Y Combinator CEO Garry Tan: Turning Ambitious Misfits into Founders

The world is 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. You know sometimes I sit there and I run into a bug whether it's a Google product or an Apple product or you know 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 people don't care. No one's paying attention. That's just one symptom out of a great many that is, you know, the result of basically treating people like, you know, hoarded resources. The world is full of problems. Let's go solve those things.

I guess I can't talk about YC without talking about Paul Graham and Jessica Livingston. Um, I mean, it started because they're remarkable people and, uh, you know, Paul when he started his company, um, I don't think he ever had the idea that, um, you he would ever become someone who created a thing like YC. He was just trying to help people and, uh, sort of follow his own interests. I think he just said uh I know how to you make products and make software and make them in a way that people can use them. And then after he actually sold that company VO web was one of the first um you know today we have Shopify uh VO web was sort of like the very first version of it. He actually basically created the first uh web browser-based uh program. So he was one of the first people to hook up a web request to an actual program in Unix. You know, today we call it CGI bin or you know all these different things. But you know, he was so early on the web that um you it was a a new idea to make software for uh the web that didn't require like some desktop thing that you had to use to configure the website. And so I think he's just always been um an autodidact, uh a really great engineer and then just a polymath. So I think that that's what really made YC. I mean he wrote essays. He sort of attracted all the people in the world who wanted to do the thing that he wanted to do. Um and so I think Paul Graham and his essays became a shelling point for people who this new thing that could really happen uh in the world. And you know that started very early. I mean I think it started literally with the web itself and you know that's why in 2005 he was able to get uh hundreds to thousands of really amazing applications from people who wanted to do what he did. And then the magic is it's only a 10-week program. Uh I think he had you only a dozen people in that very first program in 2005. And then um out of that very first program, Sam Altman went through it. Um and Sam you I guess it's interesting. I mean if you have a draw that is very profound, it will draw out of the world uh the people who you that speaks to those people. And so you end up needing in society these like sort of shelling points for uh certain ideas. And then that you know the idea that someone could sit down in front of a computer and create a piece of software that a billion people could use uh turned out to be very contrarian and very right.

And so um you know today I think of YC as really uh it's actually you know software uh events and media and you know I think you've had Naval Ravicant on before and uh you know I think I remember distinctly Naval talking about like those are the few forms of extreme leverage you have in the world and so you I think Y Combinator is this crazy thing. It's like when people realized they could start a startup, they went on Google and they searched and they found Paul's essays and then through at his essays he they found Y Combinator and then YC started funding people like you know Steve Huffman who ended up uh creating Reddit in that very first batch and selling that to Cond Nast and um you know Dropbox then Airbnb then you know today you know Coinbase, Um, you Door Dash, there are just so many companies that, you know, are incredible. I mean, Airbnb is this insane marketplace that houses way more people on any given night than, you know, the biggest hotel chains in the world. And it's like on the one hand unimaginable, on the other hand, like that's the kind of thing that you can do. Like you can just, you know, do things which is wild. And so I think that that's why it works. It's uh we attract people who want to create those things and then we give them money and then more importantly I think the knowhow is uh we give it away for free actually.

Yeah. Uh earlier just now we were chatting about this uh podcast setup, but um we spend a lot of time writing essays and putting out content on our YouTube channels and uh just trying to teach people you how do you actually do this stuff? There's like a lot of mechanical knowledge about how do you incorporate or how do you raise money for the first time and all of that is out there for free. And uh you know on the other hand I think of YC doing YC being in the program. It's a 10-week program we make everyone come to San Francisco. Now uh at the end of it it culminates in um people raising you know sort of the median raise is about a million to a million and a half bucks for you know sometimes teams that are two or three people just an idea starting at uh you know at at the beginning of the match.

And yeah, we have, you know, I think we have about a billion dollars a year in uh, you know, funding that comes into YC companies. And that's because, uh, the acceptance rate to get into YC is only 1%.

Yeah, I think it's closer to 70 80,000 at this point.

Uh well we ourselves use software but we also um have 13 uh general partners who actually read applications and we watch the one minute video you post. Um, and you know, the most important thing to me is that I want us to try the products, right? Um, you know, sure we can use the resume and you know, people's careers and uh where they went to school, you know, we're not going to throw that out like it's a factor in anything, but the most important thing to me is not necessarily uh the biography. It's actually, you know, what have you built? What can you build?

yeah I mean ultimately the best thing that we can do is actually brute force read uh and on average I think the a group partner will read something like a to-500 applications uh for that cycle that they're working so the best thing we can do is like not uh it is basically like humans trying to make decisions you know, which is maybe a little antithetical to um you know, the broader thing right now and now it's you let's just use use AI for everything. But I think that the human element is still very important.

I guess the the surprising thing that um has worked over and over again ultimately is um in those 10 minutes either you learn a lot about both the founders and the market or you don't. So, we're looking for incredibly crisp communication. So, I want to know you know what is it? Um, and you know, often what the first thing I ask is not just what is it, but why are you working on it? Like I want to sort of understand where did this come from? Did you just read about it on the internet? Or a much better answer is, you know, well, I I spent a year working on this and I got all the way to the edge of, you know, what people know about this thing. And, you know, what's cool about, you know, the bio biographical is that then it uh invites more questions, right? It's um the best interviews in 10 minutes. Like you learn about an entire market. You learn about um a set of people that you know normally you might not ever hear of. Um it's like you're traveling. It's like you're traveling the idea maze with uh the people you're talking to. This is all over Zoom. And um you know at the end of those 10 minutes like sometimes the 10 minutes becomes 15. like you want to talk to people longer cuz that's what a great interview feels like to me. It feels like uh I'm a cat and I see a little yarn and I'm just pulling on the yarn. I'm just pulling on the thread cuz it's like this you there's something here. This person understands something about the world that um you know actually makes sense to me. And um I I think what we're looking for is actual signal that there's there's a there there's a real problem to be solved. Uh there are people on that end who are willing to pay. And then you know working backwards what a great startup ultimately is uh is something real that people are willing to pay for uh that probably has durable moes that you know it it doesn't mean that you know it means that that company could actually become much bigger than you you don't want to start a restaurant for instance because there's infinite competition for restaurants but you do want to start uh you know something like Airbnb that has network effects or um

Exactly. or you know in AI today one of the more important things is um you know are people willing to pay and uh today because people are not selling software they're increasingly actually selling uh intelligence they're like you know like it or not like these are things that um you could not buy before like you probably the most vulnerable things in the world today are things that you could you know farm out to an overseas call center that's sort of like the lowhanging fruit today and um you know basically how do you find things that people want and how do you actually provide it for them and the remarkable thing is that you know in that's why it only has to be 10 minutes um you know one of the things I feel like I learned from Paul Graham interviewing alongside him so many years was that sometimes I'd go through and this person would come in they had an incredible resume you know they're like had a PhD or they studied under this famous person or you know they worked at uh Google or Facebook or all these really famous places. Uh they had an impressive resume um or they had the credentials of someone who I felt like you know

Oh, definitely. all the time. I mean, um I think that's the trickiest thing. You know, I think the system itself will always produce, um, you know, both false positives and false negatives cuz it is only 10 minutes and

Yeah. About 2 and a half% end up becoming decacorns uh sooner or later. So, but that would be the highest batting average of any VC firm, maybe with Sequoia being the exception. What's interesting to me is most of the people that I know in that space are doing hundreds of hours of work per company and you guys can't do that because you have 80,000 people applying and you're still the most or at least top tier in terms of success. Yeah. I mean what's great is I you know I don't want to compete with Sequoia or Benchmark or Andre and Horowits or uh you know they're our friends honestly done right like we're much earlier than everyone else because we want to actually give them half a million dollars when they have uh just an idea or maybe they don't even know their co-founder yet.

Yeah. You know what it is though? Um I spent five year uh 7 years actually away from YC before coming back a couple years ago. So I ended up I think in the top 10 of the Forbes Midas list as my final year uh before coming back to YC. And um why has why haven't other people you know we ask this all the time. Why haven't other people uh come for us? you know, I I think there are lots of people who are doing various things that might work and uh I guess so far people sort of lose interest or you know float off and go do higher status things. Um, working with founders when they're just right at the beginning and just an idea is actually, you know, relatively low status work because, you know, it's very high status to work with a company that is uh, you know, worth 50 or hundred billion dollars now, but guess what? Like that's 10 years from now or sometimes 15 or 20 years from now. um you know the it it all starts out very low status and all the way in the weeds like you're ask you're answering sort of relatively simple questions and you're giving relatively small amounts of money and

half a million dollars today yeah

I think some of it is um well I we find out in 10 years uh if anything I think that the unicorn rate has gone up over time you uh 10 15 years ago I think it was closer to maybe 3 and 1 half to 4% and now we're around 5 1/2% some batches from um you the maybe 2017 2018 or you know pushing 8 to 10%.

Um some of those companies in that area in that vintage uh about 50% of companies end up raising what looks like a series A. Uh and then the wild thing about it is is it is it actually takes a long time for people to get there. Um so I you know I think the YC has actually flipped a lot of the I guess myths of venture. You know one of the myths of venture maybe 1015 years ago was that uh you know within 9 months of funding a company you will know whether or not that company was good or bad. And um you know going back to that stat you know about half of companies that go through YC will end up raising a series A. That's you know much higher than any other preede or seed sort of situation that I know of. Um but about a quarter of those who raise the series A they do it in year five or later. And that's a function of like we're funding 22 year olds you know 19 year olds 24 year olds. I mean, we're funding people who are so young that sometimes they've never uh shipped software before. Sometimes, you know, they're fresh off of an internship, you know, let alone you, it takes 3 to 5 years to to mature, to um learn how to iterate on software, how to deliver really high quality software, how to manage people, how to manage people effectively, give feedback. And so the wild thing is, I mean, sometimes it takes five years for those things to come together.

Oh, that was definitely true for me. I mean um without that I feel like what my I mean I had a good a really great community at the end of the day like it was um you know my fellow Stanford grads but I guess the weird thing to say is that like being around people who are really earnestly trying to build uh helps you know 10x more. Um the the default startup scenario out there is not about signal. It's about the noise. Like you're playing for these other things like how much money can I raise and from what you know high status investor like you know some people sort of float off and they become seen they're like oh let me try to get a lot of followers on Twitter. That's the most important thing. And then what we really try to do at YC during the batch and then afterwards and you know in our office hours working with companies is like when we spot that kind of stuff it's like oh no no like maybe don't do that like you know let's go back to product market uh actually building and then iterating on that getting customers uh you know long-term retention all of those things are the fundamentals and everything else is like the trappings of success or and those will always feel I what's funny is like in other communities uh all of those things will always feel more present to hand and they're easier like you can just get it like you're you know on stage keynoting or you know even doing the podcast game I feel like guilty you know like it's kind of funny um we see that in people and then sometime you know often that will kill their startup like they take their eye off the ball you know angel investing if you're uh a startup founder and uh suddenly some you know people have heard of you and uh people try to add you as a scout like people kill their startups all the time by that just by taking their eye off the ball.

I mean it crashes and then you know sometimes you have to go and do your next startup or you know or I don't know sometimes people just go off and become VCs after that and that's okay too.

I think that that's probably the biggest danger to people who uh want to be founders. I mean, I think I've seen Peter Teal talk about this. Like, he doesn't really want people who want to start startups. It from my perspective, it's certainly much better to find people who have a problem in the world that they feel like they can solve and they can use technology to solve. And that's like sort of a more earnest way to look at it. And uh if it if you look at the histories of some of the things that are the biggest in the world, they actually start like that. You know there are lots of interviews with Steve Jobs and Steve Waznjak saying um you know I never meant to start a company or ever wanted to make money. All I wanted to do was uh make a computer for me and my friends and so you know many many more people kept coming to me saying can you build me a computer and they just you know like a cat were pulling on this thread.

Well, um, at YC, what we hope is that people actually come to San Francisco and, uh, I, you know, we do strongly advocate that they stay, but it's no requirement. Um, and then what we hope is that if they do leave, they they end up bringing the networks and uh, knowhow and culture and, you know, frankly vibes and they bring it back to all the other um, you startup hubs in the world. And I think that that's some of some of the stuff that has actually come about. I mean, um, Monzo was started by now my partner Tom Blonfield. Uh, he's a partner at YC now, but he started, you know, multiple startups and a few of them, you know, multiple unicorns actually. And both of them are some of the biggest companies in London, for instance. So what we hope is that uh San Francisco becomes sort of really Athens or Rome in anti antiquity. You know, send us your best and the brightest. You know, ideally you stay here. One one thing we spotted is that uh the teams that come to San Francisco and then stay in San Francisco or the Bay Area, they actually double their chance of becoming a unicorn.

I think what I want for San Francisco for instance is I think the rent should be lower and so rather than subsidizing demand, we actually need to increase supply like fairly radically actually and that just hasn't happened. I was I think I was looking at it for the entire last calendar year. Uh, I think, you know, maybe Scott Weiner had just posted this on X that literally there were no new housing starts in all of, you know, San Francisco proper for the last year. So, how are we supposed to actually bring down the rents and make this place, you know, actually livable? you know, if San Francisco is the microcosm where, you know, people build the future and it is sort of the siren song for, you know, 150 IQ people who are very very ambitious and have, uh, are, you know, techno optimistic ideology. Um, and it's also where they are most likely to succeed. uh society and certainly, you know, America is not serving society the right way if we're getting in the way of these smart people trying to solve these problems, trying to build the future.

I mean, if it's scary, but might might or probably will be good, I think we want to fund them. And certainly there are things that um would be bad for society but are likely to make money. And um you know the history is our our partners are everyone's independent. You know we have um a process that is very predicated on you know if you're a general partner at YC you know you pretty much can fund what you want. Um you know we run it by each other to make you sort of double check like the thinking but um I think we're pretty aligned there. Like there are lots of examples of you know maybe five or six years ago there was a rash of teleaalth companies that are focused on for instance uh ADHD meds and I distinctly remember one of our partners um Gustaf Alstr I he met that team and he said you know what um we're not going to fund these guys you know it's going to make money but I don't want to live in a world where uh it is that easy to get you know people on these drugs like they're ultimately uh methamphetamines and you know these are controlled substances and this is the wrong vibe like we didn't not like the vibe that we got from the founders of that company. So, you know, I hope that YC continues that way and I think it will. Um, ultimately we want people we want uh people who are I mean ultimately trying to be benevolent at least, you know.

I guess some of it is like are you only going to sell to five eyes? Cuz you know, uh I really liked what MIT put out recently. um they were very clear. They said, you know, MIT is a an institution and that institution is an American institution. And so, um being very clear about that I thought was totally the right move for MIT and you know, I think that YC needs to be a simil an institution of similar character.

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, uh, the thing is, you know, you can't get that. And so, um, probably the first conference that we have, the first mini conference we have when we welcome the batch in is the sales mini conference. And, um, essentially it is don't run away from the no. Spencer Skates of Amplitude has this great analogy that he uh told you know uh some companies when he came by to speak recently that I've been thinking a lot about which is sales is about um you know having a hundred boxes in front of you and maybe five or six of those boxes has uh a gold nugget in them and 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 that, you know, I have a gold nugget and then, you know, I don't 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 um high school and family and uh you know, the 10,000 hours of human training people get from their childhoods comes up in Paul Graham's essays. I would always think about that because I think that most people's backgrounds just don't prepare them for uh sales. It's a very unnatural thing to do sales. But 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 the hundred boxes immediately. And then, you know, you should aggressively try to get to a no. And um, you know, you'd rather get a no so you can spend less time on that lead and you can get on to 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 like you sort of need to be around lots and lots of people for whom that is true that has been true um and I think that you maybe that's actually one of the reasons why YC startups uh are much more successful like other people give as much money or you know as you said like venture capital uh VC firms tend to give, you know, 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 um they're not going to have as earnest people who become as formidable around you. Like it's it's actually a process.

I mean what my hope is I I feel like when Paul and Jessica created YC for my I I went through the program myself in 2008 and uh I came out transformed and then that's very explicitly what I want to happen for people um who go through the batch today. It's you know it it isn't just like show up to a bunch of dinners and network with some people who happen to be or you know it's it's much deeper than that. Like I want people to come in maybe with like, you know, the default worldview and then I want them to come out with um a a very radically different worldview. I 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 um, you know, rest in peace, Charlie Mer talks about and what Warren Buffett talks about around all of these things are in the short-term um, 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, TechCrunch 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? Like 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 uh solve some real problem put people together um 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 um you know the founders make money uh it's all aligned at at that point like yeah there's like a way to hack the hack and I don't I don't really know what the endgame 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, um, you know, you will succeed. Like I think that that's what Paul Graham's essay about being a cockroach actually is. And, you know, that's why, uh, 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 1. They don't quit year two. like you know they are learning and growing. Um I have one other really crazy stat that like I'm thinking about all the time right now. Uh there's a founder uh or there's a VC actually uh his name is Ali Tamas. He works at data collective. He wrote a book called uh superfounders and I get this email from him uh out of the blue. He says did you know that um about 40% of the unicorns from the last 10 years in the world were started by multi-time serial founders. and was like, 'Okay, that's a cool stat. Like, makes sense. Like, multi-time founders are uh, 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 uh the 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, uh, 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 you know, YC today is basically a thing that is for first- timers. Um, you know, we do have second timers apply. We have we do accept them but you know we primarily think of the half a million dollars um you know it really is for people who are starting out and it's kind of hilarious like I have no product right now for people who are uh you know for for my YC alums um and maybe that's okay you know it's uh you know that's our gift to the rest of Sand Hill Road because you know they're the ones who are going to be the fund returners for all of the rest of Sand Hill Road.

Yeah, I mean the the number one thing that I want um that comes to mind for me is uh 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. So

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 it's surprising because, you know, 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. I see it in Brian Armstrong at Coinbase like, and which is fascinating because that's definitely not the trait that you would apply to most crypto founders. And you know, I would use uh Sam Bankman Freed 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 uh that future like you know when you talk 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 and it's like international just sending money from one country to another was totally fraught and totally not you know something that was accessible to normal people like remittance is this crazy scam. It's it's insane like how many fees that people have to pay just to like send money home um or do crossber commerce right so this is something that was incredibly earnest of Brian Armstrong to do he said here is a thing that is broken in the world that you know he saw personally I think he spent time in uh you know buenosaris 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 and 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 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 um someone like Sam Banken Freed and just wondering like what's going on over there? He speed ran the 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 that's anti- earnest. Like that is the definition of he was a crook. He's in jail now. And um you know, my hope is that uh people who look, you know, if if you just look at Brian Armstrong versus SBF, I'm hoping that, you know, young people listening to this right now take that to heart. It's like the things that actually win, you know? I mean I and going back to Buffett, I you know I went to um their uh you know sort of conclave in Omaha. Oh, you went to the Woodstock for capital was I mean amazing. And uh 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 just do it the right way right um and so that's what I want I think that if YC is the shelling point for earnest friendly ambitious nerds uh to steal something from uh you know I I I have a uh a friend on Twitter go who goes by Visa uh Visakon um and you know he has a book on it. I think it's called friendly, ambitious nerd if you look it up. I mean, um I think that that's what YC by definition should be attracting. And uh you know, Brian Armstrong is like the best found one of the best founders I've ever met and got gotten the chance to work with and fund. And um 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. He 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 out of the gate and he took so much flack for that. Yeah. 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, like and then he got like I read the stuff online and I was like this is crazy. That's the media environment, right? I I thought it was interesting anyway that he came out and did that. And I 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.

I think the biggest thing that is um increasingly true and we're seeing a lot of examples of it in the last year is uh blitz scaling for AI might not be a thing scaling. So I think Reed Hoffman wrote a whole book about it. Um it was definitely true in the time of Uber. So you know that was sort of a moment when um interest rates were descending and then uh these sort of international increasingly international marketplaces the sort of you know offline to online marketplaces like Uber in cars or delivery or you could say Instacart, Door Dash, you could throw in you know Lyft. There was sort of this whole wave of um you know sort of the top startups were um marketplace startups um but also in software too. this idea that, you know, scale could be used as a bludgeon that, you know, the network effects grow um, you know, sort of exponentially and then, uh, because you could have access to more and more capital, whoever raised more money would have won. And I feel like that was extremely true um, 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, uh, we are seeing incredible revenue growth with way fewer people. And that's very remarkable. Um, we have companies basically, you know, going from 0 to $6 million in revenue in 6 months. We have companies going from 0 to 12 million a year in revenue in uh, 12 months, right? and uh with under a dozen people like you usually five or six people and so that's brand new like this is uh the the result of large language models and intelligence on tap um 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 hundred million a year in revenue um really with under you know maybe 10 people, maybe 15 people tops. Um, and so that was relatively rare and my prediction would be this becomes quite common. Um, and my hope is that's actually a really good thing. Like this is sort of the silver lining to um, you know, what has been really a decade of big tech, right? Like it's more and more centralized power. Um, you know, what might happen here is that, you know, and what we're actively trying to do at YC is we hope that there, you know, are thousands of companies that each can make hundreds of millions to billions of dollars and give consumers an incredible amount of choice. Um and we we hope that that will be very different than sort of this you the opposite I think was increasingly true like we have fewer and fewer choices in operating systems in um you know web browsers in you know across the board like just more and more concentration of power in tech.

Yeah, that was true. That was even why Y Combinator in 2005 could exist. You know, I remember working um at a startup in 1999 2000 or at like uh internet consulting firms and these were like million-dollar projects cuz 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 like rack real servers. So the cost of even starting a company was just huge. Yeah. I mean, um, I remember Jeff Bezos actually launched, um, AWS at a YC startup school, uh, at Stanford campus in 2008, right when I was starting my first company. So, um, I think, you

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. In the past it was 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, get your CTO. There was that split. Now what we're seeing is the CEO of the majority of YC companies, they are technical.

Go deeper. They have too many people, right? And then it's all, I think this is what founder mode is actually about. 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. 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, 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, the classic advice for management is hire the best people you possibly can and then give them as much rope as you possibly can and then somehow that's going to result in good outcomes. In practice, and this is the reaction that is turning out to create a lot of value across our community, but I think the memes are out there and it's actually changing the way people are running businesses. It's a shade of what you were saying earlier with Brian Armstrong. You can sit back and allow your executives to sort of run amok, and if the founder and the CEO does not exercise agency, then it's actually a political game and you have sort of fiefdoms that are fighting it out with one another. The leader is not there, then you enter a situation where neither the leader nor the executives have power or control or agency. Then everyone is disempowered. Everyone is making the wrong choice. Retention is down. You're wasting money. You have lots of people working either against each other or not working at all. That's a pretty crazy dysfunction that took hold across arguably every Silicon Valley company period. It's still mainly in power at quite a few of those companies, though I think people are aware now that that's not the way to run your company. Are the bigger companies shaping up? The way I think about this analogy is like 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.

They just didn't want somebody else to have them. Exactly. I guess it felt like a little bit of prisoner's dilemma because I think the result is that tech progress itself decelerated. You have the smartest people of a generation basically retired in place working at places that, the world is actually full of problems. Why are people retired in place pulling down insane by average American standards salaries?

Yeah. That's just one symptom out of a great many that is the result of treating people like hoarded resources instead of, the world is full of problems. Let's go solve those things. When it comes to AI, the raw inputs, if you think about it that way, are the LLM. Then you have power, compute, 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 last year with AI regulation that was potentially premature. There was a moment maybe a year or two ago and you see shades of it in Biden's EO, past a certain amount of mathematical operations, that's banned or not banned but we require all this extra regulation, you have to report to the state, you better get a license. It felt like early versions of regulatory capture where they wanted to restrict open source, 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 competing in a fair market trying to deliver models that any startup could just pick and choose. There's no monopoly danger, no crazy pricing power that one entity wields over the whole market. I think that's really good. It's a much fairer playing field today. It's an interesting moment. There's a new Google-style oligopoly emerging around who provides the AI models, but because it won't be a monopoly, that's probably the best thing for the consumer and for every citizen of the world because you're going to have choice.

It's a great question. There are a bunch of different models that I could see happening. What's emerging for me is that the first wave of people who are really worried about AI safety, not to be flippant, but my concern is that they basically watch Terminator 2. I like that movie too, but there's that moment where the AI becomes self-aware and takes agency. The funny thing is, as of today, these systems are just matrix math and there is no agency yet. They're equivalent to incredibly smart toasters. Some people are disappointed in that, but I'm very relieved and I hope it stays that way because that means there's still a clear role for humans in the coming decades. It takes the form of two very important things: one is agency. People often ask what we should be teaching our kids, and the ironic thing is we send them to a school system that is not designed for agency, it is designed to take agency away from our children. Maybe that's a bad thing. We should be trying to find ways to give our children as much agency as possible. That's why I'm personally pro screens and pro Minecraft and Roblox, giving children a playground where they can exercise their own agency.

Oh yeah, yeah, yeah. I'm a small personal investor in them and I think we're just scratching the surface on how education will actually change. That's a great example. Synthesis is designed around trying to help children actively be in these games that increase instead of decrease agency.

Incredible.

The regulation question is really interesting too because it begs the question of it's a worldwide industry. Regulating something in one country, be it the United States or another country, doesn't change what people can do in other countries. Yet you're competing on this global level.

Yeah. I think the biggest question around it is, of course, the existential fear is where are all the jobs going to go? My hope is that it's actually two things. One is that robotics will play a big key role here. If we can provide robots to people that do real work for people, that will change people's standards of living in fairly real ways. I think universal basic robot is relatively important. Some of the studies coming back about UBI, universal basic income where you just give money to people, it's just not really resulting in a different outcome. They've never read a psychology textbook. Going away from the economics of it, people need to feel like they're part of something larger than themselves. If they don't feel 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. I think we really need to give everyone on the planet some real reason why this stuff is actually good for them. If there is only a realignment without a material increase in people's day-to-day livelihoods and quality of life, maybe we're doing something wrong. Left to its own devices, it's possible. I don't know the specific things, but that's what it would look like if regulation came into play or there was some sort of realignment in reaction to the nature of work changing. That would be the outcome that the majority of people, if not all, see the benefit in some direct way. If we don't do that, there will be unrest. I don't have the answer, but that's one of the things I'd be on the lookout for.

Yeah, we're not there yet. There's some evidence that synthetic data is working and so some people believe that synthetic data is where the models are sort of self-bootstrapping.

That's right. The other really big shift is test time compute. Literally 01 Pro is this thing that you can pay $200 a month for and it actually just spends more time at the query level. It might come back 5 minutes, 10 minutes later but it will be much more correct than the predict next token version you might get out of standard ChatGPT. From what I can tell, that's where a lot of the wilder things might come out. Level 4 AGI as defined by OpenAI is innovators. We have lots of startups both YC and not YC that are trying to test that out right now. They're trying to apply the latest reasoning models from OpenAI that are about to come out, like 03 and 03 Mini, and they're trying to apply them to scientific and engineering use cases. There's a cancer vaccine biotech company called Helix that did YC a great many years ago. What they've figured out is they can actually hook up some of these models to actual wet lab tests. That's something 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? Being able to do new processes or come to a deeper understanding of cancer treatment or anything in biotech, the first experiments of that sort are happening in the next year. Even in computer-aided design and manufacturing, there's a YC company called Camper that is trying to apply, they were one of the winners of the recent YC 01 hackathon we hosted with OpenAI. Their winning entry was literally hooking up 01 to airfoil design, being able to increase the lift ratio just by spending more time thinking about it. It's able to create a better and better airfoil given a certain number of constraints. These are relatively early and toy examples, but I think it's a real optimistic point around how do we increase the standard of living and push out the light cone of all human knowledge. That is a fundamental good for AI. Between that and the inroads it might make in education, these are some real white pill things that are going to happen over the next 10 years. These are the ways that AI becomes not Terminator 2 but instead the age of intelligence, as Sam pointed out in a recent essay. If we can create abundance, increase the amount of knowledge and knowhow 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, there's a YC startup right there on the edge trying to take these models and apply them to domains. It's kind of like Google probably could have done what Airbnb did, but it didn't because Google's Google. In the same way, whether it's OpenAI or Anthropic or Meta's Lab or DeepSeek or some other lab that wins, we're going to have a bunch of different labs and they're going to serve a certain role pushing forward human knowledge. My white pill version of the world I want to live in is one where any kid with agency can get access to a world-class education, get all the way to the edge of what humans know and are able to do, empowered by these agents, empowered by ChatGPT or Perplexity or whatever agent. It's going to look like Her from the movie. We're going to have super intelligent entities that we talk to. I'm hoping that they don't have that much agency. I'm hoping that they are just inert entities that are your helpers. If that's true, that's a great scenario to be in. That's the future I want to be in. I don't think anyone wants to be under the API line of these AIs. That really passes through agency.

Yeah, there are YC companies and many startups out there that are actively trying to build that right now. My intuition is that 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, 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 next logical step. Who's doing that?

I like it. I want equity there.

Hm, it's a good question. It's a bit of a gray area these days. I'm not all the way in. I don't actually run an AI lab, even though...

Yeah, that's right. Not the meta AI lab, the meta as in all of them. Anyway, the funniest thing, my main response to all of that around provenance of the data itself is at some point it feels like it actually is fair use though. That's all the way into law.

My intuition would say people are just going to take the outputs of these AI systems. 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. So why wouldn't...

You're funded. I'm in. I got two ideas now. I love those. I don't know. I think these are all totally open and fair game. Going back to regulation, that's one of the stranger things happening right now. One of the pieces of discourse during the AI safety debates in the last year is about bioterrorism. The wild thing is, possessing instruments of creating bioweapons is already illegal. Do you really need special laws for a scenario that are already covered by laws that exist? That's my rhetorical question back when people are really worried about bioterrorism. There's a funny example where AI safety think tanks were in Congress and they were going to ChatGPT and typing in a doomsday example and it spits out an instruction manual on what you need to do, acquire this, do this in the lab. Of course, those steps are illegal. A cooler head prevailed when the rebuttal was someone next went to Google entered the same thing and got exactly the same response. So yes, I've seen Terminator 2 as well. Am I worried about it? My P(doom) score is 1%. I'm not totally unworried. It would be a mistake to completely dismiss all worries. It would also potentially be worse to prematurely optimize and make a bunch of worthless laws that slow down the rate of progress and prevent things like better cancer vaccines or better airfoils or nuclear fusion or clean energy or better solar panels or engineering manufacturing methods that are better than what we have today. There's so many things technology could do. Why are we going to stand in the way of it until we have a very clear sense that is actually what we need to do?

It's brand new, so the risk is always there. It's so funny though. I'm not unafraid. On the other hand, the principle of you can just do things still applies to computers. If the system becomes so onerous, maybe you would go and shut down the power systems, shut down the data centers themselves. Why wouldn't people try to do that? They might do that.

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 I need to live like that's what's going to happen.

I think there are lots of reasons why it won't happen right now, but who's to say? Everything is moving so quickly. These questions are the right questions to ask. I just don't have the answers to them.

It's like asking will Windows or Mac win? We're just literally living through that time where very smart people are fighting over the marbles right now. Totally. Working backwards, the best scenario is one where we have lots of marble vendors and you get choice and nobody has too much control or cornering of all the resources.

I think 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. I hope they continue.

It's kind of funny because my critique on Meta would be, they very openly make it in everyone's faces. 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, and 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. How 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. I'm a little bit mystified. If they were very unified about it, I would really get it. Clearly the way we're going to interface with computers is totally going to change. What Anthropic is doing with computer use is, I think, 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 the runtime that you run on your computer. There's going to be a layer of intelligence. You can see the shade of the very dumb version of it from Apple and Apple Intelligence, sprinkling in intelligence into notifications and things like that. I think it's virtually guaranteed that the way we interface with computers will totally change in the next few years. The rate of improvement in the models, as of today all the smartest things that you might want to do, there's still things that you have to go to the cloud for, and 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 are parent models and child models, so there's distillation happening from the frontier 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 got 84% on the AIM math test. 1.5 billion parameters is so small that it could fit on anyone's phone. DeepSeek R1 just got released this morning. 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. We're right at that moment.

Oh I don't know. I haven't tried it yet. Some of it is you can be very specific about what parts of the domain you keep.

Math might be one of those things that just doesn't require 1.5 trillion parameters. It takes 1.5 billion to do an 84% job of it, which is pretty wild. That's another weird thing of AI regulation. Biden's last EO was sort of this export ban and DeepSeek is a Chinese company releasing these models open source. I believe that they only have access to last generation Nvidia chips. Some of it is like why are we doing these measures that may not even matter? It's interesting 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.

So many rent seekers. I want to foster an environment of more competition within sort of general safety constraints, but I don't think we're pushing up against those safety constraints to the point where it would be concerning. We also operate in a worldwide environment where other people might not think the same way about safety that we do. 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 the AI czar is Shriram Krishnan who used to be a general partner at Andreessen Horowitz. I think that's a 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. I think it is a real concern that the space is moving so quickly that if it takes legislation 2 years to make it through, that might be too slow. It's 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 should be able to respond quickly whether it's through an EO or other means.

Neither do yours.

That sounds right. I think it's more profound now than ever before. The other thing that's really wild to think about is that meme on the internet where there's the guy at the dance, everyone else is dancing and they're in the corner and it's like they don't know. If you go almost anywhere in the world, people maybe have heard of ChatGPT, they definitely haven't heard of Anthropic or Claude. It just hasn't touched their lives yet. Meanwhile, the first thing they do is look at their smartphone and they're using Google and addicted to TikTok.

My hope is that there's such a flowering of choice that it's going to be your choice actually. The difficulty is then you have a filter bubble, but that exists today with social media. Okay, so here's a white pill that I don't know if it's going to happen but I hope it happens. One of the reasons why it's so opaque today is that X had thousands of people working there. You needed thousands of people maybe. Elon came in and quickly asked 80 or 90% of the people to leave and it turns out you didn't need 80 or 90% of the people. That's another thing. You can tinker around with my For You. My For You was written for me in some server some place and there's a whole infrastructure thing. You don't control it. But it's conceivable today with codegen, engineers are writing code about 5 or 10x faster than before. That capability is only getting faster and better. It's conceivable that you should be able to just write your own algorithm and run it on your own, and you'll want choice. The kind of regulation that I would hope for is open systems. I would want to actually write my own version of that. The best version is I want to see my For You algorithm very plainly and then I want to be able to convert that into the one that I want or choose from 20 different ones.

So if regulation is coming, give me open systems and open choice. That's the path towards liberty and human flourishing. The opposite is clearly what's been happening. Apple closing off the iMessage protocol so that it's literally a moat. Oh no, that person has an Android, so they're going to turn our really cool blue chat into a green chat.

Yeah, right. I know. That's just a pure example of Apple even today still, they're opening it up a little bit more with RCS, but those are in reaction to the work of Jonathan Kanter and the DOJ. There are efforts out there that are very much worth our attention around the ways in which these subtle product decisions only make money for big tech and reduce choice and ultimately reduce liberty. It'd be super interesting to have an advantage if you're big tech and you come up with this, but have that advantage erode automatically over time. You might have a 12-month lead, but what you're really trying to do is foster continuous innovation. If you're a government trying to regulate, I don't want to give you a golden ticket. I want you to have to earn it and you can't be complacent. You have to earn it every day. Maybe you have 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 push forward instead of just coasting. Apple really hasn't come up with a ton lately.

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.

That's the hope. We're friends with a great many people who are in the administration. We're very hopeful and we're wishing them, hoping that really great things come back. In full transparency, 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 an NPC in the system. But also, I'm a San Francisco Democrat, so I have very little special knowledge about how the new administration is going to run. Except that I really am rooting for them. I'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.

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. From here, the kind of world we live in will be very different if somehow the AI entities are given, maybe the line is actually will we have an AI CEO? Will we have a company that just literally gives in to whatever the central entity says? That's the exact extreme opposite of founder mode. It's AI mode. Will we live in a world where corporations decide that a human is messy and kind of dumb and doesn't have a trillion token context window and won't be able to do what we wanted to do, so we would trust in an LLM consciousness more than a human being? I'd be worried about that.

Yeah. What's funny about it is in those scenarios, you might just see a crazy speed up because of human effects. When you look at organizations and how they make decisions, so many of them have a Straussian reading. At the surface level you're like I want to do X, but right below that is something that is not about X. For a corporation, it has to be we have a fiduciary duty to our shareholders and we need to maximize profit. Right below that, corporations or any set of people do all sorts of things not for reason X on the top. It's actually, the people who are really in power don't like that person or they rub them the wrong way.

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. That's why in general we really hate politics inside companies.

You know, I guess like now that we're sitting here thinking about it, it's sort of conceivable, but in all of these cases, I would much rather there be a real human being.

Yeah, that's right. And that might be what ends up happening. Even if 90% of the time you're using the autopilot, you always need a human in the loop. 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 I feel like would be a fun sci-fi book would be just speculation playing out on how this interacts with nation states. Like China obviously is run by a central committee and arguably Xi Jinping. Seemingly if you had ASI you would only want the central committee to have it.

Form of that. You know, it's sort of.

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, right?

Fascinating.

And then yeah, the question is like well what how does America approach it? Potentially it's much more laissez-faire and then in that case, my argument would be that the most American version of it is that you and I have our own ASI and each citizen should be issued an ASI and taught how to get the most out of it. Maybe it needs to be embodied with a robot; we should all be Superman in that sense. And that would be the most empowering version of a society of free and equal people. And then there might be other versions; I'd be curious what the European version of it is. Maybe that version has all the checkmarks and every decision has to be checked if this AI assisted or not, and let's check the provenance on how that AI was trained. I don't know, there are a billion different ways these different governments are going to approach this technology.

You know how that AI was trained and I don't know, there are all these different, there's a billion different ways all these different governments are going to sort of approach this technology.

I mean, the hard part is 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 smartest people are clearly the people who are in the AI labs actually actively creating these models. But the people I know who are in those rooms, it sounds like test time compute is really it. The reasoning models are the thing that will come to bear this year; we're sort of underestimating that right now. For now, it sounds like pre-training might have hit some scaling limit, the nature of which I don't understand yet. There's a lot of debate about it. Will there be new GPT-4 style models that have more data or more compute? There are rumors of training runs gone awry, that the scaling laws may have petered out, but I don't know.

The way OpenAI talks about o1, they're sort of connected but different steps. Okay. And so we have progress there, then we have progress with the data, and then we have progress with inference.

Oh, talk to me.

So you think this is going to continue like

Trillions of dollars of investments in AI.

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 overseas to do these jobs. AI is just coming in, and the speech to text and text to speech are indistinguishable from human beings now. You can train these things, the evals are good, the prompting is good. Going back to what we were saying earlier, like it or not, it is actually replacing labor. Has anybody created an AI call center from scratch and now is ingesting customers?

I would love to see government call centers go to this.

Uh, and probably more securely and reliably and more consistently regardless of who's on the other end or how they're talking. How would you define AGI?

Like AGI, the thing is, in a lot of domains it feels like it's here actually.

You know, can it have a conversation with someone and give incredibly good wine pairing recommendations, have a perfectly indistinguishable interaction, and also 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, this is the year where maybe 5 or 10% of things are hitting the Turing test, but maybe this year it goes from 10 to 30% and the next few years are the golden age of building AI.

I mean, I'm mainly a user. I spend a lot of time with people who spend a lot of time in prompts. Probably the person I would most point people to is Jake Heller. He's the founder of CaseText. He was one of the first people to get access to GPT-4 and 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. He said that they had access to GPT-3.5 and it hallucinated too much to be used for actual legal work. With GPT-4, he found that with good evals, they could program the system in a way that it would work. What he figured out was that if GPT-4 started hallucinating, they realized they were doing too much work in one prompt; they needed to break it up into smaller steps. They found they could get deterministic output if they broke it down into steps. And what he needed to do was sort of equivalent to Taylor time and motion studies in factories. He realized he needed to look at what a real lawyer would do and replicate that in the process and prompts and workflow. So for instance, doing a summarization, he would have to go through and read all the materials. Lawyers have their many different colored flags and highlighters; they get very good at doing a read-through paragraph by paragraph, sentence by sentence, pulling out relevant things, and synthesizing them. Early versions of CaseText were still doing that. It's like, what is a specific thing that a human does? Break it down into the very specific steps that a human would do. If it breaks, you're asking too many things in that step, so break it down into even smaller steps. That worked. This is the blueprint that a lot of YC companies and AI vertical SaaS startups are doing across the industry right now. They literally model out what a human would do in knowledge work, break it down into steps, and have evaluations for each of those prompts. As the models get better, because you have the golden evals, you just run the golden evals against the newest model. You have an eval which is a test set of prompt, context window data, and output. You can even use LLMs in the evals themselves to score them.

Um, at a very granular level, you might have thousands of these. And that's how Jake Heller figured out he could create something that would basically do the work of hundreds of lawyers and paralegals and it would take a day or an afternoon instead of 3 months of discovery.

Oh, I love making stories with them. I find o1 Pro is extra good now. There's an interesting thing happening right now. I saw it up close this morning looking at some blog posts about DeepSeek R1. I was reading Simon Willison's blog post about DeepSeek R1 running. It's one of the first open-source versions of the reasoning. And so what we just described with how Jake Heller broke it down into chain of thought to make CaseText work turns out to map to how the reasoning stuff works. The difference between what Jake did with GPT-4 and what o1 and o1 Pro and DeepSeek R1 are doing is that those steps, breaking it down into steps and the metacognition of whether it makes sense at all of those micro steps, that's what the reasoning is actually happening in the background. If you use ChatGPT, you'll see the steps but it's a summary. I just saw it this morning; this is such new stuff. I was hoping someone would do an open-source reasoning model just so we could see it. Simon's blog post showed a prompt and then pages and pages of the model talking to itself. What we described as a totally manual action that a really good prompt engineer like Jake Heller did, and he sold his company CaseText for almost half a billion dollars to Thomson Reuters, is actually very similar to what the model is capable of doing on its own in a reasoning model. That's what it's doing with test time compute, spending more time thinking before it spits out the final answer. So how do you create a competitive advantage in a world where that advantage might be built into the model for free?

Okay. I want to play a game. You have 100% of your net worth. You have to invest it in three companies.

And so the first company you have to invest half, then 30, then 20. So altogether 100%. Which companies out of the big tech companies, how would you allocate that between my biggest bet, second biggest bet, and third from today going forward?

Probably.

I mean Nvidia just has an out-and-out lead. For now they're so far ahead of everyone else. It can't last forever, but the demand for building the infrastructure for intelligence in society is going to be absolutely massive, maybe on the order of the Manhattan Project. We just haven't thought about it enough. It's entirely conceivable that if Level 4 Innovators works out, it's the meta project because it's the Manhattan Project of instantiating more Manhattan Projects. If we can have more test time compute, you could do the work of 10,000 200-IQ Einsteins working on bringing us unlimited clean energy. That alone is probably the bigger problem. We know the models will continue to get better. The demand for intelligence will be unending. Even going back to the robotics question, if we end up making universal basic robotics, the limit will still be the climate crisis and the available energy. Maybe solar can do it, but I think energy and access to energy is the defining question. Everything else you could solve if it's in the realm of science and engineering. Between robots and more intelligence, we could figure things out, but not if we run out of energy.

I think Microsoft has really deep access to OpenAI and I think OpenAI is—you said public companies, right? So I think there's a nonzero, pretty large percentage of the market cap of Microsoft that is predicated on Sam Altman and the team at OpenAI continuing to be successful.

Totally.

And then why Meta? I think Meta is the dark horse because they are amassing talent and they have crazy distribution. I would never count Zuckerberg out. He is always thinking about what is the next version of computing, 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 profound way.

Oh yeah.

Oh yeah. He was great. He was very brusque with me. He said, 'You know, look, man, your titles suck and your thumbnails are even worse.' I think he spent so much time trying to understand the YouTube algorithm and what people want that he loaded it completely into his brain.

I think it's clickbait. [laughter] Unfortunately, when you're trying to make smart content, it's tricky. You don't want more clicks, you want more clicks from people who are smart. So we title our episodes differently on YouTube than on the audio feed. If you want YouTube to pay attention, you have to be more provocative intentionally.

Yeah, that's right.

Oh, usually a person looking into the camera seems to help a lot.

Yeah. But once I stopped posting so regularly, it didn't matter as much. But if you're going to post very regularly, that's pretty important. So yeah, unfortunately, it's clickbait. And there is an interesting interaction: you can optimize for better thumbnails and titles for the click-through, but if it has nothing to do with the actual body, you will not get watch time, and YouTube will not promote it because discovery is key.

And then YouTube will be like, oh people aren't watching this, so we're not going to promote it. The big thing about YouTube is discovery.

Well, you do if you are regular. And the other hack is be shameless about asking for subs. The funniest thing is that subs do very little actually. There's no guarantee you show up in people's feeds if someone subs. It helps a little bit. Liking helps more, watch time helps the most. The over-the-top hack is to ask for the like, subscribe, and hit the bell icon. If you hit the bell icon and they have notifications on, that's almost as good as having their email address.

You 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.

I want to ask just a couple 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 important is to be plainspoken and to be hyper-aware of artifice, of basically bullshit. Don't let it creep in. I sometimes am in danger of caring too much about the number of followers I have. I shouldn't be worried about that. I should be worried about staying authentic. I spend a lot of time with our YouTube team and media team at YC talking about this. If we get too focused on view count, we're liable to optimize for the wrong audience. If we're not being authentic, we're just on a treadmill. Trying to be very high signal-to-noise ratio. The thing I probably struggle with most is that sometimes I think out loud, but really great ideas are not thinking out loud. They are figuring out a complex concept and then trying to say it in as few words as possible. The amount of time Paul spends on his essays is fascinating. Sometimes days, sometimes weeks. He iterates and sends it out for comment. The amount of time he spends whittling down the words and trying to combine concepts is shocking. Writing is thinking. One of the more surprising things we do at YC is help people spend time thinking about their two-sentence pitch. You would think that's startup 101, but the reason it's important is that it's like a mantra, a special incantation. You believe something nobody else believes, and you need to breathe that belief into other people in as few words as possible. The joke is that you might run into someone who could be your CTO, introduce you to your lead investor, or be your best customer, and you only have time for two sentences. A great interview is when someone comes in and I get it immediately. That's what a great two-sentence pitch is. Knowing what it is is very hard. That's all of Paul Graham's editing down in a nutshell. People do complex things; how do you say what you do in one sentence? That's very hard. The second sentence is why is it important. Clear communication is clear thinking. When I first joined YC, I had no intention of ever becoming an investor or partner. I was a designer in residence. I did 30-45 minute office hours with companies in the YC Winter 2011 batch. I used OmniGraffle a lot. We designed their homepage. Some people took those designs and that became their whole startup, selling for hundreds of millions of dollars years later. Clear communication, great design, creating experiences for others are all the same skill. That's what a founder really is. It's not someone with a firm handshake who bends the will of people. Think about that guy—SBF. He was full of artifice, a caricature. We see very autistic, incredibly smart engineers all the time, but for him it was part of the act. He did a YouTube video with Nas Daily. I love Nas Daily, but I couldn't believe the video SBF went on. It was full of bullshit. The exact opposite of Brian Armstrong. They were always on the lookout for that. He wasn't trying to fool you; he was fooling the world. It's hard to fool somebody who knows versus somebody who doesn't know. He was trying to appeal to other people who didn't know. It's the same as going back to Buffett. Everybody repeats what Buffett says, but the people who actually invest for a living or know Warren or Charlie can recognize the frauds because they can't go a level deeper. They can't go into the weeds. Those guys can go from the 1-inch level to the 30,000-foot level and everything in between, and they don't get frustrated if you don't understand. Fraudsters can't traverse the levels and they tend to get defensive or angry with you for not understanding. That's really interesting. I just want to tie the writing back to what you said. You said if you can't get it clear in two sentences, you might miss an opportunity. That goes to the 10-minute interview. You're looking for that level of clarity. It's the work of producing that that helps you hone in on your own ideas.

Yeah.

They were always on the lookout for that.

Was that? Oh yeah, I guess so. I mean, he was fooling the world

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 spent time with them can recognize the frauds

Yeah. I feel like we're in the idea fire hose. We're hearing about all kinds of things that are very promising. The most unusual thing that I'm still getting used to is, in full transparency, the median YC startup still fails. YC might be one of the most successful institutions of its sort, but the failure rate is insane. It is still a very small percentage of teams that go on to create companies worth $50 or $100 billion. The remarkable thing is not that it's low, but that it happens at all. It's just unbelievable.

I think you have the coolest job in the world, or at least in the top 10.

Oh, that's awesome.

All that being said, it's like we're in the middle of the revolution. This is just like I mean it's not even the middle. I think it's like

I'm with you. I'm so excited to be alive right now. So lucky, so blessed to be a witness to this. 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.

Amazing. I want to just end with the same question we always ask: what is success for you? I think looking back, I always looked up to the people who made the things that I loved. Steve Jobs, Bill Gates, people who really created something from nothing. I think of Steve saying we want to put a dent in the universe. Ultimately, that's what I want. Success to me is how do we bring forward the future. When Paul Graham came to recruit me to come back to YC, I had actually left and started my own VC firm. I got to $3 billion under management, Coinbase returned $650 million on that investment alone. I was at the pinnacle of my investing career, running my own VC firm. Paul and Jessica came to me and said, 'Gary, we need you to come back and run YC.' It was really hard to walk away from that. Luckily, I had great partners. Brett Gibson, my multi-time co-founder, went through YC with me. He built a bunch of the software with me at YC before we left. He runs it now; they're off to the races. I sat down with Paul, and right after we shook hands, he said, 'Gary, do you understand what this means?' It means that if we do this right, like what Sam did with OpenAI, pulling forward large language models and AI and bringing about AGI sooner, YC is one of the defining institutions that will pull forward the future. It's not more complicated than how do we get in front of optimistic, smart people who have benevolent goals for themselves and others. How do we give them a small amount of money, a whole lot of know-how, access to networks, and a 10-week program that reprograms them to be more formidable while being more earnest? The rest takes care of itself. This thing has never existed before like this. It deserves to grow. If we could find more people and fund them and have them be successful at the same rate, we would do that all day. What are the alternatives? People are locked away in companies, in academia. The wild thing about intelligence is that it's on tap now. All the impediments to fully realizing what you want to do are starting to fall away. Through technology and access to technology, those things are coming down. If there is the will, the agency, the taste, that's what I want for society. I want them to achieve that.

That's right. Yeah. And that's sort of the quandary. 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 with you.

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