Sam Altman - How to Start a Startup

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. Uh, and what is possible to do now with a small team of people has— 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, 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 a— what will be a startup that is, like, 2 weeks old, something like that, that has an entirely redone, sort of, office productivity suite, whatever, all made for, like, a world where AI has got to be able to use documents, presentations, spreadsheets, whatever, as a first-class consumer.

And, uh, 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, like, barriers to starting startups and the, like, tools out there become more proliferated and all this stuff, you would assume that, like, harder startups are easier to start.

What it means to be 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 valuableright now because software is going to become free. But, you know, like, it won't be that long until robots get really good, and a lot of the expectations of, you know, it's really difficult to make rockets or whatever, that may change, like, quite dramatically.

I love times like this. I think startups are— they have the biggest edge when the ground is shifting the most, and when costs are coming down rapidly and cycle times are coming down rapidly. That's when startups really, I think, just have a massive inherent advantage.

And that's happening in so many places at onceright now that it seems like a great time to be doing startups, and yet 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 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 2 years, 4 years, whatever.

So it seems like an unbelievable time to be starting startups, and there's very fertile ground, 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.

Yeah.

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, impact your ability to kind of say, okay, the model is this intelligent today, it's this intelligent 3 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 at least, it doesn't feel like watching model progress is the same as, like, watching a founder develop.

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.

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, 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 okay 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 going to figure it 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 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.

You had an interesting thing that you said a long time ago, which is basically, like, the first time that 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.

Yeah.

And you're like, well, I survived the first 9, 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 2 ago, you came to the conclusion that shit was always going to be going wrong.

Yeah.

And so you kind of had to, like, internalize the enjoyment of experiencing pain or, like, not great things happening. 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.

Mm.

Because of the way that they reacted to stuff going horribly wrong versus the founder. Because I often didn't know, like, how new a company was, but I could tell if it was, like, a founder in the batch versus a founder that had been doing this for a couple of years by their, like, emotional state when they talked about a problem.

I think most people

think about the opposite of a bad experience as a good experience, and they would rather have the good experience because it seems like more fun or more pleasant or whatever. But if you think about, like, the opposite of a bad experience as no experience, and 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 too.

Naval Ravikant used to say this thing that I loved, which is if you had, like, a fast-forward button on a remote for your life, your life would be over. And so, like, the boring parts, the bad parts, it's, like, much better than no experience.

It's all part of the, like, interestingness of and the kind of, like, emotional depth and range. And, I don't know, I find it, like, fairly easy to be grateful for the bad days.

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, 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 allright. You'll still, like, at some points overly expand or not be ambitious enough. But we are, we are, like, very focused on

this is going to massively empower people. It's going to be, you know, 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, like, one of the biggest AI risks I am worriedright now is, like, AI authoritarianism and, you know, a small number of people or companies thinking they need to control the world.

That'd be very, very bad. But given this mission, 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, like, 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, like, enable this mission.

Now, there's a bunch of things you can build on top of that platform. Like, you can go build every vertical, every startup. 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, low-cost intelligence, 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, like, in a physical world and we still want stuff to happen. So, you know, we need to be able to make stuff happen in that world.

And I have wondered if, like, the fact that energy and 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.

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 on the OpenAI timelines, but also keep the rest of the world on the OpenAI timelines as well?

You talk to them a lot. You have to— and you don't just say, like, I need you to, like, deliver this turbine or this chip on this date because, you know, people will say, like, okay, whatever, they have a bunch of other priorities.

You really have to, like, show them, here is the upcoming model, here's what it enables, here's our research. Like, we— for our core suppliers, we really show them a lot about what we're doing, why we believe what we believe, what it's going to enable.

And, you know, you figure out— I mean, the most important thing is to, like, 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, like, underestimated them." How do you, like, 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. The— you know, as a kid, I was, like, very fascinated by the Industrial Revolution, 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 out 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 as, like, someone who has now spent more time thinking about business, is that the important invention was the joint-stock corporation.

And before that was invented and, you know, you had these, like, 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, like, 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 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, 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 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 100 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's, like, the most zoomed-in view of the last 100 years. 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.

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, I would not put in that category. There's a lot of very high ego CEOs, people with just, like, incredibly high opinions of themselves on a way that maybe, like, would have been just, like, purely annoying, but now because people can, like, you know, buy their shares, maybe you, like, 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. Like, 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 if placed in the exact same position that you are currently, what are the biggest differences between those two people?

Well, on the— to the previous question, the thing that drives me the most is, like, this is the most interesting, important thing I can imagine doing, and we are now, like, in the singularity. Like, this is the moment.

For 10 years ago, this was, like, a kind of far-off dream at best. It seemed very improbable. And now we're, like, actually in the moment that we used to, like, talk about at the lunch table in a very not serious way.

And so the thing that drives me is I've been waiting for this my whole life, and I think it's going to be incredible, hugely positive, awesome for the world. I'm excited to get to work on that. I also think some of the alternative visions painted by other companies are, like, quite terrifying.

I want to make sure that gets pushed against and is not what happens. But the main thing of what's different than 10 years ago is, like, we're actually in it. Like, this is the real— I think it is both true 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 curveright?

I think, like, there are still major AI alignment issues to solve and safety issues, and there are still major

economic issues, future of jobs, all of 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, you know, 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, it's going to be— 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, you know, with a lot of power and potential.

And I really care that we do it that way.

When you were talking with Patrick Carlson on stage, it must have been, like, a couple months ago, there was this fascinating thing that you said, which is basically, like, you will talk or text with 300 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 an AI model that's not that smart, but just has, like, a huge amount of, like, a short-term context on, like, whatever's happeningright now and then forget.

Does that enable you to make decisions that other people wouldn't have? Like, what company decisions you'd know when you—

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 research breakthrough impending that is going to, like, 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 and 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, like, looking backwards, I don't even know if that makes sense.

How do you think about this? How is— like, is your time horizon shortening?

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 of it.

And sometimes you do have to, like, plan a few things on a, you know, 5 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 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.

One of the people that I know the best, his top, you know, 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 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 superintelligence, what's next? But it's this— that's kind of how I subjectively feel we are close, is this the first time in, like, more than a decade I've thought about what is the next thing.

And is it the ranch?

I mean, eventually. There might be a few more things on the way, but that is— yes, that is the eventual plan.

If you had to, like, try to guess, what else does Sam want to accomplish before he ranches?

Look, AI— superintelligence is going to get built. Like, that, you know, not done, but, like, going to— we are on the glide path.

The path to the get there is very clear.

Abundance and decentralization and, like, 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. 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.

I've heard it from you.

So far, it's working pretty well.

Good.

I think—

I think it's— 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. 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.

Okay. 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." And no one knew what to think. And I could just feel these, like, storm clouds brewing and, like, everybody— 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?" And 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.

So, 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 going to have to be me"— does not go, like, show up and talk to people, I had, like, a sense it was 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 a whole thing. So I was like, "I'm just going to, like, get this over with in a short period of time."

Brian Chesky advised me to do it. He had done something for Airbnb, 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, like, lived on an airplane. It was a very strange—

Did you have a bed?

I had, like, a— yeah, I was comfortable, but yeah, I had a bed.

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. 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.

But by the end of it, like, the last few days, I started— it was one of these, like, weird, you know, half asleep, half awake kind of somewhat dreams, but I started 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."

Your, like, subconscious is fighting back or something?

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, 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 just like, I— 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, meeting, like, hundreds of people a day in some cases. And, like, tension's lowered by the end of it, but at the beginning, like, the world was, like, very nervous. 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 7 or 10-day chunk than a bunch of one-day trips spread out.

So I always do try to do it that way now.

I think a lot of people overestimate the, like, risk involved in making most actions. Like, there is a lot of risk if you're just, you know, 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 obvious example would be, like, I was always extremely high conviction when I was buying a lot of compute.

Have 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.

Not always the emotional part of it, but sometimes also.

Do you get 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, theright 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, I'm more just, like, I get upset or frustrated or say, "This is what we're going to do." And 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, '09, '10, somewhere around there than you are today.

I don't know if people would describe me as fun to work with. Like, interesting to work with. Like, effective, ambition-raising, like, very mission-focused, 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'm not— 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 problems, new insights, like, very high level of ambition, like, got me to do something I didn't think I could do," that kind of thing.

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. And 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 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, whatever. Like, the

most countries or cultures have some sort of phrase for being too ambitious, basically.

Tall poppy syndrome thing?

That's one. And you realize, like, how deep this is in people and that they, like, heard it in 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're say, "Okay, I'll try it again."

Do you do anything like Steve 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'm not, like, an— I don't do inspirational speeches. 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— I miss, like, great board games.

What was your favorite board game?

There's, like, no one board game where I'd be like, "I want to play that, like, again and again." I don't have, like— like, I'm not like 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, like, new and you have to, like, 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?

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, like, 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 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 clearlyright. And I don't understand the, like, deep mental block and lack of conviction from everybody else. It's very strange. I have— I have spent a lot of time trying to understand this.

Did you find any explanation in your, you know, man's search for why or no?

I mean, there's all the obvious stuff about, like, groupthink and, like, the big transformations just come— don't come along that often and exponential curves don't stay powerful for so long for so often. But, like, 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 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 thatright or should they?

Well, I think it's great for the world that they do.

Right.

But to go back and explain in 2019 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?

I mean, 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 they 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, like, you bolted on the product company onto the research lab, which is the exact opposite of what most companies do.

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 a getting into, like, a—

Like a direction.

Something we're not quite ready to talk about. But I am very excited for the next phase and I think I have 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, 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.

No.

The fifth day after ChatGPT launch 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 completely organically, this had all of the spectral signature to me of something that is, like, 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, like, we were about to become a company and it was going to go very fast and it was going to be a crazy— like, we were just going to turn into, like, a big company real quick.

And I had watched what these founders went through. And I came home

and Ollie was like, "Oh, I saw that you crossed a million users. Congratulations." I was like, "You have no idea how bad this is. You have no idea what's about to happen." And 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 out of the cannon. Here we go."

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 a sort of acting like it wasn't going to happen.

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 was 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, 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 Tebo 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 in associated growth so far. There was the sort of chatbots 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 the sort of persistent agents, chiefs of staff, coworkers, colleagues, whatever we call them.

And that'll— and, you know, 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."

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— you're like— you're feeding the fire here.

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.

No. No, I actually thought it was great.

I thought it was funny.

I thought it was funny. I think— I thought it was funny.

Yeah.

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. 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— well, 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. And number three, 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.

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?

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'm— I think there's going to be lots of great jobs in the future. I really do. I think we're going to 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 of something for us to study very closelyright 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, what have— 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?"

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. Like, 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 work week at Mass Scale and Society.

And I don't expect AI to change that.

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— 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 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. 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— the longest surviving works? So let's say the Bible, for example. Odds are it's still going to be impactful, like, 1,000 years from now because it's been impactful for the past 2,000 years so far.

Do you think that 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.

We love cooking.

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 going in with theright mental model?

Yes, but I got, like, psyched out by the financial markets or something. I don't know.

Okay.

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, like, vertically integrate under OpenAI's hood everything from, like, power generation to, like, token generation to, you know, serving some person in ChatGPT 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.

However, I am— 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, you can totally imagine doing.

You can, like, 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'reright about what that additional compute will eventually unlock.

How much of your time is spent thinking about how to, like, successfully design that fully robot end-to-end future where intelligence can just produce more intelligence?

Almost no time is spent thinking about it. Almost all goes into, like, execution. Like, the idea— that's a very obvious idea. It's very easy. You can, like, kind of relatively quickly say, "Here's the pieces that need to come together."

But then to, like, get that whole machinery and all those companies working together, that— that, you know, none of the glory of the big idea and trying to, like, think the big thoughts, but, like, a lot of grinding.

When you think of, like, execution, what does that typically mean for you?

There's no typical there. Like, the— 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, you know, figuring out how to, like, finance new fab buildout 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.

One thing that I know that Brian Chesky does is he talks about, like, shamelessly trying to find whoever the expert is on 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, great strat— I don't have a lot of, like, 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 and you got it?

It actually was this recent time I got on a plane that I still can't talk about, but it did work.

Okay, go back one more.

They don't always 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. And, you know, the, like, the consensus is that this kind of thing never works and you just move on to the next one.

But, you know, it's like a fool's errand to try to, like, 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, like,

unbelievable, very rare in the history of business thing. And now it is the product that most of— and model that most of the best coders that I know use. And that felt like an impossible thing. But if we hadn't asked the team, like, "Hey, we have a really important but extremely hard 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, you basically had the most distilled version of what the mission was is just trying to increase the amount of innovation in the world. My hunch is that if you actually, like, thought about why did you decide to go work on OpenAI instead of YC, you could almost make the argument that you could just have a bigger impact on increasing the amount of innovation in the world through working on.

It wasn't that intellectualized at the time. It was just, like, I kind of knew that— 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. I just— and I did think it'd be really important, but 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.

It was just, like.

Oh, like, the first few weeks once we started.

Yeah.

No, we were in Greg Brockman's apartment.

Yes.

And there were maybe, like, 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.

Had you already, like, committed to the world and a whole bunch of other people, like, were doing this?

Yeah, but it took a couple of years to, like, really get our groove and figure out what we were going to do. It just— it was not— I mean, we knew that we wanted to, like, figure out how to build AI, but beyond that, man, really unclear.

When you're in the, like, stumbling through the woods phase of this type of, you know, Manhattan project, how do you most efficiently just stumble through the trees to rapidly figure out what not to work on?

I mean, if something's not working and

you run 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, we shut down things like robotics, stuff that we were 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 and 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, like, become a, you know, OpenAI pillar?

Oh, it would have been— no, no, it would have been super successful. It was just, like, 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 are 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 a— it's not a one meeting thing. It's like a— 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, sometimes they're very happy. Sometimes they're like, "Yeah, this is theright thing for the mission."

But even if they're unhappy in the moment, they're like, "I get why we're doing this." And the kind of continuing refocus towards superintelligence is, like, a good thing.

Do you think that there's going to be projects currently that are going to get killed?

I assume so.

In order to pursue?

Yeah.

There's this amazing line from John Collison where he said, basically, "Everything in the world, if you just look around, it's, like, so difficult to make things happen, even like getting."

So difficult.

Park bench built. It's incredibly difficult. And so when you look around, you can kind of think of the world as, like, a universe of passion projects. And I think that if you are in, like, Steve Jobs's position where you're going to, like, create something where a billion people might interact with it every single day for, like, hours, you have to, like, think deeply about how do I, like, design something that people are going to love and 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 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, so I actually like it much better now.

Yeah, I keep myself on Do Not Disturb.

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, I— so here's a crazy thing that happened. When we were building the Sora app, I made myself get addicted to TikTok because I wanted to just, like, learn. I was like, you know, I had 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. And then some Saturday afternoon, I was on the 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 in 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, ten minutes a night, whatever, you know, like a little wind down 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 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.

I don't answer on his behalf.

But okay.

He has, like, talked about this before, somewhat, but it's, like, his process. You know, 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.

Did you guys basically take those books and, like, try to, like, use them as training data to make, like, 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. Like, I understand the studying. I understand the refinement of a very new concept into something great. But there is, like, a middle step, the inspiration that comes from understanding the problem really well to the, like, very novel idea kind of that seems to me to happen all at once.

And I don't understand that.

When you're thinking about designing something, what goes through your mind?

I'm not a designer in any way. I would not. I try to be, like, 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 people in things that you deeply understand. I think, you know, if they're great, I think it's 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 when 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 trap.

Super good at your strengths.

Okay. 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, I don't know, 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. But, 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 totallyright. If you look at, like, the way that the best people in the world learn video games, if you're playing, like, CS:GO, you, like, play some CS:GO 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.

100%.

At different points in the game and stuff. When you think about, like, organization pace, 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% 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 it mostly just comes down to the people.

Definitely something I think about with everybody in a 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.

Now, what was the most painful thing that happened in the last 12 months?

Honestly, having kids and working really hard at the same time is brutal. It's just extremely painful. Like, you, like, know your— and I think I'm, like, a very present dad relative. Like, 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, like, one-time thing. It's very painful.

When you think of someone like Masa, for example, what about, like, his brain and the way that he sees the world is so different? I think he will end up being, like, one of the wild successes of this decade.

Wild success. Yeah. Incredible person.

Yeah.

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? Like, what— I don't know if you've, like, talked with him, but.

I mean, 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 1 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, but it doesn't feel like we're just, like, 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. And.

Oh, yeah. This is an important thing.

Like, whenever people talked about bubbles or anything else, I was always kind of confused. Like, I'm, you know, 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, like, decipher how do you figure out whether or not something is real or fake 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 did 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 a shelf.

Whereas, like, for me with ChatGPT, it's pretty much 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. 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, like, 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, like, 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. 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. But most people just use means, like, use more Codex, and that doesn't seem like enough.