No Priors: Artificial Intelligence | Technology | Startups - How YC fosters AI Innovation with Garry Tan

Episode Date: May 23, 2024

Garry Tan is a notorious founder-turned-investor who is now running one of the most prestigious accelerators in the world, Y Combinator. As the president and CEO of YC, Garry has been credited with reinvigorating the program. On this week’s episode of No Priors, Sarah, Elad, and Garry discuss the shifting demographics of YC founders and how AI is encouraging younger founders to launch companies, predicting which early stage startups will have longevity, and making YC a beacon for innovation in AI companies. They also discussed the importance of building companies in person and if San Francisco is, in fact, back.  Sign up for new podcasts every week. Email feedback to [e-mail] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @garrytan Show Notes:  (0:00) Introduction (0:53) Transitioning from founder to investing (5:10) Early social media startups (7:50) Trend predicting at YC (10:03) Selecting YC founders (12:06) AI trends emerging in YC batch (18:34) Motivating culture at YC (20:39) Choosing the startups with longevity (24:01) Shifting YC found demographics (29:24) Building in San Francisco  (31:01) Making YC a beacon for creators (33:17) Garry Tan is bringing San Francisco back

So today, I know Pryors, we're very lucky to have Gary Tan. Gary is currently the CEO, is that the right title? Yeah, President CEO. The President CEO of Wycombinator. Prior to that, he ran initialized, an early stage venture fund. He started Posterous, which was acquired by Twitter, and has had a storied career working at a variety of Silicon Valley companies, including Palantir and others. Thank you so much for joining us today, Gary.

Thanks for having me. Well, this is going to be our first collabo episode. So part one on this podcast, part two, over at the Gary Tan YouTube channel. So thanks for having me. Thanks for doing the collab. Super excited about it. I love to work with like a real creator. Okay, let's start with like you obviously need no introduction, but people want to know this

story. Like how'd you go from being a founder to an investor at all? I think Paul Graham basically took a chance on me as a founder. And then later I got burnt out. And why see itself I like to think of at. As, you know, today, people sort of look at it as this sort of institution. It's sort of the defining place where people want to start their billion-dollar companies. But I feel like in 2008, when I first found out about it, it was a little bit more like, you know, a punk club in the 90s in Seattle.

And, you know, sort of grunge was just getting started or something. Like these things are basically subcultures and they sort of start off of the internet. And so one of the reasons why Y Combinator was so dominant and, you know, start, even had its chance to start was that Paul Graham's essays for, you know, sort of time immemorial, you know, from his experience creating Yahoo stores, that he would write these essays that basically spoke to the experience of trying to start a company at that moment. So when you go around sort of the legends of, you know, YC, whether it's, you know, Patrick

call us in at Stripe or my buddy Harge, who I work with, who co-founded a company with Patrick. You know, lots of people, even me. I mean, I basically found out about starting a startup, you know, from the news, like that suddenly, hey, there's this person who could sit in front of a computer, create software that could then touch a billion people. And it's like, oh, it's like perfect mimesis. You're like, oh, I want that. How do I do it? And then you go into Google and you type in start a startup and you find Paul Graham's essays and then increasingly they're finding this pod and they're finding my YouTube channel and they're finding the Y Combinator YouTube channel and you know I think all of that is sort of the direction we're going in but that's how it started it was

like literally starting a company was a very strange thing like when all of us came into tech that was I think more true today I think it's something that a lot more people aspire to and that's a really, really good thing. That's sort of what we want. Yeah, it's funny. In 2007, I started my first company. And I remember at the time, people, if you talk to the investor community about Y Combinator, they'd say things like, oh, there's probably adverse selection and who would take that deal and all this stuff. And that's right when Airbnb got funded by YC, when Dropbox got funded by YC. And so it's always striking how right when people start nays saying something, that's actually the moment you know it's working. I'm a little bit curious. In 2008, when you were

going through YC, who were some of the other people who were in your batch or in that same year? Yeah, I remember, you know, actually there were probably three or four companies that ended up, quote unquote, making it, I think. And how big was a batch at that time? Oh, it was only, I think it was 25 companies total, so which is funny because that's the number of companies that a group partner now has. We have 14 group partners at YC now, and each of them fund between 15 and 25 companies each. So I like to say that we basically have 14 of those sort of 2008 era batches happening all of the time. Let's see. There was a company that actually also sold to Twitter, Mike Montano and Chris Golda startup.

And I think it was in basically like comment analytics. And then Mike ended up being VP of Eng at Twitter for many years. Chris still does a ton of YC investing. That's right. Chris is doing incredible investing now. So who else? D. Scott Phoenix is now, I think, over at 50 years, but... The Vicarious. Yeah, he did Vicarious, which was one of the top AI startups for some time,

and then that sold to Google. So, you know, it's kind of cool. Like, I mean, you get started in the biz. You, like, defriend people over pizza and beers, and then years later, you're just, like, sort of trying, you're just, you know, still at it, still doing things. And then now we're trying to help the next generation, which is fun. Yeah, people forget how much longevity there is sometimes in Silicon Valley.

And they forget how you act early, really impacts almost how people perceive you 10 years later or 15 years later, etc. And so it's if you're very non-zero sum early, it really matters in the long run because all these relationships end up unfolding over time. And so it's one of those things I feel is very under discussed. Yeah, that's definitely true. So still, posturous age, Gary. When do you start making angel investments? Oh, gosh, it was much later. I mean, let's see. Posterous was funny because we had a chance to be Instagram, but we didn't know it at the time. Obviously, nobody did. I mean, you were working in the social space too a lot. That was a really interesting moment in Internet history. I think it kind of parallels what people are probably experiencing right now with AI, isn't it? Like, we all knew that something very different was happening with the way humans were sort of communicating.

You know, there was six degrees. There were, like, I mean, all of the same parallels. Like, there were a whole generation of social networks that failed. And then those were the obvious ones to point to and say, oh, this, the whole trend is bunk. Like, it's not going to work. You know, six degrees didn't work. That was a, you know, good enough team.

What happened to that? Or, like, oh, blogger, you know, it's funny because it's sometimes the same characters, right? Like Evan Williams worked on blogger. It was mostly forgotten at Google. And then he just never really. like lost the bug to work on this social space. Probably the craziest thing was, do you remember what Facebook,

like meeting Facebook people was like back then? Like it was like meeting cult members. Yeah, they had a really strong culture. And to your point on the waves, you know, before they had friendster that everybody thought was going to be the winner.

And then MySpace there thought was going to be the winner. And then I remember when Facebook came out, everybody kind of pooped it because they were like, well, it's just colleges and who's really going to care and MySpace is for everyone

and all the stuff. And then, of course, MySpace eventually just kind of in part due to over monetizing the site with too many ads and things like that. But also the founders were not technical. Yeah. Which actually, I think that's even going back to the YC, the cult of YC, I'm starting to realize that is actually one of the core things that we've always believed that extremely technical

people, those are the people who probably should be like the Zucks and the Larry and Sergei's of the world. Like those are the people who we should give extra support to and actually fund and, you Basically, the hard part about playing chess is not knowing how the pieces move. It's being smart. So let's go find the smart people. And then we can teach them, like the community will teach them how to, you know, play chess, the game itself. Your analog to AI and mobile is really interesting because I remember during the early days of mobile, like 2009, 2010.

I remember seeing half a dozen different companies all go from zero to a few hundred thousand users in like a week or two for mobile uploads, photo uploads. and then they die, and Instagram is the only one that sustained. Yeah. And its growth was actually a little bit more linear. How do you all think about that in the context of the batches that you fund at YC? Because you have, you know, over 200 companies per batch now. I think a large proportion or AI-centric.

Is it half a bit? That's about 70% right now. Yeah. So quite a lot. And that's got to be really different from a year and a half ago. Yeah. I mean, it started back then. And then now it's the, I guess the secret is out.

I think GPT4 was actually a really big. big breakthrough. If you talk to Jake Heller at Case Text, he was one of the first people to actually get access to GPT4. And then when he comes and speaks at the batch, you guys should have him on the show. He's actually, I mean, the story, his story is really crazy, actually. They actually, only two of the co-founders had access to it. And then they went off into a room to play with it. They had gotten access to three and three point five before. But four was the first one where definitively they almost never got hallucinations. And so they said, this is actually the moment where they can apply large language models

in a practical way and actually charge money. And so it was actually fascinating to hear, like, you should hear the story directly from him, but I'm just obsessed with it because they were just very pragmatic about here's this API. It literally is a form of intelligence on tap. And then because Jake was a lawyer, he's able to sort of. of go into the mechanics of what a lawyer would do like you're basically just very even like tailored time and motion level like detail of well this is what a lawyer does when they look at a brief and when they're writing a chronology specifically he's doing X and like they're opening

they're they're reading paragraph by paragraph they're converting that into a score like that's what highlighting is at the end you you know take the outputs of that and then so he would you map the specific things that a human would do in this very pure form of knowledge work that pays a lot of money. And then he would turn that into prompts and workflow and testing and scoring. And there's just like a billion different things that frankly like all like probably half of our portfolios right now are in the weeds trying to make those things work. Totally.

And I think like this sort of like if you have somebody who is really technical and our understanding of what the models can do, right? They might not be a researcher, but, like, sees it and has intuition for how to manipulate them. And you have, as you said, like, the time and motion domain person. It's kind of an obvious pattern. Like, we're both investors in Harvey. Like, it's actually a very related story. But I bet, I mean, I want to hear about some of the things you're selecting for in, like, YC founders in this era.

That hasn't changed, though, by the way. I mean, we're just selecting the same type of people that we want, like, all the time. We want highly technical people who are very clear communicators. And so, you know, the bad version of it, which, I mean, you guys get pitches like this all the time. Like you go to an event and someone's like, oh, I'm working on this thing and you dig a little bit. And it's like they haven't talked to customers. They haven't talked to users. There's no insight.

It does everything. Yeah. It does everything. It's a general purpose thing. There's not like a thin edge of the wedge. There's not, you know, some set of users that will absolutely love it. And then I guess like I was speaking about this at what was it, the startup grind. conference recently that like I'm realizing there are just really two totally different

ways to think about the world and then the founders that really do it do it almost entirely from first principles and the for a startup founder that what that means is actually going to talk to founder not not talk to other founders or even talk to investors you know that's all sort of secondhand like to go to pick a very specific set of people it's like not just all lawyers but like, I'm just going to work with litigators, right? Because, and then I'm actually going to focus on corporate litigators who, you know, do this particular segment. I would almost view it as like talking to customers is firsthand, talking to their founders as second hand, talking to investors is third hand.

Yeah. And if you ever go and talk to an investor and an investor in LP or whatever, it's like fourth hand. God help you if you're like trying to make your way by like reading the Wall Street Journal or tech crunch or even Twitter. It's like, then that's fourth or fifth hand. The fourth or fifth hand retelling of things. happened six or nine months ago. They don't know. Yeah. So if you look at the YC batches, so you have 70% of companies now doing AI, if you have, say, 200 to 250 companies a batch, the somewhere between 150 and 200 startups, and to some extent you could argue

each startup is in some sense of vote on what's interesting in AI. If you kind of aggregate up all those startups, are there common themes that are emerge, is there sort of things that are more topical or interesting from a startup perspective? I almost view it as like a lens of like a giant founder voting machine. Yeah, totally. So I'd say like, 70% are somehow related to AI, and then two-thirds of them, you would sort of argue are SaaS rappers, actually. Like, rapper is like sort of the pejorative, but I definitely believe that the sort of chat GPT wrapper thing is actually just wrong. It's like saying that all of SaaS and cloud are basically, you know, MySQL rappers. It doesn't make any sense.

Like, this is just a pure technology that can be implemented. And then essentially, it's a concentrated form of a. intelligence. And then the funny thing about it is like, it's probably only 85 IQ, actually. Like, if you look at who would you actually hire in your real workplace. Like, sorry, 85 in terms of what you need or 85 in terms of what people are using today? Oh, 85 IQ in terms of like when you ask it a question, like, I mean, it's able to give you an answer, but. So the model quality today. I think it's like an eager intern right now. Right. Yeah. It's definitely someone who doesn't know My interns are better.

It's not that. The intern is often better. I mean, you would hope that your interns would be higher IQ than that, right? So 100 IQ is average IQ, right? And then the wild thing is, I think that we're right at that moment where hopefully, you know, looking at 4-0, looking at Cloud 3, like maybe we're just past average intelligence at this point. It's still very limited. Like, you still have to be very constrained. You still have to do the tailored time and motion study to, like, break down the workflow.

to you know as literal as possible an interpretation of what a knowledge worker does but um i think that that's going to bear fruit like they're just companies that uh you know i think last batch uh the average a rr of a yc company was uh six million dollars at the beginning and at the end it was uh north of 30 mill and this was over three months so to get that kind of growth in a very short amount of time like i actually don't think that we've ever had a yc batch be able to get that type of of revenue growth. I mean, an aggregate. And these are all very early startups. These are still like two or three people, the first demo. Like, it's literally the first version of the product. But to be able to, you know, grow at that multiple in such a short time is sort of

a very good indicator. How do you explain that, right? Like, why are the companies working so quickly? Oh, I mean, I think you can walk in and solve a problem very directly that's basically a human being, like, would knock their head into that sand. You know, they would have have to knock their head against that wall always, or you're already paying, you know, an outsourcing firm. You're already, you already have a team offshore that's doing this thing. And then here's this thing that allows you to do that plus more with even less. And it's just like the pure leverage of software. Yeah, it's really interesting because it feels like it's almost like two things are happening. You have a technology disruption that opens up new capabilities for

software. And then you have this really interesting top down openness to try things because it's AI. I've noticed a lot of enterprises just want to do things because they're doing AI and there's a CEO mandate and they have no idea what to do about it and so everybody's scrambling. What does a CSO do that's AI? What does the customer support do that's AI?

And so it kind of opens up a lot of things. Are you seeing any sort of commonalities in terms of like people working at the application layer versus infrastructure? I don't know that you see as many people building models, for example. So I don't know how you think about that stack of stuff. Yeah, it's about, I mean, two-thirds is still like very practical implementation of like ideally

frontier models. And then maybe one third, increasingly are some sort of infra. So tooling, testing, you know, prompt collaboration, like things sort of in the Lang chain, Langfews. Like, there's just this huge proliferation of tools. I'm sure you guys see it all. You're in a bunch of the great ones, too. It's like it's super interesting to see that. The really interesting thing to see also is that you'll have this parallelism of the, like, close source, one that raises a lot of money.

And then you'll have the open source scrappy one that will come and commodify it. And so all of that is sort of happening simultaneously right now. So one thing about the scrappiness is, you know, YC is like, I think, respected for like the scrappiness culture, right, hacker culture. And one question is like, do you expect companies in YC to do pre-training and do their own foundation models in any way? because there is a compute-driven narrative that you need 100 million and then a billion and next generation closer to 10 in order to compete there.

Totally. I think people are starting to do it and then I guess it's kind of like when Cruz came through YC, here's this giant mega research project and you need $100 million to do it and then you work backwards from that. What are the milestones that we can get to so that we can draw a line?

from, you know, we have nothing to we have something to have really have something. You know, that's sort of the question always. So we absolutely have companies that are building foundational models. You know, diffuse bio is doing it over on the bio side. You know, there's a company working on like robotics foundational models. There's so many things that you could do. And then the half a million dollars, you know, during the three or four months, it's sort of what like Kyle did for Cruz.

He had to figure out, well, how do I make? a $10,000 automated driving attachment to an Audi A4 and how do I get people to pay for it? How do I, you know, all he did was actually make a demo that, funny enough, resembles full self-driving in any Tesla car today, but this was in 2013. You could drive up and down 101. It didn't do streets. It didn't do cities. It only did, you know, driving up and down the highway.

and that was enough to sort of show that and to you know attract talent to attract capital and then it basically is a self-fulfilling prophecy so that you know i think that's one of the really uh one of the things that yc founders tell me often is that they feel that um yc is incredibly good at pushing near-term milestones so every week what have you done if you actually followed up on the things that you said you were going to do are you talking to customers like it's very tangible and that pushes progress and i think cruz is a really good example of here's a tangible thing i need to ship. And I think there's a very strong shipping culture. Where does that come from? Is it the partners that you have? Is it originally from Paul Graham? I think there's a really strong

culture of a lot of these things that really help drive progress forward in the earliest stages of a company. Yeah. I mean, I think it was sort of like the blend of a whole lot of different things. Like I actually don't, I think Paul Graham in particular was always about helping people see how big the idea could be. Like you're doing this thin edge of the wedge. But if you do that really well and you do these other intermediate things like wow you could be a 10 billion dollar a hundred billion dollar company and so um i think paul bukite like creator of gmail he was one of the first people to make a group office hours which is sort of using social pressure it's almost like uh alcoholics anonymous as like but for founders where it's like uh you really don't want to

you i mean it's a mild form of co-opetition like you're in competition with your friends like you want them all to succeed, but at the same time, like, if you come and you don't come correct, you're going to feel bad that week. And, you know, our realities are very socially. No, I mean, the YC founder, like, founder friends will tell me, like, they're very stressed about group office hours because they have to show up, right? And like, everybody's going to look around and say, what have you done? Yeah. Did you hit your goal this week, up or down? And one of the things I was joking about, like, I haven't done yet, but it might still do is force people to do pushups if you miss your goal for that week. It sounds ridiculous.

But, I mean, I think that, yeah, our realities are basically socially constructed. And then if you can learn how to run fast, then that translates into mega success. Basically, if you can run fast for a long time in the marathon, then compounding takes care of the rest. In terms of just distinguishing, like, what are ideas that you would actually be willing to back? You've used this analogy of, like, it's a bunch of startups that are mice running around the feet of the elephant. Oh, yeah. That's definitely what's happening. What isn't going to get stomped?

We just ask them. And then if it's plausible and makes sense, you know, why not? Like, I mean, that's the amazing thing about early stage. Like, you can basically, if we learn something from people, if they are, you know, in direct contact with what's really happening, then that's the most powerful thing. What has been the most surprising version of that where you thought this company, this YC company is definitely going to get stumped by an incumbent and they just ended up winning or doing really well.

That's a good question. I mean, there's just so many examples, right? Like scale might be a good example. Like, you know, there's really, you would have assumed that, like, wouldn't Google just do this? Or there are like so many other people who have more or less, like, infinite access to information. Like, Amazon could have done that at some level.

Like, they already have Turks. Like, there's so many other people who could have done it. It's true. I mean, Google had all these organizations where they're paying massive numbers of labelers internally. They had the operational expertise and the need. Yeah, exactly. So, you know, I think that might be the good news for startups because actually the megatech companies have such unassailable moats. And they make so much money that they're actually somewhat incapable of, like, stomping anymore.

It's a weak elephant. It didn't do its push-ups every week. It just doesn't have to, right? Like, you know, necessity is the mother of invention. You know, I used to believe, for instance, that, you know, when I was first coming up, like, writing my first checks in 2012, 2013 as an investor, I didn't really understand what people were saying when they said, oh, like, don't raise too much money. I thought it was only a tactic that like a negotiation.

Yeah, I thought it was a negotiation thing. I was like, surely that's not what happens. And of course, like, you know, many years later, I feel like we have seen what that means. Like lots of, you know, some of our best companies with the best technical founders, they might have raised too much money. And then when it's time to cut, like, you know, I mean, that's a tall order to say it's time to let go 50 to 80% of your staff. Like, are people really willing to do it. Like, these are people who you've hired and you've managed and, you know, you've, like, fought. alongside for this whole time, sometimes for years, and, you know, it's actually too hard to do it, right?

And so I can see that now, like, you know, too much money equals potentially just not doing the right things. And then the worst thing is like not even being able to cut to the point where you can get back on track. Yeah. And companies are so half dependent that now you still have a series of companies that raised a bunch of money maybe later in their life cycle over the last five years. And the war chest was so large that they're still sitting on it. They're sitting on evaluation. That's very painful and trying to think about the down round and all of that. And the question is like, you know, some of these companies, there's fundamental goodness in there.

Can they make the hard decision to get through it? Yeah, that's right. How have things shifted in my C over time? So I know in the earlier days, if I recall correctly, a subset of the companies would actually emerge, right? And so they, you know, somebody would have an idea that wasn't quite working and they'd join one of the teams that was working, or they'd kind of shift ideas midstream.

And also, it feels to me without any data, so it could be wrong, that the demographics used to be younger. In other words, if I look at the early batches of YC, you know, Sam Altman was in there when he was like a Stanford dropout. And there's other people, Patrick and John from Stripe, like people joined really young. Yeah, totally.

Had there been big shifts in those sorts of trends in terms of how many companies can actually raise money out of the program, the demographics of the people? Yeah, great question. Wait, and how old were you when you did YSA? I was 27. Okay, a grown-up. Yeah, yeah, totally.

I think that that's actually the average age of YC at this point. It is trending younger. Like, I wouldn't be surprised if this year was this current batch for summer was close to 25 or 26. But it did trend much older for some time. I think some of it was probably shifting alongside, like, what was fundable and what people wanted to work on. You know, now we're deep in the AI boom. So actually working on software and being a great software engineer. is actually almost all you need sometimes.

Like when you're in a world where things are shifting this quickly, like literally week to week, people are creating new ideas, new ways to do things. I actually think that that really shifts back towards much younger founders. So we've seen far more 19, 20, 21-year-olds dropping out of college to start AI companies now, mainly because if they don't, like they'll just miss the boom. Yeah.

And that's actually a very interesting thing. But I will say like maybe three to five years ago, I mean, some of it, like sitting here, I have to say like thank you, Sam Altman, thanks Greg Brockman. Like they took a really mega bet on transformers and those architectures. And they basically showed that like, you know, scaling, you know, you can scale this stuff and that you can get a lot of value out of it. So if that didn't happen, I actually sort of wonder we're starting. would be right now.

You know, three to five years ago, I think YC even was like somewhat known a little bit better for, you know, international companies still chasing, like, standing up vertical marketplaces. And so if you're doing a vertical marketplace, like, you can't even do the vertical marketplace if you have never, you know, been in a shipyard in, you know, in Africa someplace or, like, you know, like, you can't even participate in that. So that obviously, like, skewed things to older and more international founders. That's super interesting. So you basically think that the age of founders is in some sense

dependent on the openness of markets. In other words, if markets are very open, younger people can participate. If markets are closed, then you need years of expertise to go into them. That's right. But that makes intuitive sense, right? There was definitely like, you know, five years ago, three to five years ago, some sense of like end of cycle. You actually wrote about this, I think. But across like the technology ecosystem, it wasn't like the first era of like cloud or mobile or the internet or anything, right? And I think as that happens, like domain expertise, like other advantages matter a lot more. But one of the most fun things right now has to be like nobody has any idea what's going on,

but there's a lot of value creation that's possible. Yeah, that's kind of like core YC original demo, like can make it. Yeah, we're excited about that. Yeah. And then you asked about, I guess, you know, any, I mean, the fundraising thing for YC is very interesting because historically, anytime YC ended up increasing the dollar amount that we would give, we would just get this wave of crazy innovation. And, you know, 2013, or sorry, 2012.

Yeah, it helped a lot. I don't know. 2011 was the moment. It went from maybe $15, $20,000 to $170,000. And then the year after was Instacart, Coinbase. The year after that was DoorDash. And I think we might be experiencing something similar here where, you know, I think it was 2022.

YC went from, you know, really. similar to the previous deal, like $120,000, up to half a million dollars. And then we saw this huge upsurge in really smart, young technical teams again. So I think that there's a market dynamic effect there. And then on the flip side, the most surprising thing coming back from, you know, I mean, quote unquote, being in the wilderness and, like, being on the outside of YC was, you know, And the median YC startup, I think, in 2015, 2014, did not raise, like, that much. It probably still was, like, below a million dollars.

And then these days, it's, like, close to a million and a half to two. I think some of it is probably a factor of compounding. Like, the brand has gotten a lot bigger. The number of- Better founders. We have way better founders. There are more founders who are highly technical or, like, you know, highly articulate or ideally both, actually.

Yeah, I think that we all sort of underestimate the power of compounding. And, you know, the cool thing about startups broadly is that, like, we are still in a rapidly expanding industry. So the rising tide is raising all the boats. How do you think about, you know, being in the SF ecosystem? I mean, I think being in person just makes sense. Going from zero to one, you need to be with, like, the smartest people around you. And then I actually think there's a lot of value in just like the dinner discussions that are happening around San Francisco.

You know, only here can you, you know, can the toolmakers and the foundational model builders and the researchers literally sit down and break bread with the people way out on the edge, like trying to practically deploy these things to every industry and every type of knowledge work in the world. And those are literally sort of the most high value conversations on the planet right now because, you know, know, on the one hand, like, maybe HGI will happen, like, relatively soon. On the other hand, like, it might be longer. And then we're going to be sort of trying to squeeze, like, the most out of, you know, rag out of, like, how do we make embeddings work? How do we actually make this workflow and test work? And, like, people don't know.

Like, you know, the difference between something that is a very good AI, you know, app and, like, something that's outrageously stellar is actually the devil's and the details and all of that stuff. And those people are literally coming up with the concepts and writing the open source and like sharing it on, you know, the forums are global, but like the people making them. Like I think they're within like five miles

of where we're sitting right now. You're widely credited externally as somebody who's really bringing a lot of almost like founder energy back into YC again and helping to really drive future directions. How do you think about where you want YC to be over the next couple years? Like five years from now looking back what do you want to have changed or built or accomplished?

I'm sort of assuming that there's a scenario where there will always be a need for people who understand how the stuff works to continue to build the next version. If we're in a scenario where that's not true, I have no intelligent thoughts on what's going to happen there. On the flip side, like, I think that, I mean, there's no substitute for human, like intent and ingenuity and belief and frankly ideology.

Like I think that, you know, what I love about YCE is sort of like the defining magnet for people who are ambitious and optimistic about technology and smart. And, you know, those are the people who we really desperately need to save from working at Goldman Sachs. Like, sorry my friends at Goldman Sachs, but like, you know, sort of saving people from investment banking, from consulting, from mid-ex. middle management, from working in big tech, like, you know, we're not numbers. We're free people. Like, we need to escape and create. And, you know, if it's one thing I've learned, like,

that's sort of the responsibility and the obligation, you know, to whom much is given, much is expected. And, you know, what I want YC to be is like sort of that, like, beacon and institution. Like, you know, if you have an idea, if there's a problem in the world to solve, It could be, if it could be solved through capitalism technology, which, like, I fully admit, like, you know, some people might say, like, absolutely everything can be solved that way. There probably are things that can't be solved that way. But if it can be, like, come fill out this 12-question form on the Internet and people who came before you who are, you know, basically pure of heart and, you know, ideologically with you, we'll try to help manifest that with you and we'll put you in a room with. hundreds or thousands of other people who all believe that and if not us then who you know it has to be us like we have to create a movement of people who believe this thing and then create it

should talk about s-f being back what is that going to take uh i mean i guess i'm still figuring it out and then and for context by the way for for uh people listening and at least on our side you know gary has really emerged as one of the leaders in san francisco in terms of really taking a moderate, thoughtful stance in terms of, you know, what does the city need? How can we encourage development in different ways? How can we make sure that different types of people across the city are taken care of properly? And just being very thoughtful about how do we just think about society and culture in our city? And so I think that's kind of the context. And I think the stance is also like also in terms of ambition, like expecting excellence

in San Francisco and that being possible, both in terms, you know, anything from like safety to support of businesses to support of different communities. And so I think there's an expectation that Gary is putting on a policy agenda and people here. Some of it is we just actually want effective government. So there's lots of things that like private enterprise cannot fix. Like private enterprise literally cannot help people have a great public school education. You know, I'm the product of public schools. Like if I couldn't study algebra in middle school, if I couldn't study calculus by senior year, I couldn't have gotten into Stanford. I couldn't have studied computer science, and I never would have been able to participate in, like, what is the craziest thing that's, like, I think very important, like, to be able to create technology itself's problems, right?

So, and it's crazy that we have people from around the world, the smartest people, you know, the most ambitious people in the world who immigrate here from all around the world. Like, we literally brain drain every other, you know, sort of city and country in the world to come to, like, that's why San Francisco is so diverse. like that's actually amazing like every type of food that you could possibly want like you can get like a very good version of it here like this is like the definition of a cosmopolitan city and then you know we say come like build the future and then you know when they have kids it's like oh yeah your kids can't learn algebra like it doesn't make any sense like how can we do that to ourselves and when i dug a little bit more it's actually just that people are too afraid to say things and so my main thing is like if you're listening um you know if you're you're watching, please, like, speak out, right? You know, I think that SF got very, very bad because you couldn't say basic things like, I believe in algebra for middle schoolers, right? And that war is raging in, you know,

in the hallways of the school of education at Stanford right now. You know, there are researchers who are highly politically and ideologically motivated who have control of the apparatus that is like, you know, sort of quote-unquote science, I guess. And then you have real scientists, real mathematicians, real computer scientists at Berkeley and Stanford coming and saying, what do you mean you shouldn't, you know, teach children math at that age?

And that's like the level of discourse that we're at. And then when you remove the access to math, like how could, like that actually hurts the most, the people who most need good public education. Because, you know, if you're, if you don't have money, you go to. public school. And if you can't even take math, how could you even create stuff? Like, we desperately need that. This is literally the most vibrant community of people in the world. It's like this sort of pressure cooker of the smartest people with the best, with the most ambition. And that's a good thing. And their children should be allowed and should have, you know, they don't, they shouldn't

have to be rich to be able to actually participate in what's going. I'm also a product of public schools. And I feel like there's a lot of ideological removals. of ladders. It's kind of preventing other people from climbing up as well. And so I think it's great that you're doing a lot of this work to say, okay, let's extend the ladders. Let's allow more people to rise up in different ways, learn things that are important for their education and participate in the modern economy. I think we're just getting started at some level. You know, I think there's going to be bumps along the way. But it's actually not more complicated than knowing about the issues, talking about it at dinner, and then voting, like, making sure you vote

and make sure you use the GrowSF voter guide, you know? Like, you actually have to, you know, educate yourself on, you know, the pros, cons and what's going on. And then, you know, there might be a moment in the future where it's like, oh, actually, like, maybe we did everything we could, but we are still very far from that. Like, the, it's very obvious still what we need to do. It's interesting how controversial, like in narrative, some of these issues become, because so much of it is framing. And I think, like, a voter guy that talks specifically about initiatives and budget spending is a great way to sort of disambiguate that. Because to some degree, I can't imagine, like, access to math education is, like, I mean, I'm a public school math nerd, right? And I look at, like, the people that we get to back that are changing the world that have massive access.

access to opportunity, many of whom are immigrants and children of immigrants, um, that come from diverse backgrounds. And I'm like, I think what we should be trying to do is get more people into competition math and like more access, um, versus shove down the ceiling. But again, now I'm using pointed language because I think, uh, I think when you frame it as an issue of racism or, uh, or whatever else, like, you know, it becomes a lot more complicated than actually is. Yeah. I mean, there is a lot of nuance in these things. Um, and so getting it right is hard. But, um, I think what happened is, you know, in tech, but like broadly just like normal human beings trying to make their way about in, you know, just taxpaying citizens who are just trying to

like live their lives. We sort of put blinders on it. Like it got too, like, messy and it got a little bit too scary to talk about. And I guess what I'd love and what I think is happening right now is that people are speaking up. Well, and I think a message that is perhaps not at all political, but is a good and inspiring one to end on before we go to part two, Gary's YouTube channel, and talk, you know, again, more about AI and such is, like, you know, re-igniting a grassroots degree of civic engagement

across the spectrum and making it possible to talk about these issues with nuance is a very good thing. Yeah. So I'm glad you're doing that, Gary. Thanks so much. Thanks for having me. Find us on Twitter at No Prior's Pod. Subscribe to our YouTube channel if you want to see our faces.

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