20VC: OpenAI's Sam Altman and Brad Lightcap on The Future of Foundation Models: Will They Be Commoditised | How to Solve the Problem of Compute | Open vs Closed: Which Dominates and Why | Which Companies and Verticals Will Be Steamrolled by OpenAI

Sam Altman is the CEO @ OpenAI, the company on a mission is to ensure that artificial general intelligence benefits all of humanity. OpenAI is one of the fastest-scaling companies in history with a valuation of $90BN and $2BN+ in revenue. Prior to OpenAI, Sam was the President and CEO @ Y Combinator and made angel investments in the likes of Airbnb, Stripe, Reddit, Pinterest, Asana and more. Brad Lightcap is the COO @ OpenAI and the man responsible for the incredible scaling of sales, GTM, partnerships and business to today being over $2BN in revenue. Before OpenAI, Brad was an investor at Y Combinator, where he met Sam and before that led finance and operations initiatives at Dropbox. In Today's Episode with Sam Altman and Brad Lightcap We Discuss: 1. The Partnership: The Most Powerful Double Act in Tech: How did 25 people rejecting OpenAI's CFO positions 6 years ago, lead to Brad joining OpenAI before Sam even did? What did he see that the world did not? What does Brad think is Sam's biggest superpower that the world does not know? What does Sam think it Brad's biggest superpower that the world does not now? How do decisions get made between Brad and Sam? How do they decide what to delegate vs what not to? What is the most recent disagreement they had? How did they resolve it? 2. The Next 12 Months for OpenAI: Bottlenecks, Compute and Commoditisation: What are the core bottlenecks facing OpenAI in the next 12 months? How does Sam believe we solve the fundamental problem of compute? What is the single biggest barrier to the quality of models improving? What is the end state for the model landscape? Will models become commoditised? 3. OpenAI: The Fastest Scaling Company in History: What has been the secret to how OpenAI has scaled to $2BN in revenue in 24 months? Why does Sam believe that he is "not a great operator"? What drives this thinking? What have been the first things to break in the scaling of OpenAI? What do Brad and Sam know now about the scaling that they wish they had known at the start? Why does OpenAI lean towards hiring more experienced people in the team? 4. How to Invest and Operate in a World of OpenAI: What single question can founders ask that will reveal if they will be steamrolled by OpenAI? Does Sam believe huge numbers of companies will be steamrolled by OpenAI? For investors, is there money to be made investing in the application layer of AI today? What question should all businesses be asking about how to adopt and use AI in their business? 5. Sam Altman: AMA: What have been the single biggest lessons Sam has learned from the founders he has invested in? Which founders has he learned the most from? What did he learn from each? What is Sam most concerned about in the world today? Why what? What unexpected traits or characteristics does Sam most look for in the founders he invests in? Why does Sam say that he is not happy but he is grateful?

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  There are two strategies to build on AI right now. There's one strategy, which is assume the model is not going to get better. And then you kind of like build all these little things on top of it. There's another strategy, which is build assuming that OpenAI is going to stay on its same rate of trajectory. And the models are going to keep getting better at the same pace. It would seem to me that 95% of the world should be betting on the latter category. But a lot of the startups have been built in the former category. When we just do our fundamental job, we're gonna steamroll you.

• 0:28Harry Stebbings?

  This is it. This is the show with Sam Altman and Brad Lightcap, CEO and COO at OpenAI, one of the fastest scaling companies in history, now with a valuation of $90 billion and revenues of over $2 billion. They are the company on a mission to ensure that artificial general intelligence benefits all of humanity. One of the most impactful companies of our generation. And I'm honestly just so proud to release this show today. You can watch the full episode on YouTube by searching for 20VC. And we recorded this show in person in London last week, and so that video is incredible. But before we dive into the show today, we're all trying to grow our businesses here. So let's be real for a second. We all know that your website shouldn't be this static asset.

• 1:13Harry Stebbings?

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• 1:56Harry Stebbings?

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• 2:39Harry Stebbings?

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• 3:23Harry Stebbings?

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• 3:39Speaker 02

  You have now arrived at your destination.

• 3:42Harry Stebbings?

  Guys, I'm so excited for this. I've wanted to do this for a long time. Also, this is the first time that you've done an interview together.

• 3:48Speaker 00

  I think it is, yeah.

• 3:49Harry Stebbings?

  That's right. This is going to be the most unique interview then that you've done together, so this is very exciting. I want to start, I spoke to many mutual friends before, and they said, we've got to start with context. Sam, what gave you the conviction to do this seven years ago?

• 4:02Speaker 00

  I think there were two things that seemed, well, I've been interested in AI since I was a little kid, and I studied at a college when nothing was working. But when we started, there were two things that seemed really important. One, deep learning seemed to actually legitimately be working. And two, it got better with scale. We didn't know how predictably it got better with scale at the time, but it was clear that Like bigger was better. And that seemed like a remarkable set of things. And the confusing thing to us at the time was like, why does everybody else not see this? And why is everybody else not jumping on it? But they weren't, and so we wanted to do it.

• 4:32Harry Stebbings?

  Can I ask, when there were those moments of doubt from everyone else, which there were across those years, what gave you the conviction to stick at it when very few others had that same confidence?

• 4:42Speaker 00

  It just seemed to us like it was gonna work. And we kept making progress. I would not call it blind faith, although there is some amount of you just, you gotta believe you can do a hard thing. But it felt really important to us to do this, that if we could do it, it would be hugely meaningful to the world in some way. And that it might work. Like, we had an attack vector we believed in. And then we had continued data that the approach was working. Of course, the specifics took a long time to figure out. You know, we did not start off doing language models, obviously. But we kind of knew that if we could keep doing things that we previously thought were impossible, that was somehow a good sign for progress. And we had this fundamental conviction on the approach and the attack vector at a very high level for a very long time. And the details took a long time to work out

• 5:27Speaker 00

  and many brilliant discoveries by our colleagues. But there was never any doubt that AI would be a big deal if we could do it. So that's helpful, like, it's gonna be really valuable. The approach, we got successively more confident in, although it did take some wandering in the jungle for a while, or the desert, whatever that phrase is. And then, you know, it's like, if you believe something with high conviction and everybody else doubts it, it's like slightly motivating.

• 5:51Harry Stebbings?

  Yeah.

• 5:51Speaker 00

  It's definitely kind of annoying, but it's slightly motivating.

• 5:53Harry Stebbings?

  I mean, as a VC, that would be contrarian, which is not what we do, because we're sheep. But I do want to start on actually the relationship that we have here, because it is such a unique partnership. And again, we said this is the first time you've been interviewed together. How did the partnership come to be? Brad, why don't you tell me that?

• 6:09Speaker 00

  Sam and I have worked together a long time. And we spent a lot of time at YC looking at this batch of companies that were starting to hit the growth stage that were these really deeply technical projects, nuclear fusion reactors, quantum computers, self-driving cars, satellites, things like that. And I was kind of focused on those companies from an investment perspective. And OpenAI was kind of the first company

• 6:30Speaker 03

  I saw that I was like, you know what, like this one's kind of unique because it kind of just seems to be getting better over time. It's not this kind of binary risk. And I remember pointing that out to Sam and saying, I think there's something that's going to be different about this company as compared to some of the other companies that we were looking at at the time. And I ended up spending more time with Greg and Ilya. And the properties that Sam describes of these systems just getting better with scale at first kind of unpredictably, and then more predictably, I thought that was just so unique. And I think we kind of saw the same thing, maybe somewhat from different angles. I saw it mostly from an investment perspective of if that's true, this is going to be really important just as an investment outcome, just as something that's going to have real impact on the world. And so I really felt that kind of conviction early on, and I just wanted to help anybody I could.

• 7:11Harry Stebbings?

  Do you have that plan that you wanted to join full time? Like, when did that come into fruition that you wanted this to be your mission for the next multi-decade?

• 7:18Speaker 03

  It wasn't at first. I actually was mostly just trying to help Sam recruit a CFO.

• 7:22Speaker 00

  Brad actually worked at OpenAI full time before I did.

• 7:25Speaker 03

  That's true. I beat him there. First time I've beaten Sam on anything.

• 7:28Harry Stebbings?

  Just take it as a win.

• 7:29Speaker 03

  Yeah, exactly. But no, I was trying to help him recruit. And at the time, no one wanted the job. I asked probably 25 people if they would want to be CFO of OpenAI, which at the time was just a small, kind of sleepy nonprofit. And I went 0 for 25. And honest to God, the reason I'm here is because I was so embarrassed to come back 0 for 25 that I said, you know what, why don't I just help out nights and weekends? And that turned into full time very quickly.

• 7:52Harry Stebbings?

  I had no idea about that.

• 7:54Speaker 00

  Yeah, I was sort of doing like half my time on OpenAI, half on YC.

• 7:56Harry Stebbings?

  When did you go full time YC then, Sam?

• 7:58Speaker 00

  It was kind of like a gradual-ish process, but I think like by the spring or summer of 2019.

• 8:04Harry Stebbings?

  Okay, so Brad beat you to OpenAI. I think that great partnerships are about complementary skill sets.

• 8:10Speaker 00

  That's for sure.

• 8:11Harry Stebbings?

  And so I wanted to hear from each of you, like an all-star Mr. and Mrs. What is Brad amazing at that the world doesn't know?

• 8:19Speaker 00

  One sign of like a good partnership, and I'm thankful to have this with like a lot of the key people at OpenAI, certainly Brad is like, if you can't do each other's job, you know, maybe Brad could do my job for a week. I certainly cannot do Brad's job for a week. And I think that ability to divide up as a team. And have a very high bandwidth communication channel with each person and altogether as a leadership team is super important. Brad is good at a lot of things. One is adaptability. Brad joined to do finance, obviously, and now does something, I guess it's like in the sphere of finance, but very, very different. We didn't have a business at all, or we didn't have an appreciable business until very recently. And when it became clear that we were going to have a very fast growing

• 9:02Speaker 00

  business, kind of like looked around, it's like, we really need somebody. We gotta, we gotta get someone to do this. And I kind of like looked around the room and I asked Brad to do it. And it was, and he was just like, okay, I'll figure it out. You know, I might need like a little bit of time to get up to speed, but you know, I've done like business S-ish stuff before and can go like build all this out. So the willingness to just like take on new challenges at each level of company scale and figure it out as you're going, Brad is super great at. And then the other one is, well, I'm like financially illiterate, so all of that seems amazing to me.

• 9:33Speaker 00

  But, but to build out a new product category and go to market function around that takes a very wide array of skills and a great deal of patience and sort of like a customer obsession from a product to a business model to a how we're going to deal with customer support and everything else that goes around that. And Brad's ability to see the whole picture of that and how it comes together. So that we're here today at this enterprise sales event. I think if you had said a year ago, we're going to be like a great organization. Oh, not yet a great organization. We're going to even be a very good organization at doing, you know, an enterprise go to market function. I would have said very low chance that that's going to happen. And now we have a pretty good one.

• 10:14Harry Stebbings?

  If we flip the tables, though, what would you say is Sam's biggest strength that not many people consider or know?

• 10:20Speaker 00

  Some, some people know this, but I think.

• 10:22Harry Stebbings?

  You can say none, that's fine.

• 10:25Speaker 00

  I'll, I'll say two things. They're interrelated. One is, I think at any given point in a company's life, there's only like one to three things that really matter at that point. Those things change, but there, there's almost never 10 things that really matter. And I think Sam has an incredible ability to be.

• 10:42Speaker 03

  Laser focused on those one to three things. And that spills over into how we run the team. Because if I know what he's focused on, and we may disagree on what those things are. Oftentimes, I think we agree. Yeah. If we can at least align on what those things are, and they may not be the right global bets, but they are the ones that feel the right right at the time. Then it helps me to translate down to the teams that I'm building on. You know, whether it's to that we want to be more enterprise focused, or it's that we want to really actually change the bet we're making on research, or we actually want to bet more on one thing versus another, or we really need to get this thing right. It helps to keep us moving very fast. And I think that's kind of the key to to kind of maintain velocity at scale

• 11:26Speaker 03

  that most companies start to lose inherently is the number of things. And what the perceived number of important things are goes up. And the second thing I'll say is just a long, like a very like long term future orientation. And you kind of have this like idea that you're running at this thing that's like really far out there. The process of just defining what those one to three things are, by the way, that's most important is really just a function of trying to figure out what the one to three things are that are the fastest accelerants to get us to that point. And Sam's has this like maniacal focus on that future world. My job is just to fill in everything in between.

• 11:59Harry Stebbings?

  What are the one or two things that you think are most important to you now then?

• 12:02Speaker 03

  There are a lot of AI orgs in the world that can copy what other people do. Like, once you know something is possible, once you kind of know the rest of it, once you know that people want it, that's not so hard. It's really hard to figure out how to do something new for the first time. And to do that consistently over years, and hopefully if we're lucky enough over decades. Building a research org and a product org and a whole company that puts these things out in the world, because we also innovate on business models and anything else. This culture of repeated innovation, so that we're not just making GPT five amazingly great, but six, seven, eight, whatever we're going to call those, we won't keep numbering them like that at that point. What making sure that we're set up to do that from a thinking about where the researches can take us,

• 12:45Speaker 03

  what that means for where the product's got to go, what that means where the whole company has to follow. That's a big one.

• 12:50Harry Stebbings?

  What are the biggest things that would prevent or slow down the velocity of OpenAI's decision-making innovation?

• 12:57Speaker 00

  I think we have the best researchers and best research culture that I'm aware of in the world. If we lost either of those things, that would be really bad. Not having enough compute resources would be really bad. We love doing cool research because scientific advancement is like the coolest, most exciting thing in the world. But really, we're here to like do useful stuff for other people. And if we do the best research in the world and then we make it as efficient as we can, but we still don't have enough compute to provide it to everybody on earth who wants to use it and is going to want to use it so much more as these models get way better, that would get in the way. That'd be really bad. So the second thing I was going to say for priorities is think about how we get enough compute to fulfill the demand of people who want to use these.

• 13:34Harry Stebbings?

  How do you think about answering that? I know it's the holy grail question.

• 13:37Speaker 00

  That one I probably won't answer in front of a camera, but I am optimistic. By treating that as a whole system problem, I am optimistic we will really surprise the world on the outside.

• 13:49Harry Stebbings?

  Can I ask on the decision-making? How do you guys make decisions between the two of you? How do you determine what to delegate versus what not to?

• 13:55Speaker 00

  I think it comes back to just being really aligned on what is most important. And you'll probably just hear me repeat that phrase, but things that are kind of specific to or even tangential to the most important things, we really spend a lot of time on as an executive team, as a leadership team, trying to make the right decision around. Sometimes it's obvious, sometimes it's not. Everything else gets delegated. So I probably make 10 decisions a day that don't go to Sam because they're not the most important thing. But we will spend an entire executive team meeting on one thing and then we'll spend the next meeting on that one thing if it's really the most important thing.

• 14:25Harry Stebbings?

  Do you agree with the saying that it's like one or two decisions a year define a company? Or do you agree with the you make 10 decisions a day and actually it's all about the incremental little decisions that add up to the progress of the company? I'm always stuck between both mindsets.

• 14:40Speaker 00

  One of the things that I loved about being an investor was that job is really a job about one or two decisions a year or maybe one or two decisions a decade. And an operator role is definitely not my natural, this is not my natural place in the world, by the way, but in an effort to get slightly better at it, one of the things I have learned is that it is true that there are only A handful of strategic decisions feels more like one or two a month than one or two a year, but it's not like that many like big like here is the here is the what decisions, but the like the how decisions, there are a lot of those. And I think people who claim there are not a lot of those have not tried to run a complex company before because it would be ridiculous to say that any CEO makes one or two decisions a year or a month.

• 15:22Speaker 00

  It is really nonstop. But there's a difference between like the big like we're going to do chat GPT or we're not going to do chat GPT. And then the like to make that successful along the way in the spirit of making that one decision, a successful one, here are the 10,000 little things you have to do along the way.

• 15:39Harry Stebbings?

  Why do you think you're not an operator?

• 15:40Speaker 00

  I mean, I'm manifestly not. I was very happy. Well, I had a lot of fun being an investor. It was not a fulfilling job for me, but it's a very fun one. All of the like things that people say to make fun of investors are somewhat true, like for a quality of life job, it's a great, great trade off. But yeah, with no false humility, I'm just not an operator by nature. I'm happy to do it because I like really love OpenAI and I think AGI will be the most important thing I ever touch, but this is not my natural fit. Brad would agree, I'm sure.

• 16:09Harry Stebbings?

  I would agree. Yeah, I would definitely agree. That's all my like decline to comment. No comment on that one. Can I ask, we mentioned kind of the compute element. In terms of like marginal cost versus marginal revenue, how do we think about when like marginal revenue exceeds marginal cost? I think that's one that a lot of people suggested that we talk about today, especially with other land-based products, obviously. How do we think about that? And that could be on both sides.

• 16:32Speaker 00

  I mean, truly, I think of all the things we could talk about, that is the most boring. No offense, that's the most boring question I could imagine. We will-

• 16:38Harry Stebbings?

  Really? Why is that boring?

• 16:39Speaker 00

  All you have to believe is that the price of compute will continue to fall and the value of AI as the models get better and better will go up and up. And like the equation works out really easily. There's ways it can go wrong. Like if the price of compute, if we don't make enough compute in the world and the supply demand thing gets out of balance and we choose for compute or- By a factor of bad planning, we cause compute to be really expensive. Then sure, maybe that's the way it goes. But I think we can drive the cost of a very high quality of intelligence to very near zero. And that will just be phenomenal for most things in the world. Not everything, there will be some negatives, but I think the cost of intelligence is about to get really, really cheap. How does open source and the rise of open source further enable that or impact that?

• 17:24Speaker 00

  There will be a place for open source models in the world. Some people want them, some people will want managed services, some people, a lot of people will use both. I kind of think all of these are details that are quite interesting in some sense, but miss the bigger picture, which is we are in the midst of a legitimate and pretty big technological revolution, where intelligence is going from this very limited thing, which is, you know, smart humans have it. But if you want to do something that requires a lot of intelligence, you've got to get a lot of smart people to do something. Like if you want to make a thing like OpenAI, you need a ton of smart people, a ton. If you think about everything in the stack, not just people who work at OpenAI, but the people who make chips and build data centers and all of that,

• 18:06Speaker 00

  to something where one person will be able to access abundant and very inexpensive intelligence to do just amazing things. Do you think we overestimate adoption in a year and underestimate it in 10? I mean, probably because I think that's like actually a very deep insight on the way that technology gets adopted in general. Because no matter how amazing something is, societal inertia is just a big deal. And, you know, you only ever get a lot of adoption for something amazing, but also it takes a while to get going. And so that's, I think you do for something cool, you get the one year, 10 year thing. So probably.

• 18:41Speaker 03

  I think we'll have a very fast inversion of expectation and reality. I think right now, expectations are extremely high. Reality is still pretty bad, honestly. These models are not that good. I think very quickly, expectations will start to come down as people come into contact with today's models. But then very quickly also, these models will get really, really good. And you'll see this inversion of expectations, reality, where all of a sudden then expectations have to catch up.

• 19:03Speaker 00

  I think the spirit of my, that's the most boring question came across very mean spirit and not what I meant. I meant it is just like, this is gonna be fine.

• 19:09Harry Stebbings?

  No, no, I'm now incredibly nervous to ask any question. Brad, you're the inti-

• 19:13Speaker 00

  I'll give you a nice answer.

• 19:15Harry Stebbings?

  Sam, you know what?

• 19:15Speaker 00

  Please edit that part out, I'm sorry.

• 19:17Harry Stebbings?

  No, no, listen, I think it's interesting though that you thought that.

• 19:20Speaker 00

  It seems, it seems like it's gonna be, that's gonna be such a mega non-issue.

• 19:24Harry Stebbings?

  But that's interesting.

• 19:24Speaker 00

  Yeah.

• 19:25Harry Stebbings?

  My question is, you kind of mentioned kind of actual model quality, maybe not being as good as can be and like expectation in reality. The other cool question, which might be a little bit boring, but it's just the commoditization of models. And I've never seen it before where you have like Mr. R one week, so hyped and then you have, you know, whatever bar the next week. And it's like the transience of different players being preceded in the media is kind of winning, so to speak, is so moving every week. Is this a game of commoditization?

• 19:54Speaker 00

  There was a time when there were like more than a hundred car companies in the US, I believe, or at least close to that. And if you go like, look at some of the old media at the time, it was like, now there's this better car, now there's this better one, now there's this better one. I think that same thing holds true for most new industries. I think it's fine. I mean, it's probably good, but I don't think that's where the enduring value will be. I think eventually it will shake out. There will be a small number of providers, just dozens, something like that, doing models at big scale. And it'll be extremely complex, extremely expensive. And I hope we all continue to push each other to make the models better, cheaper, faster and commoditize in that sense. And the long-term differentiation will not be, I don't think, the base model. Like, that's just, you know, intelligence

• 20:39Speaker 00

  is just like some emergent property of matter or something. The long-term differentiation will be the model that's most personalized to you, that has your whole life context, that plugs into everything else you want to do, that's like well-integrated into your life. But for now, the curve is just so steep that the right thing for us to focus on is just make that base model better and better.

• 20:57Harry Stebbings?

  Can I ask you, you mentioned obviously your time investing and, you know, Brad, you're obviously engaged with so many large enterprises around the world today. For me as an investor, I see so many AI companies and I'm not investing in any application layer AI companies because respectfully, we've seen OpenAI come out with products and it's like, well. Black killed the whole industry.

• 21:15Speaker 00

  I think fundamentally, there are two strategies to build on AI right now or startups doing with AI. There's one strategy, which is assume the model is not going to get better. And then you kind of like build all these little things on top of it. And then there's another strategy, which is build assuming that OpenAI is going to stay on its same rate of trajectory. And the models are going to keep getting better at the same pace. It would seem to me that 95% of the world should be betting on the latter category. But a lot of the startups have been built in the former category. And then when we just do our fundamental job, which is make the model and its tooling better with every crank. Then you get the OpenAI killed my startup meme. If you're building something on GPT four that a reasonable observer would say if GPT five is as much better as GPT four over GPT three was.

• 22:00Speaker 00

  Not because we don't like you, but just because we like have a mission, we're gonna steamroll you. But there's a giant set of startups where you benefit from GPT five being way better. And if you build those and AI progress keeps going the way that we think it's going to go. For the most part, you'll be really happy.

• 22:18Harry Stebbings?

  As an investor looking for an investment thesis that I'm actually lost. What are those that will not be steamrolled that I can invest in Sam versus those that could be?

• 22:27Speaker 00

  Ask the company whether 100x improvement in the model is something they're excited about. It's actually, we can tell pretty well because we know the companies that come to us saying, we want the next model. When is it coming out? When is it coming out? I want to be the first to try it. It's going to be the best thing for my company. And then there's a lot of companies that we don't hear from in that regard. And I think that's like a pretty good delineation is if there's a clear path to how better intelligence, better underlying intelligence accelerates that product and that company. Most companies can tell that story really clearly.

• 22:53Harry Stebbings?

  And so like Klarna would be an example of that.

• 22:55Speaker 00

  Klarna is a good example. And think how much better that gets if the next model is as good as we hope it's going to be. I talked just this morning to an AI like medical advisor, I guess they would call it. They were like, you know, here's the places the model's underperforming. It's still pretty useful for like these kinds of things. But if the model could just get like this much better on these metrics, we'd have all these other businesses. So like, can you all do that faster? And then we can have like, you know, this like thing that'll save all these lives and give people who have not had access to medical. Care like some access and you know, how soon can we get that? And you know, here's how many people are dying every day you delay. It was an effective pitch, actually.

• 23:30Harry Stebbings?

  There were questions beforehand that I was like, I've never asked that. That's like a terrible question. And I'm going to proceed into ask most of them. So I'm sorry for this, but we mentioned kind of model improvement there. How do we see the rate of model improvement? Is it like linear? Does it plateau at points? Obviously now it's accelerated faster than ever in the last, whatever time period we want to call that. How do we see that rate of improvement in models?

• 23:51Speaker 00

  It feels very punctuated externally, which means I think we've done a suboptimal job on one of our core beliefs. We have this idea that iterative deployment is important. And what you don't want is to go build AGI in secret in a lab. This is like the limit case toil away for a couple of decades and then push a button. And all at once, the world has to like contend with AGI. And better than that to us, it seems, is to put a model out into the world. Let people have some time to think about that, react, figure out how they want to use it, what they'd like to do differently, what they'd not like it to do, what guardrails society wants or doesn't want. And then build up sort of more societal engagement with it. And in some sense, one of the most important decisions we ever made was this one.

• 24:35Speaker 00

  And that includes things like deploying chat GPT into the world and getting the world to take advanced AI seriously, which we tried to talk about for a long time and didn't really work. And you know, deploying that really did. But as we think about future models, we underestimated, because we've like lived with these models for so long, and because we watched them get better and better little by little. We underestimated how much, even with our strategy of iterative deployment, lurch forward, some of these things would be. So as we think about the next models, we're trying to find a way to make that even smoother so that it feels closer to the smoothness we feel internally to the external world.

• 25:09Harry Stebbings?

  Do you think the strategy of iterative deployment will still be possible moving forward as you get bigger and bigger? You see, obviously, a fair and long, or at least some on like medical, scientific writing, and they got terrible blowback and had to pull it away. Bard obviously did theirs and they got an eight percent reduction in share price. As you get bigger and bigger and bigger, releasing imperfect product can have such ramifications. Is that iterative deployment still possible over time?

• 25:33Speaker 00

  I think expectation setting matters a lot, but with the right expectation setting, I think it is possible. Yeah, I would agree with that. I think we learn a lot also. And so when we released Sora, for example, we get an incredible amount of feedback from the creative community, from media, from industry. And we actually started now to incorporate that feedback in how we think about our research roadmap for that specific modality. We start with expectations really low. We just try and learn. And we really just listen to the world. And then we try and incorporate that as best we can so that by the time we actually have something we want to share, it's something that really feels useful and people have natural familiarity with it. And it almost feels like it was built more for them. And I think that's the mode that we'll operate in somewhat here.

• 26:14Speaker 00

  It is really iterative. And it really is this more code development with the world, maybe more than the world appreciates.

• 26:20Harry Stebbings?

  One final thing, and then I do want to go on to GTM. But you mentioned, obviously, the medical advisor earlier. I hear you've got a passion for how, by the way, AI can solve cancer, and specifically, certain medical.

• 26:29Speaker 00

  Well, it's more like I have a passion for how AI can, I would say, help greatly increase the rate of scientific progress. And curing cancer would be a great example of that. But I do generally believe there's definitely just a personal element of excitement. I think science is awesome, but I genuinely believe that scientific progress is the highest order bit of progress for society. Economic growth, quality of everyone's lives, all of that. And if AI can help people meaningfully increase the rate of scientific progress, which I believe it will, I think that will be a triumph.

• 27:00Harry Stebbings?

  What do you think is the biggest barrier to that happening?

• 27:02Speaker 00

  Well, I think the models are just not smart enough, which sounds like an annoying, low-information, cop-out answer. But I think it's deeply fundamentally true. The models just aren't smart enough. You fix that one thing, all these other things get better. There will be all these ways that we have to figure out, integrate tools into people's workflow. And modelability in different areas will matter a lot. But if you zoom out, doing scientific research with the help of GPT-2 would have seemed fairly laughable. With GPT-4, people do use it just to help them do science, just in extremely primitive and limited ways. And with GPT-6, I think people will say, hey, this is helping me as a general-purpose tool in all these ways. And then with GPT-8, maybe people are like, this can do some limited, maybe not so limited, tasks for me.

• 27:46Harry Stebbings?

  Can I move to the company scaling? It's really important to cover. I mean, this is the most unprecedented company scaling really in history, especially when you look at speed of revenue growth. Brad, you've been at the forefront of that. How have you scaled so fast so efficiently? And what's the secret to that? And things seemingly not breaking?

• 28:03Speaker 03

  Well, things, it's always messy behind the scenes, but I appreciate you saying that on the outside, at least it doesn't seem like things are breaking. We found a moment with ChatGPT that it was the first like really human experience people have had with the technology. And we hear stories all the time of like where people use it and it continues to amaze us actually how diverse these stories are. It's like on the one second, you're hearing like a research scientist at a company talk about how productive it's made them. And the next is like, this thing is writing code for me. I'm a software engineer at XYZ startup. And the next is like, I'm a new parent and like, I don't know how to take care of a baby. But like, I ask this thing 80 questions a day and it kind of like helps me understand how to like navigate life as a new mom. And like the same tool can power each one of those experiences.

• 28:44Speaker 03

  And when you have something that's like that fundamentally diverse, and I think that kind of, you know, fundamentally accessible, like it's just bound to have a really important impact. Like in adoption and, you know, how people use it. And I think, I mean, that obviously translates to a business impact, but our focus is, is just continuing to push on that front. The B two B business is obviously different cadence to that business. There's more of an adoption cycle in the enterprise. We've had amazing success on the developer side. So we've always been a company that has really prided itself, I think, on just, we kind of build for who we know. And so we, we've tried to build the best developer platform in the world for AI. Enterprise is, is a new focus for us. And so there'll be more of a process to building for the enterprise, but it's one that we're excited to take on and a lot more to come.

• 29:25Harry Stebbings?

  Can I ask on talent? Is it bad if talent wants to join because OpenAI is the hottest company? It's the fastest growing company?

• 29:31Speaker 03

  Probably.

• 29:32Harry Stebbings?

  So everyone has to join for the mission. Cause I'm always like, does it actually, we always say mission, mission, mission.

• 29:38Speaker 03

  I mean, I think it's bad just because it makes us like harder to filter. But yeah, like I do kind of want people to think that they're doing something that's really important. I watched what has happened to other tech companies when they just become the place you want to work because it's a good resume item. You can like filter against that to varying degrees. As you said, it doesn't literally need to be told a 100% true, 100% of cases. But I think.

• 30:01Speaker 00

  Companies that lose their mission orientation and get taken over by mercenaries usually come to regret that.

• 30:07Harry Stebbings?

  You've invested in some of the best founders. Are there any that stand out as ones that you've learned from that you've invested in and have shaped how you think about building?

• 30:14Speaker 00

  A lot, yeah. I have been extremely fortunate to work and like be along for a small part of the ride. I think with like many of the best founders of my generation. And I'm also happy that they have been willing to like spend so much time now helping me.

• 30:27Harry Stebbings?

  Can I push you? Are there one or two that stand out? And has there been a lesson or two from them?

• 30:32Speaker 00

  Chesky has been incredibly hands-on and helpful to me over the last year and a half and is really good at a lot of things that I'm not good at and have had to like come up to speed quickly on. How to think about how we talk about our products? How to think about how to build great products? He is really a special person. The Collison brothers are incredible. And like every time I talk to them, I am like, hmm, that is a new deep insight that I just never would have thought of. It's like a totally nonlinear thing. But I would like, I invested in a lot of companies for a long time. So I have like a long list of incredible founders and I'm very grateful to have been like very willing to really kind of like help out in different areas. And I think in the same way that I tried to like learn a little bit each from a lot of different investors, trying to learn a little bit each from a lot of different founders has been a great strategy.

• 31:17Harry Stebbings?

  Can I go back to usage? You mentioned the kind of divergence in usage from kind of consumers every day, maybe it parents, maybe it's scientific researchers. You've also built an incredible go-to-market with some of the largest enterprises in the world. What have been some of the biggest lessons on enterprise adoption? And how large enterprises are thinking about it, approaching it, adopting it that you think are noteworthy?

• 31:37Speaker 03

  I think the biggest one is enterprises have a very natural desire, I think, to want to throw the technology into a business process with the pure intent of driving a very quantifiable ROI.

• 31:48Speaker 00

  I know what none of those words mean.

• 31:50Harry Stebbings?

  It sounds great.

• 31:51Speaker 00

  I mean, this is my joke, but I can't do, I couldn't.

• 31:54Harry Stebbings?

  There's three strategic levers.

• 31:56Speaker 03

  I manage my supply chain and it costs me X per year. And I want to take AI and throw it at a specific process in supply chain management and cut 20% of my spend out of this specific area that I spend money on. That type of thing. And that's great. We are here and happy to help you think through that problem. I think people though criminally underrate how important it is actually and how much like return you really get on just giving people access to the technology. You can't quite quantify exactly how it works, but like someone that used to spend two days doing something that now spends two minutes doing something and is freed up to do like eighty-five other things in their daily life, that doesn't really show up in how you would think about ROI as an enterprise. But imagine doing that now ten thousand times over, a hundred thousand times over.

• 32:38Harry Stebbings?

  How do you explain that to enterprises? Because you're right, it's not like a budget line where you're like, oh, we got rid of X.

• 32:43Speaker 03

  Yeah.

• 32:43Harry Stebbings?

  It's difficult to show that supply of time shift.

• 32:46Speaker 03

  Part of it is just having time to show it. ChatGPT is a business product that's still so new. We released enterprise back basically in, you know, late August, September of last year and team is a sell-so product we released earlier this year. So the time in market's been virtually zero and enterprise adoption cycles are slower. So I think part of it will just come with time and part of it just comes with expectations of your workforce will want these tools. And also like you're going to start to hire people who will have come from a world where they could only ever use these tools and they can use as much as they'd like. And they will expect to be able to use them in the workplace. Over time, we will start to see that shift. Right now, I think that's there's this kind of weird miscalibration of of where people think they should be deploying AI that's going to have high impact with where I would say they should be deploying AI.

• 33:29Harry Stebbings?

  What questions do you think the biggest companies don't ask that they should ask?

• 33:33Speaker 03

  A lot of companies think it's static. So a lot of companies think GPT-4 is the best the model will ever get. That's understandable. Every technology they've ever had to adopt has been relatively static. If you think about like what the iPhone looked like, you know, what mobile looked like in two thousand and nine versus today, it kind of is the same thing. Like the form factors change a little bit, they're faster, they're like higher resolution, but like the technology is pretty much the same. Application development is pretty much the same. Same thing with cloud. Here they've been handed this new technology and I think their expectation is like, well, this is it. And I think they don't ask enough about really how steep that rate of change is and like how to think about like what the next wave of the technology will be in the wave after that and how to think through implementing that.

• 34:10Harry Stebbings?

  Do you think they're set up for that rate of change? Like, you know, we're obviously in London now. European corporates are not that fast moving. You change as fast as you are changing. It's almost very difficult because they get used to their workflows and processes. And then you change and you update and it's like, oh, fuck. They're all gone. They're out the window. Do you see what I mean? It's almost hard.

• 34:29Speaker 00

  Yeah, no, it is hard. And that's what makes our job hard, right? Is I think companies have a desire to want to move that fast. But when you're operating at 100,000 person or 200,000 person scale, it can be really, really hard. And so I think that'll be the big question over the next few years for us.

• 34:42Harry Stebbings?

  Sam, you mentioned the research driven kind of culture and the importance to retain that. When you bring in a go to market function and sales leaders and wholesales teams, it's very difficult to blend kind of product and sales functions or cultures so efficiently. How do you think about the challenges that one faces?

• 35:00Speaker 00

  I think this is where Brad and I have a great partnership in that we have different opinions about how to balance any particular decision. And we're, I think, very good at deferring to the other based off of where it has like more context or feels it will have a more important impact. But we have really deep agreement, I think, in a way that many people in Brad's role wouldn't about the critical focus of making sure that we let research drive product and product drive sales. Now, that doesn't exclusively mean that, of course. There's got to be feedback the other direction. And one of the reasons that we love having users now is this is like the most important reward signal you can get for if the model's good or not. It's like, how useful is it really to people like that? That's what matters. But we also know that the best thing we can do to sell more product is to make the product better.

• 35:45Speaker 00

  And the best thing we can do to make the product better is have better research. There's like zero disagreement between us ever on that. And that is really important.

• 35:53Harry Stebbings?

  It's funny, you mentioned the users that I was talking to Alex Schultz from Meta before. He said, ask Sam about growth and ask him how his mindset has been changed on growth post open AI, because it is such a different story.

• 36:06Speaker 00

  I think Alex Schultz is a legitimate growth genius. He'll be there and I'll talk about this retention curve and the 30D here and the that and the this acronym. And I mean, he really understands the dials of things. I think you usually don't learn that much from failure. You learn more from success. But I think you also don't learn that much from like extreme, break all the rules, unrepeatable success either. And what we had with ChatGPT, I would be hesitant to say I've learned anything at all about growth. Like have a once in a generation technological revolution. It's not really like actionable advice. If I wanted to learn about growth, which I do, I'm now very interested in it. Alex probably can't advise me on it at this point, but that's who I would normally ask.

• 36:42Harry Stebbings?

  Why don't you not learn from failure? So I always disagree.

• 36:45Speaker 00

  You learn something from failure for sure. You learn some things to exclude, but at least in my own experience, having failed at many, many things and succeeded at some, I have learned much more from the successes.

• 36:57Harry Stebbings?

  What's been your biggest learning from a success?

• 36:59Speaker 00

  I mean, so many, like what to look for when hiring people? I don't hire externally that often. I'm like a big believer, for like my direct reports, I'm like a big believer and try to like promote into that when you can, but certainly what to look for when promoting someone, what to look for in a founder? I would say like, yeah, I can like point to my extremely long track record of failed investments and say, I made this mistake here, I made this mistake there, I made, you know, this one over there. Well, all of the obvious things. And then some, I think some of the things that I look for more than other people are founders that are going after something that seems big if it works. I think that is way more important than people realize to like the really outlier returns. So I'm, you know, happy to like lose nine times out of 10 and like really succeed on

• 37:43Speaker 00

  the 10th company rather than kind of like do okay seven times out of 10. I think founders that are like very good at generating lots of new ideas, founders that have like a very fast iteration cycle, obviously like, you know, smart and determined and all of those things matter. Oh, great communication skills are something that I really look for.

• 38:02Harry Stebbings?

  Do you? Okay, but I've fucked up so many, I mean, I've missed so many great companies, but I've fucked up because you get an engineering led CEO and respectfully, especially at Seed or sort of as they were, I tend to invest, they're not so honed and so they don't have that communication.

• 38:15Speaker 00

  Yeah, polished, I don't worry about, but like as that great CEO used to like, I don't mean communication and like, can someone sit in an interview and be like super charismatic and, you know, hit the talking points and like, no, clearly not me either. But I do think a lot of the job is communications driven. Like you have to be able to like, explain to the company what we're going to do and why. And you have to be able to like hire people and get them to want to work with you. And you have to be able to like sell things to customers and get people to like try your product. At some point, you may have to like talk to wider audiences. So I don't mean it like literally is, you know, can the person give a polished interview because I may make it my whole life without being able to do that, we'll see.

• 38:56Speaker 00

  But in the day to day, you know, able to clearly explain what you're doing, why people should care about it, what you'd like them to do to help you, that's super important.

• 39:06Harry Stebbings?

  Final one before we do a quick fire, do you have to ask, on the people that you hire at OpenAI, one thing that's quite striking is they're a little bit older, or it certainly appears that way. How do you feel about hiring for experience versus hiring people who have been new to a job, but may have that hustle and hunger? And am I wrong to say that you hire for experience in that little bit older?

• 39:26Speaker 03

  I think, at least in my orgs where I've set hiring policy and whatnot, there's a difference in what the composition of your hires are and what the composition of responsibility is in the team. I try and keep this team where great ideas are always elevated. By and large, actually, I would say the really, really good ideas come from unexpected places on the team, not from the most experienced end of the team always. And that's my advice, is find a way to make sure that there's this very, very flat, very even playing field when it comes to how you look to the team for perspective, for decision-making, for judgment and for creativity. You do need experienced hires, I think, in that they bring a little bit more perspective, obviously. But I tend to think that really the company-changing ideas actually,

• 40:11Speaker 03

  by and large, come from places that are not those hires.

• 40:13Harry Stebbings?

  Do you agree?

• 40:14Speaker 00

  I think there's some roles where experience really matters and somewhere it either doesn't matter or is a slight negative or it could be a big negative. I think our leadership team is probably more like 30s and 40s than the 20s and 30s you would see at other startups. And I think our technical people skew slightly older. I don't have the numbers, but maybe I would guess that the average age of the technical team is like early 30s instead of the average being like late 20s at some other tech companies. I think part of that is just the path to becoming a great researcher. There's huge exceptions in both sides. And I don't want to say I don't care about experience on the whole, but I think there's amazing people with tons of experience.

• 40:58Speaker 00

  There's amazing people with almost no experience at all. I think whatever we're doing seems to be working, but I don't think about it as a like... Do we want more or less experience? I think it's very much like, who is the person? Like, is this the person?

• 41:10Speaker 03

  I'll add one thing, which is there's a lot of varies explicitly where people coming in with experience. I think what we do is so categorically different. It is an entirely new category. The way that people kind of engage with, consume, use, talk about, put your verb in there. This technology is different. So the playbooks for how you actually like bring into the world are really different. There, there aren't playbooks for a lot of these things. And so like the approach you take to solving problems doesn't necessarily, you don't necessarily benefit in all ways, at least in my world, from people who have done it for 20 years before.

• 41:40Harry Stebbings?

  Yeah, one of the joys of new industries is it levels the playing field.

• 41:43Speaker 03

  It does.

• 41:43Harry Stebbings?

  I think you saw this in crypto in particular, where suddenly 19 year olds were just as impactful as a 45 year old, because it doesn't matter.

• 41:49Speaker 00

  I think in general, if you could like sample someone at OpenAI and look at the role they're doing and the level of responsibility they have and the impact they have and say, you know, what I have expected this person to be more experienced or less experienced, given that, you would say on the whole, I would have expected slash maybe even hoped that this person was more experienced.

• 42:06Harry Stebbings?

  Are you ready for a quick fire?

• 42:07Speaker 03

  Sure.

• 42:08Harry Stebbings?

  Okay, so 60 seconds or less. Let's start Sam. What's the single biggest challenge to OpenAI over the next 12 months and then five years? 30 seconds each.

• 42:16Speaker 00

  Doing the best research and the best productization of like the best innovation on that stuff over the next 12 months. And was it five years for the second layer? Sufficient like supply chain and compute.

• 42:28Harry Stebbings?

  Brad, what if you changed your mind on most of the last 12 months?

• 42:33Speaker 03

  I think the rate of adoption in the enterprise is actually going to be way faster than people realize. I think we will buck convention on that. Enterprise is having a reputation as being slow adopters of technology. I think that will not be true here.

• 42:44Harry Stebbings?

  Does that differ by geography?

• 42:46Speaker 03

  No.

• 42:47Harry Stebbings?

  Do we have loads of experimental budgets?

• 42:49Speaker 03

  Do we have loads of experimental budgets? Well, we have real budgets and that'll help.

• 42:53Harry Stebbings?

  Sam, what are you most concerned about in the world today?

• 42:55Speaker 00

  The, the whole thing just feels like way more on the whole situation of the world, the geopolitical thing, the sort of socioeconomic stuff, politics. It feels more unstable to me than it has felt since I've been paying attention. And there's no like one thing I would say.

• 43:11Speaker 03

  That I couldn't with confidence tell you like here's the the crux of it or here's the root cause, but the the general macro instability feels high.

• 43:21Harry Stebbings?

  Brad, what's been the most unexpected thing in the scaling of OpenAI for you?

• 43:26Speaker 03

  I think it's how consistently the scaling of models has worked. It still breaks my brain like I don't maybe I've been we've I've watched the same trend line for six years now, but I still find it incredible that you can make these models bigger and they get predictably better. And that is a tremendous gift.

• 43:44Harry Stebbings?

  Sam, what do you not do much of that you'd like to do more of? If time is not particularly your friend.

• 43:50Speaker 00

  I don't really read anymore. I used to read a lot. That's a sort of sad change.

• 43:54Harry Stebbings?

  Would you like to make more room for it?

• 43:56Speaker 00

  It's probably not in the cards in the short term, but someday you only read Slack and Google Docs.

• 44:01Harry Stebbings?

  What do you wish you had more time for that you don't today, Sam?

• 44:04Speaker 00

  I'm OK with this trade for now because I know it's not a forever thing, but I have basically like run out of time for real life. I don't really get to hang out with friends that much. I don't get to like do the normal like life stuff. It is both totally a trade I'm willing to make. And then again, it helps to know that it won't be a forever thing, but it is still just sad.

• 44:21Harry Stebbings?

  Are you happy?

• 44:22Speaker 00

  I am really happy. I wouldn't say I'm having fun, but I am really like deeply happy. I have fun. That's great. Good for you.

• 44:30Harry Stebbings?

  I mean, you both also got married in the last year, which is very exciting.

• 44:34Speaker 00

  That is very exciting.

• 44:35Harry Stebbings?

  Can you impart some wisdom on how do you retain a romantic relationship, a partner, happiness there where you're also, I mean, traveling all over the world literally every day?

• 44:45Speaker 03

  Communication, I'm still learning it. Over communicate, be empathetic and appreciate that like this job is as taxing as probably anything on earth. And the person, though, that is really paying the price for that is not is not you. It's your significant other.

• 44:58Speaker 00

  Look, I just got 10F, 10 lucky. Brad did too. Christie's really great, but I think having a partner who is just sort of like, this is like not what I always signed up for. We used to have this like nice, quiet life and having a partner who is just like supportive of it, who gets it, who's like, you know what? You go deal with that. I'll like hang out and we'll have like a lot of time. That's the kind of the one other thing I make time for, but having a supportive partner, not not just supportive, having like an enthusiastic partner, which is like, this is really important. You go do this, like I'll make it work. I'll try to like be flexible around it. I am extremely, extremely grateful.

• 45:29Harry Stebbings?

  So do you know straight away with both of your respective partners that they were the ones for you? Pretty early, yeah.

• 45:34Speaker 00

  Yeah.

• 45:34Harry Stebbings?

  When you look forward 10 years, how do you see the state of the world then? And are you excited for that future state? That's for both of you. Yes, we wouldn't be doing this work if we weren't excited, or at least I wouldn't.

• 45:45Speaker 00

  Tremendously. I hope that people look back and say, we cannot believe how barbaric they had it in 2024. In the same way that we could look back a few hundred years or many hundreds of years and say that same thing. It's like, not that we're not all appreciative and grateful for life today. But people get sick and die prematurely of disease. Not everybody has access to a great education. Not everybody kind of gets to do and spend their time the way they want. To say nothing of like the unimaginable new things that we'll have in this future. Again, it won't be all good. I think there will be like real things that we lose. But on the whole, I am tremendously excited for what a world with genuine abundance looks like.

• 46:23Harry Stebbings?

  I want to say a huge thank you for doing this. Honestly, it's been so nice to do it in person. I so love doing it with both of you. So thank you both for joining me. Thank you very much. This is great. I have to say, I really feel so grateful and lucky to be able to have done that show. I think it's one that we will look back on for a long time. And I want to say a huge thank you to Brad and to Sam for being such fantastic guests. The schedule was a moving fixture there and they were incredibly patient with me. I hope you enjoyed it. Again, you can check it out on YouTube by searching for 20VC, that's two zero VC. But before we leave you today, we're all trying to grow our businesses here. So let's be real for a second. We all know that your website shouldn't be this static asset. It should be a dynamic part of your strategy that really drives conversions. That's marketing 101. But here's a number for you.

• 47:08Harry Stebbings?

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• 48:33Harry Stebbings?

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