Garry Tan: New Rules for Founders

Garry Tan 0:00 We may never achieve a utopia, but it is worthy and worth it to attempt. Everything that's awesome in my life is kind of a cult. We had to go over to the Windows team. They wouldn't reply to our emails. They wouldn't fix our bugs, and we had to go over there with a baseball bat. An org like Microsoft can't.

Anish Acharya 0:18 Yes.

Garry Tan 0:19 But a startup can.

Anish Acharya 0:20 Yes. Yes.

Garry Tan 0:20 And every startup must.

Anish Acharya 0:26 Garry, so good to have you, brother. Thank you so much for joining us today.

Garry Tan 0:30 Thanks for having me.

Anish Acharya 0:31 Amazing, dude. Well, we're gonna cover a bunch of the basics, and then we're gonna get into the advanced topics to make sure that we, uh, kind of match the, the curiosity, ambition of our audience.

Garry Tan 0:39 That sounds great.

Anish Acharya 0:40 Does that work? Awesome.

Garry Tan 0:41 Yeah.

Anish Acharya 0:41 Well, dude, maybe talk to me a bit about the beginning of your journey, 2003. You know, it feels like what's under-discussed is founder psychology and then sort of Silicon Valley culture and how the two are connected. What did it feel like when you first got in the game back in 2003 coming out of Stanford?

Garry Tan 0:55 Yeah. I guess I wanted to work at startups, but, uh, 2003 was funny in that, like, Web 1.0 had just ended.

Anish Acharya 1:02 Mm-hmm.

Garry Tan 1:02 Like, the, you know, NASDAQ had just crashed, and, uh, actually, there were no jobs that I could even find in the Bay Area other than, you know, working at Gap IT.

Anish Acharya 1:12 [laughs] Rough.

Garry Tan 1:13 And so the two job offers I had were, uh, Microsoft for Windows Mobile, which I was pretty excited about, or Expedia.

Anish Acharya 1:19 Okay.

Garry Tan 1:19 Yeah. I, you know, I had student loans, and I, you know, while I wanted to start a company, I just, you know, felt like I needed to get a job, and then actually there were no jobs in the Bay. So it was, like, kind of hard to believe, actually. Uh, that moment was so bleak, and then right before Web 2.0.

Anish Acharya 1:37 It felt like it might've been the end of tech, huh?

Garry Tan 1:39 Right. A little bit. Yeah, that's wh- that was the vibe. And then, you know, at the end of the day, like, that's the boom, that's the bust. Like, these things sort of happen over and over again.

Anish Acharya 1:47 So at the time, did it feel high status to work in tech or on startups?

Garry Tan 1:51 Not at all. I mean, you know, it's sort of lost to the sands of time, but, um, I was still excited about tech, though. Um, you know, I had done a lot of web programming.

Anish Acharya 2:01 Yeah.

Garry Tan 2:01 And then one of my regrets, actually, was, um, I was sort of chasing what was hot instead of what was clearly the thing I knew. Mark Zuckerberg was probably doing Facemash, um-

Anish Acharya 2:12 Yes

Garry Tan 2:12 ... around then.

Anish Acharya 2:13 Yes.

Garry Tan 2:13 Around 2003. And then Facebook didn't even exist yet.

Anish Acharya 2:17 Yes.

Garry Tan 2:17 Um, and I was getting out of web programming at exactly the wrong time.

Anish Acharya 2:22 Because it felt like that was the smart thing to do.

Garry Tan 2:24 It was... Yeah, it was smart, and-

Anish Acharya 2:25 [laughs]

Garry Tan 2:25 ... you know... I mean, this is true now. Um, you know, in, in front of all these people at Startup School-

Anish Acharya 2:32 Yeah

Garry Tan 2:32 ... uh, you know, I sort of started this "Don't LARP"-

Anish Acharya 2:35 Right

Garry Tan 2:36 ... um, meme.

Anish Acharya 2:37 I saw that.

Garry Tan 2:37 Uh, but I think, like, that's, that's embedded in this idea that, like, you should just be earnest.

Anish Acharya 2:43 Yeah.

Garry Tan 2:44 And then you shouldn't follow what the crowd is saying, right? Like, at that moment, people said the web was dead, but that was sort of the perfect time to work on web and social and things like that. Um-

Anish Acharya 2:55 Yes

Garry Tan 2:56 ... and, you know, I didn't do it. I, I ran off and said, like, "Oh, well, the next hot thing will be mobile," so I wanted to work at Windows Mobile, which was true, but, um, why give up, like, the thing that could've been the next thing?

Anish Acharya 3:09 What I love about what you're saying, though, is often when we hear earnest, we think naive.

Garry Tan 3:13 Mm-hmm.

Anish Acharya 3:14 But actually, what it sounds like you're saying is there's, like, earnestness is a sort of result of maturity and courage. Is that right?

Garry Tan 3:20 Courage is actually, I think, the right thing.

Anish Acharya 3:23 Yes.

Garry Tan 3:24 Like, if you know something, it sort of... If someone just, like, comes and contradicts you, or even if, like, a blog post or, like, someone on Twitter, uh, contradicts you-

Anish Acharya 3:34 Yeah

Garry Tan 3:34 ... and you're like, "Well, I, I don't, I don't agree with that because I believe my own direct experience."

Anish Acharya 3:40 Yes.

Garry Tan 3:41 I know that I'm not a time traveler because if I was a time traveler, I would've, I would've sent a message back to myself and said, "Just stay on working on web stuff. Like, you literally have, um, five years of experience on top of everyone else. Like, you could do an end run around everyone. Like, you could've built, like, any kind of social software."

Anish Acharya 3:59 Yes.

Garry Tan 3:59 But instead, I was, um... You know, I was 22, so I was, like, being whipped around-

Anish Acharya 4:04 Yeah

Garry Tan 4:04 ... by, uh, whatever I could read in The Wall Street Journal. And, you know, I... The, the classic question I'm sure you get that, you know, all investors get all the time is-

Anish Acharya 4:15 Yeah

Garry Tan 4:15 ... "What's hot, and what should I work on?"

Anish Acharya 4:16 Right.

Garry Tan 4:17 And that's the wrong question to ask.

Anish Acharya 4:19 Yes.

Garry Tan 4:19 Like, the right question is, like, what are you interested in? What do you know uniquely? And so-

Anish Acharya 4:25 Yes

Garry Tan 4:25 ... that's, like, you know, one of a great many mistakes I made in my career. I feel like I'm a little bit, uh, doomed to be the first principle storyteller of, uh, all the mistakes that I made [laughs] in my career.

Anish Acharya 4:37 Well, I think that it's, it's very inspiring for founders to hear your own journey and your own mistakes and then not feel so bad about the ones that we've all

Anish Acharya 4:45 made-

Garry Tan 4:45 Yeah. That's right

Anish Acharya 4:45 ... along the way.

Garry Tan 4:46 Yeah.

Anish Acharya 4:47 I mean, maybe talk about the culture of Silicon Valley today. You know, on one hand, maybe it was despondent 20 years ago. It's crazy to think that was just 23 years ago that you're talking about. Um, now you think we would all be incredibly elated, yet there's this undercurrent. Maybe it's the LARPing thing that you mentioned. You know, it's being outside of the light cone, the permanent underclass. Where does that come from? Do you think there's any truth in it? Talk through that.

Garry Tan 5:11 I mean, I get it. Like, there's just more competition than ever. And then, um, I think maybe it's just that we're spending too much time in distribution. I think Chris Dixon talks about this all the time-

Anish Acharya 5:25 Yeah. Yeah

Garry Tan 5:25 ... where, um, you know, you're in the idea maze, but, you know, the cool parts of the idea maze are, like, the weird fringe parts, actually.

Anish Acharya 5:31 Yeah.

Garry Tan 5:31 It's always like, uh, what is a toy? Like, and that's the pattern in Silicon Valley over and over again that bears repeating, right?

Anish Acharya 5:38 Yes.

Garry Tan 5:39 Like, the idea that you could have a computer on every desk in every home-

Anish Acharya 5:43 Yeah

Garry Tan 5:43 ... uh, today is like, of course. Like, that's what's come to pass.

Anish Acharya 5:47 Yes.

Garry Tan 5:47 But the people who created that thing, they were fringe weirdo punks, actually.

Anish Acharya 5:51 Totally. Yes.

Garry Tan 5:53 Uh, and-

Anish Acharya 5:53 They were outsiders.

Garry Tan 5:54 Yeah.

Anish Acharya 5:54 I mean, Homebrew Computer Club was not where you were getting laid.

Garry Tan 5:56 Yeah. [laughs]

Anish Acharya 5:57 That's right. [laughs]

Garry Tan 5:58 Yeah, yeah, yeah. You, you just were, like, following this weird obsession that-

Anish Acharya 6:02 Yes

Garry Tan 6:02 ... you know, actually I want my own computer.

Anish Acharya 6:05 And I think Chris has said this too, I think a good measure of how interesting the thing is is can you find the edge?

Garry Tan 6:10 Mm-hmm.

Anish Acharya 6:10 And for the most interesting things, you typically can't. Even if you find the edge of the conversation, you can't find the intellectual edge, which I think is a very good sign. I mean, I had this growing up in the '80s, maybe you had this too. There was sort of one way to be cool in grade school, and probably in high school, and maybe when you got to college you kind of found your people. And now I think one of the miracles of being Internet native generation is that people find their people much sooner. You find your people on Reddit, you find your people on, you know, X or Insta or whatever your network is.

Garry Tan 6:39 Oh, yeah. I mean, that's the coolest thing today. Like, there's probably a subreddit, there's probably, um, a part of X, like, you know, some part of Teapot that is, uh, you know, this part of T- Twitter that, um-

Anish Acharya 6:53 Right

Garry Tan 6:53 ... is just your set of super weird, but, like, really, really into that thing.

Anish Acharya 6:58 Yeah.

Garry Tan 6:58 And you can find your tribe more or less instantly.

Anish Acharya 7:01 Yeah. Yeah, can you talk a bit about the culture of Silicon Valley? It felt like 10 years ago it was sort of, you know, it was lower status to work on something like Palantir, either because people were nervous about doing things that were too much in the national interest, or because it was sort of dismissed as a services business. Now it's clearly one of the most important companies in the world with one of the most compelling CEOs. You were early there. What did it feel like? Why did you do it?

Garry Tan 7:24 Yeah. I mean, uh, I have a worse story than that. I ha- have another mistake story-

Anish Acharya 7:29 [laughs] Okay

Garry Tan 7:29 ... where, um, uh, Joe Lonsdale and Stephen Cohen, uh, were my fraternity brothers at Stanford, Phi Psi.

Anish Acharya 7:37 Wow, okay.

Garry Tan 7:38 Uh, and then I had a job, and they were, like, interns at Peter Thiel's hedge fund.

Anish Acharya 7:43 Okay.

Garry Tan 7:43 And, uh, Peter has this thing where you're supposed to, like, you know, when you start a thing, you write down on a piece of paper all the smartest people, uh, who you need to go and hire and, like, get to join you. And so, uh, they said, "Oh," B- both of them were like, "Oh, let's go get Garry. He's up in Seattle." Like, they flew me down-

Anish Acharya 8:01 Yeah

Garry Tan 8:01 ... to have dinner with him. And he said, you know, Peter said, "I'm so sure this is the right thing for you. Like, here's a check for 70 grand." That is how much I made at Microsoft at the time.

Anish Acharya 8:11 Yeah.

Garry Tan 8:11 And I said, "Thank you very much, Mr. Thiel, but I might get promoted to level 60 this year."

Anish Acharya 8:16 [laughs] Oh, no. Oh, no.

Garry Tan 8:16 Which I did. [laughs] But, uh, I think it's like-

Anish Acharya 8:19 About what, cost?

Garry Tan 8:19 ... that was like a $2 billion, 2 to $4 billion mistake at this point.

Anish Acharya 8:23 Oh, no. Oh, no.

Garry Tan 8:24 Um, and I think about it all the time. Like, basically, I did the same thing again. It was, like, the same thing that got me to go work on Windows Mobile instead of-

Anish Acharya 8:34 Yeah

Garry Tan 8:34 ... um, just staying on the thing that I knew and loved.

Anish Acharya 8:38 Yeah.

Garry Tan 8:39 Uh, it happened again. I was like, "Well, I don't know..." You know, I was working backwards from the map instead of looking down at the territory and saying, like, "Oh, well, th- these are the smartest people I know." Like, Joe and Stephen were among the smartest people I'd ever met.

Anish Acharya 8:53 Yeah.

Garry Tan 8:53 Um, and you know, if not them, like, who was I gonna, you know, be a co-founder-

Anish Acharya 8:59 Yeah

Garry Tan 8:59 ... with? Like, it just, you know, the universe was saying, like, "This is the thing you need to do." But all I cared about was what was cool, what was hot, what would a really good investor say. Um, and the thing is, like, they're, like, going off of, uh, a map.

Anish Acharya 9:14 Yeah.

Garry Tan 9:14 And, like, you can see, you can look down, you can look around, you can, like, have first principles knowledge of what's going on.

Anish Acharya 9:21 Yeah.

Garry Tan 9:21 Um, and you know, what they were doing is, like, they were going to governments and three-letter agencies.

Anish Acharya 9:27 Yeah.

Garry Tan 9:27 And it was clear that, um, the things that really good computer scientists in Palo Alto could do and create-

Anish Acharya 9:35 Yes

Garry Tan 9:35 ... uh, DC did not have access to that. And you know, it's funny how much that thing that they had identified, like Peter and Joe and Stephen, and later Alex Karp identified-

Anish Acharya 9:46 Yeah

Garry Tan 9:46 ... um, that, like, runs through almost everything that we do-

Anish Acharya 9:51 Yeah

Garry Tan 9:52 ... um, in Silicon Valley. [laughs]

Anish Acharya 9:53 Yes.

Garry Tan 9:53 It's just like, uh, the future is already here. It's not evenly distributed.

Anish Acharya 9:59 Yes.

Garry Tan 9:59 And then that's where, like, first principles knowledge or, like, y- just viewing the world as a scientist is actually very useful.

Anish Acharya 10:06 Yes.

Garry Tan 10:07 Um, and what a scientist does is, you know, sure, there's published papers, but you go and you examine all the truths.

Anish Acharya 10:15 Yes.

Garry Tan 10:15 And what you find is that once you go down into the experiment, or you go down and talk to the first party people who are experience a thing, e- experiencing a thing-

Anish Acharya 10:25 Yes

Garry Tan 10:25 ... um, then you learn secret knowledge, then you have gnosis. And so, uh, you know, from Palantir I definitely learned that, uh, everything that's awesome in my life is kind of a cult-

Anish Acharya 10:36 Yeah, yeah

Garry Tan 10:36 ... that starts with some sort of truth or belief that flies in the face of an orthodoxy, which is very punk, actually.

Anish Acharya 10:44 Yes. Yes, yes. Total- dude, that's very-- Rick Rubin would approve.

Garry Tan 10:47 Yeah. [laughs]

Anish Acharya 10:48 Yeah. Well, actually, what I love about what you're saying is that there's a beautiful truth in the fact that you've talked through some of these maybe tragic misses, but you know, the lessons are courage, the lessons are earnestness,

Anish Acharya 10:59 right? The lessons are when your instincts are pulling you to work with a set of people. So, so maybe talk a little bit about, you know, we talk a lot about how Silicon Valley and the magic is it takes outsiders and turns them into insiders, and I feel like YC is the ultimate distillation of that. You know, you go from being two founders, perhaps from a foreign country, to two people with YC on their LinkedIn, and everybody now knows what that means.

Garry Tan 11:21 Totally.

Anish Acharya 11:21 So talk about how that happens. Is it a process? Is it a mindset? And how has it changed over the years?

Garry Tan 11:27 Um, I mean, I have to credit Paul Graham and Jessica Livingston and the original founders, including Trevor Blackwell and Robert Morris. I mean, uh, what Paul and Jessica figured out was that there are lots and lots of really smart people who do not get access, um, to Silicon Valley. I mean, I think in the past you had to, like, go to the right schools, you had to know the right people, sort of, and if you didn't, you'd come to Silicon Valley and you'd try to get invited to the right parties. There was, like, a social network that you had to crack. Um, and then, uh, at YC we have a pejorative for that whole scene, which it's like we call them scenesters, actually.

Anish Acharya 12:07 Okay, okay.

Garry Tan 12:07 Uh, which is, I mean, it's sort of a nod to, like, what you used to have to do. Um, and some people still believe that's, like, how you do it.

Anish Acharya 12:14 Mm-hmm.

Garry Tan 12:15 All they did was say, "You know what? Like, here's a, here's a website. Here's 12 questions." Later, we added, like, a one-minute video.

Anish Acharya 12:23 Yeah.

Garry Tan 12:23 And, uh, people on the other end who are builders are going to try to give you a fair shake. And so today we have, uh, you know, 16 equal partners, including myself, and all of us, like, went through YC and had successful outcomes. And, um, I think there's something valuable to that, that just, you know, welcome to s- welcome to Silicon Valley. We just, um, celebrated, uh, 7,000 people coming to San Francisco, the majority of them, the very first time they came. It's, you know, our startup school every single year. Um-

Anish Acharya 12:54 So incredible

Garry Tan 12:55 ... we kinda call it, like, a birthright, but for tech.

Anish Acharya 12:57 It looked like the Roman Colosseum, dude.

Garry Tan 12:59 Yeah. Yeah, yeah, yeah.

Anish Acharya 13:00 [laughs] It was amazing.

Garry Tan 13:00 Yeah. So I, you know, I think that that's the coolest thing about Silicon Valley.

Anish Acharya 13:04 Yeah.

Garry Tan 13:04 Like, you sort of, it sort of doesn't matter where you're from or who you are. It just actually matters what your ideas are, and can you execute? The on- only other thing that I'd say, like, YC people get that a lot of people don't get is, um, a community of people who-

Anish Acharya 13:19 Right

Garry Tan 13:19 ... you can be super real with.

Anish Acharya 13:20 Right.

Garry Tan 13:20 It's like, if you go to a TechCrunch event, you look to the left, you look to the right, and it's like-

Anish Acharya 13:25 Yeah

Garry Tan 13:25 ... are you really gonna be able to tell them anything real? Like, you're gonna hold your cards pretty close, and, uh, you know, you're gonna say, "How you doing?" And they're gonna say, "Killing it."

Anish Acharya 13:34 Yeah. Right.

Garry Tan 13:34 And then they're gonna ask back, and like, "Oh, I'm also killing it." I mean, honestly, founders really need that. Like, it's very solitary. It's-

Anish Acharya 13:42 Yes

Garry Tan 13:42 ... um, you know, on the day that you lose your best customer, on the day that your best engineer quits, like, who you gonna call? [laughs] And if you have no one, like, I mean-

Anish Acharya 13:50 The day your co-founder-

Garry Tan 13:51 ... a lot of people have no one

Anish Acharya 13:51 ... loses hope and you're not allowed to.

Garry Tan 13:52 Right.

Anish Acharya 13:53 That's a tough day.

Garry Tan 13:54 Yeah.

Anish Acharya 13:54 You know? Talk about the historical upside sort of surprises of, like, founder types, business types, and the downside surprises. What have you learned through YC?

Garry Tan 14:03 I mean, what's cr- we're sort of in the middle of a big transformation now, I think.

Anish Acharya 14:07 Okay.

Garry Tan 14:07 Um, for the longest time, we really, really believed that you needed co-founders. And I think that everything else being equal, having co-founders is net really, really good.

Anish Acharya 14:16 Totally.

Garry Tan 14:17 Um, I think some of this is, like, the beginning of a cult.

Anish Acharya 14:20 Yeah.

Garry Tan 14:20 Like, you know, a cult where there's only one person, and that person can't convince anyone else to join them is, like, you know-

Anish Acharya 14:28 Worse

Garry Tan 14:28 ... worse than a cult.

Anish Acharya 14:29 Yes. [laughs]

Garry Tan 14:29 It's just, like, a crazy person, actually.

Anish Acharya 14:30 Right, right, right.

Garry Tan 14:31 Um, I think this is, like, an old Derek Sivers TED Talk.

Anish Acharya 14:34 Okay.

Garry Tan 14:34 Right?

Anish Acharya 14:34 Okay.

Garry Tan 14:34 Where it's like, uh, yeah, one person dancing in a field is a crazy person.

Anish Acharya 14:39 Yes.

Garry Tan 14:39 But, um, you know, it's really the second person-

Anish Acharya 14:42 [laughs]

Garry Tan 14:43 ... who, like, gets up-

Anish Acharya 14:44 That's right

Garry Tan 14:45 ... and joins that person. Like, then you j- what you find is l- you know, suddenly 10 people or they're-

Anish Acharya 14:51 It's a party

Garry Tan 14:51 ... all dancing. Then it's a party.

Anish Acharya 14:52 [laughs]

Garry Tan 14:52 Yeah.

Anish Acharya 14:53 Right.

Garry Tan 14:53 That's literally the TED Talk.

Anish Acharya 14:54 Love it.

Garry Tan 14:55 And, um, I think there's something to that. But, you know, I think what's happening right now with vibe coding and agentic coding-

Anish Acharya 15:02 Yeah

Garry Tan 15:02 ... um, literally any given person could be 400 [laughs] of that person, like, from two years, like, even, like, nine months ago, um, you can be a multiple of yourself. And so-

Anish Acharya 15:17 Isn't it amazing?

Garry Tan 15:18 Yeah. And so-

Anish Acharya 15:19 Do you think founders are more ambitious than they've ever been?

Garry Tan 15:21 They should be.

Anish Acharya 15:22 Yes. [laughs]

Garry Tan 15:22 Um, if anything, like, that's the number one thing that people should do-

Anish Acharya 15:25 Yes

Garry Tan 15:26 ... is realize that n- like, don't chase your success or my success.

Anish Acharya 15:30 Yes.

Garry Tan 15:30 Like, that was, you know, when we were coming up. Like-

Anish Acharya 15:32 Yeah, that's right

Garry Tan 15:33 ... the game done changed. [laughs] You know? Like-

Anish Acharya 15:36 Yep

Garry Tan 15:36 ... you actually, you can't just do a SaaS thing. Like, you know, I was just doing an analysis on, like, pure SaaS, and I was like, "Oh, shoot." Like, you know, a pure, like, per-seat SaaS thing, like, not totally clear it will exist in another five or 10 years. Like, it's perfectly fine as a wedge, but-

Anish Acharya 15:53 Yes

Garry Tan 15:53 ... if you're doing that now in 2026, like, you better hope that that's, like, a leap to some sort of moat around data or network effects or something else, right?

Anish Acharya 16:01 Yes. Yes.

Garry Tan 16:02 Um, and that's like, you know, if you, if we would time travel to, like, even two years ago, it's like SaaS was God. [laughs]

Anish Acharya 16:09 Yes. Yes.

Garry Tan 16:09 You know? Like-

Anish Acharya 16:10 Yes

Garry Tan 16:10 ... the 1020X, like, next 12 months-

Anish Acharya 16:13 Yes

Garry Tan 16:13 ... uh, revenue multiple was, like-

Anish Acharya 16:15 Yes

Garry Tan 16:15 ... you know, iron law. [laughs]

Anish Acharya 16:16 Yes.

Garry Tan 16:16 And, like, it's hard to believe. It was like, oh yeah, no, that's not true at all now.

Anish Acharya 16:20 Well, all, this is, you know, a related thing that I love is that code is no longer precious.

Garry Tan 16:24 Mm-hmm.

Anish Acharya 16:25 Like, uh-

Garry Tan 16:26 That's the best. Yeah

Anish Acharya 16:26 ... the things that we had to go through to get something shipped.

Garry Tan 16:29 Yeah.

Anish Acharya 16:29 And that's why you had to have this, like, sense that what you were making was important with a capital I.

Garry Tan 16:33 Oh, yeah.

Anish Acharya 16:33 And that actually flies against the kind of beautiful truth we were just talking about. Because often earnestness isn't obviously important with a capital I, so you pursue things that seem important when most of the most important things actually start out seeming actually unimportant.

Garry Tan 16:47 Oh, yeah.

Anish Acharya 16:48 I know you've been all over this with GStack and GBrain and, you know, when you started out to build those things, was the intention to, like, contribute to the community or just explore your interests?

Garry Tan 16:57 Oh, I was just messing around.

Anish Acharya 16:58 [laughs]

Garry Tan 16:58 Like, you know, uh, what was it? I think Boris Cherny came on Lightcone podcast.

Anish Acharya 17:03 Right.

Garry Tan 17:03 And I just felt, like, the urge to... You know, and a bunch of our f- mutual friends, like, all of them, uh, basically just started coding again.

Anish Acharya 17:11 Yes.

Garry Tan 17:11 And I was like-

Anish Acharya 17:12 Yeah

Garry Tan 17:12 ... "Oh, something's happening. I'd better start."

Anish Acharya 17:14 Yes.

Garry Tan 17:14 Um, and then initially it was just messing around. It's like, oh, I mean, what would it be like to do an, like, make an office hours?

Anish Acharya 17:23 Yeah.

Garry Tan 17:23 Um, and then the craziest thing there was, like, we had just started, um, like, recording all of our office hours-

Anish Acharya 17:30 Yeah

Garry Tan 17:30 ... actually, and then I could, I had, like, a few months of data, and there were, like, very clear things that, um, the YC partners used as, like, rhetorical devices or-

Anish Acharya 17:41 Yeah

Garry Tan 17:41 ... ways to, like, draw out, like, a step function in your ambition.

Anish Acharya 17:46 Mm-hmm.

Garry Tan 17:46 Um, and then what's funny is I have this markdown file that is basically, like, the perfect script on how to advise founders to, like, increase their ambition.

Anish Acharya 17:56 Yeah.

Garry Tan 17:56 And then I actually had to go into Claude and I said, "Reduce this by 90%. Reduce the strength and intensity of this prompt by 90%."

Anish Acharya 18:04 Yeah.

Garry Tan 18:04 And then I open sourced that. [laughs]

Anish Acharya 18:06 [laughs]

Garry Tan 18:08 'Cause some of it is, like, you gotta come and-

Anish Acharya 18:09 That's like the MyThos?

Garry Tan 18:09 ... you know, do YC and get the 100%. [laughs]

Anish Acharya 18:11 Yeah. [laughs] Of course. Of course.

Garry Tan 18:12 This is, well, we'll take care of-

Anish Acharya 18:13 I give you Fable five

Garry Tan 18:13 ... giving away the, you know-

Anish Acharya 18:13 Okay. Thank you.

Garry Tan 18:14 Yeah.

Anish Acharya 18:14 [laughs]

Garry Tan 18:15 We can't give away the crown jewels, like, for free.

Anish Acharya 18:17 [laughs] You know? Right.

Garry Tan 18:18 This, just a taste. The first one's free, you know?

Anish Acharya 18:21 Well, dude, Kevin caught this. I think it was at GStack or GBrain-

Garry Tan 18:24 Oh, yeah

Anish Acharya 18:24 ... we're deep in the open source. You had said, "Please apply to YC."

Garry Tan 18:26 Yeah. Yeah, yeah. But only if, if you're a top 10% user of Claude Code.

Anish Acharya 18:31 Incredible.

Garry Tan 18:32 Like, based on whether you're, um, thinking about users, like, thoughtful about your product and your design. Like, it's not, not everyone gets that message, actually.

Anish Acharya 18:41 Yes. Yes. Well, dude, I love that you're doing it, and I love that you're doing it so publicly because I think this comes back to the earnestness point, which is the whole thing about building intuition at this moment is just using the technology.

Garry Tan 18:51 Oh, yeah.

Anish Acharya 18:51 You know, and I think that there's this feeling like, "Oh, how can I possibly catch up?" Or there's so much seriousness around it. It's like, no, just use every model and build completely trivial things if for no other reason to have a chassis with which to learn the new technology.

Garry Tan 19:05 I think the most exciting thing is, like, you can just have ideas, and then in the past it's like, "Oh, well, I had to be the PM."

Anish Acharya 19:12 Yeah.

Garry Tan 19:12 "Let me write the spec."

Anish Acharya 19:13 Yeah. Yeah.

Garry Tan 19:13 "Like, let me make sure I have, you know, one or two engineers." Like, "Oh, how are we gonna do QA?" Like, there's just all this stuff that you used to have to worry about.

Anish Acharya 19:22 Yeah.

Garry Tan 19:22 And then now it's like, no, slash QA. Like-

Anish Acharya 19:24 Yeah

Garry Tan 19:24 ... it, it's done.

Anish Acharya 19:25 Yes.

Garry Tan 19:25 Like, you know, yeah, we tested it. It's good. Like, [chuckles] we have unit tests, like 90% test coverage, you know?

Anish Acharya 19:31 Totally. You know, it's like arranging your Zen rock garden.

Garry Tan 19:33 Oh, yeah.

Anish Acharya 19:34 It's just fun to do it, and the, like, the output doesn't matter that much, which is why everybody talks about coding agents, but very few people are showing their work.

Garry Tan 19:41 Oh, yeah.

Anish Acharya 19:41 'Cause a lot of it is sort of low-stakes work, and I think that's beautiful and okay.

Garry Tan 19:44 Yeah.

Anish Acharya 19:45 You know?

Garry Tan 19:45 No, I mean... And then I think it's crazy to what degree, like, suddenly agency and taste is just, like, off the charts important now.

Anish Acharya 19:53 Right.

Garry Tan 19:54 And then the hard part is, like, helping people realize, like, just by the act of doing it and exercising it, like, that's how you get better. It's... I, I don't actually think that, like, those things are in- innate or inborn. Like, some people have more of it coming out of the womb per se, but-

Anish Acharya 20:09 Sure

Garry Tan 20:09 ... you know, it's-- you just pra- it's like a practice, you know?

Anish Acharya 20:12 Well, let me challenge you on this 'cause-

Garry Tan 20:13 Yeah, please

Anish Acharya 20:13 ... Nikita said this a couple, maybe a year ago, and I thought it was interesting, which is, hey, we were told that the, like, highest form of art in business was, you know, film and software.

Garry Tan 20:23 Mm-hmm.

Anish Acharya 20:24 And now anyone can make films and anybody can make software, yet the same 20% who were originally doing it are still the ones who are doing it. Is there kind of this, like, is agency something that you can, you know, embrace, or are there just people that are naturally high agency and many that are not?

Garry Tan 20:39 Mm. I mean, if I look at my own career, like, I would easily say that I'm a late bloomer and-

Anish Acharya 20:45 Mm-hmm

Garry Tan 20:45 ... you know, I had to make these, like, ridiculous mistakes, like saying no to Palantir or, like, leaving web programming to, like, learn. And so, uh, I feel like my life is somewhat, like, a testament to, no, no, no, like, I can make mistakes and then I can introspect, I can reason about them, and then make different choices.

Anish Acharya 21:05 Amazing.

Garry Tan 21:05 That's the hope anyway.

Anish Acharya 21:06 Yeah. That is the hope.

Garry Tan 21:08 Yeah.

Anish Acharya 21:08 Talk a little bit about loops. I think there are kind of coding loops, um, which are well-discussed, and now the graphs thing, which is sort of, you know, both funny and, and also real. But it feels like the most interesting loops are business loops.

Garry Tan 21:21 Oh, yeah.

Anish Acharya 21:21 Like, how can you actually have a loop where the output is changing the way the business itself operates? I know that Tom gave this great talk about how to organize your company in that way.

Garry Tan 21:29 Oh, big brain. Yeah.

Anish Acharya 21:29 Talk about how YC is organizing around loops and how you're advising your companies to do it.

Garry Tan 21:33 Yeah, absolutely. I mean, I mess around with OpenClaw. I created GBrain, which is kinda like SOTA retrieval.

Anish Acharya 21:41 Mm-hmm.

Garry Tan 21:41 Um, I basically distil- I-- Earlier this year, I created garrylist.org, which is sort of like actually an agentic newsroom.

Anish Acharya 21:47 Mm-hmm.

Garry Tan 21:47 And then I had to create, like, really, really good RAG around, like, you know, uh, personal deep research just to be able to put together some of those articles.

Anish Acharya 21:56 Mm-hmm.

Garry Tan 21:56 Uh, and then all I did was, like, I had OpenClaw look at that repo, extract out, like, the agentic RAG part, especially around, like, um, like after-the-fact, uh, graph generation.

Anish Acharya 22:08 Mm-hmm.

Garry Tan 22:08 Um, and then it just ended up being SOTA even against, like, Memory Palace and a bunch of other open source.

Anish Acharya 22:14 Incredible.

Garry Tan 22:15 Uh, and then what I realized is that just allows the agent to know what million tokens to keep in its head for any given task.

Anish Acharya 22:23 Yes.

Garry Tan 22:24 And so, um, what's interesting is, like, I think there are a couple things at work right now, like, um, the frontier model labs that are, you know, letting you use ChatGPT or Claude. I think that they're still pretty constrained on cost and pretty constrained on, um, amount of compute they wanna give you.

Anish Acharya 22:44 Mm-hmm.

Garry Tan 22:44 And so if you really want to token max, you actually have to use something like Hermes Agent or OpenClaw.

Anish Acharya 22:50 Mm-hmm. Mm-hmm.

Garry Tan 22:50 Um, and then you have to, like, tune it all the way up. Like, you're just like, "Give me... Like, let me load a million tokens or 800,000 tokens in-

Anish Acharya 22:59 Yeah

Garry Tan 22:59 ... to any given request, and, like, have that be in your, like, sol.md."

Anish Acharya 23:03 Yeah.

Garry Tan 23:03 But when you do that, like, I think that you basically get to live in, uh, 2028. Like, you know, it costs, I don't know, 50 or $100,000 a year to, like, use the agents at full strength, like full 150 IP-

Anish Acharya 23:18 For every request-

Garry Tan 23:19 Like, for every request

Anish Acharya 23:19 ... for every interaction. Mm-hmm.

Garry Tan 23:20 Um, but you'll feel it more or less immediately.

Anish Acharya 23:23 Yeah.

Garry Tan 23:23 Uh, it just costs, like, a crazy amount. But, um, for a CEO or for a founder, uh, it actually makes a lot of sense to do that, and you have to give yourself permission to token max in that way. Um, but, you know, and then what you get is, like, I get-- you get to live in 2028 today.

Anish Acharya 23:40 Amazing.

Garry Tan 23:40 Um, but I think, like, going back to what founders can do, um, if you live that way, uh, not only do you wanna do that task, you wanna, like, skillify it.

Anish Acharya 23:51 Mm-hmm.

Garry Tan 23:52 Like, you, you do some, like, feat of strength, and then you turn it into a markdown file plus code plus tests-

Anish Acharya 23:58 Mm-hmm

Garry Tan 23:59 ... that can be reused and, like, put into a cron job.

Anish Acharya 24:02 Yes.

Garry Tan 24:02 And so, uh, I think we're just seeing, like, across the board, um, a markdown file is an employee.

Anish Acharya 24:11 Yeah.

Garry Tan 24:11 And it's an employee that, uh, will do the job perfectly every single time.

Anish Acharya 24:15 Yeah.

Garry Tan 24:15 And it'll do it, like, as many times as you want.

Anish Acharya 24:17 Yeah.

Garry Tan 24:18 And then, you know, at that point, all you're doing is, like, take any business process that you need in your company-

Anish Acharya 24:24 Mm-hmm

Garry Tan 24:24 ... and you just do it once perfectly. And the first time you try to do it, it's gonna be bad.

Anish Acharya 24:28 Expensive.

Garry Tan 24:29 Yeah.

Anish Acharya 24:29 Yes. Many iterations.

Garry Tan 24:30 Yeah. But then at the end, you can, you-- as long as you can Tell very, very quickly and in very simple ways, like, "Hey, agent, fix this, fix that."

Anish Acharya 24:40 Yeah.

Garry Tan 24:40 Like, "This was wrong." Um, you know, the actual trace and the actual, uh, history-

Anish Acharya 24:46 Mm-hmm

Garry Tan 24:46 ... out of, um, that agent, uh, working with you-

Anish Acharya 24:49 Mm-hmm

Garry Tan 24:49 ... it'll actually turn that into a skill file that's perfect actually.

Anish Acharya 24:53 Right.

Garry Tan 24:54 And any time it screws up in, like, a future case, it's just a bug fix, and then it's there forever.

Anish Acharya 24:58 And this loop you would apply to sales, to marketing, to customer support, to everything.

Garry Tan 25:03 Yeah, to everything.

Anish Acharya 25:04 Really interesting. I mean-

Garry Tan 25:04 And GStack was basically that for engineering, right?

Anish Acharya 25:07 Yeah.

Garry Tan 25:07 It's like there's a QA loop. I had to build something that works with browsers to go and... 'Cause that's what I found, like, early with GStack, I found myself, um, you know, automating how I thought about PM.

Anish Acharya 25:19 Mm-hmm.

Garry Tan 25:20 And then, uh, you know, I had a engineering skill-

Anish Acharya 25:22 Mm-hmm

Garry Tan 25:22 ... that was like an eng manager that made sure that there was a unit test and end-to-end test coverage.

Anish Acharya 25:28 Yep.

Garry Tan 25:28 Um, but then in the end, I found myself, like, uh, I automated all the other things so much that all I was doing at the end was black box testing to, to verify. And I was like, "Oh, no, no. Okay." Like, even that part. Like, it's interesting, like, uh, building these agentic systems today, I think that's all you're doing is you're seeing where the bottlenecks are-

Anish Acharya 25:49 Yeah

Garry Tan 25:49 ... and then, you know, almost every single time, it's like, how do I just instruct the agent to create a piece of software or a markdown file that blows away that roadblock?

Anish Acharya 26:01 Right.

Garry Tan 26:01 And then when you take a step back and you've done that for the whole task, it's like, I mean, we, we... There are companies now today that-

Anish Acharya 26:10 Yeah

Garry Tan 26:10 ... you know, we were talking about earlier. It's like literally you can go from zero to 15 mil ARR in about four months with, like-

Anish Acharya 26:17 Crazy

Garry Tan 26:17 ... two or three people-

Anish Acharya 26:18 Yes

Garry Tan 26:18 ... and, like, hundreds of agents, like, you know, a few hundred skill files.

Anish Acharya 26:22 It's amazing. So there's this, like, recursive self-improvement. There's this hill climbing that happens. Like, at what point does it start to fall over? Is there... Like, do you need error correction? Does the errors compound? Does it get constrained by exception handling, human relationships? 'Cause otherwise these companies should just be able to grow and run forever.

Garry Tan 26:41 Yeah. I mean, I guess my experience, once you get a lot of markdown files or, yeah, anytime you have, like, some large amount of data-

Anish Acharya 26:50 Yeah

Garry Tan 26:50 ... um, that's where, like, provenance matters. That's where, um, conflict management sort of... You know, when you have two facts-

Anish Acharya 26:58 Yes

Garry Tan 26:58 ... if you have provenance, then you're like, "Well, this is the more recent one." Like, this is the one that wins. You need a cron job that's sort of sweeping through that and making sure that things are accurate and from the right places. Um, but these are things that I think as you use the systems, um, you just know that you need to build these things.

Anish Acharya 27:18 Yeah.

Garry Tan 27:18 Like anyone who's... Th- I mean, this is actually one of the interesting things that I think is an advantage for founders in their 30s and 40s now.

Anish Acharya 27:25 Yeah.

Garry Tan 27:26 Um, like, I mean, I think that there are gonna be as many Patrick Collinses as ever.

Anish Acharya 27:32 Yeah.

Garry Tan 27:32 Um, but one mega trend that we're seeing is, like, the 35, 40, 45-year-old founder who've-

Anish Acharya 27:40 Yeah

Garry Tan 27:40 ... like, been around the block.

Anish Acharya 27:42 Yeah, yeah, yeah.

Garry Tan 27:42 Um, built a lot of-

Anish Acharya 27:43 Don't count out the OGs [laughs]

Garry Tan 27:44 ... entries. I mean, I think, uh, yeah, Peter Steinbrecher is, like, a perfect example-

Anish Acharya 27:48 Yes

Garry Tan 27:48 ... of that.

Anish Acharya 27:48 Yes.

Garry Tan 27:49 Where it's like he's been around the block.

Anish Acharya 27:50 Yes.

Garry Tan 27:50 Like, he knows what to build.

Anish Acharya 27:52 Yes.

Garry Tan 27:52 Um, and then if you take that person, like suddenly there's 400 of those people, like you can outperform an entire department of, like, any Mag seven.

Anish Acharya 28:01 I also think that if you've had some experience in the enterprise, there are these dynamics that, you know, you can seek to kind of mirror and explore.

Anish Acharya 28:09 So one of the things I'm really interested in is conflict, right? Most people at an enterprise would say conflict is a bad thing, but I actually think that there's this sort of productive, constructive conflict that at its best is the search for truth.

Garry Tan 28:22 Yeah.

Anish Acharya 28:22 These systems allow us to do things like explore conflicting approaches-

Garry Tan 28:26 Oh, yeah

Anish Acharya 28:26 ... and totally unbundle it from the human emotion.

Garry Tan 28:28 Yeah.

Anish Acharya 28:29 And I think that's actually very important because this is why the sort of the decentralization in an organization or an economy works well-

Garry Tan 28:36 Oh, yeah

Anish Acharya 28:36 ... because every idea gets tried, you know?

Garry Tan 28:38 Yeah. Uh, do you know, uh, Pedro from Brex is, like, the most aggressive person I've met who does this with his exec team?

Anish Acharya 28:45 No.

Garry Tan 28:46 So which is cool. Like, he uses... Like, he actually was one of the people who, like, really got me into OpenClaw.

Anish Acharya 28:51 Okay.

Garry Tan 28:51 Um, because he just came in, and you know, he had lunch with us at YC.

Anish Acharya 28:56 Yeah.

Garry Tan 28:56 And he just walked us through, um... You know, the, the vibe around OpenClaw was that it was too unsafe and-

Anish Acharya 29:02 Right

Garry Tan 29:02 ... dangerous, and like delete your whole computer and stuff like that.

Anish Acharya 29:05 Oh.

Garry Tan 29:05 Uh, what he ended up doing was, like, building an entire open source layer, which he actually has open source called Crab Trap-

Anish Acharya 29:12 Okay

Garry Tan 29:12 ... that is, like, an agent that watches all the network traffic and all the things that, um, OpenClaw does.

Anish Acharya 29:18 Nice.

Garry Tan 29:19 And then that's how he squares the circle. Like, Brex is one of the most regulated, you know, Fintechs-

Anish Acharya 29:24 Of course. Yeah

Garry Tan 29:24 ... of course.

Anish Acharya 29:24 Yeah.

Garry Tan 29:24 Um, and then the upshot of what he got is that, um, he has his agent look at the meeting transcripts from, like, all of his direct reports, and he, like, can see that, like, two levels down.

Anish Acharya 29:38 Yeah.

Garry Tan 29:38 And then the thing that really jumped out at me is, like, he can use, uh, meetings that he's not in-

Anish Acharya 29:45 Yeah

Garry Tan 29:45 ... to figure out, like, what's broken, what's in conflict, like, who's, who's in conflict with who.

Anish Acharya 29:50 Yes.

Garry Tan 29:51 Uh, and then sometimes he can show up at a meeting. He has perfect context from, like, the last three weeks of, like, that one compliance team.

Anish Acharya 29:58 Yes.

Garry Tan 29:59 And then he can walk in, and he's like, "Actually, you're right. We're doing it your way," and then he can leave. [laughs]

Anish Acharya 30:04 That's so badass.

Garry Tan 30:05 Yeah. And it's like, can you imagine? Like, that is actually one of the defining reasons why, um, startups or businesses fail.

Anish Acharya 30:13 Yes.

Garry Tan 30:13 It's like, it's actually like a, a management challenge.

Anish Acharya 30:16 Yes.

Garry Tan 30:16 Like, the business becomes too big-

Anish Acharya 30:19 Yes

Garry Tan 30:19 ... to fit in one person's head.

Anish Acharya 30:20 Yes.

Garry Tan 30:20 And then this is, like, the most profound form of you ha- you have agents, you have memory, you have retrieval.

Anish Acharya 30:27 Yes.

Garry Tan 30:27 Um, you, like, zap the rocks more. The rocks give you, like, raw intelligence about-

Anish Acharya 30:33 Yes

Garry Tan 30:33 ... like, what's happening, and it can actually introspect not just on the opinion of, like, someone two levels down in your organization-

Anish Acharya 30:39 Yes

Garry Tan 30:39 ... but it can actually look at the ground truth from the data.

Anish Acharya 30:42 Yes.

Garry Tan 30:43 Right? And it's like that, you know, that's clairvoyance, right? Like-

Anish Acharya 30:46 Yes

Garry Tan 30:47 ... you... I mean- If you, once you have that in your brain, like actually every business in the world is available for you to take their business.

Anish Acharya 30:57 Yes. Yes, yes

Garry Tan 30:58 [laughs] Like, like the world is basically built on, uh, things that are built around human beings, and human beings can only keep seven plus or minus two things in their head-

Anish Acharya 31:07 Yes

Garry Tan 31:07 ... at any given time.

Anish Acharya 31:08 Yes.

Garry Tan 31:09 And you know, guess what? You plus an agent can keep basically three Harry Potter books in your head.

Anish Acharya 31:16 [laughs]

Garry Tan 31:16 You can like rifle shot-

Anish Acharya 31:17 More to come.

Garry Tan 31:18 Yeah.

Anish Acharya 31:18 Yes, yes.

Garry Tan 31:18 I mean, and more to come, right?

Anish Acharya 31:19 Yes, yes.

Garry Tan 31:19 Like, this is as, this is as bad... There are so many cryptoisms that like-

Anish Acharya 31:23 Yeah

Garry Tan 31:23 ... applied like 10 times more to AI, which is like, this is the worst it will ever be-

Anish Acharya 31:27 Yes

Garry Tan 31:28 ... actually.

Anish Acharya 31:28 Yes. Yes, yes.

Garry Tan 31:29 Um, and so the whole world, like all business, all things that people rely on, government especially, uh, is basically still built on a world that is predicated by human beings, limited human beings that can only keep seven plus or minus two things in their head.

Anish Acharya 31:46 Yes.

Garry Tan 31:47 And it's not ready. Like, it's not ready for the world where agents can think at the speed of light, like you have unlimited amounts of it, like unlimited amounts of data. Um, and then, you know, my hope is that like, basically, products are going to be 10 or 100 times better.

Anish Acharya 32:03 Yes.

Garry Tan 32:03 Like, they should be 1,000 times better.

Anish Acharya 32:05 Yes.

Garry Tan 32:06 Like services-

Anish Acharya 32:07 Absolutely

Garry Tan 32:07 ... should be 1,000 times better.

Anish Acharya 32:08 Yes

Garry Tan 32:09 Right?

Anish Acharya 32:09 Yes.

Garry Tan 32:09 Like, you know, the invisible hand of capitalism at that point-

Anish Acharya 32:13 Yes

Garry Tan 32:13 ... like properly done, it's not about lowering the cost of something.

Anish Acharya 32:17 Yes.

Garry Tan 32:18 It should actually be, um, creating these like sort of magical things that... I was like on Wall Street Journal podcast recently.

Anish Acharya 32:26 Yeah.

Garry Tan 32:26 And the reporter like kept trying to, uh, like gotcha me.

Anish Acharya 32:30 Yeah.

Garry Tan 32:30 He kept saying like, "Are you, you know, you guys in tech, are you trying to make a utopia?"

Anish Acharya 32:35 [laughs]

Garry Tan 32:35 And I was like, "This is a trap." Like, I don't-

Anish Acharya 32:37 That's [laughs]

Garry Tan 32:37 ... I would not go f- so far to say, you know. But as I went through like a bunch of examples from like a bunch of the startups-

Anish Acharya 32:44 Yeah

Garry Tan 32:45 ... that you and I have like worked on and funded and things like that, I was like, actually like maybe.

Anish Acharya 32:49 Yeah.

Garry Tan 32:50 Right?

Anish Acharya 32:50 Yeah.

Garry Tan 32:50 Like, you know, we may never achieve a utopia, but it is worthy and worth it to attempt.

Anish Acharya 32:58 Yes.

Garry Tan 32:58 Right? And that, you know, I, I would not say that Silicon Valley or tech will achieve a utopia. I will very earnestly say that we are trying to bring about a better world.

Anish Acharya 33:10 Maybe another way to say this is just this is the least happy you'll ever be.

Garry Tan 33:13 Yeah.

Anish Acharya 33:13 You know? Because I think it, like one of the other implications of what you're describing is just the ergonomics of the sort of white-collar job today. You know, you think about e- you've worked at big companies, like you think of just the kind of morass that you had-

Garry Tan 33:26 Yeah

Anish Acharya 33:26 ... to get through.

Garry Tan 33:27 It's torture.

Anish Acharya 33:27 You think of how lossy the communication is, like the entire management science sort of managerial class, like maybe that was a 100-year distraction from what was founder mode, you know, in, in the, in the Industrial Revolution, all the way through Henry Ford, all the way through some of the early Silicon Valley founders, and then everybody just kinda hit this tidal wave of management.

Garry Tan 33:50 Oh, yeah.

Anish Acharya 33:50 Now we have this new model that can lead to dramatic productivity improvements, like three days a week of really intentional work, maybe one day.

Garry Tan 33:58 Yeah.

Anish Acharya 33:58 And the other days you're touching grass, and I think the time that you do spend is just so much less burdened by the stuff that you always felt like you had to wade through.

Garry Tan 34:07 Yeah, that's right. I mean, if you look at the typical Mag Seven day-to-day, it's insane.

Anish Acharya 34:13 Yes.

Garry Tan 34:13 Like I remember when I was 22 working on Windows Mobile, uh, we were working on, you know, these crazy devices that were like years before the iPhone.

Anish Acharya 34:21 Yeah.

Garry Tan 34:22 And, um, we needed integration, for instance, from the Windows team, which was like, you know, on the other side of the highway in Redmond.

Anish Acharya 34:29 Right.

Garry Tan 34:30 And then I remember, you know, me and my sort of PM mentor, uh, we had to go over to the, to the Windows team, and like they wouldn't reply to our emails. They wouldn't fix our bugs. They wouldn't even like mark it as won't fix. They just ignored us.

Anish Acharya 34:44 Yeah.

Garry Tan 34:44 And we had to go over there, uh, with a baseball bat.

Anish Acharya 34:47 Yeah.

Garry Tan 34:47 Like, I don't know why he brought one. Like, it's wasn't like he was-

Anish Acharya 34:50 Are you kidding?

Garry Tan 34:50 ... gonna like rough anyone up. It was just like this vague threat or something. [laughs]

Anish Acharya 34:54 Incredible.

Garry Tan 34:54 It was actually hilarious, and I think about that all the time. It's like what kind of like bureaucratic hell, uh, is it where like two perfectly smart people who are making like good tech money-

Anish Acharya 35:07 Yeah

Garry Tan 35:07 ... you know, are put into a situation where like there's a fiefdom over here, like literally there's like seven levels between us and that person.

Anish Acharya 35:17 Yes.

Garry Tan 35:17 And this person doesn't even know that we spent like four hours trying to get like a P3 bug fixed that was like a blocker for 1,000 of our users-

Anish Acharya 35:27 Yes

Garry Tan 35:27 ... or something.

Anish Acharya 35:28 Yes.

Garry Tan 35:28 It's like-

Anish Acharya 35:28 And how much humanity is just wasted?

Garry Tan 35:30 Yeah.

Anish Acharya 35:31 How many 2:00 AM sort of anxious wake-ups were there?

Garry Tan 35:33 Yeah.

Anish Acharya 35:34 Because somebody wanted to not have a hard conversation. Like it's, you know, it's, it's a really, it's a waste of the way we should be-

Garry Tan 35:39 Yeah

Anish Acharya 35:39 ... spending our time and working.

Garry Tan 35:41 Yeah. And that's a profound version of like the seven plus or minus two. Like, I don't think that like the, you know, product unit manager or whatever the heck their, you know, their title was [laughs] like I don't think-

Anish Acharya 35:51 Yes

Garry Tan 35:51 ... that they, uh, wanted us to waste our time like that.

Anish Acharya 35:55 Yes, yes.

Garry Tan 35:55 Uh, I think it's just that, you know, your day, like you just don't have enough hours in the day-

Anish Acharya 36:00 Yes

Garry Tan 36:01 ... and we're like incredibly limited human beings.

Anish Acharya 36:03 Yes.

Garry Tan 36:03 But, you know, uh, yeah, it's funny. Like I think that, you know, I think about my time at Microsoft, and it's like I remember getting an iPod and like doing, um, competitive research for-

Anish Acharya 36:15 Yeah

Garry Tan 36:15 ... Windows Mobile versus the iPod. I could imagine today at Microsoft, you could imagine a markdown file and a skill-

Anish Acharya 36:22 Yeah

Garry Tan 36:22 ... that is run on a cron.

Anish Acharya 36:24 Yes.

Garry Tan 36:24 And it's like how are, how are all the people working on this team? Like are they blocked? Who are they blocked by?

Anish Acharya 36:29 Yes.

Garry Tan 36:29 What are the external-

Anish Acharya 36:30 Yes

Garry Tan 36:30 ... dependencies? Like suddenly there is a graph.

Anish Acharya 36:32 Yes.

Garry Tan 36:33 There's a loop.

Anish Acharya 36:34 Yes.

Garry Tan 36:34 And then suddenly, like, you know, the products can actually just move fa- Like you could release something in a day or two that would've taken like six months.

Anish Acharya 36:42 That's incredible.

Garry Tan 36:43 Right? And if you could like multiply that out across like... The thing is like Probably an org like Microsoft can't

Anish Acharya 36:50 Yes

Garry Tan 36:50 But like a startup can

Anish Acharya 36:52 Yes

Garry Tan 36:52 And every-

Anish Acharya 36:52 Yes

Garry Tan 36:52 ... startup must

Anish Acharya 36:53 Yes. They must be organized this way. I also love what you said. It's almost like the mid-level of bureaucracy should be agents.

Garry Tan 36:59 Yeah.

Anish Acharya 37:00 'Cause I actually think that, you know, being in charge is somewhat overstated.

Garry Tan 37:03 Mm-hmm

Anish Acharya 37:03 Like, I'd love to actually have at least the mid-level organize the work, you know, resolve the conflicts that it can somewhat programmatically-

Garry Tan 37:11 Yeah

Anish Acharya 37:11 ... probabilistically, programmatically.

Garry Tan 37:13 Yeah.

Anish Acharya 37:13 Of course, the executive team maybe sets direction, the individual sort of decides on execution, but just the whole organization layer, which a lot of product managers historically did, should not be human.

Garry Tan 37:23 Yeah. I mean, the great thing is, um, it doesn't have to be... Do you know how, uh, Venkatesh Rao has this thing where it's like you need to be above the API line?

Anish Acharya 37:31 Right.

Garry Tan 37:31 Like, if Uber came out, like if you're an Uber driver, you're below the API line.

Anish Acharya 37:35 Yes.

Garry Tan 37:35 Like, you should be fighting to be above the API line.

Anish Acharya 37:37 Yes.

Garry Tan 37:37 I actually think AI erases the API line.

Anish Acharya 37:40 Yeah.

Garry Tan 37:40 Um, like one of the funniest things I saw recently is, uh, there's a API company, um, that we funded called Clawvisor, and they released a, um, a bug report endpoint that is not for humans to use. It's for agents who use their software to use, and there's an LLM where it's like if there's a bug in the software, um, it, like the bug report goes, but then it replies real time.

Anish Acharya 38:05 Yeah

Garry Tan 38:05 And it's like, "Actually, like, that's a good bug. We filed it. We're gonna fix it next week, but also, like, try this workaround."

Anish Acharya 38:11 Wow.

Garry Tan 38:12 And then, like, I can't get that out of my head because you could imagine, um, that could be how companies work.

Anish Acharya 38:19 Yeah

Garry Tan 38:19 Right? Um, like, instead of being below the API line and having to do what, like, I don't know, the API tells you to do-

Anish Acharya 38:28 Mm-hmm

Garry Tan 38:28 ... like this can be a back and forth, actually.

Anish Acharya 38:30 Yes.

Garry Tan 38:30 And then I always think about, um, you know, the reason why cars in the '80s got so good in Japan-

Anish Acharya 38:37 Mm-hmm

Garry Tan 38:37 ... was, uh, it was actually a management technique. Like, they realized-

Anish Acharya 38:41 Yeah

Garry Tan 38:41 ... the Toyota production system-

Anish Acharya 38:42 That's right

Garry Tan 38:43 ... meant that, like, if you are the person doing the work on the line, you should be allowed to change the line because you are the person with the most amount of context-

Anish Acharya 38:52 Yes

Garry Tan 38:52 ... to be able to improve your own working situation, and that's why American cars really started sucking and why Japanese cars became absolutely incredible. It's like this very subtle, simple way that actually empowers the worker.

Anish Acharya 39:06 Yeah.

Garry Tan 39:06 And so there's this sort of like mix that I

Garry Tan 39:08 think will happen.

Anish Acharya 39:08 Which is so interesting 'cause what's traditionally seen as a hierarchical society came up with this very bottoms-up way-

Garry Tan 39:13 Beautiful

Anish Acharya 39:13 ... of working, which led to, like arguably a 40-year generational run-

Garry Tan 39:17 Oh, yeah

Anish Acharya 39:17 ... because of process power.

Garry Tan 39:18 Yeah. Which is beautiful.

Anish Acharya 39:21 How, how many... As you think about kind of our evolution towards this vision, how many of these problems do you think are intelligence-bound? Like we need smarter models versus there will be other attributes of models that will unlock success?

Garry Tan 39:34 I mean, honestly, it's all human. Uh, humans are the ones who are gonna like slow this down, and then, um, actually, I'm realizing this might be a white pill.

Anish Acharya 39:43 Okay.

Garry Tan 39:44 So if you look at, like the tenor of what's going on just broadly in the discourse about AI, it's all like this sort of doom and gloom. Like all white-collar jobs are gonna go away. There's gonna be a permanent underclass.

Anish Acharya 39:56 Yes.

Garry Tan 39:57 And then, uh, funny enough, what I think is, um, all of the bureaucracy and the slowness and the seven plus or minus two, uh, of like every company, every institution, every organization, all the middle managers in the world-

Anish Acharya 40:13 Yeah

Garry Tan 40:14 ... that is actually the white pill. [chuckles]

Anish Acharya 40:15 100%.

Garry Tan 40:16 So, you know, these things are gonna be slower than you think.

Anish Acharya 40:21 Yes.

Garry Tan 40:21 Right? Uh, I looked at, you know, we had 7,000 people. Most of them were 18 to 22 years old.

Anish Acharya 40:27 Amazing.

Garry Tan 40:28 And I looked in their faces, and like they're all AI native. Like they were-

Anish Acharya 40:32 Yes

Garry Tan 40:32 ... born more or less like, you know... Be- they became adults in the time of ChatGPT.

Anish Acharya 40:37 Yes.

Garry Tan 40:38 Uh, and it's gon- You know, and for us, it's like now we, you know, run shit, which-

Anish Acharya 40:42 Yeah

Garry Tan 40:42 ... is nice.

Anish Acharya 40:43 That's great, right?

Garry Tan 40:43 Uh, but you know, imagine us like 20 years ago.

Anish Acharya 40:45 Yes.

Garry Tan 40:45 Like, you know, we were the ones who were native to the web.

Anish Acharya 40:48 Yes

Garry Tan 40:48 We were the ones who were-

Anish Acharya 40:49 To mobile

Garry Tan 40:49 ... native to mobile.

Anish Acharya 40:50 Yes. Yes.

Garry Tan 40:51 Um, and then now we run shit, so then all of society runs on the things that we expected from when we were 18 to 22.

Anish Acharya 40:58 Yeah.

Garry Tan 40:58 So I think that, you know, the w- white pill to me is like it's gonna be 20 years, and that's not a bad thing.

Anish Acharya 41:04 Yes.

Garry Tan 41:04 That's actually a good thing.

Anish Acharya 41:05 Yes.

Garry Tan 41:06 Um, like society is way slower than you think. Government is way slower than you think.

Anish Acharya 41:11 Yeah.

Garry Tan 41:11 Every company in the world is way slower than you think.

Anish Acharya 41:13 Yeah.

Garry Tan 41:14 Um, and there are real moats to these things. Like there are structural reasons why a Microsoft isn't going anywhere.

Anish Acharya 41:20 Yes.

Garry Tan 41:21 Um, and then I guess this is sort of a little antithetical to what most, you know, most people in Silicon Valley would say, like, "I want a startup to replace all of them."

Anish Acharya 41:30 Yeah.

Garry Tan 41:30 Uh, and the reality is like they won't,

Garry Tan 41:33 you know? [chuckles]

Anish Acharya 41:33 They won't. I love it. Okay, I have two more questions for you. Um, you know, one on this ki- sort of trying to envision the near future. What do you think the next computer looks like? What does a new computer look like?

Garry Tan 41:46 Oh, man. I think in the short term it'll probably keep looking like the way it is, but it seems inconceivable that, um, it'll stay that form factor. Like, it's pretty clearly going to be voice.

Anish Acharya 41:57 Yes.

Garry Tan 41:58 I think there's a lot around memory. Um-

Anish Acharya 42:01 Yes

Garry Tan 42:01 ... it's gonna take a while to... You know, to... We're, we're at this moment where everyone's sort of happy with ChatGPT or Claude Cowork or whatever it is.

Anish Acharya 42:08 Yeah.

Garry Tan 42:09 Um, but I don't think they will be in the long term. Like, um, I think you're gonna want a lot more context, and you're gonna want, like, all watched over by machines of loving grace.

Anish Acharya 42:19 Yes.

Garry Tan 42:19 Like you're gonna want this thing that, uh, is benevolent, knows about, like your hopes, fears, and desires-

Anish Acharya 42:26 Yes

Garry Tan 42:26 ... and then is sort of like relentlessly searching to help you in that way, and that's actually gonna be really exciting. And, you know, the path through that will probably be like computer use, memory-

Anish Acharya 42:37 Yeah

Garry Tan 42:37 ... like, uh, diarization, like ingestion, like-

Anish Acharya 42:41 Yes

Garry Tan 42:41 ... um, yeah. I mean, I think there's gonna be a lot there. And, uh, you know, the cool thing is It's actually gonna take longer. Like, this isn't a... Like, I don't think people who've been talking about this now, my guess is, like, next year, 2027, will be, like, the Harness Wars. [chuckles]

Anish Acharya 42:58 Yes.

Garry Tan 42:58 You know? And then... Uh, but it's really a cost thing. Like, it's just too expensive right now.

Anish Acharya 43:02 Yes.

Garry Tan 43:02 You know? Um, but it won't be. It... Like, there will be a war for a billion consumers-

Anish Acharya 43:07 Yes

Garry Tan 43:08 ... uh, right when, like, the frontier model compute of today-

Anish Acharya 43:13 Yeah

Garry Tan 43:13 ... will be, like, maybe 50 or 100 bucks in, like, two or three years.

Anish Acharya 43:17 Yeah. Yeah.

Garry Tan 43:18 And then that will be when, like, the most vi- the browser wars will be back on.

Anish Acharya 43:22 Yes. Yes. Well, we're already seeing it at, like, the price per token of Frontier is going to infinity. Like, Mythos is infinity dollars a token. You can't have it, and the price per token of the model that was Frontier a week ago is collapsing to zero.

Garry Tan 43:34 Yeah.

Anish Acharya 43:34 And I actually think, to me, that is a huge white pill for a lot of reasons. You know, one of the most important of which is just we need more consumer AI software, and in a world where most consumer products are free to try, you just can't do that when you have really high costs of incremental distribution. The magic of software is zero cost incremental distribution. We have these magical primitives. Like, we have computers that are emotive and have emotional texture for the first time in 40 or 50 years.

Garry Tan 44:00 Oh, yeah.

Anish Acharya 44:00 What a tragedy that we haven't built more ambitious consumer products yet.

Garry Tan 44:04 Yeah.

Anish Acharya 44:04 So I'm really excited for the sort of changing economics of models to unlock these new categories.

Garry Tan 44:09 Yeah. I mean, and we're so early. Like, I was convinced that op- like being, becoming a convert to OpenClaw made me very, very convinced that it was gonna happen right away.

Anish Acharya 44:17 Yes.

Garry Tan 44:17 And then at this point, I'm like, "That's not correct at all." Like, you know?

Anish Acharya 44:20 Well, you should try... The new ChatGPT desktop app actually has got a voice mode, and it's sort of... It's an operator or a concierge that can see all your threads.

Garry Tan 44:29 Oh, cool.

Anish Acharya 44:29 And you can access it from your phone.

Garry Tan 44:30 Yeah.

Anish Acharya 44:31 It's very OpenClaw-ish, and I'm sure Peter had his hands all over it. It, to me, it's the closest thing we've seen yet to a true consumer assistant.

Garry Tan 44:38 Oh, I can see that.

Anish Acharya 44:39 It's awesome.

Garry Tan 44:39 Yeah, yeah. ChatGPT always had, like, basically the best memory, so-

Anish Acharya 44:43 Yeah

Garry Tan 44:43 ... I gotta

Garry Tan 44:44 try it again.

Anish Acharya 44:44 They've done a great job.

Garry Tan 44:45 Yeah.

Anish Acharya 44:46 Okay. Last question. Um, you know, we talked a lot about kind of utopian visions for the world and problems that are maybe intelligence-bound. You've also put a lot of energy into sort of local politics and doing things I think are very pro-social, but it seems like more of those problems are human coordination-bound.

Garry Tan 45:02 Oh, definitely.

Anish Acharya 45:02 Yeah. How do you get energy to do that work? You know, is there a white pill for that aspect of our society? Maybe talk a bit about that.

Garry Tan 45:09 I mean, the white pill is just believing that, uh, America still has rule of law and that, um, people in government are trying to help and, like, somewhat earnest. Like, it's not perfect.

Anish Acharya 45:20 Mm-hmm.

Garry Tan 45:20 Um, I think that the white pill for me recently was even just doing jury duty in San Francisco, and to see, like, this orderly process of really a cross-section of San Francisco. Uh, one thing I realized was, like, actually we are a big part of the city. Like, we're 10, 20% of the people are, like, directly working in tech.

Anish Acharya 45:42 Yeah.

Garry Tan 45:42 And so, um, to see something that was... I mean, the judge was really good. I mean, it was a horrible case, but like, you know, government is not here to, like, ruin people. Like-

Anish Acharya 45:55 Yeah

Garry Tan 45:55 ... and so, and then at that point, um, we can vote.

Anish Acharya 46:00 Yes.

Garry Tan 46:00 Like, we actually have a say. Um, and then I think everything is downstream of media at that point. Like, I think the San Francisco moment that got me very, uh, engaged was realizing, you know, Asian Americans are 25% of the voting populace, about 30% of the population.

Anish Acharya 46:17 Yeah.

Garry Tan 46:17 But during COVID, like, we had a district attorney who was turning a blind eye to some of the most heinous crimes-

Anish Acharya 46:24 Heinous

Garry Tan 46:24 ... against our elders.

Anish Acharya 46:25 Mm-hmm.

Garry Tan 46:26 And simultaneous to that, we had a school board that was openly hostile against Asian American kids who just wanted to learn algebra in public middle school.

Anish Acharya 46:35 Mm-hmm.

Garry Tan 46:35 Which hit me because, uh, I was that public school kid in Fremont in the East Bay. Like, if I couldn't have taken algebra in middle school, I couldn't take calculus by senior year.

Anish Acharya 46:44 Mm-hmm.

Garry Tan 46:45 I wouldn't have been able to study engineering at Stanford, and I wouldn't be here doing any of the things I get to do today. And I'm like, "Oh, okay. Now, now they've made it personal."

Anish Acharya 46:54 Yeah.

Garry Tan 46:54 And like, let me understand. Uh, and it turned out to be, like, sort of all the same people, the same people who wanna destroy all data centers.

Anish Acharya 47:01 Yeah.

Garry Tan 47:01 The same people who, um, you know, don't want to build any housing-

Anish Acharya 47:05 Yeah

Garry Tan 47:05 ... in, uh, anywhere in California or the world.

Anish Acharya 47:08 Yes.

Garry Tan 47:08 Like, it's sort of NIMBYs who want to virtue signal, who, um, sort of have these ideologies that, like, don't square with mine. I mean, as a builder, you're like, "Well, the, you know, words have meaning. Like, s- supply and demand exists. Markets exist. Like, incentives exist." And then, you know, I, I think that government is when... You know, when people like us don't speak up, uh, when we don't, like, pay attention and, like, hold our media accountable, not just the government-

Anish Acharya 47:38 Yes

Garry Tan 47:38 ... uh, then things get very deranged.

Anish Acharya 47:41 Yeah.

Garry Tan 47:42 And that's what San Francisco was, I think, around COVID. And then just by sheer organization, like, you know, this is... I think that, like, the Chinese of the West Side organizing around algebra and, um, you know, the deaths of our elders, um, going to farmers markets and, like, literally physically, like, telling each other, "They're killing us. They're killing us."

Anish Acharya 48:07 Yeah.

Garry Tan 48:07 Right? Um, ABC News, uh, you know, literally the me- the mainstream media-

Anish Acharya 48:14 Yeah

Garry Tan 48:14 ... uh, TV sh- channel of, uh, San Francisco and the Bay Area would not cover anti-Chinese and anti-Asian crime.

Anish Acharya 48:22 Wow.

Garry Tan 48:23 And, um, you know, I, I... It's, like, unconscionable, right?

Anish Acharya 48:28 Yeah.

Garry Tan 48:28 Like, our institutions failed us, and the great thing is, like, when the system becomes so odious, you've gotta put your body on it.

Anish Acharya 48:36 Mm-hmm. Yeah.

Garry Tan 48:36 I think that was Mario Savio.

Anish Acharya 48:37 Mm-hmm.

Garry Tan 48:38 And it's kinda... It's, I mean, it's ironic almost [chuckles] to, like, say that, but on the other hand, like, that's what I believe.

Anish Acharya 48:43 Right.

Garry Tan 48:43 Like, uh, they can't do this to us, and we're gonna stop it, and, uh, even at, like, personal peril. Even at, um, you know, reputational cost. Like, we should be willing to take that cost-

Anish Acharya 48:55 Yes

Garry Tan 48:55 ... because that's Our covenant with our fellow man and our fellow citizen, you know? And if we don't do it, who's gonna do it? Like, nobody does it. And, uh, I'm super proud of what we're doing in San Francisco because we have beat back that ideological, uh, set of people who, like, created this mess.

Anish Acharya 49:13 Yeah.

Garry Tan 49:13 And, you know, it's not perfect in San Francisco, but it's getting better. And-

Anish Acharya 49:18 It's amazing right now.

Garry Tan 49:19 Yeah.

Anish Acharya 49:19 I mean, I think I saw that, uh, Lurie might be the most popular mayor or politician in the entire country.

Garry Tan 49:24 Yeah.

Anish Acharya 49:24 Things have gotten so much better. Everybody sees it, feels it in the vibe. Some people say, "I wonder why," but I think for those of us who know, we see that your sort of stewardship, not just of the industry, of the startup community, of sort of technology, but also of the community, is one of the big catalysts. So thank you for doing that work.

Garry Tan 49:42 Thank you so much. Yeah.

Anish Acharya 49:43 Yeah.

Garry Tan 49:43 So, and I think San Francisco should be the beacon for pushing this back in every blue city-

Anish Acharya 49:49 Yes

Garry Tan 49:49 ... in America.

Anish Acharya 49:50 Yes.

Garry Tan 49:50 And, you know, I- that's what garyslist.org [laughs] is basically.

Anish Acharya 49:54 Totally.

Garry Tan 49:54 Like, how do we take the lessons that we learned here, and, like, LA needs this. New York needs this. Minneapolis needs this. Seattle needs this.

Anish Acharya 50:02 Well, and also, let's find, you know, to connect the two, the sort of, you know, culture, society, and technology, like, let's find very local ways for the ambition that this technology unlocks to show up. You know, I was in London last week, and we were talking a little about what's possible. It's like, hey, you don't have to have an American vision for how AI impacts your society. If you want the NHS to be incredible, then, like, you could do that with this technology. So the kind of, the opportunity for ambition to be very localized in our communities, I think, is something really interesting.

Garry Tan 50:31 Yeah. And so yeah, act local, like, take care of the people right next to you.

Anish Acharya 50:36 Yeah.

Garry Tan 50:36 Like, you know, I, I think it's funny, uh, so many people get very, very obsessed with national. I mean, we want to look at national generally right now. It's like, you know what? Like, I care about San Francisco. I care about housing. I care about crime. I care about, uh, you know, treatment and recovery.

Anish Acharya 50:52 Yeah.

Garry Tan 50:52 And if we do that, like, we can have the society we want to live in, and then, you know, if we fix local, like, state and national will fix itself, 'cause, like, on a 5 or 10-year basis, like, the people who win up there, like, they, they will come up through a system that's functional, and about saying no to things that don't make sense-

Anish Acharya 51:10 Absolutely

Garry Tan 51:10 ... about saying yes to the things that-

Anish Acharya 51:12 Yes

Garry Tan 51:12 ... are awesome for the people.

Anish Acharya 51:14 I love it. All right, Garry. First of many.

Garry Tan 51:16 Yeah, man.

Anish Acharya 51:16 Thanks, brother.

Garry Tan 51:17 Thanks, bro.

Anish Acharya 51:18 This is great.

Garry Tan 51:18 Cool.

Anish Acharya 51:19 Yeah. [upbeat music]