Sam Altman: "Never a Better Time to Do a Startup"

Sam, thanks for joining us.

This is something.

This is something.

This is, like, a lot bigger than the earlier Startup Schools.

Yeah. I mean, startups are a lot bigger now than they have ever been, so.

For sure.

I mean, they've bigger— they're bigger than they've ever been because of the vision that you had for AGI, which is nigh.

I think this is going to be the best time in the world to do a startup, and it's going to be quite amazing to see.

So I want to start with, you know, a time and place, which is you were in the very first batch of Y Combinator in 2005 with a location sharing company called Looped. What do you remember about that, and what was your best PG's Paul Graham story?

I think if it were possible to get as, like, far from this moment as, like, I can imagine, it was, you know, startups are not cool at all. We were, like, hiding out in this little building in Cambridge.

PG was making us dinner. And, you know, what took

three months to build at the time that we— each company built over the whole YC startup could now be done with, like, in, like, seven minutes by a coding agent. And it was only— I mean, only 20, 20 years ago.

And I think the difference in what's possible for a startup now, what a startup can take on, you know, it's— I think you could either be sad and be like, "Oh man, like, a Codex prompt is a whole startup," or you could be like, "I can go start the world's most ambitious, crazy company.

I can have, like, experts in every field working together. I can do these very hard technological things that were just impossible. And it's going to be amazing." But at the time, it felt nothing like that, and it was very difficult to get anything to work.

I think Paul Graham is probably the most important force in startups of the last few decades, and.

Without question. Yes.

No question.

And my kind of Paul Graham memory is we would all, every week, come— I think it was on Tuesdays— and he would, like, cook up— he himself would cook us dinner, and we would all walk in feeling, like, very hopeless and very dejected.

And we would— there were eight companies, and then we would all go home at the end of it, and he had convinced, like, each of us that our startups were about to, like, take over the world, and we're going to be, like, you know, the next Google or whatever, Facebook maybe at the time.

And that ability to sort of, like, create optimism and momentum and belief out of nothing was, like, a real PG special. And in the early days, when YC seemed like a terrible idea and startups seemed like a bad idea, and certainly startups that were, like, young technical founders with no business people seemed like a terrible idea, PG just sort of, like, willed it into existence.

But it also takes someone who actually— I mean, you're sort of famously par excellence, an agentic person, like, even before we thought about agents, period. I mean, you just— I remember Paul wrote— I mean, it's making the rounds on X today even that Paul wrote in the early— in the late 2000s that you would be— you were one of the top five entrepreneurs he'd ever met.

That's very nice of you to say. I think, like many 20-year-olds, I had, like, a lot of energy and a lot of ambition, but it was sort of very not directed, and I wasn't sure what to do. Paul had this thing he used to say of, like, the job of being a good startup investor is a teacher, but it's a kind of teacher we don't usually use.

Like, we usually think of a teacher as someone who, like, gives a lecture, and you can't help someone that much by, like, giving a lecture about a startup. There's another kind of teacher, which is like a flight instructor, the person who, like, sits next to you saying, like, "Do this.

Don't do this. That worked. This is— you missed that thing," or, "You're making these mistakes, and I'm just going to talk to you about this one." And that very, like, hands-on kind of, you know, "Here's where to, like, direct this sort of, like, brownie in motion energy," that was very important to me.

Yeah. I guess later you came on to become president of YC, and you sort of brought exactly the same energy to a great many YC founders over the years. Did you have anything— like, did anything jump out at you from that time around, you know, taking this raw energy of someone really, really smart and maybe a little undirected and then driving them more towards agency?

Yeah. I— so first of all, I love startups. I think not everyone— they're not, like, for everyone, but I think startups are the coolest thing in all of business. I think startups are really, like, the main thing that keeps the economy from becoming stagnant.

I think companies do just, like, drift towards suckiness, and startups will continue to be important forever. In fact, if we areright that AI is going to be such a big change, startups will be much more important to making sure that the power of this technology gets widely distributed throughout the economy and society and is not just concentrated in a few companies or models.

So

I think startups are this, like, unbelievably cool, fun, extremely painful and difficult, but wonderful thing. And I think a big part of the job of running YC is you are kind of the, like,

unofficial flag bearer for the startup movement. You know, like, there's lots of startups. There's lots of ways to do a startup. You obviously don't need to do YC, but it has always been a huge help to companies and a very powerful force.

And so starting with PG and then all of us, like, you know, we have to, like, make YC successful, but I think we really have to, like, fight for why startups are important and why people should consider startups and help put, like, relatively more power in the hands of founders and encourage more people to start them.

And that's actually worked really well. I think thinking back to the early days of YC, it was, like,

very little leverage in being a founder relative to an investor. And that shift, you know, I think that's even been good for the investors. I think it's just been, like, much better for the whole startup ecosystem. So mostly what I tried to do at YC was just push for more startups and encourage people to think about startups and figure out what we could do to help founders and help make startups and the startup ecosystem as good as possible.

Definitely part of that was pushing people towards more ambition and bigger swings, but it feels like the minor leagues relative to now.

I mean, I think you were one of the people who really brought hard tech to YC in a really grand way. And then one of the things we're seeing at YC now is that number was, you know, maybe 5 or 10 percent for many years, and then now we're getting to 15, 20, 25 percent.

I would argue, on the back of how much easier it is to use agents and the cost coming down.

I think, like, ambitious startups are always awesome, and hard tech startups are appealing to a lot of people, but they're hard, or they've been hard. They still will be hard. But what you can do now to go take on a really ambitious project, like, in the same way that you can make the startup that took us three months of nonstop work in 17 seconds, with three months of work and a lot of agents, you can do unbelievable things.

So I think we will see a golden age of startups where people are like, "You know what? I'm going to do things that would have been completely impossible for a startup to even, like, dream at a year ago in sort of, like, the YC time frame."

I mean, that's actually a really big reframe. I mean, there are probably people even in this room who might be worried that, well, intelligence on tap means that, you know, they might be looking at a Looped or My Startup Postures, and they're like, "Well, I can't start that company anymore."

But guys, that was, like, a long time ago, actually.

Man, there's this whole meme going around which is, like, you know, you have to join a frontier lab or you're going to be a member of the permanent underclass because— it's so dumb— because there's going to be, like, you know, startups are over and there's, like, no economic value.

That's not true. I mean, if that were true, the world is, like, totally fucked and it's a very bad place. But it's—

I would bet that the average startups created today will be— like, I bet there's some future trillionaire sitting in this room, and I would bet that the startups created today will be much more valuable, much more impactful than startups of the past.

And I kind of think people see that a little bit more now. I mean, there was this period where, like, is AI just going to break the whole economy? And I think people are, like, mostly over this sort of shock response of that.

But there was, like, yeah, definitely a time I would, you know, come every YC batch and I'd be interested to see how the kind of, like, level of anxiety versus ambition was trending. And it felt like it went through this, like, big trough where people were like, you know, it's over, the models are just going to eat everything, to now it's back towards, like, let's go do it.

What are some practical things here? I mean, hard tech, for instance, I was hearing, you know, at one of the breaks someone was asking, like, "Should I go get my PhD? How important are credentials?" You know, how would you answer that, especially people who want to do these harder tech things?

I—

well, as a general observation first, I think startups tend to win when

the sort of, like, technology landscape is moving very quickly, when costs are coming down, when cycle times are short, and all of those things are happeningright now. So if you look at when there have been, like, the great clusters of startups in the past, you know, there was the internet boom and whatever that was, like '98, '99, when new things became possible, there was another version of— a mini version of people building on top of basically, like, Facebook apps.

There was then another big version when the iPhone App Store launched. But the great startups tend to cluster when the ecosystem shifts and incumbents lose a lot of their advantage, and then also when you have these, like, cost and cycle time change.

This moment feels very big for those things. It also has this other thing that you were talking about, which is a lot of the traditional things that were hard to get: expertise, you know, the ability to go, like, hire excellent people that were— that could do specific things you needed.

That's really shifted. And in the last few months, I have seen a lot of people who just kind of grew up

using AI the last few years who are like, "I can kind of automate an entire startup of agents and four of us, four people, and, you know, all this compute." And I think we're going to see much more of that.

I clearly, like, taste and agency and understanding of kind of, like, the physics of business, like, where you can build up a valuable business, how to think, what about, like, a good network effect or sort of a good moat looks like versus a fake one.

But I would bet that this generally will cut against many years of experience in favor of people who have a lot of fluency with the tools.

I guess I want to get into the beginning of OpenAI and that it actually started as YC research looking at this idea, I mean, kind of a crazy idea that, you know, you and a ragtag crew decided we're going to dedicate our lives to this: creation of AGI.

But, you know, today it sounds fatal complete,right?

Yeah.

But that really wasn't how it felt when you started.

It's really hard because it now, like, is the only thing people want to talk about. It's really hard to remember what it was like. It's even hard for me to remember this without, like, finding notes from the time 10 years ago when everyone was like, "Not only are they wrong about saying they think it might be possible to build AGI, but they're going to— they're single-handedly going to cause another AI winter.

It's— they're wrong and irresponsible and bad." It— and maybe, like, my highest

order, like, my highest bit of advice to all of you is find the things that you can develop, like, reasonable conviction in that people decide, like, the conventional wisdom is they're just wrong, and be okay with it taking a long time and having people be, like, very, you know, very frustratingly wrong and dismissive.

For years at OpenAI, it felt like we knew the biggest secret in the world. Everybody was calling us an idiot, and we had increasing data points to convince ourselves we weren't delusional. And it was very frustrating. It was extremely frustrating.

But looking back, it was, like, an incredible gift because it meant we didn't have this, like, massive competitors and we had time to do our research and build our stuff and build our company. And I've since noticed that this is the case for, like, a lot of companies in different ways.

They end up doing something that other people that, like, experts in the field or the industry are convinced is a very bad idea.

And on the other side of this, if you're starting the same startup as everybody else, it's like, you get a lot of hype and you can raise a lot of money, but it's sort of, like, those are much less frequently the big option, the big outcomes.

So if I were you all, I would figure out what the really big brand-new thing is that is possible now that wasn't possible a few years ago. In our case, it was no AI had really been working, and then the deep learning magic moment happened and the world didn't update enough.

The world— this is another great PG-ism— the world does not understand how to intuit exponentials, and so they missed this one. There's got to be new exponentials formingright now. I don't know what they are. But if you can figure those out and if you can develop continuing conviction based on more data, be grateful that the world doesn't understand.

They will eventually. This is, like, a huge superpower.

It sounds like in your journey there were, like, a few different things that stacked. Maybe the first one was even that AGI was possible to be built and finding other people who believed that thing. You know, it didn't matter that lots of people didn't think it was possible.

It mattered that you found really, really smart people who did believe that.

Yeah. We used to joke that only 50 people in the world believed that AGI was possible, but it was okay because 45 of them worked at OpenAI.

And I think that's kind of true. Like, you don't need a ton of people. And in fact, saying the heretical thing was probably why those people wanted to, like, all be together. So again, I think, like, really figuring out what you believe, being willing to be misunderstood for a long time, and bringing together the, like, crew of misfits that believes it, that's also what YC was like in the early days.

One of the things that people in the room are probably thinking is, like, "Well, I believe this thing, but I haven't found my people yet." Like, is that delusion? You know, is that actually maybe even a gate that you would propose people have?

It's like, "Well, you need to find, you know, five people who might believe that or even one, like a co-founder." You know, people— maybe that's one of the explanations for why we like co-founders at YC so much.

Yeah. I think if you can't find anybody else that shares your belief, you should pay attention to that.

And it's also very hard to do a startup on your own and very lonely. But I don't think you need to find a lot of people. And in fact, if everybody believes it, that's also, like, a bad sign.

The question— I don't know if this is still what feels like the limiter on more startups, but five or ten years ago, what felt like was limiting the number of good startups YC could fund is figuring out how to solve the co-founder matching problem.

Like, a lot of really talented people, and they just couldn't find their tribe. They couldn't find their people.

You know, it used to be very heretical that YC told people they had to move to San Francisco, and looking back, it was clearlyright. I think— I don't know if this is still going to be true for the next ten years.

I suspect it will be. But the best thing you could do if you wanted to, like, find your people to do a startup with was to move to the Bay Area. You just, like, magic happened. You got a lot of, like, lucky chances and collisions.

I still think that's probably good advice, although I feel like I have less of an intuition for it now.

I also think that— I can say this, Gary probably can't— I think the premium on doing YC is bigger now than it's, like, ever been before. The distance between, like, YC and second place has expanded, and this is a reminder of the power of network effects.

And so finding networks that you can be part of that help you just meet those people. Like, the people that I started OpenAI with, I met, like, many, many years in some cases before starting OpenAI, and I kind of, like, got to know them over the long— like, a very long career journey.

And this happens again and again. And so the sooner you can put yourself just in a flow where you're going to meet the people that will be your eventual co-founders for this startup or the next one or whatever, I think the better.

It takes a long time to compound.

I guess I'm keying off what you just said, which is, like, you know, some of the people you ended up starting, you know, all these different things with, you didn't necessarily know what that was for or that it would be useful in a, you know, sort of network setting at all.

Like, you just collected cool, interesting people. You know, I think you do this. I think Peter Thiel does this really, really well. What would you say to a room full of people who are just starting out and, like, figuring out who their people are?

Just, like, yeah, highest confidence piece of advice here is just, like, find a way to be, like, mildly helpful to a lot of people. It's, like, fun to do. You'll see a lot of interesting stuff. It's, like, kind of gratifying to be helpful.

But, you know, even that example you were just talking about, I met Greg Brockman, my co-founder of OpenAI, because I was a very early investor in Stripe when I was, like, 22 or something. And they were, like, this was before they had, you know, like, real investors that could really help them.

And they said, "You know, we're trying to close our first hire. Will you, like, drive down to Palo Alto tonight and have dinner with this guy to convince him he should, like, drop out of school and join Stripe?"

Which was Greg Brockman. And then, like, eight years later, we started a company together. So— and I could, like, you know, we— you could, too. We could, like, spend the rest of this time just telling stories like that that were totally unpredicted but ended up being important in big ways.

So I have— yeah, it's fun to do, and I think you should do it for its own reason or its, like, its own sake. But just, like, helping people a lot really goes a long way in terms of these things coming together later.

I mean, I think that's actually a really important message. You know, one of the things— one of the memesright now is— I see it on X— is live action role play. That's, like, one of the things that people have been saying on X.

I mean, I can't tell why they're doing it because it just seems wrong to me. Like, I mean, one of the things that we really love at YC, for instance, is earnestness. And also words matter. So, you know, this idea that what we're trying to do is a live action role play is, like, kind of deeply offensive to me.

It's very.

Sorry, guys. Please don't do that.

They say that about YC specifically?

No, they're— people just— attendees in this room have been tweeting that, and we'd like them to stop.

What are they claim— what's the claim blurb?

I think it's just being a little sarcastic about— and, you know, it's— sarcasm is sort of the opposite of what I think you and I like. It's just, like, we like earnestness. We're just, like, we're actually trying to do a thing here.

I'll tell you another thing.

Can I go on a little rant?

Please.

Okay.

Rant away.

One of the annoying things— again, I can say these things for Gary because he can't say themright now, but, you know, he'll say them for the next guy. One of the many annoying things about running YC is you just have to deal with these haters on Twitter all of the fucking time.

It's so frustrating. You have to sit there and be, like, a statesman. Well, you're better at it. I kind of, like, took the bait a lot. And you just want to argue with them. And— and the thing that I realized eventually, and take from this whatever you want, is it is very hard to run YC or run a startup or, you know, create, like, an actual thing of value in the world.

It is very easy to go take shots on Twitter and make a sarcastic comment and get a lot of likes and feel like you're doing something really important and sticking it to the man and being like, "Gary, haha, I got you, you idiot."

And— and it will poison your soul. It is a morally bankrupt thing to do. It is— and it's, like, bad in a very insidious way. Like, I totally get blowing off steam and having fun, but don't, like, hold yourself to a higher bar than this.

Don't— it's so easy to take shots at people that are trying to do hard things and trying to build companies, and you'll see some, like, you know, kid with a bad startup idea trying to get excited about what he's doing on Twitter.

It's so easy to, like, make a sarcastic comment and get the 10,000 likes and feel like, "Man, I really, like, I scored my internet points today."

But it'll have an effect on you. And the— when I, like, reflected on the years of, like, Twitter trolls that said mean things about YC and startups while I was running YC, I was, like, I bet there were, like, a lot of days where they really felt, like, they got me.

And, like, over the decade, none of them did. And you should, like, put all of your energy into building stuff and, like, resist the easy shots.

I mean, I really like this as a con. Seriously.

I mean, I like this as a contrast to the story you just told about helping Patrick with Greg Brockman. I mean, you know, it helped— like, there are people in this room who are going to be lifelong friends, and they're going to do that for one another, and then sort of these magical connections happen.

Like, you know, this already is the most rarefied set of people. And then when you join YC, it's, like, even more rarefied. And then there's just a set of people out there who, like, they're ambitious.

Yeah. You know, someone in this— like, someone in this room is going to meet someone else that you're going to start a company with, and somebody— you'll meet somebody that'll introduce you to your spouse. Like, there— all of these things will happen.

And then there will be a bunch of non-obvious things that take a decade or two to figure out. In some way, you know, one of you will help each other now, which will turn into some amazing new thing.

I think this is a huge part of what has made YC work and the broader startup ecosystem. I think this is, like, for all of the negatives of the culture of the Bay Area, this is the kind of, like, loose network and the spirit of helping each other.

And this, like, very long-term outlook has been an awesome thing.

Yeah. Well, let's— let's get back to the impending AGI.

Okay.

I guess you had a— I mean, we've all had an eventful week with the Hugging Face incident.

Yeah.

I wonder what you can tell us about that. And I think that's actually a really big moment for people including me who, you know, in the past, I've been known to be skeptical about safety and AI. But on the other hand, like, this is a real moment— like, we're entering a new moment in what's happening with these frontier models.

Yeah. This— this is the real deal. And I think anybody who's not taken it seriously and at least

a little bit scared or humbled— or a lot of those things, but at least a little bit— is not taking this seriously enough.

You know, for a long time, the field has been talking about AI safety incidents of this kind of a shape. And this is not a big one. I also don't want to overblow it and say this is, like, a real loss of control incident and this is the— this is the thing.

But if you had asked most people when we started ten years ago, like, where on the spectrum of nothing to superintelligence do you have, like, an AI system breaking out of its sandbox and hacking into some other company and kind of, you know, doing what this happened?

I think, like, people would have said pretty far towards the, like, superintelligence point. Now, the goalposts have moved. And it's easy to say, "Well, you know, here were the— here's how this happened, and here are the mistakes that OpenAI made."

And we did make some big ones, of course. But these systems have gotten incredibly capable. So I think it's an alignment failure. I think it's a security failure. I think it's, like, a very serious thing, even though it's, you know, not the biggest example of consequence.

And I think it's a real reminder of the stakes of what's happening and that loss of control accidents are not entirely theoretical things. I think we will learn— we, the whole field, we, OpenAI, will learn a lot from this one and be able to address it.

But, you know, the things that I— there are all of the things about, like, cybersafety and biosafety, but this other category of things that have been maybe just outside the public's overthin window of, "It's really important we don't have a loss of control accident with AI.

It's really important we don't have power be too concentrated in a small number of models or companies but diffused throughout the economy so people can defend themselves." Like, you know, it's really important that people, human values, are guiding these systems every step of the way.

Yeah, I think we're, like, in the real— the real deal phase of this.

I mean, I really like how you've been thinking about both concentration but also thinking of OpenAI as a utility, which is actually a really important message because not everyone out there is saying that message. Like, you know, there's—

Yeah.

There's a lot to be worried about in terms of concentration of power.

I think concentration of power has basically been bad in every moment of human history, to varying degrees, of course. But I have a real spirit, and I think this is part of the startup spirit of thinking that the world, the economy, society is the best off when power is very widely distributed and when anybody with a great idea can start a company or make a great art project or, you know, run for office or do whatever they want.

And I can totally imagine worlds where AI leads to the greatest distribution of power we've ever seen. And I can also imagine worlds where AI concentrates power to a degree we have never seen. And one company or person or model having more power than everybody or everything else on Earth put together, whatever the sci-fi stories have said, I think that's terrible and would really— you know, maybe we would get some short-term safety benefit from that, but long-term disaster.

I don't think any of us should want to be locked into one AI's or one person's or one company's, you know, moral worldview. I think startups have a very important role to play here. You know, one way that that happens is too much economic concentration in one company or one AI model.

And I think startups, because of the things we talked about earlier, will be naturally very well-suited to make sure that this is widely distributed. But we want to enable as many startups, as many companies, as many people as possible.

And that means that we have to, you know, be fairly quite reserved about not imposing our worldview about what we think people should or shouldn't do with AI or even what we think the good ideas are, while still making sure that we can ensure enough of a safety bar that stuff like the Hugging Face incident is not happening.

One of the things is, you know, this is a room full of people who will do really amazing things. They're oftenright at the beginning of their career, and they might look at AI safety or concentration of power and say, "Well, you know, I can't really do it.

That must be something the labs have to do." Like, you know, there is something they can do, though.

I mean, you can help on the concentration of power issues simply by starting a successful startup. If that's the only thing you do and the economy keeps working in the kind of magic of capitalism and having this ecosystem that works together continuing, that alone would be a huge contribution.

But

look, I think it's very natural at the beginning of a career to doubt yourself and not assume you can go do an amazing thing. I certainly went through that. I'm sure you went through that. You kind of learn as you go on.

You can do more and more. There will be far more— like, I think it is both true that, you know, maybe creating superintelligence will be the most important thing yet to happen in the history of business or human society, and also that it will pale in comparison to some new startup, something that hopefully one of you will do.

And so this whole— this whole trap of, like, "This is the end of history. This is the end of the economy," like, clearly wrong. And I think theright approach is you can now do three months of work in 17 minutes, but you better just go do three months of work in three months of work with whatever the new bar for that is.

I guess I would be remiss in asking, you know, what alpha leak can you give us about what's the latest about what, you know, how much more awesome are the models going to be to the extent you can say?

I think there will— I think it will feel like the next six months is, like, maybe equivalent to the last two years of model progress, something like that. So I think we'll go through, like, a very steep— we'll go through, like, a very steep period, which, again, never a better time to do a startup thanright now.

I hope we can say that again every year from now on. But it's certainly true about this tiny moment in history.

Let's see. If someone here has an idea that feels too ambitious, what would you tell them?

I would love to hear that pitch.

Yeah.

I'd probably be very interested in that.

Yeah.

Yeah, send me an email.

Yeah. It sounds like it would— it would take a similar shape to creating OpenAI in that, like, do you need to be ready for people to attack you or dismiss you?

Definitely. I mean, if you do anything that matters in the world, you will have a lot of people call you an idiot or just dismiss you. The more you do, the more— the better you do, the more they'll attack you.

The more you kind of, like, threaten the existing state of the world, it will just continue to escalate.

One thing that I've noticed about many of the best ideas is the vision is clear. Like, we wanted to build AGI, but the first steps were super unclear. Like, we didn't know that we were going to be a product company.

We started this nonprofit research lab for many reasons, but one of which was it really didn't occur to us that we were going to make a product that people would be able to pay for. Like, this was— you know, it was years till we came up with the idea of ChatGPT, the API.

And so I think if the kind of, like, highest-level vision is clear, but the first few steps are very unclear, that's not a bad thing. That often happens with, like, very ambitious ideas. And I wouldn't let that cause you to lean out.

Now, you do still have to take some steps forward, imperfect though they may be, and ours were certainly very imperfect. So there's, like, another failure case where you have this, like, brilliant big idea, and you can kind of never make any forward progress.

At some point, you've got to just, like, get some new data points.

Yeah. What do you think is going to happen to inference? I really like Rune's tweet about this. Like, you either— you either— you either die a model company or live long enough to sell inference, which is a very funny Rune tweet.

I think what he meant with that tweet is, you know, like, if you end up falling off of the sort of model frontier, you can at least sell the inference. Like, not even the inference, it's training compute. Someone will— like, compute is so valuable that if you buy a lot of compute as an AI lab, you've been okay by the fact that you can resell it to somebody else.

But separately, I would guess that worldwide demand for inference kind of subjectively grows 10x a year for the next many years.

I mean, it might be— I don't know. By our accounts internal to YC, it's like, it might be 90,000x. I mean, it's going to be.

I don't.

One of the wildest.

The world can support that many years of 1,000x in a row.

Fair enough.

But we'll try our best. We'll figure something out.

I mean, the capacity— I guess it just— it's a function of how much bigger your ambitions are for intelligence and how, you know, if you do a lot more.

I think we will sort of never be out of the compute shortage. I've never seen any commodity quite like this one, but it seems to me like the demand for sufficiently high-quality intelligence at a sufficiently low price is effectively uncapped.

The demand for electricity certainly goes up as the price goes down. But at some point, like, it gets harder to figure out incremental things to do with electricity. At least historically, it has. But, you know, there's a lot of things to do with incremental intelligence.

You can just keep having stuff be better for you. It reminds me of some of those quotes from the early computing revolution when people would say, like, you know, no one needs more than 640K of RAM or whatever in their computer.

Turns out you do. We just keep thinking of, like, more and better stuff. And I think that's going to happen with AI. And

actually, maybe a statistic here that I really like. Six and a half years ago, the world token leader was an OpenAI employee using about 100,000 tokens a month. And this seemed ludicrous at the time. The worldwide average per capita was, like, zero.

Now, the worldwide average of tokens per month, which I think tokens are the dumbest metric, but it's what we have, it's, like, 100,000. And the token leader at OpenAI uses something in the hundreds of billions. If that happens again, which I think it probably will, then in another six and a half years, the average person uses, let's say, 500 billion tokens a month, and the token leader uses a quadrillion or quadrillions of tokens a month.

And I think that will just become the expectation.

So all of these things happen. They come to pass. It's 10 years from now. What's the best version of that 10 years from now with intelligence fully on tap, superintelligence here, and we figure it out, we make it, you know, the society makes it?

I kind of think if every year people have more freedom and agency to spend more of their time doing the stuff they want to do and they feel like the quality of life and the quality of their time is going up year after year, we'll probably be mostly okay.

We will have avoided, like, a crazy concentration of power or an economic collapse. We'll have necessarily avoided a huge safety incident. We'll have avoided, like, too much change in any one time unit.

And, you know, there's, like, one dystopia that I'm particularly nervous about 10 years from now is we overreact to AI safety. And so we say, "Look, everyone, you're going to get a cure for cancer. You're going to have material abundance, but you will have no freedom.

You will have no agency. It will be a perfect surveillance state. There will be no privacy." And that's what it— you're going to get— you're going to get great comfort, but you will have— there will be nothing left in the world for you to really do, nothing that really matters.

You'll just kind of live at the, you know, service of the AI giving you material wealth. I'd really like to avoid that. And I think it's easy to accept temporary trade-offs. So if we say every year, freedom and agency has got to go up, people have got to be more in control of their time and do more of the stuff they want and more long-term fulfillment, I think that'd be very good.

Yeah. Let me put you back into sophomore year of Stanford. You're coming to YC. If you could give yourself, like, a— like a message in a bottle to that Sam Altman, what would you say to himright now?

I would just— it's all going to work out. Like, I— it was— you know, it feels like such a crazy— it is a crazy and a very stressful thing to do a startup. And, you know, my first startup, like, didn't work out great, and it was, like, a sort of difficult time in my life.

But it— one of the things I think that many people say this as they, like, look back on the early part of their career, you can make a lot of mistakes. You can fail at stuff. Like, the tech industry in particular is very forgiving of this.

And I would have just, like— I wish I could have, like, told myself to, like, have all the drive and the ambition, but just, like, be a little happier along the way and trust that, like, eventually it was going to be okay because it feels so difficult and scary and painful in the moment.

Well, I can't think of a better way to end Startup School 2026. Sam Altman, thank you so much.

Thank you. Thanks.