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Video · 2026-08-12 · 51m · 24 moments

Garry Tan: New Rules for Founders

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01
Claim

Founders should pursue what they know and are interested in rather than chasing what's hot or following crowd sentiment

Garry Tan reflects on his early career mistake of abandoning web programming to chase mobile because it seemed hot, when web was actually about to explode with Web 2.0. He argues the right question isn't 'what's hot' but 'what do you know uniquely?'

transcript

Garry Tan: I was chasing what was hot instead of what was clearly the thing I knew... 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. And you know, I didn't do it. I ran off and said like, 'Oh, well, the next hot thing will be mobile.' So I wanted to work at Windows Mobile... the classic question I'm sure you get that, you know, all investors get all the time is, 'What's hot and what should I work on?' And that's the wrong question to ask. Like the right question is like, 'What are you interested in? What do you know uniquely?'

02
Claim

Founders should follow their own direct experience and unique knowledge rather than chasing what's hot or what investors say is cool.

Garry Tan reflects on his early career mistake of leaving web programming for mobile at Microsoft instead of staying with what he knew and loved, driven by chasing trends rather than first principles.

transcript

Garry Tan: I think like that's that's embedded in this idea that like you should just be earnest 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 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 I give up like the thing that could have been the next thing. The classic question I'm sure you get that, you know, all investors get all the time is, 'What's hot and what should I work on?' And that's the wrong question to ask. Like the right question is like, 'What are you interested in? What do you know uniquely?'

provides context · 1supports · 1

03
Claim

Founders should pursue what they know and love rather than chasing what's hot — earnestness requires courage to trust your own direct experience over crowd consensus.

Garry Tan recounts leaving web programming for Windows Mobile because it seemed hot, only to miss the social/web boom. He argues the right question isn't 'what's hot?' but 'what do you know uniquely?'

transcript

Garry Tan: the classic question I'm sure you get that, you know, all investors get all the time is, 'What's hot and what should I work on?' And that's the wrong question to ask. Like the right question is like, 'What are you interested in? What do you know uniquely?'

04
Claim

Earnestness requires courage and direct experience over following crowd consensus

Tan argues that genuine earnestness requires courage — trusting your own direct experience even when it contradicts the prevailing narrative or expert opinion.

transcript

Garry Tan: Like if you know something that's 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, you're like, well, I don't agree with that because I believe my own direct experience. I know that I'm not a time traveler because if I was a time traveler, I would have sent a message back to myself and said, 'Just stay on working on web stuff.' Like you literally have 5 years of experience on top of everyone else. Like you could do an end run around everyone. Like you could have built like any kind of social software. But instead I was, um, you know, I was 22. So I was like being whipped around by, uh, whatever I could read in The Wall Street Journal.

provides context · 1

05
Claim

Great things start as toys or fringe obsessions pursued by outsider weirdos

Tan argues that the most important companies start as toys or fringe obsessions pursued by outsider weirdos, citing the Homebrew Computer Club and PC revolution as patterns that repeat across Silicon Valley.

transcript

Garry Tan: The cool parts of the idea maze are like the weird fringe parts, actually. It's always like, uh, what is a toy? Like that's the pattern in Silicon Valley over and over again that bears repeating, right? The idea that you could have a computer on every desk in every home. Today is like, of course, that's what's come to pass. But the people who created that thing, they were fringe weirdo punks, actually. They were outsiders. Homebrew Computer Club was not where you were getting laid. You You just were like following this weird obsession that, you know, actually I want my own computer.

extends · 1

06
Anecdote

Garry's refusal to join Palantir was a multi-billion dollar mistake caused by the same error as leaving web programming: working from external signals instead of direct knowledge

Garry recounts turning down Peter Thiel's invitation to join Palantir because he wanted a promotion at Microsoft. Joe Lonsdale and Stephen Cohen, his smartest fraternity brothers, were starting the company, but he ignored this direct signal in favor of chasing status.

transcript

Garry Tan: Peter said, 'I'm so sure this is the right thing for you. Like here's a check for 70 grand.' That was how much I made at Microsoft at the time. And I said, 'Thank you very much, Mr. Thiel, but I might get promoted to level 60 this year.' Which I did. But I think it's... That was like a $2 billion to $4 billion mistake at this point. 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 just staying on the thing that I knew and loved... I was working backwards from the map instead of looking down at the territory and saying like, oh, well, these are the smartest people I know.

supports · 1

07
Claim

Everything awesome is kind of a cult — starting with a truth that flies in the face of orthodoxy

From his Palantir experience, Tan learned that everything awesome is kind of a cult — starting with a truth or belief that contradicts established orthodoxy, requiring gnosis from direct examination rather than relying on secondhand maps.

transcript

Garry Tan: I was working backwards from the map instead of looking down at the territory... what they were doing is like they were going to governments and three-letter agencies. And it was clear that the things that really good computer scientists in Palo Alto could do and create — DC did not have access to that... what a scientist does is, you know, sure there's published papers, but you go and you examine all the truths. 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 experiencing a thing — then you learn secret knowledge. Then you have gnosis. And so, uh, you know, from Palantir I definitely learned that everything that's awesome in my life is kind of a cult. That starts with some sort of truth or belief that flies in the face of an orthodoxy, which is very punk actually.

provides context · 1

08
Claim

Everything awesome in life is kind of a cult—it starts with a truth or belief that flies in the face of orthodoxy

Garry distills his lesson from Palantir: the most successful ventures begin as contrarian beliefs held by a small group, which is actually very punk and aligns with embracing truth over conventional wisdom.

transcript

Garry Tan: From Palantir I definitely learned that everything that's awesome in my life is kind of a cult. That starts with some sort of truth or belief that flies in the face of an orthodoxy, which is very punk actually.

gives example · 1

09
Claim

Everything awesome in life is kind of a cult—it starts with some truth or belief that flies in the face of orthodoxy, which is very punk.

Drawing from the Palantir origin story, Tan argues that the most impactful companies and ideas begin as contrarian beliefs held by a small group, similar to a cult, before becoming mainstream.

transcript

Garry Tan: So, uh, you know, from Palantir I definitely learned that everything that's awesome in my life is kind of a cult. That starts with some sort of truth or belief that flies in the face of an orthodoxy, which is very punk actually.

gives example · 5

10
Claim

The traditional requirement for co-founders is shifting — solo founders can now multiply their output 400x with AI coding tools, making individual ambition more viable than ever.

Garry explains that while co-founders have historically been essential (referencing Derek Sivers' 'one person dancing is a crazy person' talk), vibe coding and agentic tools now let a single founder be a multiple of themselves.

transcript

Garry Tan: 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. Um I think some of this is like the beginning of a cult. 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, worse than a cult. It's just like a crazy person actually. Um I think this is like an old Derek Sivers TED Talk, right? Where it's like uh yeah, one person dancing in a field is a crazy person. But um you know, it's really the second person who like gets up and joins that person like then you just what you find is you know, suddenly 10 people are all dancing. Then it's a party. Yeah, that's literally the TED Talk. Love it. 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 um literally any given person could be 400 of that person like from two years like even like nine months ago um you can be a multiple of yourself.

11
Prediction

A single person with AI agents can now outperform an entire department of a Mag 7 company.

Tan explains how agentic coding and skill loops allow small teams to achieve massive productivity gains, enabling startups to outperform large corporations by replacing human bottlenecks with software.

transcript

Garry Tan: I think what's happening right now with vibe coding and agentic coding um literally any given person could be 400 of that person like from two years like even like nine months ago um you can be a multiple of yourself. One mega trend that we're seeing is like a 35 40 45 year old founder who like been around the block. Built a lot of companies. I mean I think uh yeah Peter Steinberger is like a perfect example of that. Where it's like he's been around the block like he knows what to build. 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.

gives example · 6supports · 1

12
Claim

Token maxing — loading 800K-1M tokens into agent requests at full compute — lets founders operate at 2028 capability levels today, and the expensive cost is justified for CEO-level work.

Garry describes using Open Claw and Hermes Agent at full strength with massive context windows, calling it 'living in 2028' — expensive but transformative for founders and CEOs.

transcript

Garry Tan: if you really want to token max, you actually have to use something like Hermes Agent or Open Claw. 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 to any given request and like have that be in your like soul.md. Yeah. But when you do that, like I think that you basically get to live in 2028. Like, you know, it costs, I don't know, 50 or 100,000 dollars a year to like use the agents at full strength, like full 150 IQ on every request. But you'll feel it more or less immediately. It just costs like a crazy amount. But for a CEO or for a founder, it actually makes a lot of sense to do that and you have to give yourself permission to token max in that way.

13
Claim

A markdown file is an employee that does the job perfectly every single time

Tan argues that turning business processes into markdown skill files plus code and tests creates reusable agents that execute perfectly every time, letting founders scale operations with a few hundred skill files instead of large teams.

transcript

Garry Tan: You do some feat of strength and then you turn it into a markdown file plus code plus tests that can be reused and like put into a cron job... we're just seeing like across the board a markdown file is an employee. And it's an employee that will do the job perfectly every single time and it will do it like as many times as you want... you just do it once perfectly. The first time you try to do it, it's going to be bad. Expensive. Many iterations. But then at the end you can tell very, very quickly and in very simple ways, like, 'Hey agent, fix this, fix that. Like this was wrong.' The actual trace and the history out of that agent working with you — it'll turn that into a skill file that's perfect. And anytime it screws up in a future case, it's just a bug fix, and then it's there forever.

14
Claim

A markdown file is an employee — it does the job perfectly every time, can be reused indefinitely, and any future errors become permanent bug fixes rather than repeated failures.

Garry describes the workflow of doing a business process once perfectly, turning it into a reusable skill file with tests, then letting agents execute it repeatedly — mistakes become permanent fixes.

transcript

Garry Tan: a markdown file is an employee. And it's an employee that, uh, will do the job perfectly every single time and it will do it like as many times as you want. And then, you know, at that point all you're doing is like take any business process that you need in your company and you just do it once perfectly. And the first time you try to do it, it's going to be bad. Expensive. Yeah, yes, many iterations. Yeah. But then at the end you can you as long as you can tell very, very quickly and in in very simple ways, like, 'Hey agent, fix this, fix that. Like this was wrong.' Um, you know, the actual trace and the actual, uh, history out of, um, that agent, uh, working with you, it'll actually turn that into a skill file that's perfect, actually. And anytime it screws up in like a future case, it's just a bug fix, and then it's there forever.

15
Claim

A markdown file is an employee that will do the job perfectly every single time and can be reused infinitely via cron jobs

Garry describes how agentic AI systems work: you create skill files (markdown + code + tests) that encode perfect execution of business processes. Once built, these can run indefinitely, enabling small teams to achieve massive scale.

transcript

Garry Tan: I think we're just seeing like across the board, a markdown file is an employee. And it's an employee that will do the job perfectly every single time and it will do it like as many times as you want. And then, you know, at that point all you're doing is like take any business process that you need in your company and you just do it once perfectly. And the first time you try to do it, it's going to be bad. But then at the end you can... turn that into a skill file that's perfect, actually. And anytime it screws up in like a future case, it's just a bug fix, and then it's there forever.

16
Data

Startups can now reach $15M ARR in 4 months with just a few people because AI agents allow for recursive self-improvement and skill loops.

Tan describes how building agentic systems involves identifying bottlenecks and creating software to remove them, leading to a recursive loop where companies can scale revenue rapidly with very few human employees.

transcript

Garry Tan: Building these agentic systems today, I think that's all you're doing is you're seeing where the bottlenecks are, 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.' 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, you know, we were we were talking about earlier that's like literally you can go from zero to 15 mil ARR in about 4 months with like two or three people and like hundreds of agent like, you know, a few hundred skill files.

provides context · 1supports · 1

17
Claim

AI agents with memory and retrieval give leaders clairvoyance — seeing ground truth across the entire organization

Tan describes how Pedro at Brex uses AI agents to analyze meeting transcripts across the organization, giving leaders visibility into conflicts and ground truth two levels down — something previously impossible due to human cognitive limits.

transcript

Garry Tan: 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. And then the thing that really jumped out at me is like he can use meetings that he's not in now to figure out like what's broken, what's in conflict, like who's in conflict with who. And then sometimes he can show up at a meeting. He has perfect context from the last three weeks of that one compliance team. 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... that is actually one of the defining reasons why startups or businesses fail. It's actually a management challenge. The business becomes too big to fit in one person's head. And then this is the most profound form — you have agents, you have memory, you have retrieval. It can actually look at the ground truth from the data. That's clairvoyance.

18
Example

Large corporations are too slow and bureaucratic for AI transformation, but every startup must and can reorganize around agents.

Tan uses an anecdote about needing a baseball bat to get a bug fixed at Microsoft to illustrate corporate bureaucracy, arguing that while large organizations can't adapt, startups must reorganize around AI agents to be competitive.

transcript

Garry Tan: We needed integration for instance from the Windows team... 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. And we had to go over there with a baseball bat... what kind of bureaucratic hell is it where like two perfectly smart people who are making like good tech money, are put into a situation where like there's a fiefdom over here. It's like probably an org like Microsoft can't. But like a startup can. And every startup must.

provides context · 1supports · 2

19
Claim

AI disruption will take 20 years rather than happening overnight because human bureaucracy and institutional slowness are the real bottleneck — and that's actually good news.

Garry argues the 'white pill' is that all the bureaucracy, middle management, and 'seven plus or minus two' human limitations mean society moves far slower than technologists expect — giving time to adapt.

transcript

Garry Tan: it's all human humans are the ones who are going to like slow this down. And then actually I'm realizing this might be a white pill. 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 going to go away. There's going to be a permanent underclass. And then funny enough what I think is all of the bureaucracy and the slowness and the seven plus or minus two of like every company, every institution, every organization, all the middle managers in the world. That is actually the white pill.

20
Prediction

The slowness and bureaucracy of institutions is actually a white pill because AI transformation will take 20+ years, giving founders time to build

Garry offers a contrarian optimistic view: all the doom about AI replacing jobs ignores that institutions are incredibly slow to change. Society, government, and corporations move glacially, so the AI transformation will unfold over decades, not overnight.

transcript

Garry Tan: All of the bureaucracy and the slowness and the seven plus or minus two of like every company, every institution, every organization, all the middle managers in the world. That is actually the white pill. So you know these things are going to be slower than you think. Society is way slower than you think. Government is way slower than you think. Every company in the world is way slower than you think. And there are real moats to these things. Like there are structural reasons why a Microsoft isn't going anywhere... the white pill to me is like it's going to be 20 years and that's not a bad thing. That's actually a good thing.

21
Claim

Society is much slower to change than technologists think — and that's actually a white pill

Tan argues that government, companies, and institutions are far slower to change than expected, which is actually positive — it provides a buffer that makes the AI transition gradual rather than catastrophic.

transcript

Garry Tan: The white pill to me is it's going to be 20 years and that's not a bad thing. That's actually a good thing. Society is way slower than you think. Government is way slower than you think. Every company in the world is way slower than you think. And there are real moats to these things. There are structural reasons why a Microsoft isn't going anywhere... I think that like the product unit manager or whatever the heck their title was — I don't think that they wanted us to waste our time like that. I think it's just that your day, you just don't have enough hours in the day and we're incredibly limited human beings.

22
Claim

Fixing local problems in San Francisco is more impactful than national politics, and tech workers have a responsibility to engage in civic life

Garry describes his civic engagement in San Francisco, where he organized against policies that harmed Asian American students and failed to address crime. He emphasizes that local action creates the foundation for broader change.

transcript

Garry Tan: The white pill is just believing that America still has rule of law and that people in government are trying to help and like somewhat earnest... if we fix local, state and national will fix itself because on a five or 10 year basis the people who win up there they will come up through a system that's functional and about saying no to things that don't make sense, about saying yes to the things that are awesome for the people... I care about San Francisco, I care about housing, I care about crime, I care about treatment and recovery. And if we do that we can have the society we want to live in.

23
Claim

Fixing local problems like crime and housing is the most effective way to improve society, as national figures emerge from functional local systems.

Tan explains his shift into local politics in San Francisco, arguing that fixing local issues is the most effective way to improve society, as national figures emerge from functional local systems.

transcript

Garry Tan: I think San Francisco should be the beacon for pushing this back in every blue city in America... act local like take care of the people right next to you... if we fix local like state and national will fix itself cuz like on a five or 10 year basis like the people who win up there like they they will come up through a system that's functional.

24
Claim

Fixing local politics — housing, crime, recovery — should be the priority because functional local systems naturally produce better state and national leadership over time.

Garry describes his civic engagement in San Francisco, fighting against ideological extremism on crime and education, arguing that fixing local problems cascades upward to state and national governance.

transcript

Garry Tan: I care about San Francisco, I care about housing, I care about crime, I care about uh you know, treatment and recovery 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 cuz like on a five 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, about saying yes to the things that are awesome for the people.

Highlight slides
Pursue What You Know✦ from: Founders should pursue what they know and are interested in rather than chasing what's hot or following crowd sentimentGarry Tan's Missed Opportunity✦ from: Founders should pursue what they know and are interested in rather than chasing what's hot or following crowd sentimentAsk the Right Question✦ from: Founders should pursue what they know and are interested in rather than chasing what's hot or following crowd sentiment创始人决策:经验优先于趋势✦ from: Founders should follow their own direct experience and unique knowledge rather than chasing what's hot or what investors say is cool.Garry Tan的教训:追逐移动而非专长✦ from: Founders should follow their own direct experience and unique knowledge rather than chasing what's hot or what investors say is cool.正确的问题:兴趣与独特知识✦ from: Founders should follow their own direct experience and unique knowledge rather than chasing what's hot or what investors say is cool.The Wrong Question Founders Ask✦ from: Founders should pursue what they know and love rather than chasing what's hot — earnestness requires courage to trust your own direct experience over crowd consensus.The Right Question✦ from: Founders should pursue what they know and love rather than chasing what's hot — earnestness requires courage to trust your own direct experience over crowd consensus.Lesson from Garry Tan✦ from: Founders should pursue what they know and love rather than chasing what's hot — earnestness requires courage to trust your own direct experience over crowd consensus.Earnestness Requires Courage✦ from: Earnestness requires courage and direct experience over following crowd consensusThe Cost of Following the Crowd✦ from: Earnestness requires courage and direct experience over following crowd consensusThe Multi-Billion Dollar 'No'✦ from: Garry's refusal to join Palantir was a multi-billion dollar mistake caused by the same error as leaving web programming: working from external signals instead of direct knowledgeSame Error, Twice✦ from: Garry's refusal to join Palantir was a multi-billion dollar mistake caused by the same error as leaving web programming: working from external signals instead of direct knowledgeThe Pattern✦ from: Garry's refusal to join Palantir was a multi-billion dollar mistake caused by the same error as leaving web programming: working from external signals instead of direct knowledgeEverything Awesome Is Kind of a Cult✦ from: Everything awesome is kind of a cult — starting with a truth that flies in the face of orthodoxyFrom Map to Territory✦ from: Everything awesome is kind of a cult — starting with a truth that flies in the face of orthodoxyAwesome things start as cults✦ from: Everything awesome in life is kind of a cult—it starts with some truth or belief that flies in the face of orthodoxy, which is very punk.From cult to mainstream✦ from: Everything awesome in life is kind of a cult—it starts with some truth or belief that flies in the face of orthodoxy, which is very punk.Agentic Coding: 1 Person = 400x Output✦ from: A single person with AI agents can now outperform an entire department of a Mag 7 company.Outperforming Mag 7 Departments✦ from: A single person with AI agents can now outperform an entire department of a Mag 7 company.The Agentic Revolution✦ from: A single person with AI agents can now outperform an entire department of a Mag 7 company.Token Maxing: Live in 2028 Today✦ from: Token maxing — loading 800K-1M tokens into agent requests at full compute — lets founders operate at 2028 capability levels today, and the expensive cost is justified for CEO-level work.Justified for CEO-Level Work✦ from: Token maxing — loading 800K-1M tokens into agent requests at full compute — lets founders operate at 2028 capability levels today, and the expensive cost is justified for CEO-level work.Corporate Bureaucracy vs AI Transformation✦ from: Large corporations are too slow and bureaucratic for AI transformation, but every startup must and can reorganize around agents.The Startup Advantage✦ from: Large corporations are too slow and bureaucratic for AI transformation, but every startup must and can reorganize around agents.Institutional Slowness Is a White Pill✦ from: The slowness and bureaucracy of institutions is actually a white pill because AI transformation will take 20+ years, giving founders time to buildAI Transformation Takes Decades, Not Overnight✦ from: The slowness and bureaucracy of institutions is actually a white pill because AI transformation will take 20+ years, giving founders time to build
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