Y Combinator CEO Garry Tan: Turning Ambitious Misfits into Founders

28:51I like that. What do you wish founders knew about sales coming in? Oh, how hard it is. And I mean, you know, like it or not, you know, the ideal founder is someone who has lived like 20 lifetimes and has the skills of 20 people. And the thing is, you know, you can't get that. And so probably the first conference that we had, the first mini conference we have when we welcome the batch in is the sales mini conference. And essentially, it is don't run away from the know. Spencer Skates of Amplitude has this great analogy that he told some companies when he came by to speak recently that I've been thinking a lot about, which is sales is about having 100 boxes in front of you and maybe five or six of those boxes has a gold nugget in them.

29:45And if you haven't done sales before, you think, I really, I'm going to gingerly, in a very gingerly way, open that first box and hope, hope, hope that, you know, I have a gold nugget. And then, you know, I almost don't want to know that there isn't a gold nugget in there. Like I'm so afraid of rejection. It's sort of remarkable how often high school and family and the 10 ,000 hours of human training people get from their childhoods comes up in Paul Graham's essays. I always think about that because I think that most people's backgrounds just don't prepare them for sale. It's a very unnatural thing to do sales.

30:26But then the sooner that you acquire those skills, like the more free you become. And what Spencer says about those hundred boxes is instead of like being incredibly afraid of, you know, getting an F or, you know, nothing's going to happen to you, just like flip open all hundred boxes immediately. And then, you know, you should aggressively try to get to a no. And, you know, you'd rather get a no so you can spend less time on that lead and you can get onto the next one. I mean, I think that that's like a very interesting example of the mindset shift that you can read about, but you sort of need, it takes a village.

31:05Like you sort of need to be around lots and lots of people for whom that is true, that has been true. And I think that maybe that's actually one of the reasons why YC startups are much more successful. Like other people give as much money or, you know, as you said, like venture capital, VC firms tend to give a lot more money. I mean, there are clones of YC right now that give like twice as much money, for instance, but I don't think that they're going to see this level of success because they're not going to have as earnest people who become as formidable around you. It's actually a process. It's so interesting to me because as you're saying that, there's something that strikes me about the simplicity of what you're doing.

31:50and then also like Berkshire Hathaway. You know, everybody's tried to replicate Berkshire Hathaway, but they can't. Yeah. Because they can't maintain the simplicity. They can't maintain the focus. They can't do the secret sauce, which obviously has a lot to do with Charlie Munger and Warren Buffett. And with you guys, it has a lot to do with the founders that you attract and you can bring together. But you have billions of dollars effectively trying to replicate it. Nobody's able to do that. I think that's really interesting. And it's not like you're doing something that's super complicated. It doesn't sound like it unless I'm missing something.

32:23It's a very simple sort of process to bring the people together. And obviously there's filtering and you guys are really good at doing that. I mean, what my hope is, I feel like when Paul and Jessica created YC, I went through the program myself in 2008 and I came out transformed. and then that's very explicitly what I want to happen for people who go through the batch today. It isn't just like show up to a bunch of dinners and network with some people who happen to be... It's much deeper than that. I want people to come in maybe with the default worldview and then I want them to come out with a very radically different worldview.

33:11I want someone who is much more earnest, someone who is not necessarily trying to sort of like hack the hack. They're trying to, you know, and I think this mirrors what you were saying from, you know, what, you know, rest in peace Charlie Munger talks about and what Warren Buffett talks about around all of these things are in the short term popularity contests. but in the end all that matters is the weighing machine so you can raise your series a you can throw amazing parties tech crunch can write about you all these twitter anons can fet you as like the next greatest thing and you could get you know hundreds of thousands of followers on x or whatever but you know at the end of the day you look down and did you create something of great value.

34:03Like did you with your hands and, you know, did you assemble people and capital and, you know, create something that, you know, when all is said and done, solve some real problem, put people together, you know, is there real enterprise value? And that's the weighing machine. And, you know, the way that YC makes money, the way that, you know, the founders make money, it's all aligned at that point. Like, yeah, there's like a way to hack the hack. And I don't really know what the end game is on the other stuff. It's just very short term. Whereas, you know, on a 5, 10, 15 year basis, like if you are nose to the grindstone, earnestly working on the thing, you know, you will succeed.

34:52Like I think that that's what Paul Graham's essay about being a cockroach actually is. And that's why 25 % of the people who reach some form of product market fit at YC do it in year five or later. It's like they don't quit year one. They don't quit year two. Like they are learning and growing. I have one other really crazy stat that like I'm thinking about all the time right now. There's a founder – there's a VC actually. His name is Ali Tamasub. He works at Data Collective. He wrote a book called Super Founders. and I get this email from him out of the blue. He says, did you know that about 40 % of the unicorns from the last 10 years in the world were started by multi-time serial founders?

35:37And I was like, okay, that's a cool stat. Like makes sense. Like multi-time founders are, you know, they know a lot more, they have networks, they have access to capital. Like that's not a surprising stat. You know, if anything, it's a little surprising that it's only 40%. Like you would have guessed maybe that was 80. But the thing he said after that really shocked me. He said, did you know that 40, you know, of those 40%, 60 % of those people, the people who created unicorns the last 10 years are YC alumni. Oh, wow. So I'm like, that's crazy. Like, I'm really glad that YC exists now because, you know, even if, YC today is basically a thing that is for first timers.

36:20We do have second timers apply. We do accept them, but we primarily think of the half a million dollars. It really is for people who are starting out. And it's kind of hilarious. I have no product right now for people who are for my YC alums. And maybe that's okay. That's our gift to the rest of Sand Hill Road, because they're the ones who are going to be the fund returners for all of the rest of Sandhill Road. Would you say, in terms of personal characteristics, it sounded like determination was definitely one of the most important outside of the company or venture. What are the other personal skills or behaviors or characteristics that people have that you say you would think correlate to not only the successful first time, but second, third, fourth?

37:12Yeah. I mean, the number one thing that I want that comes to mind for me is, I mean, maybe it's even surprising because that's not a word that you might associate with Silicon Valley founders. I think of the word earnest. What does earnest mean? Like incredibly sincere, I think. Basically, what you see is what you get. Like you're not trying to be something else. It's like authentic, but like, you know, even humble in that respect, right? like I'm trying to do this thing. The opposite, I mean, and it's surprising because I don't know if people associate that with Silicon Valley startups, but I see that in the founders that are the most successful and most durable.

37:55I see it in Brian Armstrong at Coinbase, which is fascinating because that's definitely not the trait that you would apply to most crypto founders. And I would use Sam Bankman-Fried as sort of the opposite of that. Like, you know, Brian Armstrong is an incredibly earnest founder who literally read the Satoshi Nakamoto white paper and said, this is going to be the future. And let me work backwards from that future. You know, when you talk to him, like the reason why he wanted these things like comes directly out of his own experience. I mean, at Airbnb, they were dealing with the financial systems of, you know, myriad countries.

38:39And it's like international, just sending money from one country to another was totally fraught and totally not something that was accessible to normal people. Like remittance is this crazy scam. It's insane how many fees that people have to pay just to send money home or do cross-border commerce, right? So this is something that was incredibly earnest of Brian Armstrong to do. He said, here's a thing that is broken in the world that he saw personally. I think he spent time in, you know, Buenos Aires in Argentina, and he saw hyperinflation. And he said, you know, this is a technology that solves real problems that I have seen hurt people.

39:20And I know that this technology can solve it. And then after that, he's just like nose to the grindstone working backwards from that thing that he wants to create in the world. And, you know, it's no surprise to me. I mean, there were many years in there that I think our whole community were looking at, we were looking at someone like Sam Bankman-Fried and just wondering like, what's going on over there? He speed ran this sort of money power fame game to an extreme degree, so much so that he stole customer funds to do it. And like, that was the answer. Like, that's anti-earnest. That is the definition of, he was a crook.

39:58He's in jail now. and my hope is that people who look, if you just look at Brian Armstrong versus SBF, I'm hoping that young people listening to this right now take that to heart. It's like the things that actually win. And going back to Buffett, I went to their sort of conclave in Omaha. Oh, you went to the Woodstock for capital. Yeah, it was amazing. amazing and I think those guys are by definition extremely earnest you know I don't think it's an affectation I think it's like it's like legit and serious like those guys did everything you know what is it it's their thing right it's um you know work on high class problems with high class people like I mean it's that's very very simple you know just do it the right way right yeah um And so that's what I want.

40:56I think that if YC is the shelling point for earnest, friendly, ambitious nerds to steal something from, you know, I have a friend on Twitter who goes by Visa, VisaCon. And, you know, he has a whole book on it. I think it's called Friendly Ambitious Nerd, if you look it up. I mean, I think that that's what YC by definition should be attracting. And, you know, Brian Armstrong is like the best, one of the best founders I've ever met and gotten the chance to work with and fund. And I think the world desperately needs more people like that, where, you know, in the background, just like consistent, doing the right thing, trying to attract the right people, like, you know, chop wood, carry water, that's it.

41:45he also took a big stand before it became popular uh that the workplace is like a performance place it's not you don't bring all of the your politics and all that stuff in but he did that at a time when it was courageous like it was really he was one of the first people yeah out of the gate and he took so much flack for that yeah and i'm vindicated now i know but i remember reading like his thing and i was like oh this is great but like why why are we why are we even pointing this out, you know? And then he got, like, I read the stuff online. I was like, this is crazy. That's the media environment, right?

42:22I thought it was interesting anyway that he came out and did that. And I think where it relates to the earnestness is only somebody who's really comfortable with themselves and like trying to do good in the world could really come out and take that stand at that point in time. Yeah, that's true leadership. Yeah. What's the biggest unexpected change you've seen in building companies in the AI world? I think the biggest thing that is increasingly true, and we're seeing a lot of examples of it in the last year, is blitzscaling for AI might not be a thing. What's blitzscaling? So I think Reid Hoffman wrote a whole book about it.

43:02It was definitely true in the time of Uber. So that was sort of a moment when interest rates were descending. And then these sort of increasingly international marketplaces, this sort of offline to online marketplaces like Uber in cars or delivery, or you could say Instacart, DoorDash, you could throw in Lyft. There was sort of this whole wave of sort of the top startups were marketplace startups, but also in software too, this idea that scale could be used as a bludgeon, that the network effects grow you know, sort of exponentially. And then because you could have access to more and more capital, whoever raised more money would have won.

43:50And I feel like that was extremely true in that era, sort of the 2010s. And then in the 2020s, especially by, you know, we're in the mid-2020s now, I think that we are seeing incredible revenue growth with way fewer people. And that's very remarkable. We have companies basically going from zero to six million dollars in revenue in six months. We have companies going from zero to 12 million dollars a year in revenue in 12 months, right? And with under a dozen people, like usually five or six people. And so that's brand new.

44:35Like And so that's a big change. Like, you know, I think we are seeing companies that in the next year or two will get$250, $100 million a year in revenue, really with under, you know, maybe 10 people, maybe 15 people tops. And so that was relatively rare. And my prediction would be this becomes quite common. And my hope is that's actually a really good thing. This is sort of the silver lining to what has been really a decade of big tech. It's more and more centralized power. What might happen here and what we're actively trying to do at YC is we hope that there are thousands of companies that each can make hundreds of millions to billions of dollars and give consumers an incredible amount of choice.

45:30and we hope that that will be very different than sort of this. The opposite, I think, was increasingly true. We have fewer and fewer choices in operating systems, in web browsers, across the board, just more and more concentration of power in tech. Two thoughts here. One, how much do you think that cloud computing plays into that? Because now I don't have to buy$6 billion in infrastructure to be that five-person company, I can rent it based on demand. So that's enabled me not to compete on a capital basis. Yeah, that was true. That was even why Y Combinator in 2005 could exist. I remember working at a startup in 1999, 2000, or at internet consulting firms.

46:19And these were million-dollar projects because you had to actually pay$100 ,000 or hundreds of thousands of dollars to Oracle. You had to pay hundreds of thousands of dollars to your colo to rack real servers. So the cost of even starting a company was just huge. Yeah. I mean, I remember Jeff Bezos actually launched AWS at a YC startup school at Stanford campus in 2008, right when I was starting my first company. So I think cloud really opened it up and that's part of the reason why startups could be successful. You didn't need to raise$5,$10 million just to rack your server. And that's the other big shift.

47:04I think in the past, it was very, very common to have Stanford MBAs or Harvard MBAs be the CEO. And then you would have to go get your hacker in a cage. You had to get your CTO. And there was sort of that split. And then now what we're seeing is, you know what, like the CEO of the majority of YC companies, they are technical. Is this the first revolution, like technological revolution where the incumbents have a huge advantage? You know, I think they have an advantage, but it's not clear to me that they are conscious and aware and like at the wheel enough to take real advantage of it because they have too many people.

47:53Right. And then it's all, I mean, I think this is what founder mode is actually about. So last year we had a conference with Brian Chesky. We invited our top YC alums there. We brought Paul and Jessica back from England and we had this one talk that wasn't even on the agenda, but I managed to text Brian Chesky of Airbnb and I got him to come and speak very openly and honestly in front of a crowd of about 200 of our absolute top alumni founders. and he spoke very eloquently and in a raw way about how your company ends up not quite being your own unless you are very explicit like you know I this is actually my company I am actually going to have a hand and a role to play in all the different parts of this company I'm not going to basically the classic advice for management is hire the best people you possibly can, and then give them as much rope as you possibly can.

49:04And then somehow that's going to result in good outcomes. And then I think in practice, and this is sort of the reaction that is turning out to create a lot of value across our community, certainly. But I think the memes are out there, and it's actually changing the way people are running businesses. It's sort of a shade of what you were saying earlier with Brian Armstrong, like, you know, you can sit back and allow your executives to sort of run amok. And, you know, if the founder and the CEO does not exercise agency, you know, then it's actually a political game. And then you have sort of fiefdoms that are fighting it out with one another.

49:45And the leader is not there, then you enter the situation where neither the leader nor the executives have power or control or agency. And then you have, everyone's disempowered. Everyone is making the wrong choice. Retention is down. You're wasting money. You have lots and lots of people who are sort of working either against each other or not working at all. And that's, I think, a pretty crazy dysfunction that took hold across arguably every Silicon Valley company, period. And it's still mainly in power at quite a few of those companies, actually. Though I think people are aware now that that's not the way to run your company.

50:33Are the bigger companies shaping up? The way that I think about this analogy is if I'm the young skinny kid and I'm competing against the fat bloated company, I want to run upstairs. It's going to suck for me, but it's going to suck way more for them. Right. I think this is maybe a function of, you know, blitzscaling and using capital as a bludgeon like gone wrong. You know, you can look at, you know, almost any of these companies, they probably hired way too many people. And at some point they were viewing smart people as, maybe a hoarded resource. If you were playing some sort of adversarial StarCraft and you didn't want...

51:21The ironic thing is they themselves were not using the resources properly either. They just didn't want somebody else to have them. Exactly. I guess it felt like a little bit of a prisoner's dilemma because I think the result is that tech progress itself decelerated. You have like the smartest people of a generation basically retired in place, working at places that, you know, the world is actually full of problems. Like why are people sort of retired in place, pulling down, you know, insane by average American standards, absolutely insane salaries to build software that, you know, doesn't change, doesn't get better.

52:05I mean, sometimes I sit there and I run into a bug, whether it's a Google product or an Apple product or Facebook or whatever. I'm like, this is an obvious bug. And I know that there are teams out there, there are people getting paid millions of dollars a year to make some of the worst software. And it will never get fixed because there's no way, people don't care, no one's paying attention. Yeah, that's just one symptom out of a great many that is the result of, I don't know, basically treating people like hoarded resources instead of like, the world is full of problems. Let's go solve those things.

52:45When it comes to AI, the raw inputs, I guess if you think about it that way, are sort of the LLM. Then you have power, you sort of have compute, you have data. where do you think incumbents have an advantage and where do you think startups can successfully compete? Yeah, I mean, we had a little bit of a scare, I think, last year with AI regulation that was potentially premature. So, you know, there was sort of a moment maybe a year or two ago, and you sort of see it in the shades of it did make it into, say, Biden's EO. These sort of, you know, passed a certain amount of mathematical operations, like that's banned or not banned, but we require all of this extra regulation.

53:33You have to report to the state. You better get a license. That felt like the early versions of potentially regulatory capture where they wanted to restrict open source. They wanted to restrict the number of different players. sitting here a year after a lot of those attempts, I feel pretty good because it feels like there are five, maybe six labs, all of whom are competing in a fair market, trying to deliver models that honestly, any startup, anyone, any of us could just pick and choose. And there's no monopoly danger. There's no crazy pricing power that one person, one entity wields over the whole market.

54:23And so I think that that's actually really, really good. I think it's a much fairer playing field today. And then I think it's interesting because it's an interesting moment. I think that basically there's a new Google-style sort of oligopoly that's emerging around who provides the AI models. But because it probably won't be a monopoly, that's probably the best thing for the consumer and for actually every citizen of the world. Because you're going to have choice. Let's go deeper on the regulation and then come back to sort of competition. And how would you regulate AI or how do you think it should be regulated or do you think it should be regulated?

55:11It's a great question. I guess there are a bunch of different models that I could see happening. You know, I think what's emerging for me is that the two things that I think, I think the first wave of people who are really worried about AI safety, not to be flippant, but like my concern is that they basically watch Terminator 2, you know, and I'm like, I like that movie. too, but you're right now, you know, there's sort of that moment in the movie where they say suddenly the AI becomes self-aware and it becomes, you know, it takes agency, right? And I think the funny thing, at least as of today, you know, these systems are, it's just matrix math and there is no agency yet.

56:03Like there's basically, they're equivalent to incredibly smart toasters. And some people are actually kind of disappointed in that. And personally, I'm very relieved and I hope it stays that way because that means that there's still going to be a clear role for humans in the coming decades. And I think it takes the form of two very important things. One is agency. I mean, people often ask, like, what should we be teaching our kids? And, you know, the ironic thing is we send them to a school system that is not designed for agency. It is literally designed to take agency away from our children. And maybe that's a bad thing, right?

56:48Like, we should be trying to find ways to give our children as much agency as possible. That's why I'm actually personally pretty pro screens and pro Minecraft and Roblox and, you know, giving children like this sort of playground where they can exercise their own agency. Have you tried Synthesis Tutor? Oh, yeah. Yeah, I'm a small personal investor in them. And, you know, I think that we're just scratching the surface on how education will actually change. But that's a great example. But those synthesis is designed around trying to help people have, help children actively be in these games that increase instead of decrease agency.

57:30And it's crazy. So it teaches the kids math. And my understanding just from reading a little bit is El Salvador just replaced like the K through five math with synthesis tutor. And the results are like astounding. Incredible. Yeah, it's way better. I mean, the kids get involved and they're obviously invested in it. the regulation question is really interesting too because it begs the question of it's a worldwide industry and so regulating something in one country be it the United States or another country doesn't change what people can do in other countries and yet you're competing on this global level yeah I think the biggest question around it is of course I mean the existential fear is like where are all the jobs going to go and then my hope is that it's actually two things.

58:19One is like, I think that robotics will play a big key role here, where I think that if we can actually provide robots to people that do real work for people, that will actually change people's sort of standards of living in like fairly real ways. So I think universal basic robot is relatively important. You know, I think some of the studies coming back about UVI have not, universal basic income where you just give money to people, it's just not really resulting in a different... I think they've never read a psychology textbook. I mean, just going away from the economics of it, people need to feel like they're part of something larger than themselves.

59:03And if they don't feel like they're part of larger than something, like they're contributing to something, they're part of a team, they're bigger than what they are as a person, then it leads to all these problems. Yeah, exactly. And then I think that we really need to actually give everyone on the planet some real reason why this stuff is actually good for them, right? I think if there is only sort of a realignment without a material increase in people's day-to-day livelihoods and their quality of life, like maybe we're doing something wrong actually and left to its own devices like it's you know it's possible so i don't know what the specific things are but i think that that's what it would look like you know if if regulation were come to come into play or there was some sort of realignment in reaction to you know the nature of work changing um that would be the outcome that the majority of people, if not all people, see the benefit in some sort of direct way.

1:00:13And if we don't do that, then there will be unrest. I think that that's one of the criteria. I don't have the answer, but I think that's one of the things I'd be on the lookout for. At what point do you think the models start replacing the humans in terms of developing the models? So at what point are the models doing the work of the humans in OpenAI right now? and they're actually better than the humans at improving the model. Yeah, we're not there yet. So there's some evidence that synthetic data is working. And so some people believe that synthetic data is, you know, where the models are like sort of self-bootstrapping.

1:00:50So just to explain to people, synthetic data is when the model creates data that it trains itself on. That's right. And so I guess the other really big shift is actually test time compute. Like literally 01 Pro is this thing that you can pay$200 a month for. And it actually just spends more time at the sort of query level. It might come back, you know, five minutes, 10 minutes later. But it will be much more correct than sort of the, you know, predict next token version that you might get out of, you know, standard chat GPT. yeah from from what i can tell that's where a lot of the wilder things might come out um you know level four agi as defined by open ai is uh innovators so we have you know lots of startups both yc and not yc that are trying to test that out right now they're trying to apply um the latest reasoning models from open ai that are about to come out you know like 03 and O3 Mini, and they're trying to apply them to actually scientific and engineering use cases.

1:02:01So there's a cancer vaccine biotech company called Helix that did YC a great many years ago, but what they've figured out is they can actually hook up some of these models to actual wet lab tests. And that's something that I'd be keeping track of over the next couple years. If only by applying dollars to energy that then goes into these models, will there be real breakthroughs in biological sciences, like being able to do new processes or come to a deeper understanding of whether it's cancer or cancer treatment or anything in biotech. The first experiments of that sort, that's happening in the next year.

1:02:54Even in computer-aided design and manufacturing, I mean, there's a YC company called Camfer that is trying to apply. They actually were one of the winners of the recent YC01 hackathon we hosted with OpenAI. And their winning entry was literally hooking up 01 to airfoil design. So being able to increase the sort of lift ratio just by applying, you know, spend more time thinking about this. And it's able to create a better and better airfoil given a certain number of constraints. So, you know, obviously these are like relatively early and toy examples, but I think it's a real sort of optimistic point around how do we increase the standard of living and push out like sort of the light cone of all human knowledge, right?

1:03:52That is a fundamental good for AI. Between that and the inroads it might make in education, these are some real white pill things that I think are going to happen over the next 10 years. And these are the ways that AI becomes not Terminator 2, but instead the age of intelligence, as Sam pointed out in a recent essay. I think that if we can create abundance, if we can increase the amount of knowledge and know-how and science and technology in the world that solves real problems, and I don't think it's going to happen on its own. Each of these examples are, there's frankly a YC startup right there on the edge trying to take these models and then apply them to domains.

1:04:49you know, Google probably could have done what Airbnb did, but it didn't because Google's Google, right? And so in the same way, I think that whether it's OpenAI or Anthropic or Meta's lab or DeepSeek or some other lab that wins, I think that we're going to have a bunch of different labs and they're going to serve a certain role like pushing forward human knowledge that way. And then my white pill version of what the world I want to live in is one where our kids or really any kid with agency can get access to a world-class education, can get all the way to the edge of what humans know about and are able to do or able to sort of affect.

1:05:33and then, you know, sort of empowered by these agents, empowered by chat GPT or perplexity or, you know, whatever agent, you know, it's going to look like her from the movie, right? Like we're going to have these, you know, basically super intelligent entities that we talk to. I'm hoping that they don't have that much agency, you know? I'm hoping that actually they are just like sort of these inert entities that are your helpers. And if that's true, that's actually a great scenario to be in. That's the future I want to be in. I don't think anyone wants to be, to borrow a term from Venkatesh Rao, I don't think any of us want to be under the API line of these AIs.

1:06:21And I think that really passes through agency. The minute a robot can do laundry, I'm in. I'll be the first customer. Yeah, there are YC companies and many startups out there that are actively trying to build that right now. My intuition is that it strikes me as immediate progress could come from just ingesting all of the academic papers that have been done on a certain topic and either disproving ones that people think are still correct and thus cutting off research on top of something that's not likely to lead to anything or making connections because nobody can read all these papers and make the connections and make maybe the next leap, right?

1:07:03Like not the quantum leap, but like the next logical step that who's doing that? I mean, that's inevitable. And then someone listening here might want to do it. And then in which case they should apply to YC and maybe we should do a joint request for startup for this next YC batch. I like it. I want equity there. All right. But it's also interesting because then you think about that and you're like, if I'm a government and I'm funding research, that research should all be public because I want people to be able to take it, ingest it, and make connections that we haven't made yet. And it seems like a lot of that research these days is under lock and key.

1:07:37So you get this data advantage in the LLMs where some LLMs buy access or steal access or whatever, have access to it, and then some don't. How do you think about that from a data access LLM quality point of view? It's a good question. I mean, yeah, it's a bit of a gray area these days. I mean, I'm not all the way in. I don't actually run an AI lab, even though I was not actually at one thing. You run the meta AI lab. Yeah, that's right. Not the meta AI lab. Not meta the company, but like meta as in all of them. Yeah, that's a good question. I guess the funniest thing, my main response to all of that around like provenance of the data itself is at some point, like it feels like it actually is fair use though.

1:08:25I mean, that's all the way into case law. Yeah. Well, here's another interesting twist on this then. So the airfoil, they designed this new airfoil. Is that patentable? I mean, at least in terms of like generated images, my understanding is generated images are not copyrightable. But if AI generates not only the science behind it, maybe like we're at a point where maybe in the next couple years, AI is doing more science than we've done. Is that going to be copyrightable or patentable or sort of like withheld or is that public access, public knowledge? My intuition would say people are just going to take the outputs of these AI systems and as far as I know, you can submit a patent and there's not a checkbox yet that says did you use AI as a part of it.

1:09:17Why wouldn't, here's another startup idea for anybody listening that we both want in on. Why wouldn't somebody just read all the patent filings in the US and be like, make the next logical step for me and patent that, like attempt to just patent it. Yeah, people might already be doing it. A one person company could literally ingest the US patent database and be like, okay, here's the innovation in this. What's the next quantum leap or even the next step that's patentable? Okay, automatically file and... You're funded. I'm in. I got two ideas. I love those. I don't know. I think these are all totally open and fair game.

1:09:53And then I guess maybe going back to regulation, that's one of the stranger things that is happening right now. One of the pieces of discourse out there during the AI safety debates, like in the last year, for instance, are about bioterror. And the wild thing is basically possessing instruments of creating bioweapons is already illegal. So do you really need special laws for a scenario that are already covered by laws that exist? I mean, that's just like my sort of rhetorical question back when people are really, really worried about bioterror. I think there's a funny example where AI safety think tanks were in Congress and they were sort of, you know, going to chat GPT and, you know, typing in sort of a doomsday example.

1:10:48And it spits out this, you know, kind of like an instruction manual on like, well, you need to do this, you'd have to acquire this, you know, here's this thing you would do in the lab. And, you know, of course, like those steps are illegal. And then I think a cooler head prevailed in that, you know, the rebuttal was someone next went to Google, entered the same thing and got exactly the same response. So, you know, yes, like I've seen Terminator 2 as well. You know, am I worried about it? You know, my PDOOM score is 1%. Like I'm not totally, you know, unworried, right? It would be a mistake to completely dismiss all worries.

1:11:30It would also potentially be worse to prematurely optimize and basically make a bunch of worthless laws that slow down the rate of progress and prevent things like better cancer vaccines or better airfoils or, you know, frankly, like, you know, nuclear fusion or like clean energy or better solar panels or engineering manufacturing, you know, manufacturing methods that are better than what we have today. I mean, there's so many things that technology could do. Like, why are we going to stand in the way of it until we have a very clear sense, like, that is actually what we need to do? What does scare you about AI?

1:12:09I mean, it's brand new, right? So, the risk is always there. You know, it's so funny, though. I mean, I'm not unafraid. On the other hand, like, this principle of you can just do things still applies to computers. If the system becomes so onerous, maybe you would go and let's shut down the power systems, let's shut down the data centers themselves. Why wouldn't people try to do that? And they might do that. People try to do that every day now, before AI. Right. If it became that bad, I'm sure there would be some sort of human solution to try to fix this. But just because I read about the Butlerian Jihad in the Dune series doesn't mean that I need to live like that's what's going to happen.

1:13:06So you don't believe there's going to be one winner that dominates, like OpenAI or Anthropic? or it might still happen, right? You know, I think that there are lots of reasons why it won't happen right now, but, you know, who's to say? Everything is moving so quickly. Like, I think that, you know, these questions are the right questions to ask. I just don't have the answers to them. Like, I know, but you're the person to ask. It's like asking like, I guess, will Windows or Mac win? Or, you know, we're just literally living through that time where very, very smart people are, you know, fighting over the marbles right now.

1:13:40Totally. And then to me, though, like working backwards, the best scenario is actually one where we have lots of marble vendors and you get choice and nobody has sort of too much control or, you know, cornering of all the resources. What's your read on Facebook almost doing a public good here and spending, you know, I think it's over 50 billion at this point and just releasing everything open source? Yeah, I think that what Zuck and Ahmad and the team over there are doing is frankly God's work. I think it's great that they're doing what they're doing. And I hope they continue. What would you guess is the strategy behind that?

1:14:21It's kind of funny because my critique on Meta would be they very openly put in everyone's faces, right? You can't use Facebook or Instagram or even WhatsApp without seeing like, hey, Meta has AI now. But the funniest thing is I'm very surprised that they don't think about the basic product part of it. I went to Facebook Blue app recently and I was going to Vietnam and I just wanted to say, okay, Meta AI, you're so smart. Tell me my friends in Vietnam. It didn't know anything about me. I'm like, this is some basic rag stuff. I get it. You're already spending billions of dollars on training these things.

1:15:02How about spend a little bit of money on the most basic type of retrieval augmented generation for me? They're just sort of sprinkling it in and it's a little bit of a checkbox. So I'm a little bit mystified, right? If they were very unified about it, I would really get it, right? Clearly, the way that we're going to interface with computers is totally going to change. What Anthropic is doing with computer use is, you know, I think that, you know, what I've heard is basically every major lab is probably going to need to release something like that, whether it's an API the way Anthropic has or literally built into this, you know, the, you know, runtime that you run on your computer.

1:15:47Like there's going to be a layer of intelligence. Like you can sort of see the shade of the very, very dumb version of it from Apple and Apple intelligence. It's like sort of sprinkling in intelligence into notifications and things like that. But I think it's virtually guaranteed that the way we interface with computers will totally change in the next few years. You know, the rate of improvement in the models. as of today, all the smartest things that you might want to do, they're still actually things that you have to go to the cloud for and then that opens a whole can of worms. But there's some evidence that in the frontier research of the best AI labs, it's pretty clear that there's sort of parent models and child models.

1:16:36And so there's distillation happening from the frontier, very largest models with the most data and the most intelligence down into smarter and smarter tiny models. There's a claim this morning that a 1.5 billion parameter model, I think, got 84 % on the AIME math test, which is like a 1.5 billion parameters is like so small that it could fit on anyone's phone. And that was like DeepSeek R1 just got released this morning. So it hasn't been verified yet, but I think it's super interesting. We are literally day to day, week to week, learning more that these intelligent models are going to be on our desktops, in our phones, and we're right at that moment.

1:17:25So is the model better? Is the LLM better? What makes that model so successful with so few parameters? Oh, I don't know. I haven't tried it yet. But, you know, I mean, some of it is you can be very specific about what parts of the domain you keep. Okay. And then, you know, I guess, you know, math might be one of those things that just isn't, you know, it doesn't require, you know, 1.5 trillion parameters. It takes 1.5 billion to do an 84 % job of it, which is pretty wild. I mean, that's another weird thing of AI regulation. You know, I think Biden, for instance, his last EO was sort of this export ban.

1:18:07And DeepSeek is a Chinese company releasing these models open source. And I believe that they only have access to last generation NVIDIA chips. And so, you know, some of it is like, why are we doing these like measures that like may not actually even matter? It's interesting, right? Because you think of constraint being one of the key contributors to innovation. By limiting them, you also maybe enable them to be better because now they have to work around these constraints or presumably have to work around them. I doubt they're actually sort of working around them. That sounds right. I mean, I think the awkward thing about AI regulation is there's something like$4 billion of money sloshing around think tanks and AI safety organizations.

1:18:52And someone was telling me recently, If you looked on LinkedIn for some of the people in these sort of giant NGO morass of think tanks, sorry if people are a part of that and getting mad at me right now hearing this. But there's a lot of people who went from bioterror safety experts to one entry right above that in the last even six or nine months. They've become AI bioterror safety experts. And I'm not saying that's a bad thing, but it's just very telling, right? Anytime you have billions of dollars going into a thing, maybe prematurely, people have to justify what they're doing day to day. And I get it.

1:19:38So many rent seekers. I want to foster an environment of more competition within sort of like general safety constraints. But I don't think we're pushing up against those safety constraints to the point where it would be concerning. But we also operate in a worldwide environment where other people might not think the same way about safety that we do. And then it's almost irrelevant what we think in a world where other people aren't thinking that way and it can be used against us. I think we're going into a very interesting moment right now with, you know, the AI czar is Sri Ram Krishnan, who, you know, used to be a general partner at Andreessen Horowitz.

1:20:16And I think that that's a very, very good thing. We want people who have the networks into people who have built things, who have built things themselves as close to that as possible. And I think that it is actually a real concern that the space is moving so quickly that if it takes legislation two years to make it through, that might be too slow. And so it's sort of even more important that the people who are close to the president and the people who are in the executive branch, at least in the United States, they should be able to respond quickly, whether it's through an EO or other means. I don't know what it's like in the States, but in Canada, I was looking at the Senate the other day and I was just trying to, like, is there anybody under like 60 in the Senate kind of thing?

1:21:03Does anybody understand technology? I'll grow up in the world where, you know, Google became a thing after they were already adults. And it strikes me that there's a difference, the pace of technology improvement versus the pace of law or regulation, but also the people that are enacting those laws don't tend to... They have a different pace as well. Our kids are in a different world. My kids don't know what a world without AI looks like, neither do yours. But we do, because we're similar age. And then, you know, our parents have this other thing where it's like, well, we used to have landline phones and like all of these other things.

1:21:42And it strikes me that those people should maybe not be regulating, you know, AI. That sounds right. I mean, I think it's more profound now than ever before. I mean, the other thing that's really wild to think about is what comes to mind is that meme on the Internet where like there's the guy at this dance. It's just like, you know, that everyone else is dancing and they're in the corner and it's like, they don't know. It's like, you know, if you go almost anywhere in the world, you know, people maybe have heard of ChatGPT. They definitely haven't heard of Anthropic or Claude. Yeah. You know, it just hasn't touched their lives yet.

1:22:21And then meanwhile, like the first thing they do is they look at their smartphone and, you know, they're using Google and, you know, they're addicted to TikTok and things like that. Do you think we get to a point where, and this is very like Ender's Game, if I remember correctly, in the movie where, you know, you pull up an article on a major news site and I pull up an article on a major news site. And at the base, it's sort of like the same article, but now it's catered to you and catered to me based on our political leanings or what we've clicked on or what we've watched before. Well, my hope is that there's such a flowering of choice that it's going to be your choice, actually.

1:23:00I mean, the difficulty is like, well, then you have a filter bubble, but that exists today with social media today.

1:23:11Okay, so here's a white pill that I don't know if it's going to happen, but I hope it happens. you know one of the reasons why it's so opaque today is literally that you know x has you know or x or you know before it was called twitter and twitter had you know thousands of people working at that place and um you know you needed thousands of people maybe right or i guess the tricky thing is like elon came in and quickly asked like 80 or 90 percent of the people and it turns out you didn't need 80 or 90 % of the people. So that's like another form of founder mode taking hold. But like it or not, I can't go into Twitter today and tool around with my 4U, like my 4U is written for me, right?

1:24:00It's in some server someplace and there's a whole infrastructure thing. Yeah, you don't control it. But it's conceivable, you know, today with CodeGen, And, you know, today engineers are basically, you know, writing code about 5 or 10x faster than they would before. And that sort of capability is only getting faster and better. Like it's sort of conceivable that you should be able to just write your own algorithm and maybe you'll be able to, you know, run it on your own and you'll want choice. And so, you know, the kind of regulation that I would hope for is actually open systems, right? I would want to actually write my own version of that.

1:24:41I don't want... The best version of that is actually... I maybe want to see my For You algo very plainly. And then I want to be able to see if I can convert that into the one that I want. Or I can choose from 20 different ones. Two ideas here. As you're mentioning that one, your list could be your default. I want this list to be... But the other one is like maybe there's just 20 parameters and you get to control those parameters. And it could be, you know, you could consider it political as one parameter from left to right. Right. You could be like happy, sad. Like you could sort of filter in that way.

1:25:21I know that'd be super interesting. So, I mean, if regulation is coming, like give me open systems and open choice. And that's, you know, sort of the path towards liberty and, you know, sort of human flourishing. And then the opposite is clearly what's been happening. right? Like Apple, you know, closing off the iMessage protocol so that, you know, it's literally a moat. Like, oh no, like that person has an Android. So they're going to turn our really cool blue chat into a green chat. We don't talk to those people. Yeah, right. I know, right? I mean, that's just a pure example of, you know, Apple, even today still, you know, they're opening it up a little bit more with RCS, but those are actually in reaction to the work of Jonathan Cantor and the DOJ.

1:26:09So there are efforts out there that are very, very much worth our attention around reining in big tech and reining in the ways in which these sort of subtle product decisions only make money for big tech and they reduce choice and ultimately reduce liberty. it'd be super interesting to be able to have an advantage if you're big tech and you're a company and you come up with this but have that advantage erode automatically over time in the sense that you might have a 12-month lead but what you're really trying to do is foster continuous and like if you're a government you're trying to regulate it's like i don't want to give you a golden ticket i want you to have to earn it and you can't be complacent so you have to earn it every day.

1:26:57And so yeah, maybe you have like a two-year window on this blue bubbles and then you have to open it up. But now you got to come up with the next thing. You got to push forward instead of just coasting. Like Apple really hasn't come up with a ton lately. Yeah. And then I think the reason why it's so broken is actually that government ultimately is, you know, very manipulatable by money. And that's sort of the world we live in. Do you think that'll be different under Trump? I don't tend to get into politics here, but so many people in the administration are already incredibly wealthy. Oh, yeah.

1:27:34That's the hope. I mean, we're friends with a great many people who are in the administration. We're very hopeful and we're wishing them... We're hoping that really great things come back. And, you know, in full transparency, like I think I was too naive and didn't understand how anything worked in 2016. That's not what I was saying in 2016. I was fully, you know, an NPC in the system. But, you know, also that being said, I'm a San Francisco Democrat. So I really have very, very little, you know, I have very little special knowledge about how the new administration is going to run, except that I really am rooting for them.

1:28:15I'm hoping that they are able to be successful and to make America truly great. I am 100%, even though I didn't vote for Trump, I am 110 % down for making America truly awesome. What do you believe about AI that few people would agree with you on? It might be that point that I just gave you. I think that a lot of people are hoping that the AI becomes self-aware or have agency. And from here, the kind of world we live in will be very different if somehow the literally AI entities are given. And, you know, maybe the line is actually, will we have an AI CEO? Like, will we have a company that just like literally gives in to, you know, whatever the central entity says, like, that's what we're going to do.

1:29:12Every problem, you know, it's sort of the exact extreme opposite of founder mode. It's like AI mode. like will we live in a world in the future where you know corporations decide like you know what a human is messy and kind of dumb and doesn't have a trillion token context window and like won't be able to do what we wanted to do so we would trust in AI and you know an LLM based consciousness more than a human being like I'd be worried about that I was thinking about this last night watching the football game actually and I was like why are humans still calling plays like yes for coaching but like calling players in the game and AI I feel like at this point with like 01 Pro or something we'd be ahead of where we are as humans I'm wondering if teams should try that that'd be super interesting oh that's going to be the next level of money ball then we'll just try it in preseason or try it in a regular season game I don't know but it strikes me that like they would know who's on the field who's moving slower than normal like all these a million more variables than we can even comprehend or compute or end historical data.

1:30:19You know, the last 16 weeks this team has played, you know, when you run to the right after they just subbed or something, like they can see these correlations that we would never pick up on, not causation, but correlation. It'd be super fascinating. Yeah, I mean, what's funny about it is, I think in those sort of scenarios, you might just see a crazy speed up because of human effects. I mean, when you look at organizations and how they make decisions, so many of them, you know, there's sort of like a Straussian reading of them. There's sort of like at the surface level, you're like, I want to do X.

1:30:58But like right below that is actually something that is not about X. You know, for a corporation, it has to be like, we have a fiduciary duty to our shareholders and we need to maximize profit, for instance. And then right below that, corporations or entities of any set of people, they do all sorts of things not for reason X on the top. It's actually like, oh, actually, the people who are really in power don't like that person or they rub them the wrong way. Or human. Yeah, exactly. These are extremely influenceable systems. Your idea might be best, but I'm going to disagree because it's your idea, not my idea.

1:31:40Right. And then I think that's why in general, we really hate politics inside companies. Because it sort of works against the collective. Do you think we'd ever see a city, like a mayor, then first before even a CEO as like an AI mayor? You know, I guess like now that we're sitting here thinking about it, it's like sort of conceivable. But, you know, in sort of all of these cases, I would much rather there be a real human being. kind of like a plane, right? Like we want a physical pilot, even though the plane is probably better off by itself. Yeah, that's right. And that might be what ends up happening.

1:32:17Like even if 90 % of the time you're using the autopilot, like you always need a human in the loop. And, you know, I'd be curious if that turns out to be one of the things that society learns. One of the crazier ideas I've been talking to people about that, like, I feel like would be a fun sci-fi book would be just speculation playing out on, you know, sort of how this interacts with nation states. Like, you know, China obviously is run by a central committee and arguably Xi Jinping. You know, seemingly, if you had ASI, you would only want, you know, sort of the central committee to have it. And so that might turn into like a very specific form of that, you know, China might end up having one ASI that is totally centrally controlled and then everything else about it sort of comes out of that.

1:33:15And then you might end up with... I mean, controversially, I think often they're trying to be benevolent. If you spend time in China, it's incredibly clean. I'm sure there's all sorts of crazy stuff that happens that is quite unjust. I have no idea. It's not really even my place to like argue one way or another what it's like to be in China. But that's an interesting idea. It's like, you know, that society probably, you know, unless there's other changes there, like that's, you can sort of count on a single artificial super intelligence, like sort of setting the, how everything works over there.

1:33:57I mean, probably internal to the Politburo itself, they're going to have to have all these discussions about what do we do with this ASI and who gets to where does the ultimate agency of that nation come from? Going back to something you said earlier, I think the ultimate combination at least for right now is human and machine intelligence working in concert where machine intelligence might be the default and then the human opts out and that's exercising judgment. It's like, no, we're not. And when you look at chess that tends to be the case where the best players are using computers, but they know when, oh, there's something the computer can't see here, or there's an opportunity that it just doesn't recognize.

1:34:38And I think it was Tyler Cowen who said that, like, he had a word for it, mixing the technology. Fascinating. Yeah. And then, yeah, the question is, like, well, how does America approach it? Like, potentially, it's much more laissez-faire. And then in that case, like my argument would be like the most American version of it is that like, you know, you and I have our own ASI and like each, you know, each citizen should be, you know, issued an ASI and be taught how to get the most out of it. And, you know, maybe it needs to be embodied with a robot. Like we should all, you know, we should all be Superman in that, in that sense.

1:35:11And that would be like the most empowering version of a society that of like free and, And, you know, free people created equal, right? And then, you know, there might be other versions. And I mean, I'd be curious, like, you know, what's the European version of it? Maybe that version has, you know, all the check marks. And like, oh, is, you know, every decision has to be, you know, was this AI assisted or not? And like, let's check the provenance on like, you know, how that AI was like trained. And I mean, I don't know. There are all these different, there's like a billion different ways all of these different governments are going to sort of approach this technology.

1:35:50What are the smartest people at the leading edge of AI talking about right now? I mean, you know, the hard part is like I spend most of my time not with those people. I spend most of my time with people who are commercializing it. So the very, very smartest people are clearly the people who are in the AI labs actually actively doing, you know, sort of creating these models. But, you know, sort of the people who I know who are in those rooms, I mean, it sounds like test time compute is really it. You know, that's the reasoning models are sort of the thing that will really come to bear this year.

1:36:31Like we're sort of understanding that right now. You know, for now, it sounds like pre-training might have hit some sort of scaling limit, the nature of which I don't understand yet, there's a lot of debate about it. Will there be new 4.0 style models that have more data or more compute? And seemingly, there's just rumors of training runs gone awry that basically the scaling laws may have petered out, but I don't know. So we have sort of like the LLM, we have the reasoning. The LLM and the reasoning model are different, correct? The way OpenAI talks about 01, they're sort of connected but like different steps.

1:37:13Okay. And so we have progress there. Then we have progress with the data. And then we have progress with inference. Yep. Well, we just don't have enough GPUs really. I think what's funny is I'm still pretty bull on NVIDIA and that they more or less have the monopoly on sort of the best price performance and... So you think this is going to continue? Well, the demand for intelligence is going to... Trillions of dollars of investments in AI. Basically, I think you can live in two different worlds. One world says all of this is hype. We've seen AI hype before. It's not going to pan out. And then I think the world that we're spending a lot of time in, the world really wants intelligence.

1:38:02And then the scary version of this is like, yes, some of it actually is labor displacement, right? Like in the past, what tech would do is we'd be selling you hardware, we'd be selling you a computer on every desk, like everyone needs a smartphone, you know, we're selling you Microsoft Office, we're selling you package software, we're selling you Oracle, SQL Server, like, you know, we're selling, you know, SaaS apps, like Salesforce, like, you know, it's$10 ,000, you know, per seat per year, that kind of thing. Or we're selling, you know, classically Palantir was selling, you know, million dollar or$10 million ACV, you know, very specific vertical apps, right?

1:38:48And so all of those things are selling software or hardware, and that's like selling technology. And so increasingly, what we're starting to see is like, you know, especially the bleeding edge is probably customer support and all of the things that you would use for a call center. Like those are sort of the things that are already so well defined and specified. And there's a whole training process for people in, you know, usually overseas to do these jobs. And AI now is just coming in and And the speech to text and text to speech, those things are indistinguishable from human beings now. And you can train these things.

1:39:35The evals are good. The prompting is good. Going back to what we were saying earlier, what we're seeing is like, like it or not, it is actually replacing labor. Has anybody created an AI call center from scratch? and now is ingesting customers? Yes. I mean, I funded a company in this very current batch that is called Leaping AI. They are working with some of the biggest wine merchants in Germany, which is fascinating. So, I mean, that's another fascinating thing. Like these things speak all human. They certainly speak all the top languages very, very well and are indistinguishable. and I think 80 % of the ordering volume for some of their customers is entirely no human in the loop.

1:40:30I would love to see government call centers go to this. Yeah, exactly. A, it would scale so much better. I was on the hold for like three hours the other day for like a 15-minute question that I had to answer and it's like, this could be, A, it could be done so much quicker by somebody who's not a human and probably more securely and reliably and more consistent regardless of who's on the other end or how they're talking. How would you define AGI? I guess the funniest thing is Microsoft, I think, is defining it when it gets its$100 billion back. But I am sort of skeptical of that because I think basically only Elon Musk then would qualify as a human general intelligence, I think.

1:41:18Like AGI, the thing is like in a lot of domains, it feels like it's here actually. I mean, can it have a conversation with someone and give incredibly good wine pairing recommendations and have a perfectly fine indistinguishable from a real human sort of or even better than human sort of interaction and also like take orders for very expensive wine and have that just work? Yes, that's happening right now. So I think in a lot of domains, and this is sort of the year where maybe there's like 5 % or 10 % of things that it's sort of hitting the Turing test and really satisfying that. But I think maybe this is a year where it goes from like 10 % to 30 % and the year after that it doubles again.

1:42:07And the next few years are like actually the golden age of building AI. Totally. I think I'm super optimistic, at least for the next five years, about the things we'll discover, the progress we'll make, the impact we'll have on humanity and a lot of the things that plague us. I want to get into how you use AI a little bit. What do you know about prompting that most people miss? I mean, I'm mainly a user. I spend a lot of time with people who spend a lot time and prompts. Probably the person I would most point people to is Jake Heller. So he's the founder of Case Text. He was one of the first people to get access to GPT-4.

1:42:49And we think of him at YC as the first man on the moon, in that he was the first to successfully commercialize GPT-4 in the legal space. So what he said was that they had access to GPT-3.5, and And it basically hallucinated too much to be used for actual legal work. Lawyers would see one wrong thing and say, oh, I can't trust this. GPT-4, he found, actually, with good evals, they could program the system in a way that it would actually work. And what he says, he figured out, was if GPT-4 started hallucinating for them, they realized that they were doing too much work in one prompt. They needed to take that thing that they asked GPT-4 to do and then break it up into smaller steps.

1:43:49And they found that they could get deterministic output for GPT-4 like a human if they broke it down into steps. Oh, interesting. And what he needed to do, I mean, it's sort of equivalent to Taylor time and motion studies in factories. It feels like that's what he did for what a lawyer does. Let's say you have to put together a chronology of what happened in a case. And he's a real life lawyer, which is sort of unusually perfect to figure out this prompting step. He realized that he needed to look at what a real lawyer would do and literally replicate that like tailored time and motion style in the process and prompts and workflow.

1:44:40So for instance, doing this type of summarization, he would have to go through and read all the materials. And then this is why apparently lawyers have, you know, sort of their many, many different colored little flags and highlighters and things like that. They just get very good at doing a read through paragraph by paragraph, sentence by sentence, and pulling out the things that are relevant and then sort of synthesizing it. And so, you know, early versions of case text and a lot of it today, I think is still just doing that. It's like, what is a specific thing that a human does? Break it down into the very specific steps that a real human would do.

1:45:22And then actually, basically, if it breaks, you're just asking in that step to do too many things. So like break it down into even smaller steps. And somehow that worked. And like, basically, this is the blueprint that I think a lot of YCE companies and AI vertical SaaS startups are doing across the whole industry right now. They literally are taking, you know, model out what a human would do in knowledge work and then break it down into steps and then have evaluations for each of those prompts. And then as the models get better, because you have, what we call the golden evals. Basically, you just run the golden evals against the newest model.

1:46:044.0 comes out, Cloud 3.5 comes out, DeepSeek comes out. You have evals, which is basically a test set of prompt context window data and output. And you can actually... What's funny is it's even fuzzy that way. You can even use LLMs in the evals themselves to score them and figure out, doesn't make sense. Can you give us an example of an eval, like make it tangible for people? Oh, yeah. It's really straightforward. It's just a test case, right? So given this prompt and this data, evaluate the prompt to see if... And it usually maps directly to something that is true, false, yes, no, something that is pretty clear.

1:46:47Let's say there's a deposition and someone makes a certain statement, right? You might have a prompt that is like, you know, is this, you know, is what this person said in conflict with, you know, any of the other witnesses, or I don't know, I'm totally making this example up, like, this is the kind of thing that you can do, you know, at a very granular level, you might have thousands of these. And then that's how, you know, Jake Heller figured out he could create something that would, you know, basically do the work of hundreds of lawyers and paralegals. And it would take a day or an afternoon instead of three months of discovery.

1:47:29That's fascinating. How do you use AI with your kids? Oh, I love making stories with them. So what I find is O1 Pro is actually extra good now. so yeah actually there's like an interesting thing that's happening right now and I saw it up close and personal this morning looking at some blog posts about DeepSeek R1 which is DeepSeek's reasoning model I was reading Simon Willison's blog post about he got DeepSeek R1 running it's one of the first open source versions of sort of the reasoning. And so what we just described with how Jake Heller broke it down into chain of thoughts to make case text work, it turns out that that maps to basically how the reasoning stuff works.

1:48:25And so the difference between what Jake did with GPT-4 when it first came out and what O1 and O1 Pro maybe is doing and what DeepSeq R1 is doing clearly because it's open source and you can see it is that those steps, like breaking it down into steps and the sort of metacognition of like whether or not it makes sense at all of those micro steps, that's what in theory this reasoning is actually happening. That's actually happening in the background for 01 and 03. And if you use ChatGPT, you'll see the steps, but it's like a summary of it. Right. And so it's, you know, I just only saw it this morning.

1:49:10I mean, this is such new stuff. Like I was hoping that someone would do a open source reasoning model just so we could see it. And that's what it was. I think Simon's blog post this morning showed, here's a prompt and then he could actually see, I think he said pages and pages of the model talking to itself. Literally, you know, does this make sense? like can I break it down into steps? So what we just described as a totally manual action that a really good prompt engineer CEO like Jay Keller did, and he sold his company case text for almost half a billion dollars to Thomson Reuters. That is actually very similar to what the model is capable of doing on its own in a reasoning model.

1:49:59And that's what it's doing when it's doing test time compute. It's actually just spending more time thinking before it spits out the final answer. So how do you create a competitive advantage in a world like that where perhaps that company had an advantage for a year or two and now all of a sudden it's built into the model for free? Yeah. I mean, I think ultimately the model itself is not the moat. I think that the evals themselves are the moat. I don't have the answer yet. Basically, for now, maybe it's a toss-up. If you're a very, very good prompt engineer, you will have far better golden evals and the outcomes will be much better than what O3 or DeepSeq R1 can do because it's specific to your data and it's much more in the details.

1:50:56I think that that remains to be seen. Like the classic thing that Sam Altman has told YC companies and told most startups, period, is you should count on the models getting better. So if that's true, then that might be a durable moat for this year. But it might not be past, you know, I mean, 03, we haven't even seen yet. The results seem like fairly magical. so it's possible that advantage goes away even as as soon as this year but all the other advantages still apply like you know one thing that a lot of our founders who are getting the five to ten million dollars a year in revenue with five people in a single year are saying is you know yes there's prompting there's evals like there's a lot of magic that like is sort of mind-blowing but um What doesn't go away is building a good user experience, building something that a human being who does that for a job sees that, knows that's for me, understands how to start, knows what to click on, how to get the data in.

1:52:02and so one of the funnier quips is that the second best software in the world for everything is using ChatGPT because you can basically copy and paste almost any workflow or any data and it's like the general purpose thing that you can just drop data into it and it's the second best because the first best will be a really great UI made by a really good product designer who's a great engineer, who's a prompt engineer, who actually creates software that doesn't require copy-paste. It's just like link this, link that. Okay, now this thing is now working. And so I think that those are the moats. The moats are not different actually at the end of the day.

1:52:51You still have to build good software. You still have to be able to sell. You have to retain customers. You have to, but you just don't need like a thousand people for it anymore. You might only need six people. Okay, I want to play a game. I'm going to, you have 100 % of your net worth. You have to invest it in three companies. Oh God, okay. And so the first company you have to invest half and then 30 and then 20. So altogether 100%. Which companies out of the big tech companies, how would you allocate that between, I mean, here's my biggest bet, my second biggest bet, my third from today going forward.

1:53:29Okay. I guess, you know, is it cheating to say I'd put even more money into the YC funds that I already run? But that's a cop out. That's a cop out. That goes without saying. I think that it's very unusual just because, you know, we end up like this is the commercialization arm of every AI lab is what I realize. But short of that, I mean, maybe NVIDIA, Microsoft, Meta. In that order? Probably. Why? I mean, NVIDIA just has an out and out. Like for now, they're just so far ahead of everyone else. I mean, it can't last forever, but I think the demand for building the infrastructure for intelligence in society is going to be absolutely massive.

1:54:17and maybe on the order of the Manhattan Project and we just haven't really thought about it enough, right? Like, it's entirely conceivable. Like, if, say, like, level four innovators turns out to work, like, you know, it's sort of the meta project because then it's like the Manhattan Project of instantiating more Manhattan Projects, actually. Like, you know, you could imagine if we can, If more test time compute or you could do the work of 10 ,200 IQ Einsteins working on bringing us basically unlimited clean energy, that alone will – I mean, if anything, that's probably the bigger problem right now.

1:55:06We know that the models will continue to get better. We know that the demand for intelligence will be unending. And then even going back to the robotics question, it's like if we end up making universal basic robotics, the limit will still actually be sort of the climate crisis and the available energy available to human beings. know, maybe solar can do it, but maybe there are lots of other sort of solves. But, you know, I think energy and access to energy is sort of the defining question at that point. Like everything else you could solve, like, and everything else you could sort of either, you know, if it's in the realm of science and engineering, like, you know, in theory between robots and, you know, more and more intelligence, like we could sort of figure these things out.

1:56:07But not if we run out of energy. Okay, why Microsoft and why Meta next? I mean, I think Microsoft has just really, really deep access to OpenAI. And I think OpenAI is probably, you said public companies, right? Yeah, yeah. So, you know, I think there's a non-zero, pretty large percentage of like the market cap of Microsoft that I think is pretty predicated on Sam Altman and the team at OpenAI continuing to be successful. Totally. And then why Meta? I mean, I think Meta is sort of the dark horse because they are amassing talent and then they have crazy distribution. And I think, you know, I just would never count Zuck out.

1:56:49I think that he, you know, it's so crazy that it's super smart that he is on that. You know, he's always thinking about what is the next version of computing. Like so much so that he probably put more money than he should have into AR and that was maybe premature. He might still end up being right there. But AI for a fraction of what he's put into AR is likely to push forward all of humanity and accelerate technological progress in a really profound way. I want to switch subjects a little bit. A few years ago, you met with Mr. Beast. and talked about YouTube. What did you learn? Because your channel changed.

1:57:32Oh yeah, he's great. I mean, he was very brusque with me. He said, you know, look man, your titles suck and your thumbnails are even worse. And I think that he spent so much time trying to understand the YouTube algorithm and what people want that he just loaded it completely into his brain. What makes a good title? I think it's clickbait. Unfortunately. you know unfortunately and this is the thing like um when you're trying to make smart content it's actually kind of tricky because you don't want necessarily more clicks you want more clicks from people who are smart so we title our episodes differently on youtube usually than on the actual audio feed because if you want youtube to pay attention you have to almost be more provocative intentionally that sounds right yeah like we could call this you know ai ends the world or something.

1:58:26Yeah, that's right. You know, get people to watch, but that's not actually what we're talking about at all. What makes a good thumbnail? What did you learn about thumbnails? Oh, usually like a person looking into the camera seems to help a lot. Okay. And then you want it to be relatively recognizable. Like, you know, you want some sort of style that when someone sees it, you know, I mean, basically what I was doing at the time was just taking whatever frame that was sort of kind of representative and throwing it in there. But when you train someone to look at YouTube back to back to back every time it shows up, you sort of want to be highly recognizable.

1:59:08So you want to have a distinct thumbnail, like yours with the overlay, sort of like the red. Yeah. But once I stopped posting so regularly, then it sort of didn't matter as much anymore. but if you're going to post very regularly, that's pretty important actually. So yeah, unfortunately it's clickbait. And then there is an interesting interaction. Like, you know, yes, you can optimize for better thumbnails and better titles for the click-through, but if it has absolutely nothing to do with the actual body, as you mentioned, you will not get watch time. And then YouTube will be like, oh, people aren't watching this, so we're not going to promote it.

1:59:49Because the big thing about YouTube is discovery. and like we notice this all the time where it's sort of like you just get this audience but you don't get to keep the audience as a creator which is really interesting well you do if you are regular and then the other hack is be very shameless about asking for subs and then the funniest thing is like subs do very little actually there's no guarantee that you show up in people's feeds if someone subs it like helps a little bit liking helps more watch time helps the most and then the extreme like you know over the top hack that you know probably you should do here is you should ask for the like subscribe and hit the bell icon because if you hit the bell icon and they have notifications on that's the only thing that is almost as good as having their email address and emailing them you heard it here people Gary just told you.

2:00:49You got to click like, subscribe, and hit the bell icon because you want knowledge. You want to be smart and this is the place to get it. Oh, I love that. Thank you. Good advertising. I want to ask just a couple of random questions before we wrap up here. What are some of the lessons that you learned from Paul Graham that you sort of apply or try to keep in mind all the time? I think the number one thing that is very hard, but is so, I mean, you can see it and read it in his essays. It's to be plain spoken and to sort of.

2:01:52be hyper aware of our YouTube team and our media team at YC talking about this. It's like, if we get too focused on just view count, we're liable to just, yeah, like optimize for the wrong audience. If we're not being authentic to ourselves or, you know, if we're just trying to like follow trends or, you know, do things that get clicks, it's like, that's not helpful to them either. Like, then we're just on this treadmill, right? Yeah, basically, like, trying to be very, very high signal to noise ratio. You know, the thing that I probably struggle with most, and you know, I don't know, maybe some of the listeners here might feel this.

2:02:31It's like, sometimes I think out loud. And then, you know, really, really great ideas are not like thinking out loud. They're actually figuring out a very complex concept and then trying to say it in like as few words as possible. And, you know, the amount of time that Paul spends on his essays is fascinating. It's, you know, sometimes days, like sometimes weeks, like he'll just, you know, iterate and iterate and send it out to people for comment. And, you know, the amount of time he spends whittling down the words and trying to like combine concepts and say the most with the least number of words, it would shock you.

2:03:17And then also that is actually thinking, like writing is thinking. Like one of the more surprising things that we do a lot of at YC is we help people spend time thinking about their two sentence pitch. So, you know, you would think that that's, oh yeah, that's like something, you know, startup 101, like you're helping people with their pitch that sounds so basic. Like, yeah, I guess that makes sense. Like that's what an incubator would do. But the reason why it's very important is that it's actually almost like a mantra. It's like a special incantation. Like you believe something that nobody else believes and you need to be able to breathe that belief into other people and you need to do it in as few words as possible.

2:04:04Like, so if you, the joke is like, oh yeah, like what's your elevator pitch? But like, you might run into someone who could be your CTO, who could introduce you to your lead investor, who could be your very best customer. And you will literally only have that time. You know, you will only have time to get two sentences in. And so, and even then, I mean, I guess it's kind of fractal. Like, that's what I love about a really great interview. Like, you know, someone comes in and I'm like, oh yes, I get it. Like I know what it is and I know why that's important. I know why I should spend more time with you.

2:04:39That's what a great two sentence pitch is. And, you know, knowing what it is, is very hard. Like that's all of Paul Graham's, you know, sort of editing down and whittling down in a nutshell. It's like people do really complex things. How do you say what you do in one sentence? That's very hard actually. And then, you know, the second sentence is like, why is it important? Why is it interesting? Why should I, you know, and then that may well change with like the person that you're talking to. So yeah, to the degree that clear communication is clear thinking, you know, one of the things I did when I first joined YC, I had no intention of ever becoming an investor, ever being a partner, let alone running the place.

2:05:24I was just a designer in residence. And what I did was I did 30-minute, 45-minute office hours with companies in the YC Winter 11 batch. Back then as an interaction designer, I used OmniGraffle a lot. And so we just sat there and designed their homepage. And it's like, this is what the call to action is to say. Put the logo here. Here's the tagline. Maybe you have a video here or right below you have a how it works. And then what's funny about it is some people would take the designs we did in those 30, 45 minute things and that would be their whole startup. And sell those companies for hundreds of millions of dollars years later, which is just fascinating to think about.

2:06:09It's like clear communication, great design, creating experiences for other people. All of those are sort of exercising the same skill. And so that's what a founder really is. a founder to me is a little bit less what you might expect. It's like, oh, this is someone with a firm handshake who looks like a certain way and bends the will of the people. You might think of an SBF that's like, that's all artifice. Think about that guy. That guy was full of shakes and the guy was on meth. Everything about it was an affectation. He was a caricature of an autist. right like we see very autistic incredibly smart engineers all the time but you know for him it was like that was part of the act yeah like i remember he did a youtube video with nas daily and i love you know nasir's great and i love nas daily but i couldn't believe the video that spf went on it's just like full of basically bullshit right and um the exact opposite of brian armstrong and um Yeah, we're always on the lookout for that.

2:07:17He wasn't trying to fool you. Was that? Oh, yeah, I guess so. I mean, he was fooling the world. Because you know, right? It's hard to fool somebody who knows versus somebody who doesn't know. And he wasn't trying to appeal to you. He was trying to appeal to other people who didn't know. It's the same as going back to Buffett, just tying a few of these conversations together, right? Everybody repeats what Buffett says. But the people who actually invest for a living or know Warren or Charlie or have spent time with them can recognize the frauds because they can't go a level deeper into it. They can't actually go into the weeds, whereas those guys can go from the one-inch level to the 30 ,000-foot level and everything in between, and they don't get frustrated if you don't understand.

2:08:01Whereas a lot of the fraudsters, one of the tells is they can't go, they can't traverse the levels. And then they do tend to get defensive or sort of angry with you for not understanding what they're saying, which is really interesting. And then I just want to tie the writing back to what you said. You said, if you can't get it clear in like two sentences, you might miss an opportunity. That goes to the 10 minute interview, right? Where you're looking for, maybe it's not the perfect pitch, but you want that level of clarity with people. And it's really the work of producing that that helps you hone in on your own ideas and discover new ideas.

2:08:37Yeah, I mean, I feel like we're in like the idea fire hose. So we're just like hearing about all kinds of things that are very promising. And then I think the most unusual thing that, you know, I'm still getting used to is, I mean, in full transparency, I mean, probably, you know, the median YC startup still fails, right? Like, you know, YC might be one of the most successful, you know, sort of, you know, institutions of its sort that has ever existed, you know, inclusive of venture capital firms on the one hand. On the other hand, like the failure rate is absolutely insane, right? Like, you know, it is still a very small percentage of the teams actually do go on and, you know, create these, you know, companies worth 50 or 100 billion dollars.

2:09:27but the remarkable thing is not that it's that low. The remarkable thing is that it happens at all. It's just unbelievable that... I think you have the coolest job in the world or at least warmly. If I had to pick the top 10, you'd be up there. I agree. Especially to have... I pinch myself every day on the regular... In the morning, I wake up and it's like, oh, this AI thing is happening and then somehow I'm filling the shoes of the person who, I mean, Sam Altman probably brought forward the future by five years, 10 years, at least 10 years. Like all of the things that him and Greg Brockman and all the researchers he brought on were working on, that happened, that was going to happen, right?

2:10:20I think there's a lot of the Sam Altman haters or the open AI haters out there love to point out like, oh, you know what? Like the Transformer was made by all these teams. I mean, some of it's like, these teams absolutely did incredible things. Like you can't take away from that, right? The researchers did, you know, Demis did incredible things. But at the same time, it's like they believed a thing that nobody else believed and they brought the resources to bear. And so recently, you know, Sam Altman came back to speak at our AI conference this past weekend. And I couldn't think of another way to start that conference than have Sam Oman and a bunch of his old...

2:11:03We had Bob McGrew there. We had Evan Morikawa, who was the eng manager who released ChatGPT. Bob McGrew actually worked with me at Palantir back in the day, but he's outgoing chief research officer. Jason Kwan was there. he actually worked at YC Legal before leaving to run a lot of things at OpenAI. And so I had them all stand up. And we had a room full of 290 founders, all of whom were working on things that happened essentially because OpenAI existed. And there was like a standing ovation. Oh, that's awesome. So, and, you know, Sam, to his credit, was like, you know, not just us. You know, these researchers did so many things as well.

2:11:49But all that being said, it's like we're in the middle of the revolution. Oh, totally. This is just like, I mean, it's not even the middle. I think it's like just after the first pitch of the first inning of like what is about to be like a great, great time for humanity, for technology. I'm with you. I'm like so excited to be alive right now. I was so lucky, so blessed to be a witness to this. And I think we're going to make so much progress on so many things. And go back to the haters. There's always people pulling you down, but they're never people that are in the trenches doing anything. I've rarely seen people who are working on the same problem attacking their competition like that or undermining them.

2:12:32On our end, we're just hoping to lift up the people who want to build. This is the golden age of building. Amazing. I want to just end with the same question we always ask, which is what is success for you? I think looking back, I mean, growing up, I always just looked up to the people who made the things that I loved. And, you know, Steve Jobs, Bill Gates, like the people who really created something from nothing. and I just think of Steve saying, we want to put a dent in the universe and ultimately that's what I want. Success to me is how do we bring forward? This is actually when Paul Graham came to recruit me to come back to YC, I had actually left and started my own VC firm, got to$3 billion under management.

2:13:30Yeah, you guys did Coinbase. Yeah, totally. I mean, returned$650 million on that investment alone. I was sort of right at the pinnacle of my investing as if you're running my own VC firm. And Paul and Jessica came to me and said, Gary, we need you to come back and run YC. and it was really, really hard to walk away from that. Luckily, I had very great partners, Brett Gibson, my partner, my multi-time co-founder, went through YC with me. He actually built a bunch of the software with me at YC before we left. He runs it now. They're off to the races and still doing great work. And I sat down with Paul right after we shook hands and he's like, Gary do you understand what this means it means that if we do this right we kind of like I think what Sam did with OpenAI with pulling forward large language models and AI and bringing about AGI sooner like YC is sort of one of the defining institutions that is going to pull forward the future and it's not more complicated than how do we get in front of optimistic, smart people who have benevolent goals for themselves and the people around them?

2:14:58How do we give them a small amount of money and a whole lot of know-how and a whole lot of access to networks and a 10-week program that hopefully reprograms them to be more formidable while simultaneously being more earnest. And then the rest sort of takes care of itself. Like, this thing has never existed before like this. And it deserves to grow. Like it deserves to, you know, if we could find more people and fund them and have them be successful at even, you know, the same rate, we would do that all day. I mean, and I think what are the alternatives, right? Like I think of all the people who, you know, they're locked away in companies, they're locked away in academia, you know, or heck like, you know, these days, the wild thing about intelligence is like intelligence is on tap now, right?

2:15:54Like all of the impediments to being able to, all the impediments to fully realizing what you want to do in the world are starting to fall away. Like, you know, there's always going to be something that stands in the way of any given person. And I'm not saying those things are equal, but through technology and through access to technology, those things are coming down. If there's the will, if there's the agency, if there's the taste, that's what I want for society. I want them to achieve that. In a lot of ways, we have more equality of opportunity now than we've ever had in the history of the world, but not equality of outcome.

2:16:36That's right. Yeah, and that's sort of the quandary, right? Like you have to choose. Do you want the outcomes to be equal or do you want a rising tide to raise all boats? I'm a huge fan in equal opportunity, but not unequal outcome. I'm with you. Yeah. Thank you for listening and learning with me. If you've enjoyed this episode, consider leaving a five-star rating or review. It's a small action on your part that helps us reach more curious minds. You can stay connected with Farnham Street on social media and explore more insights at fs.blog, where you'll find past episodes, our mental models, and thought-provoking articles.

2:17:16While you're there, check out my book, Clear Thinking. Through engaging stories and actionable mental models, it helps you bridge the gap between intention and action. So your best decisions become your default decisions. Until next time.