Uncapped #46 | Brad Lightcap from OpenAI

23:16They're obsessive about the quality of the model. And because of where we are in terms of how models are trained, the cycle time on how fast we can kind of drive improvement is starting to collapse. And so that's why you're seeing these jumps from 5.1 to 5.2 to 5.3 to 5.4. And now it's not surprising that you get a model like GBT-54 that as of today is, you know, here we are in mid-March and the model's a few days old and is doing a billion dollars run rate revenue. It's doing five trillion tokens a day. That's crazy. Is, you know, now far and away our kind of most dominant model of our set of API models and is also driving, you know, driving codex growth at the rate it's going.

23:55And I think that's only going to increase this year. And so by the end of the year, I think we'll look at the models that power codecs and our APIs today and kind of think we'll laugh. We'll think they're kind of pedestrian. Obviously, like OpenAI started, you know, in chat and then moved into all these different things. And over time, I think has become probably, you know, it's one of the most unique companies in general, but included in that uniqueness is like you guys have done a lot of things. How are you thinking about that now? Obviously, like the market is starting to somewhat mature. you guys have had new companies come out, you know, spin out of OpenAI and, you know, focus on areas that have, you know, turned out to be really productive.

24:33I'm sure that's like changing the way you guys are thinking. So I'm just curious of like the state of the union, you know, in early 2026, when you like look at, you know, here's where we are, here's what's around us, what matters now? Like, what do you care about? Like, what do you, what do you say this got us here? This is what's going to get us there. What's the focus? One of the cool things about OpenAI is it has a a very wide aperture on, I think, how it looks at what its kind of ultimate mission is. These lines that people, I think, drew maybe in the world prior of, you know, your B2B or your B2C or your hard tech or your software, you know, all of the things that kind of the VC ecosystem segments themselves.

25:13Got out of the lane. Yes. We don't see those walls. We kind of see AI as having, being this enabling technology that drives, is going to drive innovation cycles across all of the above. And that could be in, you know, it could be in the enterprise, it could be in consumer, it could be in, you know, in creativity, it could be in robotics, it could be in hardware. And I think what we want to understand is what do each of those bets look like? And OpenAI has an operating model that we've, has been kind of tried and true for us really since the company started, which is being able to be experimental, being able to kind of try and iterate, being able to be very kind of model forward, I think, in how we think about a problem and not really feeling like we have the incumbency of the kind of last generation.

25:58And then trying to kind of see if we can build the thing that we think is possible. And if it works, you kind of build an effort around it. And if it doesn't work, then you kind of, you shut it down and you recycle those people back into a new thing. And that was really the way that OpenAI operated early on. It still somewhat is, is this kind of expansion contraction model and research where you've got, okay, maybe there's 20 projects that are kind of all trying different things and going on at the same time, maybe two or three of them will really work. You scale those up, you consolidate people kind of back into those projects to scale them up.

26:30And then over time, as you kind of shift into a next paradigm, you start to kind of, you know, you spread back out again and see if you can take more bets. And I think that's going to be how this goes. I think that same, everything is in my mind downstream of research. And so if that's the kind of cycle of how research is working, in some sense, I think the product and deployment cycle should look similarly. I also feel like I can just tell from the way that it's a unified model, the way the product's feeling, it's going to all just be a unified thing at some point here soon. Like it's already kind of going that direction.

27:01And that thing will just be used by people, whether they're at home or work. And, you know, it's like people use Google at home and at work and it's just like, you know, becomes the tool. Yeah. We need the models to start doing more work for users is what I would say. I think if there's been one really big gap in my mind and kind of the user consumer experience in AI so far, it's been that users have to do too much work and you're kind of promised this future of these really smart models. And, you know, they kind of can solve all your problems very dynamically. And yet here we are, like with 18 things in a model picker.

27:31And, you know, do you want like thinking fast mode and, you know, or do you want pro thinking hard mode? It's just like, it's time to move on. Yeah. It's time to move on. That to me feels like the direction where I think you're describing of this more of this consolidated, like, I just don't want to think about it. I just want, I just want intelligence and I'm going to let the model kind of decide how to allocate that, you know, on a token level most efficiently. Okay. I want to move the conversation to a selfish place now. Okay. You've been an investor before. My question is what should I invest in?

28:01And like, you know, like maybe to put a little like framing around it, there's, there's like a frequent worry among founders of opening AI, releasing something and I'm going to get my face blown off and, you know, what's safe from AI and what will or won't the models do? Where can a startup like predictably add value? You know, Sam talked about you should build your company such that you're planning for the models to get smarter. And if them getting smarter is good for you, that's a good thing. If them getting smarter is bad for you, you know, that's going to be really tough. But maybe can you unpack it a little bit more now just as months and years have gone on?

28:39What are the safe places for a startup to try to do work that they can expect to still be available to them in three years? Yeah. I mean, I'll go back to what I said. Or should they just all join OpenAI? I don't think they should all join OpenAI. First of all, the level of energy in the ecosystem right now is like nothing I've ever seen. The quality of founders and the - And the effort. The effort. And just like, there's like this intensity and there's like urgency. Do you remember the startup ecosystem like right before ChatGPT? Like, you know, like pastors are like, you know, we have come down from like the SaaS, you know, glory moment.

29:14And that was tough. Yeah. I don't know where we'd be right now without, you know, it would be not fun. I was at YC and, you know, in kind of 2016, mid 2018. And that was good. It was the like front end of that was a fun time to invest a growth. It was, you know, we were fortunate enough to invest in, I think, you know, in the growth rounds of a lot of the companies that had been built in, you know, call it the last five years prior to that. And then weirdly, it just got it got less fun. Yeah, I think kind of in 2017, 2018. And I don't know what it was. It just it felt like the ecosystem was kind of tired.

29:45Like, I think there didn't feel like there were a lot of new ideas. I think a lot of the obvious stuff had happened at that point. Yeah. And I think without like a new technology shift, like at some point, you know, there's always more to do. But at some point, the first, you know, the 80 of the 80, 20 gets done. Yeah. And now you're, you know, rooting around in the 20. I think that's right. But it feels firmly now like there's this entirely new cycle and that the kind of the urgency and the excitement is very much there. And I think the invest, like also just the ambition of the companies that we engage with, you're like, like, I just, it's like stunning to me sometimes.

30:19I'm like, you're going to do what? Then you realize also there's an enablement factor of like, as soon as you get models, for example, that are good enough at software engineering that they can start to, you know, themselves like design and write in new programming languages, or that they can speed the time from being able to take old, you know, code bases, refactor them, and then kind of rewrite them into new, you know, new and modern frameworks that enable another company to exist and serve an area that was historically traditionally underserved. You realize that like, oh, like, there's an entire industry here that didn't exist that's about to get built.

30:57And then you've got a founder who sees that and they're like, I'm gonna go after that. You know, that's partly the answer to the first question is, if you kind of think of model capability as, you know, kind of dropping successively larger rocks in the pond and the ripples from those rocks kind of, you know, reverberate wider and further and it creates more and more surface area around the circumference. And I think the way I would kind of look at it is like, you don't want to be right under the rock dropping. You're going to drown. That's a very hard place to be, but you want to really be right out on that outer edge, on that surface of what is the thing now that is enabled by this advancement in the capability that wasn't previously workable before in a very specific and opinionated area on a very hard problem that has historically been underserved.

31:43Yeah, I mean, I guess to stick with your metaphor, I feel like some of the fear is that the next rock you drop is going to be bigger than the circumference of the ripple of the last rock. And so things that, you know, were at the edge before are now squarely in the center of the model. Yeah, I think there's no substitute, though, for being familiar with a user, a problem, you know, like how the existing industry serves that problem or doesn't serve that problem. And just being very, very close, you know, like YC always had this thing was like basically, you know, effectively just like talk to users.

32:13It's kind of the simple advice sounds trivial, but not enough people do it. And when you actually get into it and you realize like, oh, like the world is gigantic, you know, 99 % of people get to use bad tools or don't have any tools at all. You know, the quality of experience of the people that exist as their customers and users is not very good. Everyone's lived that in some capacity. Everyone has like lived the bad experience of going to modern life and dealing with the things that we have to deal with. I don't know. I just I think if you're kind of sitting there lamenting the idea that, you know, there's no more good ideas and no more new ideas, like it's just kind of lazy.

32:46I feel like there's at least two other things that can just like give you comfort as a founder. One is that like, I don't think any company, no matter how great it is, can do everything. And there's just, you know, there might be 10 ,000 people working at the labs, but there's millions of people other places and you just can't do everything. The other is that I've been surprised by is some of these markets are just so ridiculously big that there's like eight things that are all doing well around, let's say, like code gen and, you know, website building and sort of like internal tool creation and whatever.

33:21You could do that probably straight out of codex, but you can also use other products that are great that are, you know, based on codex and things like that. So I think some of it is just these markets are just hard to appreciate how big they are. Yeah. And everyone's got like, like, again, there's no substitute for being able to talk to users and being able to identify like, what do people really want? Like, open AI is like our focus is really on trying to improve the models and do the best research we can possibly do. But like, you know, for someone in a very specific area of the world who has a very specific set of needs, you know, who wants to do one thing and they want it to do it really well.

33:55You know, there's there's probably some alpha there. I do think it changes the kind of way you need to build a company versus in the past, though. I agree. Like what I've noticed is a lot of the great founders today seem very willing to just rip everything out that they've done up till this point and keep only like their team knowledge, customer relationships. But, you know, if the product we built so far is wrong, we're going to just trash it in a way that I think people were much more precious about before. But I think some of this goes to there's like a new like ephemerality to a lot of these things.

34:24When software is super easy to build, I can make a UI that works for me today, but I'll throw it away because I can just make a new one tomorrow. I think that's like an interesting trend, too. Yeah, I have seen a handful of times now founders of companies that were built in that, you know, that period of between call it 2008 and 2016 or something like that, you know, who are kind of the canonical darlings of software from the last decade or so who have founders who are still running the company, who have basically decided like, I'm effectively restarting the company. And they have taken it on themselves to fork off of the kind of the mainline effort to basically go figure out like what is like the second chapter of this company look like in a world where the primitives and the tools and the assumptions have changed.

35:07Which is a hard thing to do for, you know, just there's just so much sunk cost to it all. Yes. But I think the people who are able to adapt to that, it's a huge advantage, it seems like. Totally. And like there's no, in my opinion, like there's no, like you can iterate so fast now. Like you can explore the action space so quickly. Yeah. And you have the benefit of like, you know, legacy customer relationships. You've got the benefit of existing teams. So in some sense, you almost are starting with a head start. The way I see it is like, like you can learn faster versus, you know, if I were to start a new company tomorrow, I'm starting with no customers and starting with, you know, no funding, starting with no product and no team.

35:42I guess related to this, how do you feel about the sort of like sell off in public markets? Like obviously outside of like, you know, the big companies, which have done great, But sort of like, you know, public software companies have like taken a pretty bad beating. When you think about the work that you've been doing with them and what you've been seeing, are you watching that and you're like, this makes sense? Or are you like, actually, this is like sort of a misunderstanding and you're feeling bullish about those companies? It's hard to comment on specifically that like the market is like a very frenetic thing, as you know.

36:16Here's what I kind of live day to day is. So we work with basically every company that, you know, sits in the NASDAQ that you could imagine. And A is like all of these companies are kind of as motivated and moving as quickly as any startup. B is they've got amazing customer relationships. They've got amazing kind of depth of understanding of the problems they're trying to solve, the areas that they serve. Obviously, they've got years and years of perspective that have been built. and I think like now in some sense, they're able to leverage and benefit from the same tools that anyone else is. And so the conversations we're having with them are really about them starting to rethink end-to-end their entire customer experience, their product, starting to think about how do they serve adjacent markets, starting to think about ways that they can pass capability through to their users.

37:09So like creating entirely new experiences that weren't possible before. So I think you could take the other side, actually. I think you could basically take a very long view here, which is that... Yeah, in some ways, the software itself is like the easiest thing at this point. Yeah. Having all the relationships, the team, the trust with all the customers, that's actually the hardest, you know, pull of the tent to have now. You know, if that class, if that segment was asleep, I would say, okay, maybe that, you know, concern is more warranted. Yeah, but they're not. No, and it's happening at the CEO level and the founder level in some cases where everyone is as motivated to figure this out and figure out, you know, how to create value for their customers and their business as anyone else is.

37:49And so I think, you know, it's the beginning of a new cycle is my guess. You're always going to get new companies that form that are trying to take a fresh and new approach. Often the benefit that those new companies have is that the incumbents don't realize what's going on and are too slow to move. Here, you actually don't have that dynamic. You've got everyone running, trying to run at the same speed. And so I think that's exciting. And I would say if you're kind of long, long AI and long, you know, startups, then it might even make sense. Maybe, you know, the contrarian opinion to be long, long legacy software too.

38:22I don't know if you're experiencing it one way or another, like what you think it takes for more experience. It doesn't have to be founders, but just like even people joining open AI from some old company, you know, that had not been AI native. Like how do you help people reset? Like, what does it take for people who have lived in the pre-AI era to like, you know, work the new way? I think you got to like see it firsthand. And if you're not like playing with Codex every day, like I think it's hard to intuitively grok just like how disruptive and crazy it is. Like Codex for me has replaced ChatGPT on a kind of daily driver basis.

38:56And I'm not even technical. Like I don't, I don't write software for a living, but it has a general capability that I'm specific enough about the set of things that I want that I know. And I've kind of developed enough familiarity with it. So what are the like not what are you doing with it? Like what's like the daily quick use case? My life is basically a kind of daily struggle of like thing that I would like to see get done. And then it's a question. My life is a daily struggle. Well, that too. But of, you know, thing that I would like to see get done and then kind of how fast can our team mobilize and operationalize to kind of get it done.

39:28and at a busy, you know, fast growing, very busy company, like sometimes those timelines drag. And then when those timelines drag, it means like the thing that I kind of want to see us do starts to drag. And everything kind of elongates into this kind of like, okay, something that really should take, if everyone 100 % focused on this thing, something that should take two days, you know, now takes basically kind of a month. And so one of the things I've started, you know, using it for basically is kind of supplementing that, that thing, it gives me like a first version of everything. So, for example, we're building a fairly substantial forward deployed engineering org, which we can talk about.

40:03But recruiting for that has been, like, challenging. Like, recruiting is hard. Unless you're using it to recruit. Well, I'm using it actually to basically kind of go figure out, you know, of lists of people that we're thinking about recruiting. How do you navigate and stack rank among that list before you start getting into, you know, the candidate engagement? And it's crazy because like everyone today kind of has this like online presence and, you know, a lot of people have blogs and X accounts and all that. And so I just told Codex, I was like, here, take this list and basically go figure out like what public presence any of these people have.

40:35And, you know, basically come up, come back to me and effectively like read, you know, read their online thing and score it against how you think about some of the kind of technical elements of our work and what, you know, the job descriptions are of the things that we're doing. It works for even what is kind of a non-technical task like that. It basically writes a program and it will come up and figure out how to like go efficiently look at each of these profiles and come back and give me kind of these scores on how good it thinks each of these candidates kind of online writing has been. Yeah.

41:05And it's cool because it actually surfaced for me, you know, three or four candidates who I couldn't have picked off the list, staring at a list of 200 names. But where I was like, OK, like, let me go double click on this. And now it gives me an opportunity to go, like, really look into that candidate's, you know, profile and their blog and whatever and start to just get to know them better. And that process would have taken, you know, a kind of a normal busy recruiter, probably a couple of weeks. Right. It's a lot of names. Yeah. And here it's just like it collapses down. By the way, I bet a lot of this is like what is going to be needed for people to just broadly be excited about AI, not like frustrated about it, is using it and realizing that it's like super empowering.

41:43Very much. Yeah, I think like. Versus thinking like, oh, all these other people are using it to be empowered. It's like, no, just start using it. And I guess a lot of that is, you know, you getting the tools to a place where, you know, it can be adopted super easily by everybody. For sure. And I think like almost in some sense, one of the things that I feel like is kind of the story that hasn't like yet. really diffused into more mainstream conversation on this is just like how general these tools are. Like you don't have to be a software engineer to use Codex. It's just fascinating that you prefer Codex over chat for a lot of your work.

42:14It's cool. Yeah. I mean, the Codex app is amazing if you haven't used it. I check it out. But it is, you know, so like the terminal based use is maybe a little more intimidating if you're not technical. But, you know, in an app interface, it kind of just looks like chat. And I think that, you know, it's got much more general agent capabilities. Yeah. On the topic of like the forward deployed stuff and private equity, like what's the thinking there? The thinking is very much what I was kind of talking about earlier, which is if you think about kind of like the way that software is going to get built in the future, in some sense, now any specific problem within any company in any part of their process, historically, it would not have made sense economically to have spent a lot of time thinking about how to solve that one corner of a problem.

43:02It's too expensive to hire a bunch of people, to build a bunch of software, and for that software to then have to be maintained. And obviously for the most important problems in most large enterprises, you could hire people to do that type of thing. And there's entire industries that have gotten built around that. But for 99 % of problems, for kind of 99 % of businesses, that's totally out of reach. you'd have to either decide that you wanted to hire a couple of people to try and build something on their own that maybe didn't work super well. Or you look to see if the market offers a solution and the problem.

43:39But the problem is that solution doesn't necessarily fit exactly what your shape of problem is. So now you've got people kind of contorting themselves, trying to figure out how to adopt the thing off the shelf that wasn't really built for their company. It was just built as a kind of general purpose tool. And I think that that entire era is over. I think like now you actually can reason how almost every problem inside of a business can have solutions that are kind of custom built for it. And it goes back to this kind of weird paradox of what do you think is going to happen with with jobs where, you know, we wouldn't be wanting to hire FDEs as aggressively as we would if it felt like software engineering jobs were going away.

44:16The jobs of those FDEs are different. You know, if you'd hired an FDE five years ago, they'd be doing something different than what they're going to do in the future. But the amount of demand and the amount of opportunity that we see to be able to go address surgically every area in a business that could benefit from solution design and not solution design that happens on the order of 18 months, as is the kind of industry norm solution design that happens on the order of maybe 18 days, if not faster. That to me is like an incredibly large opportunity that I think will be the story somewhat of how the next few years goes.

44:48And so the FDs we're hiring is really to help address that. Last question I have is just sort of your reflections working with Sam. It's kind of funny. I'm just, you know, I obviously know him as a brother. You know him as someone you've worked with for a long time now. I'm curious sort of like what the evolution you've seen has been like, you know, now that he's obviously, you know, gotten to a different place in like the public sphere. And, you know, there's this whole public persona and, you know, then you obviously work with him on a daily basis. Just like, what's the whole experience like for you with him?

45:19Yeah. You know, I think, well, so we worked together for 10 years. uh 10 years in january and the first year or two was yc yeah first two and a half years was yc and then um i got to open an eye before he did so i would say i recruited him up and um but uh uh you know he's he's like a he's a remarkable individual you know that um and uh i wish more people could spend more time with him kind of off the record i think he's not innately i think someone that enjoys being a kind of a public face of things i think certainly it feels like an unnatural thing for him. He is someone who much prefers spending his time sitting in a huddle of like five people talking about the future and having a deeply technical conversation about some niche topic.

46:02That's kind of who he is internally at OpenAI. It's what I've always known him to be. And I think that if you could spend more people to spend more time with him, you'd realize he's like an infinite optimist. That's crazy because the way I experience it, It's almost like this like sacrifice to have done to put himself out so publicly, which is a requirement, I think, to make all of this happen and like show the world that by accumulating talent, compute and all these ideas in one place, like that's what made all of this possible. Then everybody can see it. But like it's such an uncomfortable thing to have done.

46:35Yeah, well, you know, it's it's it's interesting because like he thinks on a timescale that's like more like a decade plus. and I think the the world kind of struggles to think beyond like a quarter forward yeah I've always felt like there's this kind of mismatch in there's a total mismatch and so it's like he'll say something and everybody's like that's crazy yeah and then three years later it's exactly where we are sometimes sooner than that and then it's like you know there's no like reconciliation backwards just like now he's saying a new crazy thing and people like oh you've been crazy all along.

47:07And that's like a weird thing to watch. And there's no, there's no sort of way to tie that together really. No, everyone's trying to figure out what's happening right now. Cause I think in some sense, the whiplash is so real. And I have like a lot of empathy for that as, you know, I spent a lot of time with like our customers with, you know, friends, family, like that are kind of like looking at me and calling me being like, what is going on? Like, what is happening? What is this codex thing? Like, why, why is everyone upset? And I think in Sam's head, we were already so far beyond that point in terms of what's coming, um, that it's trying to kind of bridge for people like where we're going relative to where we are.

47:40And I think it's disorienting. It's really an insane thing that you all have done and continue to do to pull all these pieces together. Like, I think this has got to be like the most hard mode company of all time. It's very, very impressive. I'm sure you like, I'm just used to it all, but hopefully you appreciate what a ridiculous feat you guys are pulling off. Well, I appreciate that. I very much feel like it is far from incomplete. far from complete it's highly incomplete um and i feel like you know it's like interesting when we formed the company early on the mission orientation of the company was like very strong but i always kind of tell people like in a very literal sense like i think a lot of companies have these kind of high level kind of lofty missions that you can't really actualize like it's like okay no shade on anyone specifically but like it's like don't be evil okay like that seems like a good thing um It's or it's like make the world more connected.

48:31Seems good. It's also like, OK, so if the plan is don't be evil, like then what? It's like very debatable from right. Well, how do you actualize that? What do you do? Right. And I think one of the kind of interesting things about OpenAI is the mission from day one is this very actualizable mission. We try and kind of run everything that we do somewhat through the lens of, OK, is this consistent with the outcome that we are trying to create? And I always used to joke at OpenAI is like there was a world where we talked about like, OK, we do the thing we say we're going to do and then we like go home and we're done.

48:58Like, it's like, okay, like, you know, that's the end of the story. And like, we all go back and, you know, in practice, is it going to work that way? I don't, I don't know. I don't think so, but maybe, but it is a company that has a very specific orientation toward a very specific goal. And I think amid all the craziness of all the things that are happening, like it's very focusing to be like, okay, guys, like there's still this one thing that we were really trying to deliver. It's very easy to come back to that mission and say, is this something that drives toward that outcome or not? And if it's not, we're just not going to do it.

49:27Love it. Well, this was really fun. And Brad, thanks for being time to do it. Yeah, good to see you.