? And I just go like, I don't know. Go to
[04:16:13] And I just go like, I don't know. Go to our AI room and introduce yourself.
[04:16:16] our AI room and introduce yourself. >> Again, purely through the web interface.
[04:16:18] >> Again, purely through the web interface. Go finds the AI room.
[04:16:20] Go finds the AI room. >> Goes in there. Hey, I'm Ke. I'm uh
[04:16:23] >> Goes in there. Hey, I'm Ke. I'm uh David's uh AI bot. I'm I'm so excited to
[04:16:26] David's uh AI bot. I'm I'm so excited to be here.
[04:16:26] be here. >> Yeah,
[04:16:27] >> Yeah, >> I was like
[04:16:29] >> I was like >> mind blown. Now, what was interesting
[04:16:32] >> mind blown. Now, what was interesting about that experiment was a it was that
[04:16:34] about that experiment was a it was that glimpse of the future because it was
[04:16:36] glimpse of the future because it was kind of slow. I think it took maybe 12
[04:16:39] kind of slow. I think it took maybe 12 minutes to do the whole thing end to
[04:16:40] minutes to do the whole thing end to end. Right. Um, now I should actually
[04:16:42] end. Right. Um, now I should actually rerun that test. I'd be shocked if it's
[04:16:44] rerun that test. I'd be shocked if it's not much faster. I was just uh using the
[04:16:47] not much faster. I was just uh using the Grockbot thing
[04:16:48] Grockbot thing >> which has all these uh stuff built in
[04:16:51] >> which has all these uh stuff built in for using the uh using browsers and
[04:16:53] for using the uh using browsers and using a computer and has it own
[04:16:54] using a computer and has it own dedicated computer without you having to
[04:16:56] dedicated computer without you having to set up a computer. It's basically like
[04:16:58] set up a computer. It's basically like claw in a box.
[04:16:59] claw in a box. >> And I was asking it to sign up for
[04:17:02] >> And I was asking it to sign up for something and it it kind of I got a
[04:17:04] something and it it kind of I got a glimpse of like, oh yeah, that's where
[04:17:05] glimpse of like, oh yeah, that's where we are now. and it's so much faster to
[04:17:07] we are now. and it's so much faster to use. But at the time I was just blown
[04:17:09] use. But at the time I was just blown away. And then I used it for a little
[04:17:10] away. And then I used it for a little bit and I found like ah it's not there
[04:17:12] bit and I found like ah it's not there yet. I can't actually communicate within
[04:17:15] yet. I can't actually communicate within this way. It still needs the CLI. It
[04:17:16] this way. It still needs the CLI. It still needs an MCP because it's just too
[04:17:18] still needs an MCP because it's just too slow and too token inefficient and and
[04:17:20] slow and too token inefficient and and so forth. But it was just glimpse of the
[04:17:22] so forth. But it was just glimpse of the fusion. Then after that I kind of just
[04:17:25] fusion. Then after that I kind of just didn't use it because the things I want
[04:17:27] didn't use it because the things I want to use agent for I was mostly in front
[04:17:29] to use agent for I was mostly in front of my computer to do. Now, that has
[04:17:32] of my computer to do. Now, that has changed a little bit lately and is one
[04:17:33] changed a little bit lately and is one of the reasons why I'm so
[04:17:37] of the reasons why I'm so kind of okay about using Cloud Code
[04:17:40] kind of okay about using Cloud Code because Claude has the best mobile app
[04:17:43] because Claude has the best mobile app where any session you start Cloud Code
[04:17:46] where any session you start Cloud Code in your terminal on a computer is
[04:17:48] in your terminal on a computer is accessible through the app without you
[04:17:50] accessible through the app without you having to do anything at all.
[04:17:52] having to do anything at all. >> Yep. And you can do a terminal like I I
[04:17:54] >> Yep. And you can do a terminal like I I installed terminus and it can run harder
[04:17:56] installed terminus and it can run harder and so on but it's a little cumbersome
[04:17:57] and so on but it's a little cumbersome and you're doing live typing on a
[04:17:59] and you're doing live typing on a computer so you feel the latency when
[04:18:01] computer so you feel the latency when you're using the cloud app to your cloud
[04:18:03] you're using the cloud app to your cloud code instances it feels just like
[04:18:05] code instances it feels just like chatting with it without the
[04:18:06] chatting with it without the cumbersomeness of having to set up a
[04:18:08] cumbersomeness of having to set up a telegram account and and so forth. Now
[04:18:10] telegram account and and so forth. Now if you want to use an open claw to like
[04:18:12] if you want to use an open claw to like run your life well then this doesn't do
[04:18:15] run your life well then this doesn't do that but I haven't been so interested in
[04:18:17] that but I haven't been so interested in that for some reason. Maybe one of the
[04:18:18] that for some reason. Maybe one of the reasons is that um Jamie wife is like,
[04:18:21] reasons is that um Jamie wife is like, "We're not getting a robot inside the
[04:18:23] "We're not getting a robot inside the house." So, I'm like, "Ah, better not
[04:18:24] house." So, I'm like, "Ah, better not hook it up to the uh um sort of smart
[04:18:28] hook it up to the uh um sort of smart house here. If it starts turning lights
[04:18:30] house here. If it starts turning lights on and off like a poltergeist, I don't
[04:18:32] on and off like a poltergeist, I don't think I'm going to be all that popular."
[04:18:34] think I'm going to be all that popular." So, and part of the reason I say I've
[04:18:36] So, and part of the reason I say I've heard some of the stories of people who
[04:18:38] heard some of the stories of people who have hooked it up to their whole life.
[04:18:40] have hooked it up to their whole life. And um I mean it's not my story to tell,
[04:18:42] And um I mean it's not my story to tell, so I'll just share sort of the brief
[04:18:43] so I'll just share sort of the brief anecdote. One guy was telling the story
[04:18:45] anecdote. One guy was telling the story about how he hooked it up to both his
[04:18:47] about how he hooked it up to both his health health data
[04:18:49] health health data >> Mhm.
[04:18:49] >> Mhm. >> and his Tesla car and his uh his agent
[04:18:53] >> and his Tesla car and his uh his agent got obsessed with the fact that he
[04:18:54] got obsessed with the fact that he wasn't drinking enough water and like
[04:18:57] wasn't drinking enough water and like hey you you got to drink more water. So
[04:18:59] hey you you got to drink more water. So at some point he's driving along and
[04:19:01] at some point he's driving along and suddenly the Tesla starts driving in a
[04:19:03] suddenly the Tesla starts driving in a new direction.
[04:19:04] new direction. >> Yeah.
[04:19:04] >> Yeah. >> The agent had realized there was a
[04:19:07] >> The agent had realized there was a grocery store on the way home that they
[04:19:09] grocery store on the way home that they could swing by. That's great.
[04:19:10] could swing by. That's great. >> And pick up some water.
[04:19:12] >> And pick up some water. >> That's great. And you're like, this is
[04:19:13] >> That's great. And you're like, this is one of those things where it's like both
[04:19:15] one of those things where it's like both funny and also totally black mirror and
[04:19:18] funny and also totally black mirror and also totally like well okay it there's
[04:19:21] also totally like well okay it there's not that many steps from here where the
[04:19:23] not that many steps from here where the poltergeist is in your house. So I was
[04:19:25] poltergeist is in your house. So I was just like I don't need that. I do
[04:19:28] just like I don't need that. I do actually now like the fact that I can
[04:19:30] actually now like the fact that I can control the agents through cloud code
[04:19:32] control the agents through cloud code just through the app if I even if I
[04:19:34] just through the app if I even if I don't use them that much. I do think
[04:19:36] don't use them that much. I do think it's very useful to for both open call
[04:19:38] it's very useful to for both open call and Hermes agent to um to use it to get
[04:19:42] and Hermes agent to um to use it to get a a glimpse of a different interaction
[04:19:44] a a glimpse of a different interaction mode.
[04:19:45] mode. >> Yes.
[04:19:45] >> Yes. >> And like because it feels like the
[04:19:48] >> And like because it feels like the future, not necessarily in this way, but
[04:19:50] future, not necessarily in this way, but it's in some ways going there.
[04:19:52] it's in some ways going there. >> I think what what's also different with
[04:19:53] >> I think what what's also different with those systems is they have this whole
[04:19:56] those systems is they have this whole memory system where they're building up
[04:19:59] memory system where they're building up knowledge of who you are and what you
[04:20:00] knowledge of who you are and what you like. Mhm.
[04:20:01] like. Mhm. >> Um Toby has told the stories about how
[04:20:03] >> Um Toby has told the stories about how his agent will shop for him that has an
[04:20:06] his agent will shop for him that has an allowance and it'll pick out clothes for
[04:20:08] allowance and it'll pick out clothes for him and it'll just show up at the door
[04:20:10] him and it'll just show up at the door because his agent bought something for
[04:20:12] because his agent bought something for him and like it's one of those things
[04:20:13] him and like it's one of those things where like man that feels future also a
[04:20:16] where like man that feels future also a little scary.
[04:20:17] little scary. >> Um but I can live vicariously through
[04:20:20] >> Um but I can live vicariously through others who are on that frontier
[04:20:22] others who are on that frontier >> and like you said you're thinking of the
[04:20:25] >> and like you said you're thinking of the in the future doing a mobile version of
[04:20:28] in the future doing a mobile version of Machi. So I mean this is the delusions
[04:20:29] Machi. So I mean this is the delusions of grander that start kicking in once
[04:20:31] of grander that start kicking in once you get the seemingly unlimited powers
[04:20:34] you get the seemingly unlimited powers I've witnessed with the creation of
[04:20:35] I've witnessed with the creation of quattro.
[04:20:36] quattro. >> So what would that look like? Where did
[04:20:38] >> So what would that look like? Where did I scratch? Are you do you mean like
[04:20:40] I scratch? Are you do you mean like Android?
[04:20:42] Android? >> That's the obvious path right? So
[04:20:43] >> That's the obvious path right? So Android is open source and you can fork
[04:20:46] Android is open source and you can fork it and people have there's all sorts of
[04:20:47] it and people have there's all sorts of graphine OS is one such version. There
[04:20:50] graphine OS is one such version. There are limitations to that model. I know
[04:20:52] are limitations to that model. I know that uh tap to pay and other things
[04:20:54] that uh tap to pay and other things around camera models and and so forth,
[04:20:57] around camera models and and so forth, but that all seems surmountable. It all
[04:20:59] but that all seems surmountable. It all seems that I would love if my phone was
[04:21:02] seems that I would love if my phone was as malible as my computer. If it looked
[04:21:04] as malible as my computer. If it looked as cool as my computer now does. If I
[04:21:06] as cool as my computer now does. If I could get essentially um mobile, that
[04:21:08] could get essentially um mobile, that sounds amazing. I wonder how much work
[04:21:10] sounds amazing. I wonder how much work that is.
[04:21:11] that is. >> I'm going to find out.
[04:21:12] >> I'm going to find out. >> Yeah. You know, it's like those things
[04:21:14] >> Yeah. You know, it's like those things that you're you realize once you start
[04:21:16] that you're you realize once you start building, for example, that a browser is
[04:21:19] building, for example, that a browser is very difficult to do.
[04:21:20] very difficult to do. >> Yes. And so like I wonder the operating
[04:21:23] >> Yes. And so like I wonder the operating system.
[04:21:23] system. >> Yeah, the developers of Ladybird is is
[04:21:25] >> Yeah, the developers of Ladybird is is is finding that out like Andreas and his
[04:21:28] is finding that out like Andreas and his team. Now interesting with that project
[04:21:30] team. Now interesting with that project was the browser is basically the second
[04:21:32] was the browser is basically the second most complicated software system in the
[04:21:34] most complicated software system in the world. The first one being the Linux
[04:21:35] world. The first one being the Linux kernel, right? In terms of um
[04:21:37] kernel, right? In terms of um >> these large tens of millions of lines of
[04:21:41] >> these large tens of millions of lines of code systems. So very audacious actually
[04:21:44] code systems. So very audacious actually to begin such a mission with a small
[04:21:46] to begin such a mission with a small team like Andreas did before we had
[04:21:48] team like Andreas did before we had agents. But now that we do have agents,
[04:21:51] agents. But now that we do have agents, we're going to we're going to see and
[04:21:53] we're going to we're going to see and we're probably going to see sooner
[04:21:54] we're probably going to see sooner rather than later. I mean, if one if
[04:21:57] rather than later. I mean, if one if there's one thing agents are already
[04:21:59] there's one thing agents are already exceptionally good at, it is to read
[04:22:02] exceptionally good at, it is to read specs and implement them. And I mean, I
[04:22:06] specs and implement them. And I mean, I don't know how long the specs are for
[04:22:07] don't know how long the specs are for CSS and HTML at this point and
[04:22:09] CSS and HTML at this point and JavaScript on top, but um they're very
[04:22:11] JavaScript on top, but um they're very long
[04:22:11] long >> and it would take humans many, many
[04:22:13] >> and it would take humans many, many years to implement them.
[04:22:15] years to implement them. >> We're going to find out just how quickly
[04:22:16] >> We're going to find out just how quickly agents could do them.
[04:22:18] agents could do them. You mentioned getting some criticism for
[04:22:20] You mentioned getting some criticism for Amachi. So, uh, let's
[04:22:24] Amachi. So, uh, let's walk further down that path of
[04:22:26] walk further down that path of criticism. You have, uh, made some of
[04:22:30] criticism. You have, uh, made some of your political opinions known.
[04:22:33] your political opinions known. Um, I guess you could broadly put in the
[04:22:36] Um, I guess you could broadly put in the category of immigration or illegal
[04:22:38] category of immigration or illegal immigration or what.
[04:22:39] immigration or what. >> I'd say mass immigration.
[04:22:41] >> I'd say mass immigration. >> Mass immigration.
[04:22:43] >> Mass immigration. the role of demographics
[04:22:46] the role of demographics in the
[04:22:48] in the in the formation
[04:22:50] in the formation uh of of a culture of a society of a
[04:22:52] uh of of a culture of a society of a nation and you've gotten quite a lot of
[04:22:55] nation and you've gotten quite a lot of criticism for that and create a lot of
[04:22:57] criticism for that and create a lot of drama. Do you regret any of that drama?
[04:23:07] Like what's your general thinking about? >> Not for a second. Okay. And the reason I
[04:23:10] >> Not for a second. Okay. And the reason I say that is that the overtone window
[04:23:12] say that is that the overtone window does not open itself. It opens one nudge
[04:23:15] does not open itself. It opens one nudge at a time by people risking a little a
[04:23:19] at a time by people risking a little a little reputation, a little push back
[04:23:21] little reputation, a little push back and a little criticism or maybe
[04:23:22] and a little criticism or maybe sometimes a lot of reputation or a lot
[04:23:24] sometimes a lot of reputation or a lot of criticism or a lot of push back. And
[04:23:27] of criticism or a lot of push back. And I think the question of mass immigration
[04:23:29] I think the question of mass immigration in Europe was for many years this total
[04:23:33] in Europe was for many years this total taboo and it still is in several
[04:23:36] taboo and it still is in several European countries. how for
[04:23:40] European countries. how for reasons of maybe just chance and happen
[04:23:43] reasons of maybe just chance and happen stance, they weren't in Denmark. The
[04:23:45] stance, they weren't in Denmark. The Dane started having the discussion
[04:23:47] Dane started having the discussion around mass immigration and the
[04:23:49] around mass immigration and the consequences thereof in the mid '9s
[04:23:52] consequences thereof in the mid '9s >> really early and some of it can be uh
[04:23:55] >> really early and some of it can be uh traced back to one man
[04:23:59] traced back to one man who was a very quirky character. I
[04:24:03] who was a very quirky character. I remember him seeing him on the TV in the
[04:24:04] remember him seeing him on the TV in the 80s talking about the dangers of mass
[04:24:07] 80s talking about the dangers of mass immigration and this was at a time where
[04:24:09] immigration and this was at a time where I grew up in the 80s and in the uh
[04:24:13] I grew up in the 80s and in the uh neighborhood I grew up in in uh in Bonto
[04:24:16] neighborhood I grew up in in uh in Bonto in what was it 84 99%
[04:24:20] in what was it 84 99% ethnic Danes
[04:24:23] ethnic Danes people who could trace their lineage
[04:24:25] people who could trace their lineage back to Danes who' lived in that country
[04:24:27] back to Danes who' lived in that country for a thousand years the Danes have one
[04:24:30] for a thousand years the Danes have one of the oldest monarchies in the world
[04:24:32] of the oldest monarchies in the world all the way back to Harold Bluetooth
[04:24:34] all the way back to Harold Bluetooth who's literally who has named the
[04:24:36] who's literally who has named the standard Bluetooth. So well over a
[04:24:38] standard Bluetooth. So well over a thousand years like there's a long
[04:24:39] thousand years like there's a long lineage there are people who lived in
[04:24:40] lineage there are people who lived in the same place and 99% of the people
[04:24:44] the same place and 99% of the people lived in that neighborhood and then
[04:24:46] lived in that neighborhood and then early 90s I think it goes to to 5% or
[04:24:49] early 90s I think it goes to to 5% or something like that and then at this
[04:24:50] something like that and then at this point it's down to around 60 something
[04:24:52] point it's down to around 60 something or 70%.
[04:24:53] or 70%. >> Mhm. in in that's a big change and the
[04:24:58] >> Mhm. in in that's a big change and the DNE started noticing that or talking
[04:25:01] DNE started noticing that or talking about that that this was not an
[04:25:04] about that that this was not an undivided blessing
[04:25:07] undivided blessing uh that there were downsides to mass
[04:25:10] uh that there were downsides to mass immigration in about the '90s and the
[04:25:12] immigration in about the '90s and the debate really roared through the 2000s
[04:25:15] debate really roared through the 2000s in a way that didn't happen in the
[04:25:17] in a way that didn't happen in the neighboring countries. So Sweden in
[04:25:19] neighboring countries. So Sweden in particular just didn't have that debate
[04:25:20] particular just didn't have that debate at all. Total taboo. Same thing with
[04:25:23] at all. Total taboo. Same thing with Norway. Same thing with other uh
[04:25:24] Norway. Same thing with other uh countries in Europe. And suddenly now
[04:25:29] countries in Europe. And suddenly now after some years after 15 where we had
[04:25:32] after some years after 15 where we had the big migration of a million Syrians
[04:25:34] the big migration of a million Syrians uh walking up through the highways in in
[04:25:36] uh walking up through the highways in in Europe and Germany choosing to take a
[04:25:39] Europe and Germany choosing to take a lot of them and and 30,000 arriving in
[04:25:41] lot of them and and 30,000 arriving in Denmark and so forth. Um it's gotten
[04:25:43] Denmark and so forth. Um it's gotten more of a focus, right? Because this
[04:25:45] more of a focus, right? Because this change has has happened. And one of the
[04:25:49] change has has happened. And one of the ways I find that you can spot where sort
[04:25:53] ways I find that you can spot where sort of there's something that isn't right in
[04:25:55] of there's something that isn't right in the culture is like what are you allowed
[04:25:57] the culture is like what are you allowed to to talk about? What are you allowed
[04:25:58] to to talk about? What are you allowed to notice actually is how I should put
[04:26:00] to notice actually is how I should put it. And what I noticed in an essay, what
[04:26:03] it. And what I noticed in an essay, what was that? Only a year and a half ago.
[04:26:05] was that? Only a year and a half ago. Uh, as I remember London, was that I
[04:26:08] Uh, as I remember London, was that I started coming to London in late '9s or
[04:26:10] started coming to London in late '9s or something like that at the time,
[04:26:12] something like that at the time, whatever, it's 59 60% ethnic uh, Brits,
[04:26:16] whatever, it's 59 60% ethnic uh, Brits, and then 20 years later, we're down to
[04:26:20] and then 20 years later, we're down to 34% or something like that. Like, that's
[04:26:22] 34% or something like that. Like, that's noticeable. Like, literally just walking
[04:26:24] noticeable. Like, literally just walking on the street, you realize, well, this
[04:26:26] on the street, you realize, well, this is a different city from what it was
[04:26:27] is a different city from what it was when I visited 20 years ago. And if you
[04:26:30] when I visited 20 years ago. And if you went 20 years before that, you get back
[04:26:33] went 20 years before that, you get back to similar rates as what the Danes have.
[04:26:35] to similar rates as what the Danes have. This was like a country of ethnic Brits
[04:26:39] This was like a country of ethnic Brits in the 85s, 90s percentiles. If you get
[04:26:43] in the 85s, 90s percentiles. If you get further back, that's a different country
[04:26:45] further back, that's a different country in a generation. It's okay to notice
[04:26:47] in a generation. It's okay to notice that. It's also okay to think, do you
[04:26:51] that. It's also okay to think, do you know what? I don't agree with that. I
[04:26:53] know what? I don't agree with that. I wish it wasn't that way. I mean, if if
[04:26:57] wish it wasn't that way. I mean, if if um the last time I was in China was 19,
[04:27:01] um the last time I was in China was 19, 2019, I was in in Shanghai.
[04:27:04] 2019, I was in in Shanghai. Um it was all Chinese. If I when I go
[04:27:08] Um it was all Chinese. If I when I go back here this October suddenly find
[04:27:11] back here this October suddenly find that there's only 30% Chinese and then
[04:27:13] that there's only 30% Chinese and then there's 70% other people, I'd be a
[04:27:16] there's 70% other people, I'd be a little weird. I'd probably be like, "Uh,
[04:27:20] little weird. I'd probably be like, "Uh, what happened?"
[04:27:22] what happened?" Um and I I would not take offense if the
[04:27:25] Um and I I would not take offense if the Chinese in that instant would go like we
[04:27:28] Chinese in that instant would go like we don't like that. So this idea that
[04:27:33] don't like that. So this idea that countries of Europe don't have a right
[04:27:37] countries of Europe don't have a right to a notice what's happening and b
[04:27:40] to a notice what's happening and b oppose what's happening I find just to
[04:27:42] oppose what's happening I find just to be
[04:27:43] be uh
[04:27:46] uh wrong. Right? Like there's just I think
[04:27:48] wrong. Right? Like there's just I think there's a moral argument for
[04:27:50] there's a moral argument for self-determination and we invoke that
[04:27:52] self-determination and we invoke that argument all the time in other regions
[04:27:54] argument all the time in other regions around the world that like oh the people
[04:27:56] around the world that like oh the people who live in that region they have a
[04:27:57] who live in that region they have a right to self-determination
[04:28:00] right to self-determination uh for the country and I think it's
[04:28:01] uh for the country and I think it's completely fair for say the Danes or the
[04:28:04] completely fair for say the Danes or the Swedes or the Norwegians to go like well
[04:28:06] Swedes or the Norwegians to go like well we've been um kingdoms here for a
[04:28:07] we've been um kingdoms here for a thousand years with a certain ethnic
[04:28:10] thousand years with a certain ethnic mixup.
[04:28:11] mixup. It's a I mean I'm a big fan of
[04:28:14] It's a I mean I'm a big fan of immigration. I'm a I'm an immigrant to
[04:28:16] immigration. I'm a I'm an immigrant to the US.
[04:28:17] the US. um cherrypicked immigration where
[04:28:20] um cherrypicked immigration where countries compete to attract the
[04:28:23] countries compete to attract the smartest, most talented people around
[04:28:26] smartest, most talented people around the world is is really good.
[04:28:28] the world is is really good. >> Illegal merit-based immigration.
[04:28:31] >> Illegal merit-based immigration. >> Merit based is key here because there's
[04:28:33] >> Merit based is key here because there's actually virtually no illegal
[04:28:35] actually virtually no illegal immigration in most of Europe. Southern
[04:28:37] immigration in most of Europe. Southern Europe has some illegal immigration, but
[04:28:39] Europe has some illegal immigration, but most of Europe does not have a big
[04:28:41] most of Europe does not have a big problem with illegal immigration. And
[04:28:44] problem with illegal immigration. And the problem is with mass immigration of
[04:28:46] the problem is with mass immigration of other kinds and that you end up with
[04:28:48] other kinds and that you end up with demographics that are just totally
[04:28:50] demographics that are just totally different from what they were even a few
[04:28:53] different from what they were even a few short decades ago.
[04:28:55] short decades ago. And I think the countries of Europe
[04:28:58] And I think the countries of Europe would benefit from immigration. In fact,
[04:29:01] would benefit from immigration. In fact, one of the interesting things about the
[04:29:03] one of the interesting things about the Danes is they carry meticulous
[04:29:05] Danes is they carry meticulous statistics on immigration. I'm not
[04:29:08] statistics on immigration. I'm not entirely sure why they're so detailed.
[04:29:11] entirely sure why they're so detailed. Maybe it's all the way back to Mon
[04:29:13] Maybe it's all the way back to Mon Glistrop and and his um discussion in
[04:29:16] Glistrop and and his um discussion in the 90s, but they do. And what's clear
[04:29:17] the 90s, but they do. And what's clear from those statistics is that when the
[04:29:19] from those statistics is that when the Danes have folks from the UK, France,
[04:29:24] Danes have folks from the UK, France, the US show up, on average, those
[04:29:28] the US show up, on average, those immigrants are really beneficial to the
[04:29:30] immigrants are really beneficial to the Danish state. They contribute far more
[04:29:33] Danish state. They contribute far more than
[04:29:34] than what they ask of the state. So the
[04:29:38] what they ask of the state. So the Danish should accept immigrants. um who
[04:29:41] Danish should accept immigrants. um who do that who contribute far more than
[04:29:43] do that who contribute far more than they they take. Then you look at other
[04:29:45] they they take. Then you look at other forms of immigrant groups. There was
[04:29:46] forms of immigrant groups. There was just a a a tally that came out uh last
[04:29:50] just a a a tally that came out uh last week from a Danish politicians that had
[04:29:52] week from a Danish politicians that had asked the I think finance minister to to
[04:29:55] asked the I think finance minister to to do this tally with the latest numbers.
[04:29:57] do this tally with the latest numbers. What does it cost the Danish state to to
[04:30:00] What does it cost the Danish state to to have the positive immigration? this
[04:30:02] have the positive immigration? this cases I mentioned I think for the
[04:30:06] cases I mentioned I think for the on that list whatever France UK US they
[04:30:09] on that list whatever France UK US they were all clustered around the same thing
[04:30:10] were all clustered around the same thing about $25,000
[04:30:12] about $25,000 net benefit to the Danish state every
[04:30:14] net benefit to the Danish state every year I was like wow that's very positive
[04:30:18] year I was like wow that's very positive that's average again right and then at
[04:30:21] that's average again right and then at the other end of the spectrum on the
[04:30:23] the other end of the spectrum on the most costly immigrants was Somali they
[04:30:27] most costly immigrants was Somali they ended up costing the Danish state on
[04:30:28] ended up costing the Danish state on average $28,000
[04:30:31] average $28,000 a year.
[04:30:34] a year. I think it's fair for the Dan to go like
[04:30:36] I think it's fair for the Dan to go like we'd prefer to get more French, Brits,
[04:30:40] we'd prefer to get more French, Brits, and Americans
[04:30:42] and Americans and not so many Somali.
[04:30:44] and not so many Somali. >> Why do you think you got so much hate on
[04:30:46] >> Why do you think you got so much hate on that post?
[04:30:48] that post? >> That's a very
[04:30:51] >> That's a very uh taboo topic in a lot of circles.
[04:30:53] uh taboo topic in a lot of circles. >> Some of it has to do with Overton window
[04:30:55] >> Some of it has to do with Overton window expansion,
[04:30:56] expansion, >> I'm sure. But I also think I mean I want
[04:30:59] >> I'm sure. But I also think I mean I want to take the steelman argument here. I I
[04:31:02] to take the steelman argument here. I I do think that it this can turn ugly,
[04:31:05] do think that it this can turn ugly, right? Is it possible for some of these
[04:31:08] right? Is it possible for some of these things to just veer into
[04:31:10] things to just veer into overt
[04:31:12] overt racism that isn't founded in anything
[04:31:15] racism that isn't founded in anything else but a hatred of other people. Yeah,
[04:31:18] else but a hatred of other people. Yeah, that could happen. But that risk does
[04:31:21] that could happen. But that risk does not negate the need to have a discussion
[04:31:25] not negate the need to have a discussion about the makeup of your country and
[04:31:27] about the makeup of your country and what your immigration policy should be
[04:31:29] what your immigration policy should be like. And what I also find so funny is
[04:31:31] like. And what I also find so funny is especially in Europe, it's it's so kind
[04:31:34] especially in Europe, it's it's so kind of myopic that this discussion about
[04:31:36] of myopic that this discussion about whether Europeans should have a right to
[04:31:39] whether Europeans should have a right to self-determination about what their
[04:31:40] self-determination about what their countries look like, that standard seems
[04:31:42] countries look like, that standard seems to only apply there. No one is trying to
[04:31:45] to only apply there. No one is trying to tell the Japanese, "Hey, you you're
[04:31:48] tell the Japanese, "Hey, you you're you're too Japanese."
[04:31:50] you're too Japanese." Like uh whatever it's 98% I think in
[04:31:53] Like uh whatever it's 98% I think in Tokyo that's um uh ethnic Japanese,
[04:31:56] Tokyo that's um uh ethnic Japanese, right? Like is anyone trying to tell the
[04:31:58] right? Like is anyone trying to tell the Japanese that there Tokyo would be a
[04:32:00] Japanese that there Tokyo would be a much better country if if they were down
[04:32:02] much better country if if they were down to London levels of ethnic uh Japanese
[04:32:04] to London levels of ethnic uh Japanese that it was whatever 37%. I don't think
[04:32:07] that it was whatever 37%. I don't think so. Uh so there's this weird almost
[04:32:11] so. Uh so there's this weird almost self-loathing in my opinion. I mean, uh,
[04:32:16] self-loathing in my opinion. I mean, uh, God calls it suicidal empathy that
[04:32:20] God calls it suicidal empathy that permeates the stuff to a degree that I
[04:32:23] permeates the stuff to a degree that I still haven't fully unpacked. Like,
[04:32:24] still haven't fully unpacked. Like, where is this coming from? Why is it
[04:32:26] where is this coming from? Why is it that way? But regardless, I just
[04:32:29] that way? But regardless, I just noticed,
[04:32:31] noticed, hey, London looks different.
[04:32:34] hey, London looks different. I preferred the old London as I would
[04:32:37] I preferred the old London as I would say I preferred uh the neighborhood that
[04:32:42] say I preferred uh the neighborhood that I grew up in in Copenhagen how it looked
[04:32:45] I grew up in in Copenhagen how it looked in the 80s.
[04:32:47] in the 80s. Like
[04:32:48] Like I I totally get how you can then jump
[04:32:51] I I totally get how you can then jump five leaps and go like okay well that's
[04:32:55] five leaps and go like okay well that's racist. And I also I don't care anymore.
[04:32:58] racist. And I also I don't care anymore. like this is a fair discussion to have.
[04:33:01] like this is a fair discussion to have. Countries and peoples have a right to
[04:33:04] Countries and peoples have a right to set an immigration policy and this
[04:33:07] set an immigration policy and this notion that we shouldn't have any
[04:33:10] notion that we shouldn't have any borders or or even worse than that, it's
[04:33:12] borders or or even worse than that, it's all just a blank slate that all peoples
[04:33:15] all just a blank slate that all peoples are just the same and we can take people
[04:33:18] are just the same and we can take people from
[04:33:19] from one place of the earth and we can place
[04:33:21] one place of the earth and we can place them in another place of on the earth
[04:33:23] them in another place of on the earth and everything's just going to work out
[04:33:25] and everything's just going to work out hunky dory. empirically not true. Europe
[04:33:28] hunky dory. empirically not true. Europe has been running that experiment since
[04:33:31] has been running that experiment since the 80s. It hasn't panned out well. And
[04:33:36] the 80s. It hasn't panned out well. And now there are forces in Europe who want
[04:33:38] now there are forces in Europe who want to undo that experiment who wants to end
[04:33:43] to undo that experiment who wants to end mass immigration as it's been run so
[04:33:45] mass immigration as it's been run so far. And I happen to believe and so do a
[04:33:49] far. And I happen to believe and so do a majority of Danes and a bunch of other
[04:33:51] majority of Danes and a bunch of other people that like you know what? Yeah, it
[04:33:53] people that like you know what? Yeah, it hasn't been working how we've been doing
[04:33:54] hasn't been working how we've been doing it. We got to make some changes. And I
[04:33:57] it. We got to make some changes. And I don't think that means again zero
[04:33:58] don't think that means again zero immigration. Again, I'm an immigrant. I
[04:34:00] immigration. Again, I'm an immigrant. I think US generally speaking have
[04:34:02] think US generally speaking have benefited tremendously from immigration.
[04:34:05] benefited tremendously from immigration. But that's the kind of slight of hand.
[04:34:08] But that's the kind of slight of hand. Immigration depends greatly on who
[04:34:11] Immigration depends greatly on who immigrates.
[04:34:12] immigrates. And a country benefits when the people
[04:34:14] And a country benefits when the people who immigrate are net contributors to
[04:34:18] who immigrate are net contributors to the society. And in most cases that the
[04:34:21] the society. And in most cases that the they assimilate with the local culture.
[04:34:23] they assimilate with the local culture. If you come to Denmark and you want to
[04:34:24] If you come to Denmark and you want to become a Dane and you put in all the
[04:34:26] become a Dane and you put in all the effort and you contribute to the
[04:34:28] effort and you contribute to the society, I think most Danes would be
[04:34:31] society, I think most Danes would be quite happy to allow that in in a
[04:34:35] quite happy to allow that in in a reasonable number. If you come to
[04:34:37] reasonable number. If you come to Denmark and you don't want to assimilate
[04:34:39] Denmark and you don't want to assimilate and you are net drain on society and you
[04:34:41] and you are net drain on society and you live in a parallel society, it's also
[04:34:44] live in a parallel society, it's also fair for Dane to say like let's stop
[04:34:46] fair for Dane to say like let's stop doing that. Yeah, it's interesting that
[04:34:49] doing that. Yeah, it's interesting that uh I'm not wellversed on the immigration
[04:34:52] uh I'm not wellversed on the immigration system in the United States, but as far
[04:34:54] system in the United States, but as far as I understand married based system
[04:34:55] as I understand married based system have not uh passed here.
[04:34:58] have not uh passed here. >> And then also American culture is very
[04:35:00] >> And then also American culture is very different. This is a point I did not
[04:35:03] different. This is a point I did not fully appreciate until living both
[04:35:05] fully appreciate until living both places extensively. America has a
[04:35:09] places extensively. America has a culture of optional assimilation where
[04:35:13] culture of optional assimilation where it is much easier and much more condoned
[04:35:16] it is much easier and much more condoned for someone coming from Denmark or
[04:35:19] for someone coming from Denmark or Ukraine or wherever come to America, buy
[04:35:23] Ukraine or wherever come to America, buy into the American set of values and
[04:35:25] into the American set of values and norms and culture and then be able to be
[04:35:28] norms and culture and then be able to be respected as Americans by other
[04:35:30] respected as Americans by other Americans.
[04:35:32] Americans. This is what's so funny to me when
[04:35:35] This is what's so funny to me when there's discussion like America is such
[04:35:37] there's discussion like America is such a racist country. I'm like have you ever
[04:35:39] a racist country. I'm like have you ever been anywhere? Do you know what other
[04:35:42] been anywhere? Do you know what other countries are like? Like if you think
[04:35:44] countries are like? Like if you think America is the most racist country, you
[04:35:47] America is the most racist country, you are simply
[04:35:50] are simply misinformed.
[04:35:51] misinformed. >> Yeah.
[04:35:51] >> Yeah. >> I mean I we're dealing with that the
[04:35:55] >> I mean I we're dealing with that the with time we've spent in Denmark. Uh my
[04:35:57] with time we've spent in Denmark. Uh my wife is American of Scandinavian
[04:36:02] wife is American of Scandinavian heritage
[04:36:03] heritage >> but multiple generations in the US. Very
[04:36:06] >> but multiple generations in the US. Very difficult.
[04:36:07] difficult. >> Very difficult as a blond, blue-eyed
[04:36:10] >> Very difficult as a blond, blue-eyed >> woman who've putting in
[04:36:12] >> woman who've putting in >> all sorts of efforts of learning the
[04:36:14] >> all sorts of efforts of learning the language and doing everything. still
[04:36:17] language and doing everything. still very very difficult to assimilate to to
[04:36:19] very very difficult to assimilate to to Danish culture in a way where if if that
[04:36:22] Danish culture in a way where if if that had been the other way around and and
[04:36:24] had been the other way around and and she had been Danish and moving to the US
[04:36:26] she had been Danish and moving to the US it would not have been that difficult at
[04:36:27] it would not have been that difficult at all. And this was the other thing I mean
[04:36:29] all. And this was the other thing I mean living in a country like Denmark with a
[04:36:32] living in a country like Denmark with a an American wife who is of Scandinavian
[04:36:34] an American wife who is of Scandinavian heritage and has put in all the effort
[04:36:36] heritage and has put in all the effort and still realizing
[04:36:38] and still realizing man assimilation is incredibly difficult
[04:36:41] man assimilation is incredibly difficult even when you're 97% there all the way.
[04:36:45] even when you're 97% there all the way. Holy smokes must it be almost impossible
[04:36:49] Holy smokes must it be almost impossible if you come from a completely foreign
[04:36:51] if you come from a completely foreign culture and foreign norms and the rest
[04:36:55] culture and foreign norms and the rest of it. And of course that's what the
[04:36:58] of it. And of course that's what the stats I just quoted bear out that the
[04:37:00] stats I just quoted bear out that the more dissimilar the culture is and the
[04:37:03] more dissimilar the culture is and the further it is the less likely to be
[04:37:07] further it is the less likely to be successful.
[04:37:08] successful. >> Has uh articulating that stance cost you
[04:37:11] >> Has uh articulating that stance cost you friendships, relationships?
[04:37:14] friendships, relationships? Yes, but not just that alone. I would
[04:37:19] Yes, but not just that alone. I would say it's more of the great divide that
[04:37:22] say it's more of the great divide that happened around 2020 where I think a lot
[04:37:25] happened around 2020 where I think a lot of these political fault lines really
[04:37:28] of these political fault lines really opened up and I mean the shorthand in
[04:37:32] opened up and I mean the shorthand in the US I think is were you woke or not?
[04:37:36] the US I think is were you woke or not? And
[04:37:37] And clearly I had a bunch of people that I I
[04:37:40] clearly I had a bunch of people that I I thought I had good relations with for
[04:37:43] thought I had good relations with for many years who suddenly once that
[04:37:46] many years who suddenly once that political
[04:37:48] political fault line opened up, they were clearly
[04:37:50] fault line opened up, they were clearly just not anymore. And I think that's
[04:37:54] just not anymore. And I think that's regrettable. And I think I've I've I've
[04:37:57] regrettable. And I think I've I've I've tried to put an effort into
[04:38:00] tried to put an effort into um sort of both understanding where that
[04:38:02] um sort of both understanding where that comes from in part because I've changed
[04:38:04] comes from in part because I've changed my mind on several of these topics over
[04:38:06] my mind on several of these topics over the years. And it was like, well,
[04:38:08] the years. And it was like, well, sometimes you just change your mind
[04:38:10] sometimes you just change your mind after time. Sometimes you change your
[04:38:12] after time. Sometimes you change your mind after you get new information.
[04:38:14] mind after you get new information. There's all sorts of reasons and moments
[04:38:16] There's all sorts of reasons and moments why you may change your mind. And we
[04:38:17] why you may change your mind. And we don't all change our mind on the same
[04:38:18] don't all change our mind on the same schedule or at all. Mhm.
[04:38:20] schedule or at all. Mhm. >> Um
[04:38:22] >> Um so surrounding yourselves and and or at
[04:38:25] so surrounding yourselves and and or at least interacting with people who don't
[04:38:27] least interacting with people who don't think like you on every topic I think is
[04:38:30] think like you on every topic I think is quite healthy. I mean I occasionally
[04:38:33] quite healthy. I mean I occasionally discuss politics with my brother. I mean
[04:38:35] discuss politics with my brother. I mean we don't quite see eye to eye on all
[04:38:38] we don't quite see eye to eye on all these topics and sometimes the
[04:38:39] these topics and sometimes the discussions can get a little heated but
[04:38:42] discussions can get a little heated but then they'll also calm down and we
[04:38:43] then they'll also calm down and we realize all right okay so we don't agree
[04:38:45] realize all right okay so we don't agree on this and then we agree on a lot of
[04:38:47] on this and then we agree on a lot of other things. We appreciate a lot of the
[04:38:49] other things. We appreciate a lot of the same things. Now, this was actually one
[04:38:51] same things. Now, this was actually one of the things when we had our big blow
[04:38:52] of the things when we had our big blow up at base camp, I came to appreciate in
[04:38:55] up at base camp, I came to appreciate in a whole new way this
[04:38:58] a whole new way this uh earlier norm that talking politics or
[04:39:02] uh earlier norm that talking politics or religion or money with strangers or even
[04:39:07] religion or money with strangers or even acquaintances and certainly with
[04:39:08] acquaintances and certainly with colleagues was just not a good idea.
[04:39:12] colleagues was just not a good idea. that you had a much
[04:39:15] that you had a much higher likelihood of being able to carry
[04:39:17] higher likelihood of being able to carry a good working relationship with someone
[04:39:19] a good working relationship with someone if you're not rubbing your political
[04:39:20] if you're not rubbing your political differences up against each other all
[04:39:22] differences up against each other all the time. So I actually think liberals
[04:39:25] the time. So I actually think liberals and conservatives should work together.
[04:39:27] and conservatives should work together. I think the country would be much worse
[04:39:29] I think the country would be much worse off if there's a complete um separation
[04:39:34] off if there's a complete um separation between the tribes and then there can't
[04:39:36] between the tribes and then there can't be any overlap or interaction. And I
[04:39:38] be any overlap or interaction. And I think that mingling is so much easier to
[04:39:42] think that mingling is so much easier to do if you just don't focus on your
[04:39:44] do if you just don't focus on your differences all the time. Focus on what
[04:39:46] differences all the time. Focus on what you like together. I mean, this is some
[04:39:48] you like together. I mean, this is some of the people I've had unfortunately uh
[04:39:52] of the people I've had unfortunately uh drifted from in tech. We had so much in
[04:39:55] drifted from in tech. We had so much in common, so much shared love for say Ruby
[04:39:59] common, so much shared love for say Ruby or other things. And like isn't that
[04:40:02] or other things. And like isn't that unfortunate? I would like to live in a
[04:40:03] unfortunate? I would like to live in a world where the differences are the are
[04:40:06] world where the differences are the are very interesting to also talk about.
[04:40:09] very interesting to also talk about. >> Yes.
[04:40:09] >> Yes. >> And not to be overly emotional.
[04:40:13] >> And not to be overly emotional. >> Correct.
[04:40:14] >> Correct. >> About even radical differences because
[04:40:18] >> About even radical differences because in the differences first of all that's
[04:40:20] in the differences first of all that's where interesting stuff is.
[04:40:23] where interesting stuff is. >> Yes.
[04:40:23] >> Yes. >> And and but also it's uh it's how you
[04:40:27] >> And and but also it's uh it's how you grow. It's it's a sign of health in
[04:40:30] grow. It's it's a sign of health in society. if the the differences are
[04:40:33] society. if the the differences are embraced and they are brought together
[04:40:36] embraced and they are brought together into community where you can talk about
[04:40:38] into community where you can talk about it.
[04:40:38] it. >> One of the great illustrations of that
[04:40:40] >> One of the great illustrations of that for me was when I watched a clip from uh
[04:40:42] for me was when I watched a clip from uh William F. Buckley's show, I think it
[04:40:44] William F. Buckley's show, I think it was called Firing Line or
[04:40:46] was called Firing Line or >> something like that
[04:40:47] >> something like that >> and he had a member of the Black
[04:40:49] >> and he had a member of the Black Panthers
[04:40:50] Panthers >> on his panel.
[04:40:52] >> on his panel. >> It was quite obvious that those two
[04:40:54] >> It was quite obvious that those two gentlemen did not share a lot of
[04:40:58] gentlemen did not share a lot of politics. They were able to carry a
[04:41:00] politics. They were able to carry a conversation for I think I watched it 25
[04:41:03] conversation for I think I watched it 25 minutes and Buckley is just asking like
[04:41:06] minutes and Buckley is just asking like so what do you think about this? What do
[04:41:08] so what do you think about this? What do you think about this? And like the Black
[04:41:09] you think about this? And like the Black Panther would reply as you would expect
[04:41:12] Panther would reply as you would expect the Black Panther to reply in the 70s.
[04:41:14] the Black Panther to reply in the 70s. Like there was not a lot of uh sort of
[04:41:17] Like there was not a lot of uh sort of consiliary tones and I just thought like
[04:41:20] consiliary tones and I just thought like wow that is so rare. If you had seen
[04:41:24] wow that is so rare. If you had seen that show today it would have been a
[04:41:27] that show today it would have been a shouting match. It would have been just
[04:41:29] shouting match. It would have been just accusations being hurled back and forth.
[04:41:32] accusations being hurled back and forth. The fact that Bugley was able to just
[04:41:34] The fact that Bugley was able to just have these conversations with people he
[04:41:37] have these conversations with people he vemently disagreed with and still
[04:41:40] vemently disagreed with and still explore all the intellectual facets of
[04:41:43] explore all the intellectual facets of their standpoints and letting them speak
[04:41:45] their standpoints and letting them speak to those facets
[04:41:47] to those facets talks of a lost era that I'd very much
[04:41:51] talks of a lost era that I'd very much like to get back to. I mean, I always
[04:41:54] like to get back to. I mean, I always actually loved talking politics with
[04:41:56] actually loved talking politics with friends that I trusted could talk about
[04:42:00] friends that I trusted could talk about these topics in a way where it didn't
[04:42:02] these topics in a way where it didn't have to be existential. But, but there's
[04:42:04] have to be existential. But, but there's something about the current era where
[04:42:06] something about the current era where that's harder and harder to come by. And
[04:42:10] that's harder and harder to come by. And so what you just articulate is important
[04:42:12] so what you just articulate is important to say regularly to remind people of an
[04:42:15] to say regularly to remind people of an idea we should all strive for to be able
[04:42:17] idea we should all strive for to be able to have differences and and talk and
[04:42:20] to have differences and and talk and talk about them cuz like politics is
[04:42:21] talk about them cuz like politics is fun. Like I I've gotten used to saying I
[04:42:24] fun. Like I I've gotten used to saying I hate politics at this point. But what I
[04:42:26] hate politics at this point. But what I really mean is whatever the system
[04:42:28] really mean is whatever the system that's currently happening where there's
[04:42:31] that's currently happening where there's certain topics I just know we know all
[04:42:33] certain topics I just know we know all the phrases you can say
[04:42:36] the phrases you can say uh that somehow put you in a bin of blue
[04:42:38] uh that somehow put you in a bin of blue or red and that creates drama versus a
[04:42:43] or red and that creates drama versus a conversation. I I could I could think of
[04:42:46] conversation. I I could I could think of a lot of harmless if I wasn't paying
[04:42:48] a lot of harmless if I wasn't paying attention to the internet. I could think
[04:42:50] attention to the internet. I could think of a bunch of harmless statements
[04:42:52] of a bunch of harmless statements I could make analyzing the situation in
[04:42:56] I could make analyzing the situation in the world that would trigger everybody
[04:43:00] the world that would trigger everybody to say, "Oh, that guy's a leftist piece
[04:43:03] to say, "Oh, that guy's a leftist piece of or
[04:43:06] of or you know, right-wing fascist." And then
[04:43:10] you know, right-wing fascist." And then objectively, if I wasn't paying
[04:43:12] objectively, if I wasn't paying attention to the internet, I would be
[04:43:13] attention to the internet, I would be and I have been shocked because I had
[04:43:16] and I have been shocked because I had haven't been paying attention to the
[04:43:17] haven't been paying attention to the internet deeply. uh uh but reading and
[04:43:20] internet deeply. uh uh but reading and preparing a lot for example for uh for
[04:43:24] preparing a lot for example for uh for the war in Ukraine and I have been
[04:43:26] the war in Ukraine and I have been shocked how certain
[04:43:30] shocked how certain statements from me can come off as one
[04:43:32] statements from me can come off as one way or the other and they get viciously
[04:43:34] way or the other and they get viciously attacked for it. But what that attack is
[04:43:37] attacked for it. But what that attack is doing is it's saying, "Hey, you
[04:43:40] doing is it's saying, "Hey, you who thinks you could just move about and
[04:43:43] who thinks you could just move about and think freely, pick a bin and sit in that
[04:43:46] think freely, pick a bin and sit in that bin. put on that blue shirt or
[04:43:49] bin. put on that blue shirt or red shirt and then and then actually
[04:43:51] red shirt and then and then actually what I've realized is things calm down.
[04:43:54] what I've realized is things calm down. They don't the system doesn't pick on
[04:43:57] They don't the system doesn't pick on you if you just say I'm a blue person or
[04:44:01] you if you just say I'm a blue person or I'm a red person,
[04:44:02] I'm a red person, >> right?
[04:44:02] >> right? >> But if you're just like curiously
[04:44:04] >> But if you're just like curiously exploring the world and reasoning about
[04:44:06] exploring the world and reasoning about the world, the system punishes you. And
[04:44:09] the world, the system punishes you. And I I I hate that because I want to get
[04:44:11] I I I hate that because I want to get back to the the Buckley and the Black
[04:44:13] back to the the Buckley and the Black Panther discussion.
[04:44:14] Panther discussion. >> Yes. and you were just saying opinions,
[04:44:17] >> Yes. and you were just saying opinions, but then looking pragmatically at the
[04:44:19] but then looking pragmatically at the situation,
[04:44:21] situation, I have realized not to mention politics
[04:44:24] I have realized not to mention politics unless I really care about an issue cuz
[04:44:26] unless I really care about an issue cuz I realize there's a cost there. They'll
[04:44:29] I realize there's a cost there. They'll they'll put you in the blue bin or red
[04:44:30] they'll put you in the blue bin or red bin.
[04:44:31] bin. >> So, you have to be more deliberate about
[04:44:33] >> So, you have to be more deliberate about choosing
[04:44:34] choosing >> and I have trying to be more conscious
[04:44:37] >> and I have trying to be more conscious of that too.
[04:44:39] of that too. And then when I do choose to speak up
[04:44:42] And then when I do choose to speak up about it, it's usually because I have
[04:44:43] about it, it's usually because I have deliberated and I think you know what
[04:44:45] deliberated and I think you know what this is worth it.
[04:44:46] this is worth it. >> Yeah.
[04:44:47] >> Yeah. >> Now I say that and then I also catch
[04:44:52] >> Now I say that and then I also catch myself thinking the opposite all the
[04:44:54] myself thinking the opposite all the time that I follow some person or
[04:44:56] time that I follow some person or another for whatever their technical
[04:44:58] another for whatever their technical work and then I learned their political
[04:45:02] work and then I learned their political standpoint and I often do think I wish I
[04:45:06] standpoint and I often do think I wish I didn't know that. So it's hypocritical
[04:45:10] didn't know that. So it's hypocritical then to think that of other people and
[04:45:12] then to think that of other people and then go like well occasionally I will
[04:45:14] then go like well occasionally I will >> chime in on a debate that's
[04:45:16] >> chime in on a debate that's controversial and then you have to
[04:45:19] controversial and then you have to accept that there is a price to that and
[04:45:20] accept that there is a price to that and I do think you should and more people
[04:45:23] I do think you should and more people should be somewhat conscious about that
[04:45:26] should be somewhat conscious about that and again we're both contradicting
[04:45:29] and again we're both contradicting ourselves here but saying like wouldn't
[04:45:30] ourselves here but saying like wouldn't it be nice if we could talk about
[04:45:31] it be nice if we could talk about politics in more free and open form and
[04:45:33] politics in more free and open form and just intellectually turn ideas around
[04:45:35] just intellectually turn ideas around yes it But is that currently possible in
[04:45:39] yes it But is that currently possible in the climate of social media and so
[04:45:41] the climate of social media and so forth? It's quite difficult. Now, some
[04:45:44] forth? It's quite difficult. Now, some of it could simply also be a
[04:45:48] of it could simply also be a moment and we could get past that
[04:45:49] moment and we could get past that moment. Maybe there is a way to get back
[04:45:51] moment. Maybe there is a way to get back to Buckley's conversation with the Black
[04:45:53] to Buckley's conversation with the Black Panthers
[04:45:55] Panthers even on social media in a way where
[04:45:57] even on social media in a way where those discussions don't lead to the sort
[04:46:00] those discussions don't lead to the sort of just vicious mob cancellation
[04:46:03] of just vicious mob cancellation nonsense drives that we've had, right?
[04:46:05] nonsense drives that we've had, right? Uh, I actually think we're closer there
[04:46:07] Uh, I actually think we're closer there now than we were 5 years ago. Like the
[04:46:11] now than we were 5 years ago. Like the tribalism and the sanctions those tribes
[04:46:14] tribalism and the sanctions those tribes were able to exact on heretics in 2020
[04:46:19] were able to exact on heretics in 2020 was way greater than it was in 2025.
[04:46:21] was way greater than it was in 2025. Certainly within tech. Now, I know if
[04:46:23] Certainly within tech. Now, I know if you're in academia, I mean, try going
[04:46:25] you're in academia, I mean, try going into the sociology department at uh, I
[04:46:27] into the sociology department at uh, I don't know, Harvard and mention some
[04:46:30] don't know, Harvard and mention some right-wing ideas. I don't think it's
[04:46:31] right-wing ideas. I don't think it's going to go over very well and I don't
[04:46:33] going to go over very well and I don't think you're going to recover from it
[04:46:34] think you're going to recover from it quickly. But in in tech and in many
[04:46:36] quickly. But in in tech and in many other business domains at least, it is
[04:46:39] other business domains at least, it is now possible to have a opinion that does
[04:46:43] now possible to have a opinion that does not square with what the consensus was
[04:46:45] not square with what the consensus was in 2020. That's for sure.
[04:46:47] in 2020. That's for sure. >> Well, there's some uh drama in the Rails
[04:46:49] >> Well, there's some uh drama in the Rails community. There's some drama elsewhere.
[04:46:52] community. There's some drama elsewhere. Is it is is it all How did that turn
[04:46:55] Is it is is it all How did that turn out? Is that all okay?
[04:46:57] out? Is that all okay? >> In the sense that every single round of
[04:47:00] >> In the sense that every single round of drama shrinks. So, it's like we've we
[04:47:03] drama shrinks. So, it's like we've we had this peak infection of mega drama
[04:47:07] had this peak infection of mega drama around the same time every other
[04:47:08] around the same time every other community had the peak infection of
[04:47:11] community had the peak infection of drama around 2020. And then you just see
[04:47:13] drama around 2020. And then you just see like every time there's a new flare up,
[04:47:16] like every time there's a new flare up, it's less. And the kind of people who
[04:47:18] it's less. And the kind of people who are ideologically wedded to sort of that
[04:47:21] are ideologically wedded to sort of that struggle just shrinks and shrinks and
[04:47:23] struggle just shrinks and shrinks and shrinks. And at this point, one of the
[04:47:26] shrinks. And at this point, one of the best things that happened for X, in my
[04:47:27] best things that happened for X, in my opinion, was that Blue Sky and Macedon
[04:47:30] opinion, was that Blue Sky and Macedon came around because it kind of was like
[04:47:33] came around because it kind of was like this honeypot for just the most uh
[04:47:38] this honeypot for just the most uh vicious individuals on X and Twitter at
[04:47:43] vicious individuals on X and Twitter at the time, right, who just congregated
[04:47:45] the time, right, who just congregated here in an evershrinking
[04:47:48] here in an evershrinking eco chamber that just went through
[04:47:51] eco chamber that just went through purity cycle after purity cycle and
[04:47:52] purity cycle after purity cycle and shrank every single time to the point
[04:47:54] shrank every single time to the point that
[04:47:56] that there were just not a lot left and the
[04:47:57] there were just not a lot left and the people who are left now there there just
[04:48:00] people who are left now there there just out of sight out of mind and that's not
[04:48:03] out of sight out of mind and that's not to say that X is some sort of perfect
[04:48:05] to say that X is some sort of perfect place or there aren't firing squads
[04:48:07] place or there aren't firing squads occasionally there or there aren't but
[04:48:08] occasionally there or there aren't but there's less of it like every single
[04:48:11] there's less of it like every single time I've been pulled into a mastadon or
[04:48:13] time I've been pulled into a mastadon or not been pulled in just spectated from
[04:48:15] not been pulled in just spectated from afar thread or blue sky or whatever it
[04:48:17] afar thread or blue sky or whatever it was like oh yeah this is what
[04:48:19] was like oh yeah this is what Twitter used to be like Jesus and now
[04:48:23] Twitter used to be like Jesus and now you can actually be on X as I am and
[04:48:26] you can actually be on X as I am and like 90% of my engagement is about cool
[04:48:31] like 90% of my engagement is about cool Linux stuff, cool technology stuff.
[04:48:33] Linux stuff, cool technology stuff. Look, I discovered a new computer. Can
[04:48:35] Look, I discovered a new computer. Can you see how fast it is? And I can have
[04:48:36] you see how fast it is? And I can have those conversations with other people
[04:48:38] those conversations with other people who just also excited about computers
[04:48:40] who just also excited about computers and then there's like 10% of it left
[04:48:41] and then there's like 10% of it left that's like, all right, I'll chime in on
[04:48:43] that's like, all right, I'll chime in on something that's a little controversial
[04:48:44] something that's a little controversial and we can have a little discussion
[04:48:45] and we can have a little discussion there and then we just go back to being
[04:48:46] there and then we just go back to being excited about computers. Yeah,
[04:48:48] excited about computers. Yeah, >> the algorithm is actually very good at
[04:48:49] >> the algorithm is actually very good at finding stuff that you will find
[04:48:51] finding stuff that you will find interesting or I shouldn't say that
[04:48:53] interesting or I shouldn't say that engaging. Sometimes it's enraging, but
[04:48:55] engaging. Sometimes it's enraging, but it is engaging and therefore revealed
[04:48:58] it is engaging and therefore revealed preference is that most people want a
[04:49:00] preference is that most people want a for you page. They don't want just a
[04:49:01] for you page. They don't want just a following feed.
[04:49:02] following feed. >> No, but this uh they're addicted to the
[04:49:04] >> No, but this uh they're addicted to the for you page, right?
[04:49:05] for you page, right? >> Yes, that's true. I
[04:49:06] >> Yes, that's true. I >> I think an LLM like if we had a strong
[04:49:09] >> I think an LLM like if we had a strong LLM doing the feed that's personalized,
[04:49:12] LLM doing the feed that's personalized, it would do much better. The the problem
[04:49:14] it would do much better. The the problem is how to deliver that scale is
[04:49:16] is how to deliver that scale is extremely difficult.
[04:49:17] extremely difficult. >> Well, the problem is the the reward
[04:49:20] >> Well, the problem is the the reward function is engagement and as soon as
[04:49:23] function is engagement and as soon as the reward function is engagement,
[04:49:25] the reward function is engagement, engagement is going to follow base
[04:49:26] engagement is going to follow base instincts and here we go. But I also
[04:49:30] instincts and here we go. But I also don't want to be so negative to me and I
[04:49:32] don't want to be so negative to me and I get we all have our own personalized
[04:49:34] get we all have our own personalized algorithms
[04:49:36] algorithms and sometimes it gets a little much but
[04:49:38] and sometimes it gets a little much but I would say on average over the last 10
[04:49:40] I would say on average over the last 10 years this is the best X has ever been.
[04:49:42] years this is the best X has ever been. And I say that as someone who cares
[04:49:43] And I say that as someone who cares about a lot of technology talk, a lot of
[04:49:46] about a lot of technology talk, a lot of Linux talk, a lot of that that that's
[04:49:48] Linux talk, a lot of that that that's able to happen now in a way where it
[04:49:51] able to happen now in a way where it doesn't constantly get gate crashed by
[04:49:53] doesn't constantly get gate crashed by people who want to drag it into some
[04:49:55] people who want to drag it into some political discussion
[04:49:57] political discussion >> I find to be really awesome. I find
[04:50:00] >> I find to be really awesome. I find actually eggs to be a great place to
[04:50:02] actually eggs to be a great place to find that. Now, it's also a place to
[04:50:04] find that. Now, it's also a place to find other things and we all have our
[04:50:06] find other things and we all have our own algorithms, but you can't make any
[04:50:08] own algorithms, but you can't make any declarative
[04:50:09] declarative announcements about what eggs is or what
[04:50:11] announcements about what eggs is or what it isn't. Your feed is probably totally
[04:50:13] it isn't. Your feed is probably totally different from my feed and it's totally
[04:50:14] different from my feed and it's totally different from someone else's feed,
[04:50:16] different from someone else's feed, right?
[04:50:16] right? >> Yeah. I I can't I can't comment on this
[04:50:20] >> Yeah. I I can't I can't comment on this because
[04:50:22] because because of the nature of the fact that I
[04:50:24] because of the nature of the fact that I interview a wide variety of people, my
[04:50:28] interview a wide variety of people, my feet is probably just a
[04:50:29] feet is probably just a >> Is this good for your feet or is it bad
[04:50:30] >> Is this good for your feet or is it bad for your feet?
[04:50:32] for your feet? It's bad cuz I could be like, "I'm
[04:50:33] It's bad cuz I could be like, "I'm eating this apple.
[04:50:35] eating this apple. >> It's so delicious." And then a bunch of
[04:50:37] >> It's so delicious." And then a bunch of people will show up. Oh, it's because
[04:50:39] people will show up. Oh, it's because you're Zilinski shill or you're a Putin
[04:50:41] you're Zilinski shill or you're a Putin shill, you piece of
[04:50:43] shill, you piece of >> It's like, all right,
[04:50:45] >> It's like, all right, >> I'll just
[04:50:47] >> I'll just I occasionally have a little bit of that
[04:50:49] I occasionally have a little bit of that where you just go like, "Wait, what?
[04:50:51] where you just go like, "Wait, what? What are we talking about? What are why
[04:50:53] What are we talking about? What are why would you show up in this way?" This is
[04:50:55] would you show up in this way?" This is one of the reasons why I actually really
[04:50:56] one of the reasons why I actually really enjoy podcasts because I have found that
[04:50:58] enjoy podcasts because I have found that even in long form writing when I make
[04:51:00] even in long form writing when I make long form arguments, people hear it in
[04:51:02] long form arguments, people hear it in whatever voice they have in their head
[04:51:04] whatever voice they have in their head for me. And that often gets
[04:51:06] for me. And that often gets pre-programmed in advance of the
[04:51:08] pre-programmed in advance of the arguments just like, well, this guy is a
[04:51:11] arguments just like, well, this guy is a whatever fascist.
[04:51:13] whatever fascist. Um, and then they hear the words and
[04:51:16] Um, and then they hear the words and they read the words in those when they
[04:51:17] they read the words in those when they see or hear the actual tone of how I'm
[04:51:21] see or hear the actual tone of how I'm presenting the arguments, they may not
[04:51:22] presenting the arguments, they may not agree with those arguments. I mean, many
[04:51:23] agree with those arguments. I mean, many of them of course obviously don't. But
[04:51:25] of them of course obviously don't. But it's much harder to just dismiss or hate
[04:51:28] it's much harder to just dismiss or hate someone like that.
[04:51:29] someone like that. >> Mhm.
[04:51:30] >> Mhm. >> At least that's what I found and that's
[04:51:31] >> At least that's what I found and that's the response that I've gotten that
[04:51:33] the response that I've gotten that people like, well, I had a certain
[04:51:34] people like, well, I had a certain opinion and then I heard you on Lex.
[04:51:38] opinion and then I heard you on Lex. That actually sounded much more
[04:51:39] That actually sounded much more reasonable.
[04:51:40] reasonable. >> But even more than that, I I would love
[04:51:42] >> But even more than that, I I would love it if people just exercise
[04:51:45] it if people just exercise this kind of approach to other people of
[04:51:49] this kind of approach to other people of like assuming they're a good person.
[04:51:52] like assuming they're a good person. Yes.
[04:51:53] Yes. >> And then and if they have an opinion you
[04:51:55] >> And then and if they have an opinion you disagree with they're a good person who
[04:51:58] disagree with they're a good person who has an opinion. You could maybe think
[04:52:00] has an opinion. You could maybe think they're stupid. Fine. Just think they're
[04:52:01] they're stupid. Fine. Just think they're lost. But think of them as a good
[04:52:03] lost. But think of them as a good person. I think if you think of you
[04:52:06] person. I think if you think of you start that there's one of the things
[04:52:08] start that there's one of the things that gets engagement is kind of
[04:52:11] that gets engagement is kind of on other people,
[04:52:12] on other people, >> right?
[04:52:12] >> right? >> And if you just approach other people as
[04:52:15] >> And if you just approach other people as they're you're looking for bad, you will
[04:52:18] they're you're looking for bad, you will always find bad in them. There's
[04:52:19] always find bad in them. There's something annoying about them. And if
[04:52:22] something annoying about them. And if you look at people in that way, you're
[04:52:23] you look at people in that way, you're not going to learn from it and you're
[04:52:25] not going to learn from it and you're going to fill your heart with hate.
[04:52:27] going to fill your heart with hate. You're not going to It's just a bad way
[04:52:29] You're not going to It's just a bad way to live and to interact with the world.
[04:52:31] to live and to interact with the world. And that is one of the things that the
[04:52:33] And that is one of the things that the internet kind of encourages. So it'd be
[04:52:35] internet kind of encourages. So it'd be nice if you just approach
[04:52:38] nice if you just approach even people who you really disagree
[04:52:39] even people who you really disagree with. It's like, oh, I might learn
[04:52:41] with. It's like, oh, I might learn something from this person. The Black
[04:52:42] something from this person. The Black Panther person, William Buckley, you
[04:52:44] Panther person, William Buckley, you might hate. Um
[04:52:46] might hate. Um >> so microcosm of this
[04:52:48] >> so microcosm of this >> there's a guy Theo I don't know if you
[04:52:50] >> there's a guy Theo I don't know if you follow um we had a bit of a thing over
[04:52:55] follow um we had a bit of a thing over the fact that uh we stopped using
[04:52:57] the fact that uh we stopped using TypeScript
[04:52:58] TypeScript >> for a project and
[04:53:00] >> for a project and >> he didn't like that and had opinions
[04:53:02] >> he didn't like that and had opinions about that and other actions and after
[04:53:04] about that and other actions and after that I thought like what a bozo and and
[04:53:06] that I thought like what a bozo and and you know what I still think that was a
[04:53:08] you know what I still think that was a bozo move and then I can also think like
[04:53:10] bozo move and then I can also think like well the dude's really into AI he's
[04:53:12] well the dude's really into AI he's trying all these models and we can share
[04:53:14] trying all these models and we can share some excite about that. So, I just
[04:53:16] some excite about that. So, I just started following him yesterday.
[04:53:17] started following him yesterday. Awesome.
[04:53:17] Awesome. >> Like, you know what?
[04:53:18] >> Like, you know what? >> I don't have to agree with you and
[04:53:20] >> I don't have to agree with you and everything. I don't even have to like
[04:53:22] everything. I don't even have to like some of the things that you did or said
[04:53:24] some of the things that you did or said or whatever. I can follow you anyway.
[04:53:27] or whatever. I can follow you anyway. So, if I can follow back Theo, then uh I
[04:53:31] So, if I can follow back Theo, then uh I think there's room for world peace here.
[04:53:34] think there's room for world peace here. Yeah, he's actually a really good
[04:53:35] Yeah, he's actually a really good example. He he's really opinionated. It
[04:53:38] example. He he's really opinionated. It changes his mind quite a bit. Can get
[04:53:40] changes his mind quite a bit. Can get snarky, but I think that's a good person
[04:53:42] snarky, but I think that's a good person underneath. And either way, I just you
[04:53:44] underneath. And either way, I just you know what? My feed is more interesting
[04:53:47] know what? My feed is more interesting when there's some people talking about
[04:53:48] when there's some people talking about things that I care about. And yeah, I
[04:53:51] things that I care about. And yeah, I don't have to agree with you and
[04:53:52] don't have to agree with you and everything. I just don't. This this I
[04:53:56] everything. I just don't. This this I found pretty funny that um you mentioned
[04:53:58] found pretty funny that um you mentioned something your wife said
[04:54:01] something your wife said that stuck with you that all this tech
[04:54:03] that stuck with you that all this tech adjacent extreme longevity focus in men
[04:54:06] adjacent extreme longevity focus in men is like anorexia in women, a physical
[04:54:08] is like anorexia in women, a physical manifestation of anxiety and lack of
[04:54:10] manifestation of anxiety and lack of control.
[04:54:12] control. that somehow rang true a little bit.
[04:54:14] that somehow rang true a little bit. >> It certainly did to a lot of people. I
[04:54:15] >> It certainly did to a lot of people. I think that tweet really popped up and I
[04:54:18] think that tweet really popped up and I don't know if you noticed, but uh Brian
[04:54:21] don't know if you noticed, but uh Brian Johnson chimed in on on the thread and
[04:54:25] Johnson chimed in on on the thread and I could see how Brian would read that as
[04:54:28] I could see how Brian would read that as a bit of a of a jab
[04:54:30] a bit of a of a jab >> and I do think that um Jamie was
[04:54:34] >> and I do think that um Jamie was probably thinking of him amongst other
[04:54:37] probably thinking of him amongst other people in that conversation. And
[04:54:41] people in that conversation. And it's also an example of where
[04:54:46] it's also an example of where even though I'm not subscribing to
[04:54:50] even though I'm not subscribing to Brian's mission of I think it's the
[04:54:52] Brian's mission of I think it's the slogans don't die.
[04:54:53] slogans don't die. >> Yeah.
[04:54:54] >> Yeah. >> I actually
[04:54:56] >> I actually I do want to die. I I don't want to do
[04:54:58] I do want to die. I I don't want to do this forever. I think the human lifespan
[04:55:01] this forever. I think the human lifespan of about 90 to 100 sounds about right.
[04:55:04] of about 90 to 100 sounds about right. I'm embracing the finitude of life. We
[04:55:08] I'm embracing the finitude of life. We don't have to agree on that. In fact,
[04:55:11] don't have to agree on that. In fact, Brian is a vastly more interesting human
[04:55:14] Brian is a vastly more interesting human to me because we don't agree with that.
[04:55:16] to me because we don't agree with that. And Brian's
[04:55:20] And Brian's willingness to literally put his own
[04:55:22] willingness to literally put his own skin and all sorts of other body
[04:55:24] skin and all sorts of other body elements in the game for that mission.
[04:55:28] elements in the game for that mission. It's really interesting. Now, I can have
[04:55:32] It's really interesting. Now, I can have that view. This is really interesting.
[04:55:33] that view. This is really interesting. I'm glad Brian is pursuing this passion
[04:55:37] I'm glad Brian is pursuing this passion of his and then also find
[04:55:41] of his and then also find my wife's analysis to ring true that it
[04:55:44] my wife's analysis to ring true that it does seem like there is some
[04:55:48] does seem like there is some underlying
[04:55:50] underlying uh I don't know fear of I was talking to
[04:55:53] uh I don't know fear of I was talking to Jamie yesterday about this and she was
[04:55:55] Jamie yesterday about this and she was saying um or or comparing it to this
[04:55:59] saying um or or comparing it to this sense of people who didn't feel like
[04:56:01] sense of people who didn't feel like they had lived enough and One of the
[04:56:03] they had lived enough and One of the reason perhaps that they hadn't lived
[04:56:05] reason perhaps that they hadn't lived enough was that modern society now is a
[04:56:09] enough was that modern society now is a surveillance state. Not by the state
[04:56:11] surveillance state. Not by the state actually, but by each other. There
[04:56:13] actually, but by each other. There camera phones everywhere. Every
[04:56:16] camera phones everywhere. Every indiscretion or even outburst of fun or
[04:56:20] indiscretion or even outburst of fun or cringe
[04:56:22] cringe is highly likely to be recorded and then
[04:56:25] is highly likely to be recorded and then shared to the point of ridicule. And
[04:56:27] shared to the point of ridicule. And what is the rational reaction for humans
[04:56:30] what is the rational reaction for humans under those conditions is to pull back,
[04:56:32] under those conditions is to pull back, is to make sure you don't dance like
[04:56:34] is to make sure you don't dance like nobody's watching because they're
[04:56:36] nobody's watching because they're probably filming you
[04:56:38] probably filming you >> to your great and internal embarrassment
[04:56:41] >> to your great and internal embarrassment on the internet. So maybe you just
[04:56:42] on the internet. So maybe you just shouldn't dance at all.
[04:56:44] shouldn't dance at all. >> And therefore, if we have all retracted
[04:56:47] >> And therefore, if we have all retracted to the point that we're barely living,
[04:56:49] to the point that we're barely living, we're clinging on to wanting it to last
[04:56:52] we're clinging on to wanting it to last forever.
[04:56:54] forever. >> Yeah. Now,
[04:56:55] >> Yeah. Now, >> I mean, I'm sure that thesis does not
[04:56:56] >> I mean, I'm sure that thesis does not apply in all circumstances. I don't even
[04:56:58] apply in all circumstances. I don't even know if it applies to Brian or or anyone
[04:57:00] know if it applies to Brian or or anyone else here, but I think there's something
[04:57:01] else here, but I think there's something to this that
[04:57:03] to this that >> if you feel like you've really lived,
[04:57:07] >> if you feel like you've really lived, you're okay thinking, I've lived enough
[04:57:10] you're okay thinking, I've lived enough and that that
[04:57:13] and that that it having an end is not something to be
[04:57:18] it having an end is not something to be fought. Now,
[04:57:21] fought. Now, is it also possible that this is all
[04:57:22] is it also possible that this is all just existential post-rationalization
[04:57:24] just existential post-rationalization and if tomorrow there was a live forever
[04:57:26] and if tomorrow there was a live forever pill, we'd all take it? Yeah, it's
[04:57:28] pill, we'd all take it? Yeah, it's possible. Is it also possible that if we
[04:57:30] possible. Is it also possible that if we did that, society be would be worse off?
[04:57:33] did that, society be would be worse off? Yes. Is it possible that the human
[04:57:37] Yes. Is it possible that the human lifespan is the length it is for
[04:57:41] lifespan is the length it is for sociological reasons, not just
[04:57:43] sociological reasons, not just biological reasons? Yes. So I think
[04:57:46] biological reasons? Yes. So I think these are just all interesting questions
[04:57:48] these are just all interesting questions and I just thought her analysis
[04:57:51] and I just thought her analysis really got to something here and that
[04:57:54] really got to something here and that discussion has come up afterwards. I
[04:57:56] discussion has come up afterwards. I mean that I think that tweet is like a
[04:57:58] mean that I think that tweet is like a year old but just recently we've been
[04:58:01] year old but just recently we've been talking about this uh overoptimizers. I
[04:58:03] talking about this uh overoptimizers. I saw Chris Williams on Modern Wisdom had
[04:58:06] saw Chris Williams on Modern Wisdom had a bit where was like, "Yeah, okay. Maybe
[04:58:08] a bit where was like, "Yeah, okay. Maybe we did go a little overboard." And the
[04:58:10] we did go a little overboard." And the triggering thing was The Diary of a CEO
[04:58:13] triggering thing was The Diary of a CEO where the host was saying something to
[04:58:15] where the host was saying something to the effect of, "I had a glass of wine
[04:58:17] the effect of, "I had a glass of wine and the next three days were ruined."
[04:58:20] and the next three days were ruined." >> Okay.
[04:58:20] >> Okay. >> And that to me, I mean, in his
[04:58:23] >> And that to me, I mean, in his circumstance, I'm sure that's true.
[04:58:24] circumstance, I'm sure that's true. Like, if you have not drank any alcohol
[04:58:26] Like, if you have not drank any alcohol for a very long time and you have just a
[04:58:28] for a very long time and you have just a little, I could see how it can have
[04:58:29] little, I could see how it can have effect. But also there's something in
[04:58:31] effect. But also there's something in that that just triggered a visceral
[04:58:34] that that just triggered a visceral reaction I think for a lot of people and
[04:58:35] reaction I think for a lot of people and myself included where I was like
[04:58:37] myself included where I was like man I should have a glass of wine just
[04:58:39] man I should have a glass of wine just right now even though I don't usually
[04:58:40] right now even though I don't usually drink
[04:58:41] drink >> and and in fact I think the alcohol
[04:58:43] >> and and in fact I think the alcohol question is a good microcosm to zoom in
[04:58:45] question is a good microcosm to zoom in on so
[04:58:46] on so >> we've all stopped drinking apparently
[04:58:48] >> we've all stopped drinking apparently like alcohol sales are way down
[04:58:50] like alcohol sales are way down >> certainly amongst young people and then
[04:58:53] >> certainly amongst young people and then on the one hand on the pure health
[04:58:56] on the one hand on the pure health metrics whatever we can go like oh wow
[04:58:58] metrics whatever we can go like oh wow isn't that great
[04:58:59] isn't that great >> and then I like I'm not so sure it is
[04:59:01] >> and then I like I'm not so sure it is like the social lubricant that alcohol
[04:59:04] like the social lubricant that alcohol can provide maybe missed is missed. I
[04:59:07] can provide maybe missed is missed. I mean we are in an absolute epidemic of
[04:59:10] mean we are in an absolute epidemic of loneliness and misery and depression and
[04:59:13] loneliness and misery and depression and and whatever and a fair amount of it
[04:59:15] and whatever and a fair amount of it just probably comes because you're not
[04:59:17] just probably comes because you're not interacting enough with other people.
[04:59:19] interacting enough with other people. Now that's before we even talk about
[04:59:21] Now that's before we even talk about coupling, right? Like uh way down people
[04:59:24] coupling, right? Like uh way down people having a very hard time meeting a spouse
[04:59:27] having a very hard time meeting a spouse and a lot of that has moved over to apps
[04:59:30] and a lot of that has moved over to apps that have all sorts of
[04:59:33] that have all sorts of negative outcomes and consequences,
[04:59:35] negative outcomes and consequences, right? Like maybe we will look back or
[04:59:38] right? Like maybe we will look back or maybe we already are looking back and
[04:59:39] maybe we already are looking back and thinking like ah do you know what maybe
[04:59:41] thinking like ah do you know what maybe getting wasted every once in a while was
[04:59:42] getting wasted every once in a while was not the worst thing in the world. And
[04:59:43] not the worst thing in the world. And whether wasted or not, maybe just having
[04:59:45] whether wasted or not, maybe just having a couple of drinks every Friday or
[04:59:48] a couple of drinks every Friday or Saturday when you're out and about was
[04:59:52] Saturday when you're out and about was part of what helped society get to where
[04:59:54] part of what helped society get to where it is. Maybe the fact that humans have
[04:59:57] it is. Maybe the fact that humans have literally been drinking for whatever it
[04:59:59] literally been drinking for whatever it is like 13,000 years for mending things
[05:00:02] is like 13,000 years for mending things had a social purpose and we pull out
[05:00:05] had a social purpose and we pull out Chester's fence at our own chrin. Right.
[05:00:08] Chester's fence at our own chrin. Right. I should mention in the spirit of that.
[05:00:11] I should mention in the spirit of that. So when I traveled across rural China, I
[05:00:14] So when I traveled across rural China, I did smoke a little bit in in my early
[05:00:16] did smoke a little bit in in my early 20s, but I picked up just for that trip.
[05:00:20] 20s, but I picked up just for that trip. >> A social
[05:00:22] >> A social connector, right?
[05:00:22] connector, right? >> And I drank humongous amounts, even
[05:00:25] >> And I drank humongous amounts, even though I don't really drink these days
[05:00:29] though I don't really drink these days because of the social things. It's the
[05:00:30] because of the social things. It's the way they show love. And I also ate
[05:00:33] way they show love. And I also ate shitload of carbs, which I'm usually low
[05:00:36] shitload of carbs, which I'm usually low carb. I just like meat. So just because
[05:00:39] carb. I just like meat. So just because it's the way they show love and actually
[05:00:41] it's the way they show love and actually even in that society uh cigarettes but
[05:00:45] even in that society uh cigarettes but in most societies liquor is a thing to
[05:00:48] in most societies liquor is a thing to do together
[05:00:49] do together >> and it's a bond. It doesn't the the
[05:00:52] >> and it's a bond. It doesn't the the benefits that that entails
[05:00:56] benefits that that entails can in many situations outweigh the
[05:00:58] can in many situations outweigh the negative consequences like long-term for
[05:01:00] negative consequences like long-term for whatever however you measure them. And
[05:01:02] whatever however you measure them. And this is the myopia of modernity that we
[05:01:06] this is the myopia of modernity that we reduce things down to like well one
[05:01:08] reduce things down to like well one glass on this long run study meant that
[05:01:10] glass on this long run study meant that you had a 0.1% greater risk of some
[05:01:13] you had a 0.1% greater risk of some heart defect.
[05:01:15] heart defect. Yes, but if you didn't live at all
[05:01:16] Yes, but if you didn't live at all what's the point? And again, it's also
[05:01:19] what's the point? And again, it's also easy to flip over the other side like
[05:01:21] easy to flip over the other side like the only way to live is to get drunk
[05:01:23] the only way to live is to get drunk every weekend and eat a bunch of crap
[05:01:25] every weekend and eat a bunch of crap and smoke 40 cigarettes a day. No, it's
[05:01:28] and smoke 40 cigarettes a day. No, it's not. Like it doesn't have to be the
[05:01:31] not. Like it doesn't have to be the eitheror. This is one of the reasons I
[05:01:32] eitheror. This is one of the reasons I stopped wearing my Aura ring. So I wore
[05:01:34] stopped wearing my Aura ring. So I wore the Aura sleep ring for many years, four
[05:01:37] the Aura sleep ring for many years, four years.
[05:01:39] years. And one day I was just like, I don't
[05:01:42] And one day I was just like, I don't need to know that I had a bad night of
[05:01:44] need to know that I had a bad night of sleep. Like I know this
[05:01:48] sleep. Like I know this added
[05:01:50] added >> I don't want to call it anxiety. I don't
[05:01:52] >> I don't want to call it anxiety. I don't have a lot of anxiety, but this added
[05:01:54] have a lot of anxiety, but this added just like reminder
[05:01:56] just like reminder >> that I had a bad night of sleep. What
[05:01:58] >> that I had a bad night of sleep. What purpose is it actually playing here? Why
[05:02:00] purpose is it actually playing here? Why do I need to have all these stats? Why
[05:02:03] do I need to have all these stats? Why do I need to optimize everything to the
[05:02:06] do I need to optimize everything to the point where again after that single
[05:02:08] point where again after that single anecdote from dire CEO I was like I
[05:02:12] anecdote from dire CEO I was like I kind of want the opposite like
[05:02:14] kind of want the opposite like >> I don't barely drink at all like a glass
[05:02:17] >> I don't barely drink at all like a glass of wine once a month maybe like you know
[05:02:19] of wine once a month maybe like you know what I should start uh just on the
[05:02:22] what I should start uh just on the weekends get a glass maybe two.
[05:02:25] weekends get a glass maybe two. >> Yeah. And also, I mean, I've never been
[05:02:28] >> Yeah. And also, I mean, I've never been the person to fret about my diet. Um,
[05:02:32] the person to fret about my diet. Um, this is one of the great privileges of
[05:02:36] this is one of the great privileges of being married to, and I'll do a quick
[05:02:38] being married to, and I'll do a quick aside here, don't ever call a woman in
[05:02:41] aside here, don't ever call a woman in her in her 40s a wonderful woman. My
[05:02:44] her in her 40s a wonderful woman. My wife was so pissed that not only last
[05:02:46] wife was so pissed that not only last year did I come on her birthday, that
[05:02:48] year did I come on her birthday, that was bad enough, but that I called her a
[05:02:50] was bad enough, but that I called her a wonderful woman on the show because that
[05:02:53] wonderful woman on the show because that sounded like her name was Nancy and she
[05:02:55] sounded like her name was Nancy and she was 65 in the suburb of Rochester. So
[05:02:58] was 65 in the suburb of Rochester. So I'm like
[05:02:58] I'm like >> I was trying to play the the fifth year
[05:03:01] >> I was trying to play the the fifth year like I don't know. I'm Danish. How would
[05:03:03] like I don't know. I'm Danish. How would I know? But that didn't go over well. So
[05:03:05] I know? But that didn't go over well. So I'm going to say awesome woman instead.
[05:03:07] I'm going to say awesome woman instead. M if you
[05:03:09] M if you marry an awesome woman who also not only
[05:03:11] marry an awesome woman who also not only knows how to cook but enjoys it. Um do
[05:03:14] knows how to cook but enjoys it. Um do you know what? There's a very
[05:03:16] you know what? There's a very traditional division of labor here that
[05:03:19] traditional division of labor here that has been quite stable through several
[05:03:23] has been quite stable through several tens of thousands of years in human
[05:03:25] tens of thousands of years in human societies. That perhaps also wasn't the
[05:03:28] societies. That perhaps also wasn't the worst idea in the world. And I also know
[05:03:30] worst idea in the world. And I also know there are plenty of men who like to cook
[05:03:32] there are plenty of men who like to cook and there are women who don't. But as
[05:03:34] and there are women who don't. But as stereotypes go,
[05:03:37] stereotypes go, that certainly helped me. Like I I don't
[05:03:39] that certainly helped me. Like I I don't think um I would have been able to just
[05:03:41] think um I would have been able to just be as relaxed about food if I didn't eat
[05:03:44] be as relaxed about food if I didn't eat relatively healthy on a on a regular
[05:03:46] relatively healthy on a on a regular basis. But the overall point being just
[05:03:49] basis. But the overall point being just getting out of that optimization game
[05:03:51] getting out of that optimization game without turning in to the opposite. You
[05:03:54] without turning in to the opposite. You don't have to be a fat slob on the couch
[05:03:56] don't have to be a fat slob on the couch either. You you can move around.
[05:03:59] either. You you can move around. >> Yeah. And then the bigger point we're
[05:04:01] >> Yeah. And then the bigger point we're talking about is um that the finitness
[05:04:04] talking about is um that the finitness of life. And I agree with you on this.
[05:04:07] of life. And I agree with you on this. >> This was actually a feature I built it
[05:04:08] >> This was actually a feature I built it into a machi.
[05:04:09] into a machi. >> So
[05:04:11] >> So momento mori.
[05:04:12] momento mori. >> Yeah.
[05:04:13] >> Yeah. >> Remember death.
[05:04:14] >> Remember death. >> Yeah.
[05:04:15] >> Yeah. >> If you pull down the calendar in Amachi,
[05:04:17] >> If you pull down the calendar in Amachi, you open it by clicking the clock. It
[05:04:19] you open it by clicking the clock. It opens up. And the first funny thing I
[05:04:21] opens up. And the first funny thing I took it off the internet. There's this
[05:04:23] took it off the internet. There's this account called years progress. And it
[05:04:25] account called years progress. And it every day it updates and it just show
[05:04:27] every day it updates and it just show 63% done with 2026. I don't know if
[05:04:30] 63% done with 2026. I don't know if you've seen that one.
[05:04:30] you've seen that one. >> So, it just fills up. So, I built that
[05:04:32] >> So, it just fills up. So, I built that into the calendar. So, right now it says
[05:04:33] into the calendar. So, right now it says we're 63% done with 2026. But then, if
[05:04:36] we're 63% done with 2026. But then, if you double click that,
[05:04:37] you double click that, >> it'll ask you when were you born?
[05:04:40] >> it'll ask you when were you born? >> How long do you expect to live? And the
[05:04:41] >> How long do you expect to live? And the default is 90. So, I put in 1979. And
[05:04:44] default is 90. So, I put in 1979. And then right below the line of like how
[05:04:46] then right below the line of like how long are we done with the year is a new
[05:04:48] long are we done with the year is a new line that shows
[05:04:49] line that shows >> how long are you done with your life? I
[05:04:51] >> how long are you done with your life? I think I'm at 62%.
[05:04:53] think I'm at 62%. >> Yeah.
[05:04:53] >> Yeah. >> I'm like, if you hover over it, it says
[05:04:55] >> I'm like, if you hover over it, it says momento.
[05:04:56] momento. >> That's beautiful. Fair number of people
[05:04:58] >> That's beautiful. Fair number of people found it morbid, but this was why it is
[05:05:00] found it morbid, but this was why it is an Easter egg. It's not like exposed.
[05:05:01] an Easter egg. It's not like exposed. You got to click a few things to get
[05:05:03] You got to click a few things to get there. I like the reminder. I like the
[05:05:05] there. I like the reminder. I like the reminder that time is finite and I
[05:05:08] reminder that time is finite and I should make the most of it. And this is
[05:05:10] should make the most of it. And this is also one of the privileges of having
[05:05:13] also one of the privileges of having children. You really realize that the
[05:05:16] children. You really realize that the cliches are all true. Oh my god, it goes
[05:05:18] cliches are all true. Oh my god, it goes so fast.
[05:05:19] so fast. >> And I remember my now 13-year-old being
[05:05:23] >> And I remember my now 13-year-old being one, being two. I'm like, this was just
[05:05:25] one, being two. I'm like, this was just yesterday. And the reason it's a cliche
[05:05:28] yesterday. And the reason it's a cliche is because it's a shared experience.
[05:05:30] is because it's a shared experience. Cliches are good. They remind you that
[05:05:33] Cliches are good. They remind you that you are part of the human experience and
[05:05:36] you are part of the human experience and others have been here before you.
[05:05:39] others have been here before you. >> I have to ask you, you mentioned the
[05:05:40] >> I have to ask you, you mentioned the amazing woman um and and great cook.
[05:05:43] amazing woman um and and great cook. >> Amazing. Amazing.
[05:05:44] >> Amazing. Amazing. >> Very important to remember. Not
[05:05:46] >> Very important to remember. Not wonderful. Amazing.
[05:05:48] wonderful. Amazing. >> Amazing. So there's this you talked you
[05:05:50] >> Amazing. So there's this you talked you talked some about croissants or
[05:05:52] talked some about croissants or something. I saw this
[05:05:55] something. I saw this in a tweet. So, is the the Danish
[05:05:57] in a tweet. So, is the the Danish croissants somehow better?
[05:05:59] croissants somehow better? >> Actually, Danish croissants are not
[05:06:00] >> Actually, Danish croissants are not particularly good. In my opinion, the
[05:06:02] particularly good. In my opinion, the only place you can find a half decent
[05:06:04] only place you can find a half decent croissant of all places is 7-Eleven,
[05:06:07] croissant of all places is 7-Eleven, which is hilarious to me because
[05:06:08] which is hilarious to me because 7-Eleven in the US is the place where,
[05:06:11] 7-Eleven in the US is the place where, at least in Chicago, you'd go to get a
[05:06:13] at least in Chicago, you'd go to get a slushie and try to avoid getting
[05:06:15] slushie and try to avoid getting murdered. Yeah.
[05:06:16] murdered. Yeah. >> But in Denmark, 7-Eleven is this very
[05:06:18] >> But in Denmark, 7-Eleven is this very upscale, super nice convenience store,
[05:06:22] upscale, super nice convenience store, and they just happen to make decent
[05:06:24] and they just happen to make decent croissants. Yeah.
[05:06:26] croissants. Yeah. >> And it always baffled me that I lived in
[05:06:29] >> And it always baffled me that I lived in the United States for 20 years. I have
[05:06:32] the United States for 20 years. I have yet to have a single croissant that's
[05:06:35] yet to have a single croissant that's even at the level of a 7-Eleven
[05:06:37] even at the level of a 7-Eleven croissant in Copenhagen. That seems
[05:06:42] croissant in Copenhagen. That seems >> understood why.
[05:06:44] >> understood why. >> No, I've I've legitimately considered
[05:06:46] >> No, I've I've legitimately considered hiring an investigative journalist to
[05:06:48] hiring an investigative journalist to get to the bottom of this because the
[05:06:50] get to the bottom of this because the number of theories I've heard have been
[05:06:52] number of theories I've heard have been all over the place. It's the water. It's
[05:06:54] all over the place. It's the water. It's the butter. It's the skill. It's the
[05:06:57] the butter. It's the skill. It's the this, it's the that, it's the other
[05:06:58] this, it's the that, it's the other thing. I'm like, none of it adds up to
[05:07:00] thing. I'm like, none of it adds up to me. If it's the butter, can't you just
[05:07:02] me. If it's the butter, can't you just import it? I thought I saw Danish butter
[05:07:05] import it? I thought I saw Danish butter in some uh supermarkets over here, the
[05:07:07] in some uh supermarkets over here, the lure. So, that can't be it. Can it be
[05:07:10] lure. So, that can't be it. Can it be the skill? No, it can't be the skill.
[05:07:11] the skill? No, it can't be the skill. There are plenty of French people and
[05:07:12] There are plenty of French people and Belgian people, the best croissant
[05:07:15] Belgian people, the best croissant makers in the world who live in the US.
[05:07:16] makers in the world who live in the US. Like, what is the reason? And then I get
[05:07:19] Like, what is the reason? And then I get the second thing, which is, no, no, you
[05:07:21] the second thing, which is, no, no, you just haven't gone to the to the right
[05:07:22] just haven't gone to the to the right place. I've literally gone to 15 of
[05:07:25] place. I've literally gone to 15 of quote unquote the right place and all
[05:07:27] quote unquote the right place and all the croissants were Yeah.
[05:07:28] the croissants were Yeah. >> So before I leave the planet, I have to
[05:07:32] >> So before I leave the planet, I have to get to the bottom of why the United
[05:07:34] get to the bottom of why the United States cannot make a proper croissant.
[05:07:36] States cannot make a proper croissant. And I don't I'm not even asking about
[05:07:38] And I don't I'm not even asking about peak
[05:07:40] peak French croissants, peak Belgian
[05:07:42] French croissants, peak Belgian croissants, which are the best
[05:07:42] croissants, which are the best croissants in the world. I'm just asking
[05:07:44] croissants in the world. I'm just asking about the 7-Eleven croissant from
[05:07:46] about the 7-Eleven croissant from Copenhagen.
[05:07:48] Copenhagen. Is that too much to ask for?
[05:07:49] Is that too much to ask for? >> That's
[05:07:52] >> That's fascinating. mystery. Uh, what zooming
[05:07:55] fascinating. mystery. Uh, what zooming out, what's your what's your favorite
[05:07:56] out, what's your what's your favorite This makes me want to know. What's your
[05:07:58] This makes me want to know. What's your favorite meal? Like if if I gave you a
[05:08:00] favorite meal? Like if if I gave you a last meal, what to murder you after?
[05:08:02] last meal, what to murder you after? >> It all depends whether it's lunch or
[05:08:04] >> It all depends whether it's lunch or it's dinner. If it's lunch, it
[05:08:05] it's dinner. If it's lunch, it >> it's one meal. What's it was I I feel
[05:08:08] >> it's one meal. What's it was I I feel like if you're getting murdered,
[05:08:10] like if you're getting murdered, it doesn't really matter if it's lunch
[05:08:11] it doesn't really matter if it's lunch or dinner.
[05:08:12] or dinner. >> Depends on what time of day you're
[05:08:13] >> Depends on what time of day you're getting murdered.
[05:08:14] getting murdered. >> Oh, I see.
[05:08:14] >> Oh, I see. >> If I If it's a If it's an afternoon
[05:08:16] >> If I If it's a If it's an afternoon execution, I only get lunch.
[05:08:19] execution, I only get lunch. >> Okay. And if I get lunch, it's at um
[05:08:23] >> Okay. And if I get lunch, it's at um Louisiana,
[05:08:25] Louisiana, the museum in north of Copenagen. I was
[05:08:30] the museum in north of Copenagen. I was just there with Jamie
[05:08:32] just there with Jamie >> uh two days ago and we go there all the
[05:08:34] >> uh two days ago and we go there all the time. The museum is lovely. We don't go
[05:08:37] time. The museum is lovely. We don't go for the museum. We go for the cafeteria.
[05:08:39] for the museum. We go for the cafeteria. That in itself sounds crazy. Like you're
[05:08:41] That in itself sounds crazy. Like you're going to you're going to drive half an
[05:08:42] going to you're going to drive half an hour to go to a cafeteria. Well, it just
[05:08:44] hour to go to a cafeteria. Well, it just so happens to be it is the best lunch
[05:08:48] so happens to be it is the best lunch I've probably ever had in my life. The
[05:08:50] I've probably ever had in my life. The chef there is just unbelievably
[05:08:53] chef there is just unbelievably good. And not only is the food amazing,
[05:08:56] good. And not only is the food amazing, what's even more amazing to my system
[05:08:59] what's even more amazing to my system thinking brain is that at any one time
[05:09:01] thinking brain is that at any one time when we were up there, I think there
[05:09:02] when we were up there, I think there were probably 200 people waiting for the
[05:09:04] were probably 200 people waiting for the food and our food was delivered in 5
[05:09:08] food and our food was delivered in 5 minutes. They have a small menu and
[05:09:11] minutes. They have a small menu and clearly they make it in bulk and it's
[05:09:13] clearly they make it in bulk and it's unbelievably
[05:09:15] unbelievably delicious.
[05:09:16] delicious. >> Just a cafeteria at a museum.
[05:09:18] >> Just a cafeteria at a museum. >> It's a cafeteria at a museum that
[05:09:19] >> It's a cafeteria at a museum that happens to have the best lunch I've ever
[05:09:21] happens to have the best lunch I've ever had.
[05:09:21] had. >> What kind of food are we talking about?
[05:09:22] >> What kind of food are we talking about? What's What kind of lunch?
[05:09:23] What's What kind of lunch? >> It's like Nordic cuisine. So it's it's
[05:09:26] >> It's like Nordic cuisine. So it's it's the funny thing is the menu when I look
[05:09:27] the funny thing is the menu when I look at it I was like do you know what? If I
[05:09:29] at it I was like do you know what? If I saw this menu as a kid I'd go like I'm
[05:09:31] saw this menu as a kid I'd go like I'm not eating here. It's like I don't know
[05:09:34] not eating here. It's like I don't know fruit fruit and and onions and all sorts
[05:09:37] fruit fruit and and onions and all sorts of healthy stuff. That sounds
[05:09:38] of healthy stuff. That sounds disgusting. And then you sit down and
[05:09:40] disgusting. And then you sit down and eat it and the angels sing. But it's
[05:09:43] eat it and the angels sing. But it's even more particular than that. It's the
[05:09:45] even more particular than that. It's the butter.
[05:09:46] butter. >> Yeah.
[05:09:47] >> Yeah. >> The whipped butter that they have there.
[05:09:49] >> The whipped butter that they have there. The best butter anywhere in the world.
[05:09:50] The best butter anywhere in the world. >> I think that has to be connected to the
[05:09:52] >> I think that has to be connected to the cross.
[05:09:53] cross. >> There must be some connection. But
[05:09:54] >> There must be some connection. But literally, even in
[05:09:57] literally, even in Paris, I've never had whipped butter
[05:10:00] Paris, I've never had whipped butter that tastes as delicious as the butter
[05:10:03] that tastes as delicious as the butter does at Louisiana in Copen. Literally, I
[05:10:05] does at Louisiana in Copen. Literally, I would drive 30 minutes
[05:10:07] would drive 30 minutes >> to have bread and butter at the
[05:10:09] >> to have bread and butter at the cafeteria in Louisiana.
[05:10:10] cafeteria in Louisiana. >> Well, how did you discover that? Just
[05:10:12] >> Well, how did you discover that? Just one day you went to the museum and
[05:10:14] one day you went to the museum and >> I think we just went to the museum
[05:10:15] >> I think we just went to the museum >> and you tried and we had the lunch and
[05:10:17] >> and you tried and we had the lunch and we were like,
[05:10:19] we were like, >> "This is weird. This is rivaling the
[05:10:21] >> "This is weird. This is rivaling the best tasting restaurants I've ever been
[05:10:24] best tasting restaurants I've ever been to in my life. And I've gone to NMA a
[05:10:26] to in my life. And I've gone to NMA a couple of times and
[05:10:28] couple of times and tried what there is to try and this is
[05:10:31] tried what there is to try and this is right up there."
[05:10:32] right up there." >> All right. What about dinner? Since you
[05:10:34] >> All right. What about dinner? Since you mentioned, is it something different?
[05:10:36] mentioned, is it something different? Did you have to think?
[05:10:37] Did you have to think? >> Well, I think there's a lot of good
[05:10:38] >> Well, I think there's a lot of good options in uh Copenhagen, but actually
[05:10:41] options in uh Copenhagen, but actually I'll pick a place in Spain. So, there is
[05:10:45] I'll pick a place in Spain. So, there is um
[05:10:46] um this place in Maya called Pente Romano.
[05:10:50] this place in Maya called Pente Romano. It's a hotel and down by the beach they
[05:10:53] It's a hotel and down by the beach they have this beach restaurant with fresh
[05:10:55] have this beach restaurant with fresh seafood.
[05:10:58] seafood. >> Unbelievably
[05:11:00] >> Unbelievably delicious.
[05:11:01] delicious. I'm trying to remember what it's called,
[05:11:03] I'm trying to remember what it's called, but yeah, if you look it up, the beach
[05:11:05] but yeah, if you look it up, the beach seafood place at Pentto Romano is
[05:11:08] seafood place at Pentto Romano is incredible.
[05:11:09] incredible. >> How much of great food is like the place
[05:11:12] >> How much of great food is like the place and the the person you're with, right?
[05:11:14] and the the person you're with, right? Or the or the experience when you first
[05:11:17] Or the or the experience when you first are there.
[05:11:18] are there. >> I mean, the ambiance certainly helps,
[05:11:20] >> I mean, the ambiance certainly helps, but I think my taste buds are also just
[05:11:23] but I think my taste buds are also just in legit. It's just good food. It's just
[05:11:25] in legit. It's just good food. It's just really good food
[05:11:27] really good food because for that cafeteria it is there's
[05:11:31] because for that cafeteria it is there's a lot of people like I wouldn't rate it
[05:11:33] a lot of people like I wouldn't rate it as like oh my god this is just a place I
[05:11:34] as like oh my god this is just a place I want to sit for two hours but the food
[05:11:36] want to sit for two hours but the food is so delicious. That's one of the
[05:11:38] is so delicious. That's one of the things I'm in traveling across the
[05:11:41] things I'm in traveling across the country I'm realizing it's a
[05:11:44] country I'm realizing it's a sample without bias just try things.
[05:11:47] sample without bias just try things. >> Yeah
[05:11:48] >> Yeah >> cuz you might I guess you might just be
[05:11:50] >> cuz you might I guess you might just be surprised. Maybe I'll find your cross.
[05:11:53] surprised. Maybe I'll find your cross. All right, we've talked about mortality,
[05:11:56] All right, we've talked about mortality, talked about food,
[05:11:57] talked about food, >> settled end of life. Uh,
[05:11:58] >> settled end of life. Uh, >> what do you uh thousand years from now,
[05:12:00] >> what do you uh thousand years from now, what do you think is the future of
[05:12:02] what do you think is the future of humans, human civilization? You think
[05:12:03] humans, human civilization? You think we're going to make it
[05:12:04] we're going to make it >> a thousand years from now?
[05:12:06] >> a thousand years from now? >> Yeah,
[05:12:06] >> Yeah, >> man. I'm having trouble predicting 12
[05:12:09] >> man. I'm having trouble predicting 12 months from now.
[05:12:10] months from now. >> I know.
[05:12:10] >> I know. >> Thousand.
[05:12:11] >> Thousand. >> You think we got a shot?
[05:12:12] >> You think we got a shot? >> I'm I'm going to bet on optimism. I'm
[05:12:13] >> I'm I'm going to bet on optimism. I'm going to bet on multilanetary species.
[05:12:16] going to bet on multilanetary species. I'm going to bet that um Elon get that
[05:12:18] I'm going to bet that um Elon get that rocket to Mars and we figure out how to
[05:12:20] rocket to Mars and we figure out how to bend uh space time and discover some
[05:12:23] bend uh space time and discover some wormholes or or something.
[05:12:25] wormholes or or something. >> Once we do, do you think you think all
[05:12:28] >> Once we do, do you think you think all humans on Earth will die once or twice
[05:12:30] humans on Earth will die once or twice and be repopulated
[05:12:33] and be repopulated after we get a good backup going?
[05:12:36] after we get a good backup going? >> I mean, that was actually one of my
[05:12:37] >> I mean, that was actually one of my favorite episodes of Black Mirror, the
[05:12:40] favorite episodes of Black Mirror, the one where they get uploaded to the 1980s
[05:12:43] one where they get uploaded to the 1980s sea town somewhere. Um, and I just
[05:12:46] sea town somewhere. Um, and I just thought like, wow, this is both such a
[05:12:48] thought like, wow, this is both such a dark moment yet also so beautiful in the
[05:12:52] dark moment yet also so beautiful in the shared recognition that like the '8s
[05:12:53] shared recognition that like the '8s were actually kind of amazing.
[05:12:56] were actually kind of amazing. Like I don't have a lot of nostalgia for
[05:12:58] Like I don't have a lot of nostalgia for many moments, but I do have nostalgia
[05:13:00] many moments, but I do have nostalgia for the 80s. And they say something
[05:13:03] for the 80s. And they say something about like whatever place in time you
[05:13:05] about like whatever place in time you were in, the music you were listening to
[05:13:06] were in, the music you were listening to when you were 12 or or 14, 15, something
[05:13:09] when you were 12 or or 14, 15, something like that. That's what's going to stick
[05:13:10] like that. That's what's going to stick with you. like, no, I was only I got to
[05:13:13] with you. like, no, I was only I got to be 10 in the 80s. So, this was my early
[05:13:16] be 10 in the 80s. So, this was my early childhood and I still have an
[05:13:18] childhood and I still have an unbelievably fond affiliation with the
[05:13:21] unbelievably fond affiliation with the 80s. So, if I'm going to be uploaded to
[05:13:23] 80s. So, if I'm going to be uploaded to this guy,
[05:13:24] this guy, >> you want it to be the '8s.
[05:13:25] >> you want it to be the '8s. >> I'm doing the 80s.
[05:13:26] >> I'm doing the 80s. >> Wow. I don't think I've actually ever
[05:13:28] >> Wow. I don't think I've actually ever heard anyone say that. Usually 70s or
[05:13:31] heard anyone say that. Usually 70s or 90s. The 80s is
[05:13:33] 90s. The 80s is >> I really
[05:13:36] >> I really don't like the ' 90s. Can we talk about
[05:13:38] don't like the ' 90s. Can we talk about this? No,
[05:13:41] this? No, >> to me this was the great turning point
[05:13:43] >> to me this was the great turning point of nihilism that both the music, the
[05:13:48] of nihilism that both the music, the genre, the fashion, everything turned
[05:13:52] genre, the fashion, everything turned from like this glamour, the pop, the
[05:13:55] from like this glamour, the pop, the optimism, even the yuppies and
[05:13:57] optimism, even the yuppies and everything to grunge and
[05:14:00] everything to grunge and >> navana. And even though I mean I I like
[05:14:03] >> navana. And even though I mean I I like the music, I don't like the ethics. I
[05:14:05] the music, I don't like the ethics. I don't like the morals. I don't like any
[05:14:07] don't like the morals. I don't like any of the underpinnings to it. There was
[05:14:08] of the underpinnings to it. There was just such a
[05:14:10] just such a >> defeatism to it that in retrospect, I
[05:14:13] >> defeatism to it that in retrospect, I look back upon it, if I'm going to get
[05:14:14] look back upon it, if I'm going to get reinserted into the Matrix, it's going
[05:14:16] reinserted into the Matrix, it's going to be the '8s.
[05:14:18] to be the '8s. >> That was full of optimism and fun. Yes.
[05:14:21] >> That was full of optimism and fun. Yes. >> And colors.
[05:14:22] >> And colors. >> Yes.
[05:14:24] >> Yes. I remember having these orange pants.
[05:14:29] I remember having these orange pants. >> Yeah.
[05:14:29] >> Yeah. >> With like white dots on them. That was
[05:14:32] >> With like white dots on them. That was just a normal thing kids could wear in
[05:14:34] just a normal thing kids could wear in the 80s. I've never seen that
[05:14:38] the 80s. I've never seen that today. Um or I mean even in the '9s it
[05:14:42] today. Um or I mean even in the '9s it all turned just like Seattle gray.
[05:14:45] all turned just like Seattle gray. >> Great regression.
[05:14:46] >> Great regression. >> So they nian, you know this idea of
[05:14:49] >> So they nian, you know this idea of eternal recurrence. If you do a
[05:14:51] eternal recurrence. If you do a groundhog day and you live forever, you
[05:14:53] groundhog day and you live forever, you wanted to be in the orange pants with
[05:14:55] wanted to be in the orange pants with the white dots.
[05:14:56] the white dots. >> Maybe skip the orange pants, but I'm
[05:14:58] >> Maybe skip the orange pants, but I'm definitely picking the 80s.
[05:14:59] definitely picking the 80s. >> You said it.
[05:15:01] >> You said it. All right, DJ. Thank you so much for
[05:15:03] All right, DJ. Thank you so much for everything you do. Thank you for being
[05:15:04] everything you do. Thank you for being inspiration to all of us, for building
[05:15:07] inspiration to all of us, for building cool in the world, and uh thank you
[05:15:10] cool in the world, and uh thank you for talking today.
[05:15:12] for talking today. >> Anytime. Thank you, Lex again for having
[05:15:14] >> Anytime. Thank you, Lex again for having me.
[05:15:15] me. >> Thanks for listening to this
[05:15:16] >> Thanks for listening to this conversation with DHH. To support this
[05:15:19] conversation with DHH. To support this podcast, please check out our sponsors
[05:15:20] podcast, please check out our sponsors in the description where you can also
[05:15:23] in the description where you can also find links to contact me, ask questions,
[05:15:26] find links to contact me, ask questions, give feedback, and so on. And now, let
[05:15:28] give feedback, and so on. And now, let me leave you with some words from Ralph
[05:15:29] me leave you with some words from Ralph Waldo Emerson.
[05:15:32] Waldo Emerson. Once you make a decision, the universe
[05:15:34] Once you make a decision, the universe conspires to make it happen. Thank you
[05:15:37] conspires to make it happen. Thank you for listening and hope to see you next
[05:15:40] for listening and hope to see you next time.

All frames

Total: 80. Hero frames flagged with star.

• frames/frame_0001.jpg (t=00:00) frames/frame_0002.jpg (t=04:33) frames/frame_0003.jpg (t=13:09) frames/frame_0004.jpg (t=15:34) frames/frame_0005.jpg (t=26:40) frames/frame_0006.jpg (t=39:20) frames/frame_0007.jpg (t=43:40) frames/frame_0008.jpg (t=44:49) frames/frame_0009.jpg (t=57:10) frames/frame_0010.jpg (t=01:03:19) frames/frame_0011.jpg (t=01:04:17) frames/frame_0012.jpg (t=01:04:43) frames/frame_0013.jpg (t=01:04:52) frames/frame_0014.jpg (t=01:05:54) frames/frame_0015.jpg (t=01:06:36) frames/frame_0016.jpg (t=01:23:04)
• frames/frame_0017.jpg (t=01:27:27) frames/frame_0018.jpg (t=01:32:37) frames/frame_0019.jpg (t=01:39:48) frames/frame_0020.jpg (t=01:43:11) frames/frame_0021.jpg (t=01:43:31) frames/frame_0022.jpg (t=01:43:33) frames/frame_0023.jpg (t=01:43:56) frames/frame_0024.jpg (t=01:43:58) frames/frame_0025.jpg (t=01:44:15) frames/frame_0026.jpg (t=01:44:16) frames/frame_0027.jpg (t=01:44:45) frames/frame_0028.jpg (t=01:46:35) frames/frame_0029.jpg (t=02:02:31) frames/frame_0030.jpg (t=02:10:13) frames/frame_0031.jpg (t=02:10:28) frames/frame_0032.jpg (t=02:12:07)
• frames/frame_0033.jpg (t=02:16:45) frames/frame_0034.jpg (t=02:19:45) frames/frame_0035.jpg (t=02:37:53) frames/frame_0036.jpg (t=02:38:14) frames/frame_0037.jpg (t=02:40:27) frames/frame_0038.jpg (t=02:45:35) frames/frame_0039.jpg (t=02:47:31) frames/frame_0040.jpg (t=02:51:19) frames/frame_0041.jpg (t=02:51:28) frames/frame_0042.jpg (t=02:51:36) frames/frame_0043.jpg (t=02:51:47) frames/frame_0044.jpg (t=02:51:50) frames/frame_0045.jpg (t=02:52:00) frames/frame_0046.jpg (t=02:52:50) frames/frame_0047.jpg (t=02:52:52) frames/frame_0048.jpg (t=02:52:54)
• frames/frame_0049.jpg (t=02:53:10) frames/frame_0050.jpg (t=02:54:20) frames/frame_0051.jpg (t=02:57:10) frames/frame_0052.jpg (t=02:57:14) frames/frame_0053.jpg (t=03:12:49) frames/frame_0054.jpg (t=03:13:10) frames/frame_0055.jpg (t=03:14:30) frames/frame_0056.jpg (t=03:14:45) frames/frame_0057.jpg (t=03:14:49) frames/frame_0058.jpg (t=03:14:51) frames/frame_0059.jpg (t=03:15:00) frames/frame_0060.jpg (t=03:15:40) frames/frame_0061.jpg (t=03:20:16) frames/frame_0062.jpg (t=03:20:31) frames/frame_0063.jpg (t=03:29:43) frames/frame_0064.jpg (t=03:35:18) frames/frame_0065.jpg (t=03:35:44) frames/frame_0066.jpg (t=03:44:18) frames/frame_0067.jpg (t=03:44:42) frames/frame_0068.jpg (t=03:49:58) frames/frame_0069.jpg (t=03:50:29) frames/frame_0070.jpg (t=03:50:33) frames/frame_0071.jpg (t=03:51:34) frames/frame_0072.jpg (t=04:00:33) frames/frame_0073.jpg (t=04:04:00) frames/frame_0074.jpg (t=04:04:18) frames/frame_0075.jpg (t=04:04:21) frames/frame_0076.jpg (t=04:04:53) frames/frame_0077.jpg (t=04:12:56) frames/frame_0078.jpg (t=04:26:15) frames/frame_0079.jpg (t=04:34:47)
• frames/frame_0080.jpg (t=04:35:12)