[0:00:00] Today, I'm sitting down with Sam Altman, the co-founder of OpenAI. A long time ago, you talked or did a talk at Stanford focused on how to start a startup. What is the biggest thing that has kind of shifted over the past like 10 years since you initially did those talks? Clearly AI. And what is possible to do now with a small team of people and the speed with which you can do it. And also, not only what's possible, but like what you have to do to be competitive given how much the world has shifted.
[0:00:28] It feels totally different. It is amazing to me what a 10-week-old startup now can look like. And also, if you look like a 10-week-old startup from 10 years ago, you sort of are in bad shape. If you think of the 10-week-old startup in your mind today, what is the one that is the best example of a startup that moved extremely quickly? I don't even know what they're called, but I met what will be a startup that is like two weeks old, something like that, that has an entirely redone sort of...
[0:00:56] Office, productivity, suite, whatever, all made for a world where AI has got to be able to use documents, presentations, spreadsheets, whatever, as a first-class consumer. And I don't know, I felt like it would have been a year's worth of work for a startup pretty recently. I would assume that if the barriers to starting startups and the tools out there become more proliferated and all this stuff, you would assume that harder startups are easier to start. What it means to be...
[0:01:25] A hard startup is changing so incredibly quickly that I don't think I have a perfect mental model for what over the many years that it takes to build a very successful company, what are going to be the really hard and really valuable things. Like, you know, I've heard a lot of people say, well, anything in the physical world is extra valuable right now because software is going to become free. But, you know, like won't be that long until robots get really good. And a lot of the expectations of.
[0:01:55] Thank you.
[0:02:26] Most startups are like, I'm going to go build AI agents for Enterprise Vertical X. Now, that actually will work in a lot of cases. It'll be very competitive. And it may not be like, in fact, I'd say it probably won't be like the most successful defining startups of that era. But it will work. But given how much the landscape is in flux, I am surprised there are not more people doing the like, I'm going to go.
[0:02:57] Take on the crazy, the crazy thing with this completely new set of tools and also being willing to truly internalize the fact that scaling laws are going to continue and planning for the things that are not possible or economical this month, but will be possible in two years, four years, whatever. So it seems like an unbelievable time to be starting startups and there's very fertile ground.
[0:03:19] But there's also, and no judgment if this is what people go for, there's this incredible temptation to just like go apply today's agents to the easy wins. And I get it. One thing that you've said throughout the years is you basically try to, whenever you meet someone new, you try to like plot where they are on your mental model of who they are as a person. And then the next time that you meet them, you basically want to figure out how far or how fast have they progressed. Did that sort of thing and like doing this across maybe thousands of people.
[0:03:48] Impact your ability to kind of say, OK, the model is this intelligent today. It's this intelligent three months later. Suddenly you can like plot this out and it makes it easy to believe in the growth. I think there's like a general thing behind both of those, which is I just like I developed a great trust in exponentials in people or companies or models. I don't I don't think that subjectively it doesn't feel like watching model progress is the same as like watching a founder develop.
[0:04:18] But I think the underlying belief system about the world is the same. If I were still advising startup founders, this is the most important thing I would try to get them to wrap their heads around. And it is evidently hard for the same reason that there's like free money left in the market for betting on high growth young founders. And it's like one of the market is still not adapted enough for that.
[0:04:45] I think the market is also still not adapted enough for like the exponential of model progress is going to continue. And it is okay to start working on things now that require smarter or cheaper models. This idea of constantly shifting chaos. How do you get good at it? How do you get good at operating in a chaotic environment? I think it's just practice. There are a handful of things that I think no matter how much you intellectually understand.
[0:05:14] Take a lot of reps to like emotionally be able to handle and operating in a lot of chaos and trusting that you'll figure it out and it'll be OK. And like this is not going to be the thing that kills you and you don't quite yet know how you're going to solve it, but you're figured out. This seems to me to be something that you can only learn by going through it. And I actually think this is a real weakness of.
[0:05:42] Young founders is that they have not had the career experience of getting to emotional peace with this. And so they have a very hard time with it in the early days. And then they eventually learn it, but at, you know, great pain and cost and unforced errors. You definitely will, if you end up in a high stress sort of impactful job, you will definitely learn how to deal with chaos and function very well through it. At least most people will. But I don't think it's teachable. I think it's only learnable.
[0:06:13] You had an interesting thing that you said a long time ago, which is basically like the first time you experienced this company killing event. It feels like the world's falling apart. And then you make it through. And then by the 10th time, it's not nearly as bad. And you're like, well, I survived the first nine. This one's probably not that bad. You also had this other idea where you said at some point, I think it was like a year or two ago, it came to the conclusion that shit was always going to be going wrong. And so you kind of had to like internalize the enjoyment of experiencing pain or like not great things happening.
[0:06:42] How did you make that transition? I was reflecting earlier when you were saying this about how when I would do office hours at YC, I could always tell who the new founders were because of the way that they reacted to stuff going horribly wrong versus the founder. Because I often didn't know how new a company was, but I could tell if it was a founder in the batch versus a founder that had been doing this for a couple of years by their emotional state when they talked about a problem. I think most people think about the opposite.
[0:07:14] Of a bad experience is a good experience and they would rather have the good experience because seems like more fun or more pleasant or whatever. But if you think about like the opposite of a bad experience is no experience at some point in the not distant future, you'll be in no experience land. Then, you know, you can be grateful for the bad experience.
[0:07:41] When you think about like hard problems and like what rallies people to get excited to go work on hard problems, how do you decide?
[0:08:10] Like internally at the company, which things to go tackle and when, and like when you want to like focus on just your core competencies versus like expanding the scope. I think like a clear mission and then a deep understanding of the problem together do a fairly good job of pointing to what you should do. You won't get it all right. You'll still like at some points overly expand or not be ambitious enough.
[0:08:39] We are very focused on this is going to massively empower people. It's going to be choppy, but wonderful. And it's extremely important to us that power in the world get more decentralized and more spread out. And in fact, one of the biggest AI risks I am worried right now is AI authoritarianism and a small number of people or companies thinking they need to control the world. That'd be very, very bad. But given this mission,
[0:09:10] We feel like we need to figure out how to make AI extremely abundant, extremely cheap, extremely powerful, put it in everyone's hands, and have a lot of it to get to use. And as we look at what's in the way of that, there's a whole bunch of new constraints like chips and energy and data centers and robots and all the pieces that need to come together to build this platform so that we can enable this mission. Now, there's a bunch of things you can build on top of that platform. You can go build every vertical, every startup,
[0:09:39] We have no desire to do that like that. I think a decentralized economy is important and good. And I would like us to just be really great about producing these units of intelligence and make the world like, man, this is just, you know, incredibly capable, an incredibly great deal. And we're going to imbue it in every product and service. And so I think that's very instructive to us about what we have to go do. My, interestingly, the kind of key inputs to like extraordinarily abundant, high quality.
[0:10:09] A lot of those things, like energy, like robots, are also things that you really want in a world of abundant intelligence. If ideas are plentiful and there's all this great stuff, we still live in a physical world and we still want stuff to happen. So we need to be able to make stuff happen in that world. And I have wondered if the fact that energy and...
[0:10:37] Robots are going to be so important to staying on this intelligence infrastructure ramp. And also the things that you need immediately after it are energy and robots. Says anything deep at all, or is just like the most boring, obvious thing, which is like to produce anything, intelligence included, you need to manipulate matter. But it is kind of interesting that we need these new areas so much for what we're doing now and then so much more immediately after.
[0:11:03] What do you think your biggest bottleneck is? If you just say like, we want this to continue scaling unabated, what is the biggest bottleneck that you can see? Transistors and then electrons in that order. So let's say, you know, you take someone like Jensen, where he's like incredibly good at aligning all his suppliers towards, you know, his vision for the future. I think you're also extremely good at this. How do you kind of think about not only keeping OpenAI?
[0:11:31] On the OpenAI timelines, but also keep the rest of the world on the OpenAI timelines as well.
[0:12:01] I mean, the most important thing is to get them to believe in the mission and why they need to prioritize it. But you also try to figure out how to align their incentives with yours as much as you can. Charlie Munger has this awesome line where he's like, every time I've thought that I understood the power of incentives, I've underestimated them. How do you successfully align all the incentives of the different partners as well as the people inside of OpenAI? Well, companies are amazing vehicles for this to start. You know, as a kid, I was very fascinated by the Industrial Revolution.
[0:12:31] And I understood it as a bunch of technologies that happened to come around the same time and for some puzzling reason happened to scale it around the same time. And, you know, I would like talk to my friends or my parents or whatever about whether it was like this technology was the most important invention or this one or that one. And my read of it from my current lens is like someone who has now spent more time thinking about business is that the important invention was the Joint Stock Corporation.
[0:13:01] And before that was invented, and you had these kind of family businesses that ran on trust and you had to know everyone, and you didn't have the idea of a corporation, you didn't have the idea of stockholders really. And then all of a sudden, this new thing was invented. Countries like the sovereigns of the world granted this sort of a new kind of status, really, a thing that didn't exist before. This very powerful thing that we're going to let these...
[0:13:31] New entities emerge and not give them the power of a state, but give them like much more than the power of a person. And fundamentally, this was about, you know, incentive alignment, liability protection, which is another kind of incentive alignment, the ability to like amass capital. And all of a sudden you could do things beyond what a family business could do. And that environment let people raise money to develop technologies.
[0:14:01] Very speculative nature. Pool Capital, figure out ways to get different companies to sort of specialize in different ways and interact with each other. Serious financial systems and new kinds of instruments. This was really an incredible thing. And the idea of a company has done a huge amount to align incentives of very large groups of people. Now, you know, millions of people can be shareholders of a company. There's a bunch of other things we do, but I don't want to diminish.
[0:14:32] What has been this incredible invention and like the just ridiculous overperformance of capitalism in human society. Like a chart that I think people should look at much more than they do is the like fall of extreme poverty over the last hundred years. Like infant mortality and all the other things. Any of them that you want. Any of the associated things. You know, if you like kind of look back at that, that's like the most zoomed in view of the last hundred years.
[0:15:01] But if you look back at kind of economic growth, quality of life improvements, all of these things, and you just like drew out all of human history and you put the line when like the company was invented, you would see like a really quite interesting change in the shape of that curve after it. Beyond that, I think we have a mission that transcends any amount of economic power anything else could ever do. And that's probably more important.
[0:15:31] One of the things that I've thought is the most interesting is, have you ever seen one of those stats where it's like, I don't know, what percentage of like CEOs are sociopaths and psychopaths? It's like very, very high. I've heard people talk about this. So I wonder if capitalism is the first system that allowed these people that are like super kind of self-serving to like their incentives are realigned with societies and just create great products. And then suddenly you help society, but you also win. I definitely know a lot of sociopathic CEOs, but I would say the best ones I know.
[0:15:59] I would not put it in that category. There's a lot of very high ego CEOs, people with just incredibly high opinions of themselves on a way that maybe would have been just purely annoying, but now because people can buy their shares, maybe you tolerate their annoyance and antics a little more. So there's definitely some aligning thing there. I don't know. I think there are a lot of CEOs of very large companies that I would not put in the sociopath category at all. What do you think drives those people? I mean, it's different for different ones of them.
[0:16:31] Definitely seeing how good they can get at the game or like how much they can get better than themselves every year, I think is a huge part of it. You know, it's like intellectually quite stimulating for all of the other problems. Like you're kind of playing the most interesting strategic game and that can be fun. If you had to think about the way that you operate today versus the way that you would have operated 10 years ago, placed in the exact same position that you are currently, what are the biggest differences between those two people? Well, to the previous question, the thing that drives me the most is like,
[0:16:59] This is the most interesting, important thing I can imagine doing. And we are now in the singularity. This is the moment. Ten years ago, this was a kind of far-off dream at best. It seemed very improbable. And now we're actually in the moment that we used to talk about at the lunch table in a very not serious way. And so the thing that drives me is...
[0:17:29] I think it is both true.
[0:17:55] That it is all one crazy exponential and any one moment is not like the tipping point. And also that we are somehow in another one of those decisive periods where the curve can go one way or another like it was when we started 10 years ago. What do you think the biggest impacts are on getting this part of the curve right? I think like there are still major AI alignment issues to solve and safety issues. And there are still major...
[0:18:25] Economic issues, future of jobs, all that kind of stuff. But I think the fight of the current moment is, are we going to head to a world of AI authoritarianism or liberty? Are we going to decide that because of the very real safety issues and economic issues that we want one single model to be the machine god or the company associated to do that? Or are we going to say like, you know what?
[0:18:55] It may be a little messy, but every time that humanity has traded off its liberty for safety, it's been a long-term net loss. And so we are going to put this in the hands of people. We are going to empower them. We are going to let society express its ideas and use this technology in the way they want. Of course, according to some guardrails, with some guardrails, but with a lot of power and potential. And I really care that we do it that way. When you were talking with...
[0:19:25] Patrick Halston on stage. It must have been like a couple of months ago. There was this fascinating thing that you said, which is basically like you will talk or text with three to 400 people a day internally. I text more people than anybody else I know. I don't think this is like a good thing. I think this is actually like a bad habit. Why? Because it takes up like most of my time and I get like into, I have a very short attention span now. Interesting. What does that enable you to do that like otherwise you couldn't? Well, I have a huge amount of context. I mean, I'm like a...
[0:19:54] AI model that's not that smart, but just has like a huge amount, like a short term context on like whatever's happening right now. And then you forget. Does that enable you to make decisions that other people wouldn't have? Like what company decisions? I don't know. I mean, it lets me make different decisions than other people would. What different decisions would you have you made in the last like 12 months that you wouldn't have made if you didn't have so much context? I don't know if I have like a specific one I can share publicly, but there's like a lot of things where, you know, because I know about some random.
[0:20:22] Research breakthrough impending that is going to affect some customer or some supplier or whatever. I can make a slightly different decision in the moment. And if I hadn't known it that morning, I would have made a different decision. It would have been worse. One of the things that I think you are the best at is kind of like long-term thinking. And yet it also seems like things are moving so quickly and the world is changing so fast that planning 20 years out and then looking backwards, I don't even know if that makes sense. How do you think about this? Is your time horizon shortening?
[0:20:51] I actually don't try to plan backwards. I try to have like a small number of strongly held convictions about the future that are like directions to head towards. But then I try to like plan forwards from the current state about like, what can we do now? What can we do this year? And sometimes you do have to like plan a few things on a five or 10 year horizon. But I try to plan forward guided to a small number of beliefs about the future. I think there are a lot of people who have way too many beliefs about the future.
[0:21:20] And a kind of rigid worldview that they try to fit. And then, but what happens is they end up like chasing, you know, you see like space companies turn into AI companies or whatever. And like having just a small number of things that you deeply believe about the future and being very flexible on the rest and staying very true to the core is helpful.
[0:21:41] One of the people that I know the best, his top company core value is just critical path and just focusing on the critical path and like staying focused on the key drivers of whatever the biggest roadblock is, just unfuck that and then go to the next one and do that again. How do you think about critical path in your own life when you're kind of like trying to make these decisions? I mean, for so long now, I have felt focused on this singular goal of abundant intelligence and a belief that like incredible human prosperity will come from that as long as.
[0:22:10] We don't have a weird power concentration and kind of a new kind of authoritarianism. It has been fairly clear to me at any given time what's on the critical path to get there. And I have not been tempted by, you know, should I reconsider the goal or should I think about these other things? I have been thinking about that a little bit more recently of like, okay, if we really are close to super intelligence, what's next? But it's this, that's kind of how I subjectively feel we are close. This is the first time in like more than a decade I've thought about.
[0:22:39] What is the next thing? And is it the ranch? I mean, eventually. There might be a few more things on the way, but yes, that is the eventual plan. If you had to try to guess, what else does Sam want to accomplish before he ranches? Look, SuperIntel is going to get built. Not done, but we are on the glide path. The path to get there is very clear. Abundance and decentralization.
[0:23:07] Wide access to it and making sure that it ends up with like broadly shared prosperity. I'd really like to accomplish that. So maybe that's the thing that I've been like thinking about as the next thing. Like how does technologically we're going to accomplish our mission? I think a lot of our worldview and a lot of our beliefs about safety and the impact it's going to have have also we've gotten those things done too. But, you know, very broadly shared prosperity and a real focus on enabling the world here.
[0:23:37] That seems very important. I've heard you say again and again this idea of get on planes in marginal situations. I've done this a huge number of times. How's it working out for you? So far, it's working pretty well. Good. I think it's very solid advice. When was the last time that you got on a plane in a marginal situation? Well, I can't say what for, but very recently, and it worked out. Congratulations. Thank you.
[0:23:59] And I really didn't want to. It was like a very inconvenient two overnights. Didn't want to do it. New baby, whole mess. But I did. OK, actually, take me into your like mental process for deciding to do this world tour. That is just I mean, it again, it's like hard to rewind three years because now like it feels like AI has been here forever. But three years ago, we had just launched GPT-4. The world was melting down. Everybody was freaking out. Everybody was just like, oh, man.
[0:24:29] And no one knew what to think. And I could just feel these like storm clouds brewing. Like people just getting angry? It was like world leaders were like, do we need to like take control and shut things down? Like is this thing waking up? It was a weird time. And because it had all happened so fast, people had not had time to like wrap their head around it, go through this process, whatever.
[0:24:57] You know, we were like getting all of this escalating stuff and all these like world leaders were like, will you come meet us? We're like, you know, thinking about doing this and that. And I was like, I think if I or someone from the company, but at the time the company was not very big. So I was like, probably gonna have to be me. Does not go like show up and talk to people. I'd like a sense it's about to go very badly. And I was thinking about doing like a bunch of short trips, but I hate long flights. I hate jet lag. I had the whole thing. So I was like, I'm just going to like get this over with in a short period of time.
[0:25:26] Brian Chesky advised me to do it. He had done something similar for Airbnb, but he had done like eight cities or something. And you were like, fuck it, we ball. Let's just do 30. I think we did 28 countries. 35 days. I lived on an airplane. It was a very strange thing. Did you have a bed? Yeah, I was comfortable, but yeah, I had a bed.
[0:25:47] I fly coach, so it's a little bit different. This is better than that. Right. This is a lot better than that. But like, you know, it's like travel still sucks. Like you can make it as comfortable as you want and you still like miss your own bed and your own time zone and your office and whatever. One thing that I've learned is no matter how many people have like these cures for jet lag, they're all bullshit. Like it just sucks. Your brain doesn't like it. I never, because I went to so many places, I think my biggest time zone change was four hours the whole trip.
[0:26:16] And mostly it was like a one hour at a time hop. So I wasn't that jet lagged. I was just like exhausted. And it was very strange. It was kind of cool to get to see the world so quickly because you really do get a sense for like cultural differences that are very subtle when you go from place to place.
[0:26:46] Having this like vision, feeling, whatever of being in my childhood bed. Interesting. Which I never had before or since. But I would sort of like vaguely wake up and I would think I was in my childhood bed in my childhood room. And I was like, okay, this is some like deep, it's time to go home thing. You're like subconscious is fighting back or something like that. Interesting. When you're in zombie mode and you're kind of like trying to function, I think, or goblin mode, whatever you prefer.
[0:27:14] How do you change? Like what is different about you? How do you decide to keep on going? I definitely got to this point near the end where I was like counting down the days till I could be home. I was like, all right, because each day was like, it was like, you know, 14 hours of like nonstop. And I'm like not an extroverted person. You know, I was meeting like hundreds of people a day in some cases. And like tensions lowered by the end of it. But at the beginning, like the world was like very nervous.
[0:27:44] And then like, you know, I think once it just like it did calm down. I think one thing that helped is it was clear that like I knew when I was going to get home and I knew I was going to have to do it again for a while. I've done smaller ones since I probably do like something like that once or twice a year. But I was going to say like a thing I learned is that I would much rather put a bunch of international travel together in like a seven or 10 day chunk than a bunch of one day trips spread out.
[0:28:15] So I always do try to do it that way now. I think a lot of people overestimate the risk involved in making most actions. There is a lot of risk if you're just buying a bunch of call options on Robinhood, but there's probably a lot less risk on getting on planes and stuff. What have been the best examples of times where you basically did something that seemed really risky to other people, but you knew wasn't or you believed wasn't? I guess the...
[0:28:43] Obvious example would be like I was always extremely high conviction when I was buying a lot of compute. You ever seen the meme, everything's high risk if you're a pussy? No. Good meme. I spend a lot of time trying to talk to people about why they think a specific decision is high risk or low risk. And I have found that just getting people to speak about it out loud will often at least get through their intellectual blocks in either direction because people are usually wrong one way or the other.
[0:29:13] Not always the emotional part of it, but sometimes also. If you had to think through one of these meetings where someone is like firmly against some decision that you want to do, what is the most effective way to kind of help them see what you see? I don't think I'm very good at this, to be honest. I think like the right answer is to spend a lot of time really trying to explain it and get people there. And I actually think I used to be better at that. And as life has gotten so busy.
[0:29:43] I'm more just like, I get upset or frustrated or say this is what we're going to do. I don't think it's like a positive trait. And I would like to get back to more of the like, let's really talk it through. You said that you used to be much harder to work with, I don't know, 2008, 9, 10, somewhere around there than you are today. I don't know if people would describe me as fun to work with. I like interesting to work with, like effective, ambition raising, like very mission focused.
[0:30:13] But like day to day, like really fun to work with. I don't think I'm like a particularly fun person in general. I feel like if you are having a good time, it tends to be infectious. And I think if you are generally working on things that you want to work on, it is having a good time. Maybe I'm wrong. I mean, you could go ask a bunch of people I work with. I don't think you would get like a resounding fun to work with. Maybe not that language. I think people would say stuff like creative solutions to...
[0:30:45] What does it typically look like when you go into a meeting with someone and you realize that they are not ambitious enough and you need to try to help them become more ambitious? The version of this that came to mind when you were saying that was like first office hours I would have with new YC founders.
[0:31:09] You take average person who's worked in corporate America or, you know, at a big tech company for a few years and the level of ambition, scaled thinking, self-belief, whatever, it's just catastrophically low. Horrible, horrible. And you realize that like this person has never not had a boss in their life. They have never not had a parent or a teacher or a manager or whatever that kind of would tell them.
[0:31:39] What to do or what they were allowed to do or whatever. And they also kind of got punished for being too creative or wanting too much or thinking too big or too ambitious or whatever. Like the most countries or cultures have some sort of phrase for being too ambitious basically. Tall poppy syndrome. That's one. And you realize like how deep this is in people.
[0:32:09] And that they like heard it and their parents said it to them, their teachers said it to them, their friends said it to them, whatever, from when they were like quite little. And getting people to just like not think that way takes some real time. What's the most effective path to get someone from not believing in themselves to believing in themselves? I think small repeated wins. Like you do something you didn't think you could do or you kind of try something that felt, you know, too ambitious or too high expectation and it works and you say, okay, I'll try it again.
[0:32:39] Do you do anything like deep jobs where he would like, if someone was worried, he would like stare into their eyes and get, no, nothing like that. I don't think so. It's like, you can do it. I don't, I don't, I'm not like an, I don't do inspirational speeches. I don't, I don't do like the hardest, none of that. What's your favorite strategy game? I have not played a game other than like my poker night with friends in so long. I wish I had, I guess I'll have to say poker, but I,
[0:33:11] I miss great board games. What was your favorite board game? There's no one board game where I'd be like, I want to play that again and again. I'm not someone who's like, Catan is the best board game of all time or whatever. But they're all fun. And they're fun because they're new and you have to figure out a new set of challenges and rules and everything else. When you're thinking about the business world, I think you build your company differently than almost anyone else is able to build companies, is willing to build companies. What allows you to do that?
[0:33:40] I actually think every big company is pretty different. I don't think this is a unique thing. I think just like if you make a list of the 20 biggest tech companies or whatever, they're all like shockingly different from each other in terms of their strategy and how they operate and their culture. And I think we are quite different than everybody else, but that's not a deep insight. What do you think your superpower is? I think we did a really good job of a principled conviction on something that no one else believed, even though it was the obvious thing.
[0:34:11] One should believe. And then putting together all of the pieces and the talent around that to sort of make it happen. What allowed you to kind of have that conviction that where other people just didn't? I have thought about this a lot. I do not know. It seemed so clearly obvious to all of us that I was more worried that we were drinking our own Kool-Aid than everybody else was wrong. But with the benefit of hindsight, we were clearly right. And I don't understand the like deep.
[0:34:46] Mental block and lack of conviction from everybody else. It's very strange. I have spent a lot of time trying to understand this. Did you find any explanation in your man's search for why or no? I mean, there's all the obvious stuff about like groupthink and like the big transformations just don't come along that often and exponential curves don't stay powerful for so long for so often.
[0:35:18] You know, maybe between 2016 and 2018, we had to get really lucky and it required like a lot of great belief. But then by 2019, certainly by 2020, we shouldn't have really gotten to exist. Google should have just run away with it. Yeah, I think Jeff Bezos called it like a business miracle that they built AWS and then didn't have any serious competition for like seven years. And I feel like OpenAI is like another business miracle. There's clearly something here.
[0:35:48] About why big companies get sclerotic and set in their ways and it helps them in a lot of ways too. But this is like, I mean, this is wonderful. I think it's great that the big companies don't stay the only dominant forces forever. That'd be really bad. But there's clearly something where these business miracles happen and they shouldn't. Is that right or should they? Well, I think it's great for the world that they do. Right. But to go back and explain in 2019.
[0:36:16] Why OpenAI was like allowed by the giants with huge amounts of capital and talent and everything else to do what we've done. It's like hard to explain. Why did Microsoft give you the money? That I think is easier to explain, which is Google had DeepMind and Microsoft did not have an AI bet. And, you know, big companies feel like they should have something in play in all of the major areas of technology. Was it kind of like they think it's going to be big, but then underestimated how big it would be?
[0:36:46] I think it's been like great for them. I don't know if we've added $1 trillion, $2 trillion or whatever market cap to Microsoft, but I think it's been a lot. And I think they have gotten incredible technology and cloud growth and will continue to. So yeah, I'm sure it's bigger than I thought it was going to be, but I think they made a good bet and have done super well with it. And I'm very happy about that. There's been different versions of OpenAI. The first one was the research lab. Next one was the product company. And you kind of said that like you bolted on the product company onto the research lab, which is the exact opposite of what most companies do.
[0:37:15] And now you're basically going to be like a massive infrastructure company and like almost all the value from OpenAI is just going to come from this like low margin infrastructure. And then you also said that basically in order to transition into the next phase of this business, it's not necessarily something the way that your brain works is naturally like designed to operate in that kind of model. What do you have to change? And like, what is that next phase of the business? I don't answer this because I don't like I think this is now getting into like a like a direct business thing. Something we're not quite ready to talk about.
[0:37:44] I am very excited for the next phase. And I think I figured out how to align something that I am very good at and very passionate about with what will be the next like 10 or 100x of our growth. So how did the transition of Sam, the research lab head to Sam, the product company head? Like, what was that? What were the biggest transitions for you on that? I mean, the whole thing was just extremely different. Like, it has felt like two almost completely unrelated jobs. And it's not quite to say like,
[0:38:13] I did one and now I do the other because I also still am responsible for the research lab. But they are almost separate things. And definitely running the research lab did not prepare me for running the product company in really any way. Did the YC experience prepare you? More. Like I had watched a lot of people have to scale big companies. Was it fun to kind of like finally get in the driver's seat? No.
[0:38:42] The fifth day after ChatGBT launched was the day we crossed a million users. And I had like watched it go up the first day and then come down in the afternoon and then go up the second day to a higher peak and then come down, go up the third day to a higher peak and then come down. And each of these days, the researchers were like, oh, that was some crazy flash in the pan PR thing. This is like over and, you know, that's not going to happen. And I had seen enough at YC that I knew that when something was growing like that.
[0:39:12] Completely organically. This had all of the spectral signature to me of something that was going to happen. And then on the fifth day, it crossed a million users. And I came home. And that was when it really hit me that we were about to become a company. And it was going to go very fast. And it was going to be crazy. We were just going to turn into a big company real quick. And I had watched what these founders went through. And I came home.
[0:39:44] And Ollie was like, oh, I saw that you crossed a million years. Congratulations. I was like, you have no idea how bad this is. You have no idea what's about to happen. It's not just bad for me. It's bad for you too. Like we have this nice, quiet life. You know, it's really wonderful. It's about to like kind of go through a cannon. And that is what happened. But it was like a very abrupt transition. I knew it was going to come. And I had watched other people go through it. And I knew that it was like not a pleasant experience. But I was like, well, we're being shot at the cannon. Here we go.
[0:40:14] Were you like subconsciously just like preparing yourself for years? If you know that this is eventually going to happen and the intelligence is going to get good enough where like there will be a magical product. My take on it is that I intellectually knew it was going to happen at some point. I had no idea when. I didn't know that was going to be the moment, of course. But that I had decided to pretend to myself and I had successfully deluded myself into sort of acting like it wasn't going to happen.
[0:40:45] Truly running the research lab was the coolest, most fun, most amazing job and lifestyle setup I could possibly have imagined. How so? I mean, you were like, it's not stressful at all. It was intellectually incredibly satisfying. It was the smartest group of people with probably the most important work that has happened in like the last century, maybe longer. I don't know. And I had this like front row seat and like.
[0:41:15] That was a once in many generations moment. It was unbelievable. It was the coolest thing. Are you guys experiencing that same kind of growth? You know, I keep on seeing Tebow post on Twitter that basically here's another reset. Here's another reset. Are you seeing that same like ChatGPT-esque experience again? Totally. I think there have been two giant form factors and associated growth so far. It was the sort of chatbots.
[0:41:44] And then the coding agents and the coding agents are just going totally nuts. There will be a third one soon, I think, which will be this idea of this sort of persistent agents, chiefs of staff, co-workers, colleagues, whatever we call them. And I think that'll come pretty soon. So we're going to go through like the third of these waves pretty fast. So a long time ago, apparently in August last year, I saw you tweet something and I thought to myself, this is not going to help the reputation.
[0:42:12] Let's see. Why? Why did you do that? Well, first of all, I love that scene from the movie. Like the Death Star is coming out of hyperspace and there's this dramatic music and it's like a great it's like a great scene. I thought it was a funny like I was it was like, you know, I was scrolling Twitter. I think it was late at night. I don't really remember. This is where the conspiracy theories happen. Like you're like you're feeding the fire here.
[0:42:44] I just thought it was, it amused me at the time. There was like, it was, I don't know. It was not a great tweet, to be honest, to be clear. I actually thought it was great. I thought it was funny. I thought it was funny. I think, I thought it was funny. I do feel like this is more and more what the world feels like. Yes? Yes. Okay. Yes. That's a good, that's a good meme.
[0:43:15] The way that somebody explained kind of the marketing challenge for OpenAI and the industry in general is, number one, we are close to creating what we need to explain to the world. Number one, we are close to creating a genie that can grant any wish. Number two, we are going to make sure that our first wishes broadly benefit humanity and that we kind of get the world to a place where a lot more people get to have a lot more wishes.
[0:43:46] The space of what you can wish for is incredibly big and creative and it'll be quite exciting to like figure that out with real sort of human values and preferences. But I think there's a fourth thing too, which is exactly that. You start making these wishes, the computer grants them, and then you're like, I didn't think that was going to work. Yeah. What now? It's a weird feeling.
[0:44:11] Yeah, it's just like the problem where I guess, you know, people spent like 100 years trying to disprove some, what was it, Jacobian? Yeah, this thing. And then some guy just asked Claude. And it was like, I don't know, within a few days or something like this. So I think there's gonna be lots of great jobs in the future. I really do. I think we're gonna have lots of intellectual fulfillment. And I think most jobs are going to adapt more than it seems like they should. But math, I think, is a very important example.
[0:44:40] Of something for us to study very closely right now, of something that may not go that way. In fact, I would say probably won't go that way. It seems like even as the systems get better and better, the people that I know that like no one is less busy. Everyone is more busy. Everyone's just doing more stuff, except for the people that are like, oh, I spent a trillion tokens. And like, I love this thing that I saw where someone said, like, I spent, you know, ungodly numbers of tokens. And then someone said, why aren't you more successful?
[0:45:10] You know, technology for a long time has been promising people that they're going to work less and they're going to have all this leisure. And it has gone in that direction. I think people do have more time for leisure than they had at many previous points in history and a higher quality of life in many ways. But somehow we never get the promise of the four-hour workweek at mass scale in society. And I don't expect AI to change that.
[0:45:41] Clearly, society is not working for a lot of people. And more productivity gains that actually accrue to people would be a great thing. And I suspect they will. I suspect that will happen. But I think that I really admire about people is our expectations go up. We always want more. We think of new things to do, to create for each other, to want for ourselves. And we, you know, it's like a...
[0:46:09] It's like a relative game. People are like very focused on how they're doing relative to other people. And so the competition that drives the economy and the kind of, I think the very wonderful desires about wanting to be useful to other people and create something and be of service and that whole cluster, I expect that to keep going. And I think we're all going to be much busier than we thought we were supposed to be in a post-superintelligence world. And we're still going to complain about it, but secretly we're going to be happy. How do you think the status games change?
[0:46:39] As less and less of our direct input is correlated with like value creation. I don't, I don't think it will feel at all like our direct, like the things that we value, I suspect will be things that are like very human. Well, like one thing is like cooking for people. You're not like creating a bunch of value in the world, but it like shows love. You are creating value in that it's like, those are the experiences that you're not creating like economic value in the maybe traditional sense.
[0:47:10] Cooking for people is a great example. I suspect that people cooking and eating together will remain important long after robots can do a great job cooking food. Do you think that a good heuristic would almost be like the greatest works of the longest surviving works? So let's say the Bible, for example. Odds are it's still going to be impactful like a thousand years from now because it's been impactful for the past 2000 years so far. Do you think that...
[0:47:41] If you had to like extrapolate out what are the things that humans are still going to care about? It's like, what is the most primal earliest thing? You know, we love adventure. We love a good quest. Yeah, I think betting against evolutionary biology is like usually a bad bet. Yeah. And so I would, I would assume those things continue. When was the last time that you realized that you weren't like being ambitious enough? I mean, I definitely badly undershot on the compute investments. Could you have known?
[0:48:09] Yes, but I got psyched out by the financial markets or something. I don't know. That was clearly a mistake. How do you correct that in the future? Well, I mean, hopefully I'll learn from it and I'll make some new mistakes, but I won't make that one again. On the compute side, this is kind of like the biggest infrastructure project of maybe all time, or is about to be? Yeah. Are you going to try and vertically integrate under OpenAI's hood everything from power generation to token generation to...
[0:48:40] You know, serving some person in ChachiPT or Codex or something like that. Or are you going to try and have a bunch of partners? We're not literally going to try to do it all inside of OpenAI, obviously. But we will try to do a better job of a well-functioning supply chain than we have done so far. Like, we have brought chip design and model design together, and that's been good. I don't think we need to bring, like, electron production together in the same way because that's more of a commodity.
[0:49:10] However, when you really think about the whole supply chain that has to come together to produce intelligence, I would say there is relatively too much focus on algorithms that create better algorithms and not enough focus on data centers that can create more data centers, which in a world of robots and a truly automated supply chain.
[0:49:41] You can totally imagine doing it. You can spend a data center's thinking power to drive a fleet of robots to make more copies of the data center. And that's probably a very wonderful thing to do relative to other uses of that compute if we're right about what that additional compute will eventually unlock. How much of your time is spent thinking about how to successfully design that fully robot?
[0:50:03] Almost no time spent thinking about it. Almost all goes into execution. That's a very obvious idea. It's very easy. You can relatively quickly say, here's the pieces that need to come together. But then to get that whole machinery and all those companies working together, none of the glory of the big idea and trying to think the big thoughts, but a lot of grinding. When you think of execution, what does that typically mean for you? There's no typical there.
[0:50:35] I mean, to the degree that there is, it's that you just like do whatever step is required in the problem and figure out how to make it happen. But figuring out how to like finance new fab build out is very different than figuring out how to get a great chip design team together and then get them to work with the research team and then actually get the supply chain running well. Like each of those is like a very different approach.
[0:51:02] One thing that I know that Brian Chesky does is he talks about like shamelessly trying to find whoever the expert is and any given thing and then basically just go ask them whatever question he has if he's trying to come up to speed on something. What is your process for doing something like that if it's something new that you need to become good at in a very rapid period of time? Definitely finding the experts and talking to them, reading as much as I can. I don't have a lot of like...
[0:51:30] I don't have a lot of novel strategies here. I've always been really grateful and pleasantly surprised by how much experts are willing to help people if they ask. It's like a very nice thing about humanity. One thing I've heard you say is you should always ask for what you want. Because not all the time you get it, but sometimes you do. Sometimes you do. And when you do, amazing things can happen. When was the last time that you asked for something that would seem absolutely insane to someone else?
[0:52:00] And you got it. Actually, it was this recent time I got on a plane that I still can't talk about, but it did work. Go back one more that you can talk about. I mean, in some sense, Codex was an example of this. Like, this is not the most recent one, but it was one that I think it's instructive. We were way behind Claude Code, and it seemed like a kind of crazy kamikaze mission to try to beat them with a coding app.
[0:52:30] The consensus is that this kind of thing never works and you just move on to the next one. But it's like a fool's errand to try to win when someone else already has momentum in a particular product category. But we decided we thought it was really important. We asked a team to do it. They performed a legitimate, unbelievable, very rare in the history of business thing. And now it is the product and model that most of the best coders that I know use.
[0:53:00] And that felt like an impossible thing. But if we hadn't asked the team, like, hey, we have a really important but extremely important mission for you, it just wouldn't have happened. Why did you make that decision? Why didn't you just give up? Because it felt like one of these few very strategic areas that was going to happen very quickly. And coding is so important to RSI to say nothing of the economic value that we just didn't, it didn't feel like one we could give up on. At YC.
[0:53:29] It wasn't that intellectualized at the time. It was just like, I kind of knew that.
[0:53:59] I mean, my whole life I wanted to work on AI. And I kind of knew that it would be the most important thing I could ever touch. Like for me, it was like my passion. And I did think it'd be really important. I just wanted to do it. What were those first few weeks like? I know that there was this, I don't know if you'd describe it as a camp, but people just basically like all got together on some kind of retreat. And it wasn't even like meant to be a company at the time, I think. Oh, like the first few weeks once we started. Yeah. No, we were in Greg Brockman's apartment. Yes. And there were maybe like...
[0:54:28] 10 of us, 12 of us. And, you know, it had been all of this work to get it going. And then we showed up one day, the first day. I was like, you know, January 4th, something like that. And I was like, so here we are. What are we going to do? We should get a whiteboard. We should start talking about ideas. Maybe we should write papers. And I had this like, oh, fuck, what have we done? Like, it was like a really crazy moment.
[0:54:58] Had you already committed to the world and a whole bunch of other people were doing this? It took a couple of years to really get our groove and figure out what we're going to do. It was not... I mean, we knew that we wanted to figure out how to build AI. But beyond that, man, really unclear. When you're in the stumbling through the woods phase of this type of Manhattan project, how do you most efficiently just stumble through the trees to rapidly...
[0:55:27] Figure out what not to work on. I mean, if something's not working and you ran out of ideas, you can kill it. That's kind of easier. The really hard thing is when something is working super well, when do you decide to kill the other things to make it work even better? So there have been a lot of quite important moments in OpenAI's history where one thing started to really work and we killed other good things to make the best thing work better. So when GPT-3 started to work,
[0:55:59] We shut down things like robotics, stuff that we're really excited about to really focus on this. And then when coding agents started to work recently, we shut down things like Sora that we were also really excited about in the browser to really work on this. And that is difficult to do. Let's say you invest a billion dollars into some new business like Sora. How do you decide whether or not that business is going to become an OpenAI pillar? Oh, it would have been super successful. It was just like...
[0:56:27] It was more important to put the compute and the energy into coding agents. Take me into one of those meetings. Like, imagine you're in that meeting. I guess maybe you were in that meeting where you were saying, we've spent a year plus on this thing, huge amounts of money, huge amounts of compute, lots of people and resources, a lot of momentum into it. People use it. They love it. And then you decide we're going to pull the plug. Like, how do you make that call? Yeah, it's not like it's not a one meeting thing. It's like a...
[0:56:55] I think it's a real, it's like a somewhat gradual realization that there is a more important use of this compute, these people, you know, this product direction. And we're going to make a very painful decision to get there. How do you realign people once you do have to like kind of kill their baby to move them to another baby? People kind of understand the mission and the stakes and the need to reorient to get there. So even if they're like unhappy in the moment,
[0:57:27] Sometimes they're very happy. Sometimes they're like, yeah, this is the right thing for the mission. But even if they're not happy in the moment, they're like, I get why we're doing this. And the kind of continuing refocus towards super intelligence is like a good thing. Do you think that there's going to be projects currently that are going to get killed? I assume it's harder to pursue. Yeah. There's this amazing line from John Collison where he said, basically everything in the world, if you just look around.
[0:57:50] It's so difficult to make things happen, even getting a park bench built. It's incredibly difficult. And so when you look around, you can kind of think of the world as a universe of passion projects. And I think that if you are in Steve Jobs' position where you're going to create something where a billion people might interact with it every single day for hours, you have to think deeply about how do I design something that people are going to love.
[0:58:19] Ideally, not be unhappy about. How do you think about design? I feel super lucky to get to work with Johnny Ive on designing beautiful things. And I have learned so much from him about how he really studies a problem before trying to get to the solution and not even letting him think too much about the solution until he really designs, really understands the problem. And I think this is a key that I didn't appreciate before, like really great design.
[0:58:50] is way more about understanding the problem than the flash of insight. And if you try to rush towards the thing or lock yourself too much into the thing, you will not do as good of a job. I think the iPhone is the greatest piece of technology humanity has collectively yet made. It is an incredible thing. But I don't like love my relationship with it anymore. I turned off my notifications. I actually like it much better now. Yeah, I keep myself on do not disturb.
[0:59:18] That wasn't even enough. I just like, I turned off notifications for everything except a very small number of things. And I never have them on because I just, you know, I can like look at it if I want to look at it. Even messages apps? Even messages apps. That was like a big life upgrade. And I deleted TikTok because it was just like too powerful. You were addicted to TikTok? You know, so here's a crazy thing that happened. When we were building the Sora app, I made myself get addicted to TikTok.
[0:59:45] Because I wanted to just like learn. I was like, you know, I never really used it before. I mean, I had like people would send me a TikTok or whatever, but I never got sucked into it. And I was like, I really don't want to build something that is going to have that kind of thing. Absorb people's time, but not. And I loved it. I loved TikTok. I really thought it was great. And then I thought I could like control it. I was like, oh, you know, it's actually kind of fun, but I only use it for like 10 minutes to wind down before bed. And I'm like totally in control of it. And then it was like an hour one night.
[1:00:13] And then some Saturday afternoon, I was on my couch for like three hours. And I was like, this is like really not what I thought the iPhone was supposed to be about. Now, I'm really enjoying it at the moment like a drug, but I can tell it's bad for me. And then I like briefly got it back under control and I was down to like five, 10 minutes a night, whatever, you know, like a little wind up before bed. Then I was just like, enough. I think the iPhone is amazing. And yet I did not feel like I had enough self-control to keep that app or.
[1:00:43] I did not feel like the notifications on messaging apps were like a net good thing for me. And I'm sure we will make an incredible, beautiful, like really helpful, empowering set of devices. And I'm also sure that people will misuse them and it'll make people's lives worse in ways we can't imagine and we'll adapt. But this is a thing about powerful technology. You're inventing a new device. What is that process of exploration through the problem space? Like if you're Johnny.
[1:01:10] I don't answer on his behalf. He's like talked about this before somewhat, but it's like his process. When he's doing the car, he will like go study all the history of motorsport and then like the different typefaces that people use for the text in the cabin of a car and the materials and why and like the different sounds that engines have made over time and why some have appealed. I mean, he'll write literal books of all of his explorations of all of these like unbelievably detailed small components.
[1:01:39] Did you guys basically take those books and try to use them as training data to make a Johnny model? No, but that would be a great thing to try. There is definitely a part of his process that I don't understand. I understand the studying. I understand the refinement of a very new concept into something great. But there is a middle step, the inspiration that comes from understanding the problem really well to the very novel idea that seems to me to happen all at once, and I don't understand that.
[1:02:08] When you're thinking about designing something, what goes through your mind? I'm not a designer anyway. I would not. I try to be pretty good about realizing what I'm not good at. And I wouldn't try to have a strong opinion there. What are you the worst at on the business building side? Maybe product. Really? Maybe. Okay, how do you find great product people if you're bad at product? This is a thing that I've never quite agreed with people on. There's like a business meme that you can only hire...
[1:02:41] People and things that you deeply understand. I think you know if they're great. I think this is just clearly not true. I don't understand design either. I know Johnny's great at design. Like there's lots of things I can point to and you talk to him for 30 minutes. It's very obvious. Which things do you try to actively get better at? And then which things do you just try to outsource and understand that you're just never going to be one of the best? I am a big believer in you should try to get better at your strengths and the whole like obsession with I'm going to get better at the things that I'm just not good at at all and never going to be good at. Huge trump. Super good at your strengths. Okay.
[1:03:11] What are your biggest strengths? If you had to like force rank. I hate this question. I don't hate this from a false modesty perspective. I think it's like very hard to say anything insightful about your own strengths. You're clearly good at really rallying people around some objective. Sure, but I don't like, I don't think I could teach someone who isn't good at that how to be good at that. I think the things that come super naturally to someone are very hard to...
[1:03:38] I don't know, or at least in my own case, I don't like deeply understand why I'm good at that or what to do about it. Although I think we talked about earlier, like this category of things that you can learn, but you can't teach. I think this is quite important to understand. And like, if you want to get good at something like that, asking someone to explain it to you, in my experience, never works. Really studying them and like sitting with them in meetings and just trying to observe it and learn it yourself. That does work.
[1:04:07] And like when there has been something that I do want to get better at, I have tried to just be around someone who's great at it and really deeply study it. But I don't think they would have been able to explain it to me. I don't think they could have like taught it to me by talking to me about it. I think that's totally right. If you look at like the way that the best people in the world learn video games, if you're playing like CSGO, you like play some CSGO. So you have like the basic game dynamics and then you just go watch a pro and like see how they interact on the map at different points in the game and stuff. When you think about like organization pace.
[1:04:37] You know, there's like ambition and all these other things. But like you ideally over time want your organization, you obviously don't want it to slow down, but ideally it even moves faster. How do you like bake that in? I think it's like 90% of the people you put in leadership roles. Okay. There's like other things you can do. People have all these different sort of operating rhythms and how they try to run the company and this management technique and that one. And I think it's, I think mostly just comes down to the people. Definitely something I think about with everybody in a...
[1:05:04] Role like that is like, are they a fast mover or a slow mover? How do you measure that without actually having worked with them in the past? Well, ideally you have worked with them in the past. I think most of the time executives at a company should be promoted internally, not hired externally. Okay. But when you do need to hire someone externally, you spend a lot of time talking to them, spend a lot of time reference checking. You try to like work together in some kind of casual way. Slightly different note. What was the most painful thing that happened in the last 12 months?
[1:05:35] Honestly, having kids and working really hard at the same time is brutal. It's just extremely painful. And I think I'm a very present dad. I don't do anything but work and hang out with my family really at this point. But I still feel like I'm missing so much of this one-time thing. It's very painful. When you think of someone like Masa, for example, what about his brain and the way that he sees the world is so different?
[1:06:05] I think he will end up being one of the wild successes of this decade. Incredible person. Dear friend, incredible person. Massive conviction and belief and not afraid at all of big numbers and scale. And it's great. There are not many Masa-like people in the world and we should be very grateful for them. What made him? I don't know if you've talked with him. I mean...
[1:06:34] As far as I can tell, he was like always like this. Do you also have the same sort of just like no concept, like no ceiling concept of scale? Not, I think Masa is like an N of one character. Do you kind of view OpenAI as a little bit like the golden goose? In what way? Spawning a bunch of very valuable things over time and just building like a core competency of increasing intelligence in the world. Not really how I think of it. I get what you're saying.
[1:07:05] But it doesn't feel like we're just spitting out golden eggs. It feels like we're building this kind of compounding thing. I think one of my favorite mental models that I've taken from you is this idea of real trends versus fake trends. Oh yeah, this is an important thing. Whenever people talked about bubbles or anything else, I was always kind of confused. I studied Warren Buffett and Charlie Munger a bunch, and so they love to talk about bubbles and things being overvalued. I was trying to decipher how do you figure out whether or not something is real or fake.
[1:07:35] And whether or not it's going to persist and continue, or it's just going to, you know, revert to the mean. And what'd you figure out? Well, it was, I think your mental model of basically, if there's a small group of people, like what is a real trend versus a fake trend? A fake trend is, you know, the VR situation where someone, there's a lot of hype, but then someone buys the thing. They don't really love it. They don't really start to like design their life around the experience of using it. And then it sits on itself. Whereas like for me with ChagiBT, it's pretty much.
[1:08:04] Every day? And maybe for like sometimes I need to work a lot so I spend like three hours or some days it's like almost nothing but it's like there, persistent in my life. How do you kind of like figure out now whether or not something is a real trend or a fake trend inside of the company and just generally? Same principle. Like is there real deep enduring usage? How did you come to that philosophy or mental framework? Well, I like kind of watched a lot of startups.
[1:08:31] There are many amazing things about working at YC, but just the amount of data you get. And as long as you're willing to spend the time trying to analyze it and make sense of it, you can really figure out a lot of things. Are there any big mental frameworks that you used to have that you think are wrong in today's environment and will continue to get more wrong over time as intelligence explodes? I mean, I kind of think a huge amount of them are wrong. They weren't necessarily wrong at the time, although I'm sure I was wrong about a bunch of things too.
[1:09:01] But a huge amount of them are wrong now. I think a startup of today still looks mostly like a startup of 10 years ago because that's what the received wisdom says you're supposed to do. And sure, it's different in some ways. People are like, well, I'm going to hire less people and spend more money on tokens for Codex or whatever. But it should probably look very different. And I have met a few people who are trying to do a startup in a completely different way.
[1:09:29] But most people just use means like use more codecs and that doesn't seem like enough.