Inside OpenAI’s $500B Valuation | Altimeter’s Largest Bet

0:00Do you think that the winner of the AI super cycle is going to be worth more than$150 billion at the time? It is clear that chat GPT has become a verb. OpenAI is on its path to being a winner of the consumer AI super cycle. And, you know, OpenAI is our largest investment in the history of Altimeter. Talent, this is where the war is now. You mentioned Meta, like they're generating about$100 billion of operating cash flow. To put that in perspective, OpenAI just raised this massive round,$40 billion. So they got the text moment, they got the voice moment, they got the image moment. Just this year alone, you've had Operator and Deep Research and chat GPT agents and Codex and GP5 now.

0:33This was an interesting release because I don't think it went the way many had expected. There was a lot of hype around it. It didn't go so well. We're halfway through the year and they've had such big releases. I feel like that is the secret sauce. That is the defensibility. Speed is the only note. Boundtour was actually a very misunderstood business for majority of its existence. And in large part because of how customer obsessed Boundtour is. Give us the rundown on Expo. How did you get into this investment? What do they do? Well, the punchline is the number one hacker in the world is no longer a human.

1:11Apoorv, welcome to Sorcery. Delighted to be here. Thanks for having me. Thanks for having me. We're at Altimeter's office. That's right. Welcome to Altimeter. Thanks. We have a lot to discuss today. We're going to go deep into OpenAI, the$500 billion valuation, the philosophy around ChatGPT's parasocial relationship that's formed with its users. We're also going to talk about the talent wars, all the money flowing into that, some of your recent investments. And then we'll go into your time at Palantir, how that cemented your career and how you think about things as a forward deployed engineer.

1:49So to start, let's get into the$500 billion valuation. When did you first invest into OpenAI? We've tracked OpenAI for a bit. Obviously, a very important company. We first invested last year. And ultimately, what gave us the confidence was it is clear that chat GPT has become a verb. OpenAI has been on its path to being a winner of the consumer AI super cycle. And if you study the past super cycles, let's start with the internet. One of the biggest technology super cycles produced a large winner in Google, two and a half trillion in market cap. The next one, mobile, created a large winner in Apple, three and a half trillion in market cap.

2:39Social, meta, 1.8 trillion in market cap. Enter Gen AI. Do you think that the winner of the AI super cycle is going to be worth more than 150 billion at the time? Definitely, right? And so the real question was, is OpenAI that winner? And while it's not a layup, we got increasing comfort that OpenAI with ChatGPT had caught magic in a bottle. It was a brand, not a technology, not a product. It was a brand, something that was impacting our day-to-day lives. And that's what ultimately gave us the confidence. I'm happy to dig into the numbers. Let's dig into the numbers. You know, I'll start with the consumer side of things.

3:21Consumer markets tend to be winner-take-most, if not winner-take-all sometimes, right? You look at search. Google has 90 % plus market share. If you and I were internet investors in the year 2001, and we had the hard job of deciding which search engine to back, you could have backed Lycos and Alta Vista and Ask Jeeves. And the truth is, you'd be right, because the numbers are all going top and top and right. All you had to do was wait until 2004, Google's IPO, and you'd have gotten 99 % of all gross profits generated in search. That's a little bit of how I feel about what's happening with ChatGPT right now.

4:02They've publicly disclosed they've got 700 million weekly active users. They recently crossed a big revenue milestone. I believe they announced$10 billion revenue run rate in June. and a similar dynamic is going on in AI where if you took the user count of ChatGPT on one side and all the other AI apps on the other side, let's do Perplexity and Cloud and Crock and Gemini and long tail of apps that people use, add them all up, multiply it by 10, it's probably still less than ChatGPT's user base. Same on revenue. And so we saw this, This is the sign of a power law playing out, the same power law that played out in the internet, the same that played out in mobile, the same that played out in social.

4:50And so the rough math as we see it is, they've announced 700 million weekly active users, let's say on a monthly active user basis, it's somewhere between one and two billion. Revenue was announced at 10 billion. So roughly 1 billion users, 10 billion revenue, earning about$10 per user per year, round numbers. we think over time the number of users could go up to three to four billion users we think on the monetization side over time it could go from 10 today to 60 70 dollars per user per year which is where meta and google and other large consumer platforms are and together you know p times q um three to four billion users multiplied by 60 70 dollars a user gets you to about $200 billion of a revenue opportunity over some medium amount of time frame.

5:41That is the consumer AI opportunity. That is what we're playing for. The other parts of the business, you know, the enterprise business, the API business, we'll have a shot as good as any other. And enterprise markets tend to be more fragmented, not as concentrated. and that's where we are, ChadGPT Enterprise is doing really well. We use it. So those are the numbers on OpenAI. That's how we think about it. And how much did you invest at the time? What was their valuation? We entered last year at the$150 billion round. What's unique with you and Altimeter is that you've only invested into OpenAI, whereas other funds have spread their bets amongst other LLMs.

6:28So how do you think about that concentration and what is your investment strategy? Our business is defined by power laws. The rough math of our business is there's 5 ,000 companies that raise every year that we track. 500 of those, so 10 % of those, will raise from tier one investors. 15 of the 5 ,000 will return over 90 % of the gross profits for a given vintage. You might have heard of the Pareto, certainly the 80-20 or the 90-10. 15 of 5 ,000 is 0.3%. This is not 80-20. This is not 90-10. This is 99.7 % and 0.3%. The power law is so sharp that very few companies actually return majority of the gross profits.

7:14And so when we think we found one that is on that power law, we think OpenAI is definitely on that power law. There's a couple others on that power law in our business. We try to concentrate into them. We had a similar experience with Snowflake. And OpenAI is our largest investment in the history of Altimeter. What sets OpenAI apart from Anthropic and even Google? It's a great question. All of those are formidable, formidable teams with incredible products. Obviously, Anthropic's crushing it with their API. Probably one of the most loved developer products out there, both with the API, but also the Cloud Code product.

7:56and so I would say they're winning in their own right in the enterprise segment with developers on the coding use case and doing a great job at it Google, same thing I mean, there's a lot of great products they've built I would say that a lot is yet to be seen from them I feel like the best of Google is ahead of them so a lot more to come there but at least that's how we see it I think those are the two most formidable players, as you mentioned. Going back, like circling back a little bit more. So 700 million weekly active users, they've developed a very strong consumer brand. They have a cult.

8:38They have a cult brand. They've achieved this. It's actually insane the rate they did this. I think you published a chart on this. And then also the other charts from East Mies West. Those are great. We'll add all these in. I'm curious from your standpoint as an investor and a user and understanding their commercial efforts. How does the consumer adoption bleed into enterprise? Look, I think ultimately there's three legs to the stool on the usage numbers that you highlighted. It's obviously the number of users. It's how much time they spend per day and what is the retention of those users. I would say those are the three legs of the stool that we measure to have a sense of the health of a consumer app.

9:25And on the first one, as I mentioned, I think they are far and above larger than any standalone AI app today. In terms of time spent, you know, we've published this analysis. They are far and above time spent per user per day compared to any of the other AI apps today. Actually, not just AI apps. one of the analysis we did is they're now larger than some of the mainstream consumer apps like X. Yeah. And retention, it's pretty wild, actually. So what we call smile curves are starting to show up in retention, meaning that in a chart where you see the number of users that stay on an app after they started the journey, typically you would expect an exponential decay of the users on this app.

10:13for very few apps, the curve actually goes up. So it looks like a smile. And chat GPT exhibits a smile curve. The other apps that exhibit smile curves are Instagram and TikTok. And the implication is users are finding so much value on this app that they want to come back to it. And how this bleeds into habit formation is I have this beautiful thing at my personal phone that I use for my personal life, and I want that at work. And so your question about how this bleeds into enterprise motion is similar to the effect that good software has or good devices have is you want to use at work what you have at home.

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11:45With same day and even same hour liquidity, access your funds anytime. Companies like Scale AI, DoorDash, Service Titan, HIMSS, Anthropic, Flexport, Robinhood, and Plaid trust and use Brex. Start today at brex.com slash sorcery. That's B-R-E-X dot com slash sorcery. How did this momentum start? I know that they have this crazy strategy, but I'd love to hear it from you. We've talked about this before, but could you just go deeper into the momentum that they build and how this is like, what's the formula? Look, I think it all starts with going back to November 2022. I actually have vivid memories of it.

12:31It was the same month that my wife and I got married. And so we were at our honeymoon playing with Chad GPT, just obsessed with it. and I think they caught magic in a bottle. That moment is so precious. There is no amount of launch prep you could do for what happened in November 2022, magic in a bottle. They had incredible viral adoption, hundreds of millions of users within a bunch of weeks and over time, if you look at the charts, the user growth has been a steady climb. And you can see the kinks when they've launched significant milestones. So for example, you know, in 2020, 2023 was like a steady climb.

13:16At some point, they took off the sign-in page and that you didn't have to log on to use ChatGPT and you saw like a kink. Then you saw the next big one in 2024 with advanced voice mode, right? Then you saw another one with Studio Ghibli, the image gen, you know, so they got the text moment, they got the voice moment, They got the image moment. And so it's, I think the strategy is as much as it is, like it's like the grind of the feature velocity is so high. Keeping up with OpenAI product updates is a full-time job. And that's the strategy, is ship fast. And I feel like that done at a consistent pace, I mean, just this year alone, you've had Operator and Deep Research and ChatGPT agents and Codex.

14:05And these are in GPT-5 now. I mean, we're halfway through the year and they've had such big releases. I feel like that is the secret sauce. That is the defensibility. Speed is the only mode. This is where the story gets funny, right? What we saw with GPT-5 was they turned off GPT-4. And that caused a lot of unrest with users. And there was a story that really came to surface. And Sam wrote a tweet about this. But it was really clear people had parasocial relationships with the chat itself. And so how do you think about this? It's probably a little bit more philosophical. But how do you think about that connection with the product?

14:48ChatGPT is no longer a website. It is no longer a product. It is a relationship. that users have with technology similar to the way, the relationship that I have with this phone. I use this for half a dozen hours a day. If I forget this at home, I will know within minutes. And I think ChadGPT is starting to get to a point where it is such a steady stream of a companion, a shop. I mean, I don't buy anything above$100 without consulting ChadGPT. Really? Like a lot of research. Spent so much time doing research. so much travel, so much learning, language learning, planning. And I think what happened over the weekend was, you know, the hashtag for forever was a reminder that like most important technology releases, this is changing the human experience.

15:46The same thing happened with desktop and PC. Gaming, you know, people got addicted to gaming. The same happened with mobile. the same happened with you know social networks and if i was to construct two axes molly on call it dopamine factor how much sugar is there in the product and and social call it network effects i would say chat gpt is actually quite safe and quite healthy because you know on the on the dopamine factor there's no doom scrolling there's no cat videos there's the amount of dopamine that you have on chat gpt versus i don't know pick your favorite twitter or instagram is a lot lower x the level of sugar is a lot lower whereas and then the other one which is network effects like if my friend um molly brad jammin or eric are on instagram i'm more likely to be there if they're on x i'm more likely to be there but if they're on chat gpt you know i don't have an incremental reason to be there.

16:47So the network effects are not as sharp right now. Despite that, this has become a dominant experience for relationship with people. And I think that's what the biggest takeaway I had over the weekend was, wow, this is becoming technology that people have a relationship with in a way that makes it incredibly sticky. Memory in particular, I think, adds so much context for your life that switching out of it would be so hard. And so I think those were some of the takeaways that I had as that weekend unfolded. In today's high-speed business world, staying ahead means using the smartest tools possible, including the powerful capabilities of artificial intelligence.

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18:11Time and time again, mostly, unless it's a CTO, it's ChatGBT. And it's because of the context and the memory. And when you feel it over and over and over again. Not everyone is having a parasocial relationship. Some people are extreme doomers. And David Sachs tweeted not too long after this, exposing the doomers, talking about the doomers. Guess what? We're not there yet. And what we've seen with these model releases over and over again, that the world is not ending. We're not going to get destroyed quite yet. It's going to take longer to build. Where do you think we are in the AI adoption curve?

18:48Yeah. Jeffrey Moore wrote this book called Crossing the Chasm. I'll refer to some of the concepts that he describes in that book. But I think David's not wrong. Look, there's, with any sufficiently advanced technology, you've got the tech enthusiasts or call it the developers or the super users who will adopt it first. And so I think of it as like technology that raises the ceiling and technology that raises the floor. And on the ceiling, you've got super users, tech enthusiasts, typically 10 to 15 % of the population. And then at the ceiling, you've got the vast majority of the population. The majority, even the skeptics.

19:29And so I think the way adoption plays out for really any technology is I evaluated on, hey, is this new product release raising the ceiling or is it raising the floor? So, for example, let's talk about raising the floor. What people who are the vast majority in laggards need is remove friction. Look, they don't wake up to use AI. They wake up to live their lives. and AI has got to find a job, find a way to be a part of their life. Advanced voice mode reduces the friction. I've got an action button dedicated to voice mode. Incredibly useful. 1-800-CHAT-GPT. WhatsApp with chat GPT or Meta AI. Those are, I would say, ceiling feature releases that will accelerate the adoption over the 6, 12, 18 months.

20:23Sorry, raising the floor. The reason the ceiling would be, you know, these are users who are vibe coding. They're coding their own daily software. They're experimenting with chat agents. They're playing with codecs. They're playing with cloud code. And there's a set of features that are targeted to them this year. This would be deep research. This would be the computer use operator. And I think both of these will go up over time. And ultimately, the biggest, I would say, experience will ultimately transcend beyond chat. Maybe we'll have wearables. Maybe what Johnny Ives is working on is a wearable.

21:04I don't know what it is, but it could be a pair of glasses, could be a phone, could be a device, could be a watch. and how you engage with that could really remove friction of communicating with a future interface. So I think those are some of the big things that I'm looking forward to. What a time to be alive. Maybe we've reached AGI. Maybe we're going to reach it soon. I don't know. The definition is unclear. But with AGI and superintelligence, we are approaching a lot of really fun, philosophical, evolutionary, existential questions. How do you think about humans' relation with technology and where this might go?

21:49AGI. And I think if I start with start at the start, like, you know, I started my career, I was an intern at a firm called Rocket Fuel, and we were using AI to target ads to maximize some reward function. And that predictive machine learning or AI felt magical to me. Two years later, in 2012, the team at AlexNet beat the ImageNet benchmark identifying cats and dogs better than humans. I thought that was magic. A couple of years later, I was at Palantra. I was a software engineer. I started using this tool called Kite. It was a coding copilot that would help you code faster. I thought that was magic.

22:29I thought that was great AI. Self-driving cars, GPT-3, voice mode. I mean, every two years or so, there's been a moment where I was like, wow, that's magical AI. Isn't that AGI? And so I guess my point is that the bar for what AGI is, is going up fast. And what we define to be, I guess, a lot of great intelligence is going up. And so now to actually answer your question, how that changes society, I think, you know, I wasn't around, but I'm told that there was a time when there was teams at banks whose job was to calculate the interest rates. And then the calculator came through. I, you know, I remember this.

23:13As a child, somebody gifted me an encyclopedia. I remember reading it cover to cover, but it's completely not really needed anymore. You could just look it up pretty quickly. You could look up really any fact pretty quickly. I feel the same way about most forms of intelligence, I suspect, in five to ten years, we wouldn't have to work to earn a living anymore. And what do you do in a world where you don't have to work to live? I suspect relationships would matter a lot. I suspect, as Victor Frankel talks about in his book, Man's Search for Meaning, creation would matter a lot. You would get a lot of joy in doing things that you enjoy and, you know, finding meaning.

24:04But it's certainly going to look like a brave new world. It's a great book. As we talk about the new releases, we have to talk about GPT-5. This was an interesting release because I don't think it went the way many had expected. There was a lot of hype around it. It didn't go so well. But my biggest observation, what I thought was pretty interesting out of this was Sam actually took action really fast. He immediately went back to work and was iterating off of the feedback. What do you think that means today for what it takes to be competitive as a founder, as a CEO? You know, I think one of the things that strikes me about Sam and the OpenAI team in general is the single word to define them is anti-fragile.

24:55I've seen this for years now. Remember the time the blip happened when Sam was for a hot second not at OpenAI? And it felt like, oh, what's going to happen to this org? You know, this is obviously a pretty big, big deal. But I feel like they've gotten stronger. very few orgs get faster over time i feel like open air has gotten stronger over time faster over time and the gpt5 release is not not anything different i feel like for an org that is antifragile they took they're taking incredible amounts of feedback they're working with all the teams and they're gathering feedback and fast the doors are open the lines are open and again a sign of uh evolving fast ultimately being the mode speed is the mode um and so that's what i think about the GPT-5 release, you know, I think it was a complicated release.

25:44It was the first time they released a system, not a single model. It has a model router. It makes, bakes in a lot of thinking of how much compute resources to allocate to a query coming in. And so, again, a sign of anti-fragility. Why was it so significant, technically speaking? Yeah. You know, I think each of our, each of the OpenAI prior releases have been typically a model or a set of models. This was the first time they released a system, a unified system that makes the decision of how much compute to allocate. Should I give you a quick response to a simple query like what's the capital of United Kingdom, which could just be a lookup?

26:21You don't even need to scramble the jets for that one, as opposed to a more complicated query like you're an investment analyst, help me analyze, gather feedback for, summarize the feedback on all the users of Neuralink so far. That would employ an orchestrator agent, it would go scrape the web, it would gather all the data, it would summarize it, it would probably package it together in a table, and that's probably like a three or four minute query. That delineation, which was previously something that the user would have to make in a model selector, is now made for you. That's a pretty significant change because remember the framework of raising the ceiling versus raising the floor.

27:00This is raising both. For a user who is, the majority of users who don't really want to select a model, this is great. This is simple, clean UX, a Google-like bar. You just start. And the same for on the ceiling. If you wanted to ask complicated questions, you don't have to think about, hey, what is the best model for me to do this? Is it 03? Is it 04 mini? Is it 03 pro? And I think that was one part of significance, called the consumer experience. The second part was, you know, obviously they focused very heavily on a couple of domains, coding and design and healthcare and so on. And so the feedback for those focused domains has been pretty good.

27:45Given they are a consumer product, do you think the structure of having these demos, these releases, is the most effective way for them to communicate? Or do you think they should adopt other things? I mean, they do go on podcasts. Like Sam definitely did a podcast tour beforehand, but how do you think about that and talking to who their real customer is? Because then people bring up benchmarking and how they perform and all of this sort of like stuff that, you know, is not what, you know, I don't know, Sally is doing on the couch before homework, you know? Yeah. You know, Ben Thompson wrote a great note on it.

28:23I'll share something he wrote about, which is that once you have a large enough user base, it's really hard for you to satisfy everybody. You just have to make choices. And not every upgrade, model upgrade, new product will please everybody. And I think that's kind of what happened here. Ben, on your question on benchmarks, I think the benchmarks are the starting line, but they're by no means the finish line. The benchmarks are kind of saturated, right? Do we need them? Like, what is the point? What do they even mean? I feel like they're all arbitrary. They're a starting line. Exactly. They're not the finish line.

29:03You typically start with, you know, a bunch of models that are at some zip code of a performance metric. And what you actually need is more proprietary evals. Let's say for Sorcery, you had 100 or 200 custom evals that work for your use case that you know work well. And then, hey, is the model doing better than a human on those evals? Or you might have particular features or just making sure there's no better tool user or inner debugging. So there's like a long tail of custom evals that I think do a better job now. than benchmarks? It was interesting to watch. I obviously love Calci, but I was watching the Calci chart on this for the essay of the month.