Sam Altman's Top 10 Rules for Success

Most people don't take enough risk, especially early in your career. Being young and unknown and poor, that is actually a great gift in terms of the amount of risk you can take.

Sam Altman is the CEO of OpenAI, former president of Y Combinator, and a prolific tech investor behind stakes in companies like Reddit, Stripe, and Helion Energy. He went from teaching himself to code on a used Macintosh and being a college dropout living off ramen noodles in a cramped apartment while struggling to launch his first startup, Looped.

Joining us now is Looped founder and CEO Sam Altman, whose Apple The application was one of the first to be designed for the iPhone.

I also feel like I kind of like was wasting my time, for lack of a better phrase, working on Looped. I don't— I definitely don't regret it. It's like all part of the tapestry of life, and I learned a ton.

To leading one of the most groundbreaking AI organizations in the world and amassing a net worth estimated at over $3.3 billion.

This is the best time ever in the history of technology, ever, period.

To start a company.

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Watch a top ten with Believe Nation.

If you've been here before, drop a hashtag believe in the comments below so I can feature you here in a future video. And if you're new, welcome to Believe Nation, the only channel that helps you believe in yourself daily, one video at a time. Okay, let's kick it off with rule number one: practice.

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 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 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 great pain and cost and unforced errors. You definitely will, if you end up in a high-stress impactful job, you will definitely learn how to deal with chaos and function very well through it, or at least most people will. But I don't think it's teachable. I think it's only learnable.

Rule number 2, react with an abundance of caution.

You have these small things that you can point to in our RL process or alignment concerns combined with what we can see coming down the road of these amazingly capable new pre-trained models. And it's really that intersection that made us wanna react with an abundance of caution. Now, I don't wanna overstate this either. I don't think this is like, you know, we're in this extremely critical potential catastrophe point. But I also think that as the stakes get higher, as the models get more capable, because of what our mission is and because of how important it is that safety outweigh all the other, you know, Pressures we have, we wanted to react with an abundance of caution. And I think that's the right thing to do. I think it's good that we're doing that. I think it is a good time to slow down and make sure we can have new safety cases that justify the runs we wanna make. I think that previously more of the risk in the world was on how the models were deployed and used. We are moving to a world where there's more risk during the actual training and production of the models, and it's good to react. But I don't wanna like overdramatize it either.

Rule number 3, learn from the bad experiences.

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 is no experience, And at some point in the not distant future, you'll be in no experience land, then you can be grateful for the bad experience too. Naval Ravikant used to say this thing that I loved, which is, if you had a fast forward button on a remote for your life, your life would be over. And so the boring parts, the bad parts, it's much better than no experience. It's all part of the interestingness of And the kind of emotional depth and range. And I don't know, I find it fairly easy to be grateful for the bad days.

Rule number 4, make bold decisions.

I think you can look at our actions and what we've said and what we've done, and we have a track record now for a long time, and we've done a lot of unpopular things along the way. In fact, even the original thing of iterative deployment was widely panned by the AI safety community and said, we shouldn't tell the world about this. This is bad. We need to build this in the secret. too much knowledge for the world to have, and, you know, then we'll have some wise people figure out how to use it and give the fruits of this to humanity. That has never been our strategy, even when it's been very, very unpopular. My favorite historical analogy of a technology, what I aspire for us to be like, is the transistor. It was, it is an incredibly powerful technology for the world. It has delivered huge economic value, and not just economic, like the way we live our lives, I think is much better because the transistor was discovered and industrialized. But very little of the value accrued to the transistor companies. It mostly just diffused throughout the economy. The transistor companies did fine, and I think our track record has backed us up.

Also, if you want to take real action after this video, I made a free worksheet just for you. It covers the top lessons from this video, helps you build a simple action plan. It's 100% free. Just click the link in the description below to go grab it, and I'll see you there. Rule number 5, use the new opportunities.

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. I've heard a lot of people say, well, anything in the physical world is extra valuable right now because software is going to become free. But It won't be that long until robots get really good and a lot of the expectations of it's really difficult to make rockets or whatever, that may change 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 once right now. Yeah. 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 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.

Rule number 6, take responsibility.

You can understand how every piece of it happened, but the number of things that came together for the Hugging Face incident to happen was a real— wake-up call is too strong of a word because again, we had talked about this, but it was like that and the things that happened at other companies were a legitimate moment of like, wow, the AI capability level has reached new heights. And our alignment of the alignment of the model, the security we have around the model that failed. Now we treated that as an accident, and we've responded as such. And I think that is the way to make things better. But that was that was when this whole period of these last couple of months started. We then potentially hit cyber critical under our preparedness framework. We then saw some things during an RL training run where we said, well, you know, we need. stronger alignment guarantees and we need new methods and to make more progress here. But I feel both very proud of how we've reacted to it, very like, okay, we're in this in a way that feels like kind of, I mean, it feels strange to have been thinking about this for the last decade and for it now to be happening. And then like, you know, we know what to do.

Rule number 7, embrace uncertainty.

I think it's Very hard to predict exactly how something evolves or predict exactly what the jobs of the future are going to be. Not that long ago, it would've been very hard to predict either of our jobs. If you go back 100 years, the idea of this CEO of an AI company or a podcaster probably would've been things that didn't seem to be the most obvious evolutions of the things people were Doing at the time.

Yeah, you just seemed almost probably crazy even in trying to explain those to someone.

You would. And now, in fact, 2 of the jobs— I heard that the job that young people most want is some version of your job. The job that young people most want is to be a podcast influencer, YouTube. They want a YouTube channel, like whatever it is. They, like, 6, 7-year-olds, they don't know how to describe it, but that's what they want. And a lot of people also want my job. They want to do like a startup or they want to work on AI. And these just didn't exist.

Yeah.

So, like, the rate with which the new things come along is fast, and also trying to predict what they are, I don't know. The thing I say all the time is no one knows what happens next. It's like, we're gonna figure this out. It's this weird emergent thing. Does the current job of a historian exist in the same way? I'll bet not quite. But another thing I believe is that humans are obsessed with other people. Like, we are so deeply wired to care about other people, to care about stories, And history, our own history, is extremely interesting to us. So I would say somehow or other, we're still going to care about that. There's going to be some kind of job doing that.

Rule number 8, invest long-term.

I think the number one advantage that you can have as an investor is to have a longer time horizon than everybody else and be willing to expose yourself to more illiquidity and more volatility than everybody else. So, you know, if I invest in something and my kids get the shares, I'm perfectly fine with that. I don't think enough people do enough of that.

I think we should still be investing in things that might take 100 years. Rule number 9, don't follow the investor crowd. The number one mistake was that I cared too much about what other investors thought. And the sooner you can free yourself of this, the better. I think this is a very common mistake that people

make when they start investing. You get very swayed by what previously successful investors think. The first question that most people ask YC startups is, who else is investing in your round? People totally outsource, I would say 80% of investors outsource 80% of their decision-making to what other people think about an investment opportunity. But the problem is everyone does that. And so there's this weird schooling effect where a company gets hot for no discernible reason or it fits a trend or whatever. And then everybody wants to invest in one company. And it's just because a few people decided they liked it.

So the number one mistake I made was to be too swayed by what other investors thought good and bad about a company.

And rule number 10, the last one before a very special bonus clip, is help others.

How do you advise people to select sort of who they're working on things with?

This is really hard. Finding your tribe, finding the sort of people that you end up working with on and off for the rest of your career is really hard. I think I'll tell you some things I've learned, and I will admit that I don't have a perfect answer to this yet, but I think one thing is you should be willing to move. For whatever you're doing, there tend to be pockets of it around the world where there are similar people that are doing great work in whatever field you care about, and it's really worth trying to go be near them. And so, you know, we get criticized sometimes at YC for having people move to the Bay Area, but bringing people together that are interested in this similar thing of startups, I think, has been really valuable for a lot of people. I think another thing that I have learned is that whenever I've helped people for no immediate benefit, and with no intention of ever getting a benefit at all, time and again in my career, it has really later benefited me a lot. So I think you at some point often get to a point in your career where you're limited by how many good people you know, and how many of those you can

work with or get to do things together. And so just helping a lot of people and spending a lot of time with a lot of people has benefited me, you know, years after I've really helped someone for no reason, I get to invest in their startup and it goes on to be this huge success. Or we're able to work on OpenAI together, any number of things. I think just trying to help a lot of people and out of that seeing who is really impressive and who gets things done is helpful.

Focusing more specifically on productivity, what are some life hacks that maybe you apply to make your everyday more productive?

I mean, I think there's a lot of crap written about productivity secrets on the internet and people sort of get into this thing where they spend more time trying to be productive about their productivity system than actually getting things done. I will say, I think that— well, I'll say 2 pieces of advice that aren't that obvious. One is, I think far more important than any particular system, is just figuring out the right things to work on. And so all of the time that people spend with this new productivity app or that or whatever, would be better spent really trying to think diligently about, I have the same number of hours as anybody else, what am I going to spend them on?

And getting that right is more important than exactly being perfectly productive with those hours. A big part of that is not doing things that waste time. I think if you can just focus on the things that are important and not do the things that waste time, you can be fairly sloppy with productivity otherwise, and you will still get the far more done than most people. It's really hard to do, though. The other thing that I think people don't think about enough is figuring out your own personal rhythms of productivity. And there's huge variance, I've noticed, between people that figure this out and don't. So for me personally, it turns

out that I am most productive if I go to sleep late, wake up late, and then keep the first 3 or 4 hours of the day and don't schedule any meetings, work from home, get through my list of stuff then, and then pack all my

meetings when I'm kind of less productive at just grinding stuff out or thinking creatively in the afternoon. And it took me some number of years to figure that out, because it didn't fit well with the work schedule I was naturally in, but then I was like, all right, if this is the thing that makes me most productive, then I'm going to make my whole schedule work to support that. support that. And that was like a really important change for me. So I think figuring out your own personal, like, optimal times to work on what kind of different things— people don't really talk about that much, and at least for me, it had a huge impact.

And congratulations, you're one video closer to who you're meant to be. To learn how Sam Altman thinks about AI, startups, and success, Check the video right there next to me. I think you'll love it. Continue to believe, and I'll see you there. Sam Altman is the CEO of OpenAI and one of the leading figures shaping the future of artificial intelligence. He went from building startups as a young founder and leading Y Combinator in Silicon Valley to overseeing the development.