Inside Dan Sundheim's Bets on Anthropic, OpenAI, and SpaceX

I want to spend a bunch of time talking about public versus private. You do both. You started investing in privates more than 10 years ago. You were one of the pioneers of this. You've got some amazing, huge private positions—SpaceX and lots of others.

Draw the contrast today, in 2026, between how the 2 markets feel. I'm curious about a lot of things here, like how you think about valuation differences, what one tells you about the other, and the business of privates versus a public equity hedge fund. I want to go into all of it, but at a high level, what is your feeling on the difference between the 2 markets?

It changes over time. It depends where you are in a cycle. I'd say right now I think that there's a lot of interesting opportunities in late-stage privates. It's a moment in time. You've never seen this: Some of the largest companies in the world by market cap are private right now.

Not only are they large and private, they are innovating in a way that's going to change the world, right? So this moment is particularly interesting. I think that, in general, private markets are less competitive. There's obviously the core skill set of analyzing businesses, which is the majority of what creates value, but there are other aspects of it too.

Oftentimes, there's no disagreement among private investors that a certain company is excellent, but that company has to want you to be an investor in the company. So it's competitive from the standpoint of being able to create a situation where you can invest in the best companies. But in terms of just pure—how difficult is it to generate returns by assessing companies?—I'd say the public markets are the most competitive in the world.

Even though they are less efficient than they were before, you still have more people in more places looking at information on companies. On the private side, just by definition, you have fewer people looking at every situation and less capital.

One difference that equalizes it a bit is that you don't have this dynamic on the private side of people doing things that are economically irrational because they're focused on the short term, or because their business model is not consistent with investing based on long-term intrinsic value, where you have that in the public markets.

In the private market, every time we're looking at a business, everybody's doing the same thing. We could talk to other firms that are investing in the same company. Their research may be different than ours, but it is all trying to get at the same answer. That's very different from the public market.

So there are fewer people competing, but they're all doing the same thing. Whereas in the public markets, there are tons of people competing, but they're all playing a different sport.

1. Public vs. Private Markets

If you think about the key companies in your private portfolio today—Anthropic, OpenAI, companies like SpaceX, Ramp, and so on—what does that group teach you? What do you think you see coming that maybe the public markets don't fully appreciate yet because they don't have that same exposure to these great private businesses?

As long as I've been doing private and public investing, at some points in time, there is synergy. But I'd say, if you go back to when we founded the firm, 25% of the time we looked at a private company, there was some synergy with what we were doing on the public side.

Now, because of AI and because there's so much innovation happening in the private markets, the synergies are just greater than I've ever seen before. I think if you're going to take a view on public companies that are deeply impacted by AI—which eventually will be almost every public company—you should have an opinion on where the technology is now, where the technology is going, and what the implications of it are.

Investing in those companies gives you that perspective in a way that I've never seen greater synergy.

When you first were considering your initial investments in OpenAI and Anthropic, did you pattern-match their businesses or their business models on anything that you had seen historically? Did they remind you of anything?

They were very different. When we first invested in OpenAI, I wouldn't say it was contrarian at all. To some extent, we invested originally at the $125 billion round. I don't think people were entirely sold on LLMs as a business model, but if you wanted to invest in LLMs as a business model, OpenAI was the one.

Whether you invested in LLMs or didn't invest in LLMs was debated quite a bit. I think there was a lot of uncertainty about the ultimate business model of these companies, so that was what we had to figure out. Anthropic was a different situation.

When we first invested in Anthropic, a number of people that I spoke to who I think are very smart drew the analogy of Uber versus Lyft: Why are you going to invest in the second player? In most industries, investing in the second player is not the path to glory.

The way I viewed it was that it was incredibly difficult at that stage to say who was going to be first and who was going to be second. The pattern recognition, to answer your question, for me on Anthropic was just reading Dario's essays and listening to him on podcasts.

When I look back at my career and look back at the companies we missed, like Amazon in the early days, I think, What could I have seen? If you look at their income statement, you would just see a sea of red. You wouldn't have seen anything.

The only telltale sign was reading Jeff Bezos's 1997 shareholder letter.

Just the clarity of thought and his understanding of what he wanted to achieve and how to create value for shareholders were greater than those of almost any public CEO I dealt with. If I had read that and almost ignored everything else, it would have been a really important sign and very profitable.

Dario struck me like that. It wasn't that the models at that point were so differentiated. I think they were considered to be 1 of probably 5, 6, or 7 players that could ultimately be important. There was still a lot of debate around LLMs as a business model, but I felt like he was incredibly skilled and extremely focused.

I place a lot of weight, rightly or wrongly, on clarity of thought and the ability to communicate as a CEO what you want to achieve and how you're going to achieve it. Especially in written form, because taking the time to write something down means you actually really have to go through everything you plan to do and express it in a way that makes sense to everybody else.

Dario just did that better than almost any CEO I've seen since Bezos.

How would you frame the debate today about LLMs as a business model, now that we know a bit more?

Back then it was, are these businesses ever going to generate an economic return? I think one analogy was, AI will be huge—so is air travel.

Airlines were not a good business, right? There was nothing differentiating one airline from another, and therefore the returns just go down to the cost of capital. Obviously, we took a different view, but that was like a 65/35, 70/30 degree of confidence in that at that point. It was more about the skew: if things played out like we thought and the business models were actually moated, it would be huge.

I think at this point, we're in a different place in terms of the debate that's important. If you want to look through a positive lens, businesses have taken slightly different lanes and excelled at different things within AI. OpenAI has been great at consumer and has had good traction in enterprise. Anthropic has been incredibly successful at coding.

There was a thesis when we first invested that APIs, or the business of having other software companies and developers plug into your model, would be commoditized because they could just use one model one day and another model the next day; it would be a race to the bottom. I think that debate is more or less irrelevant because you've just seen with Claude Code, and even with OpenAI's business, that these are durable businesses. Yes, you can switch, the same way you could switch AWS or Azure, but it's not worth it for a lot of businesses to do it, and there's sufficient differentiation among the models.

If you look at the underlying margins of these companies, they are not the margins that you see in a commoditized industry. The gross margins are quite high. The competitive landscape, I think, is not heavily debated. At this point, you probably have 4 or 5 LLMs that will be relevant in the long term. I don't see that changing.

It's not that there's not sufficient talent out there. It's just that the capital required to get into this business is too great, and these companies are too big at this point. Then you get the snowball: The more capital you have, the more compute you get and the better researchers you get. I think it would be very difficult, so the competitive landscape is not really in question. I don't think anyone would say that these business models are commoditized.

I think the real debate is that these are extremely capital-intensive businesses, to a degree that we've never seen before in the history of business. The question is, you're spending a ton of capital, and the ultimate return on that capital is unknown. It's not like a normal business that builds a factory and knows what it's going to sell. You are spending tons of capital to train a model, and the question is, do the scaling laws work such that the returns on that capital continue to be attractive? That means you'll be able to attract more capital and build better models.

Or are you going to get to a point where everyone looks back and says, “We raised too much money. We spent too much training models. We didn't get the economic return”? I think equally likely, if not more likely, people would say, “Ultimately, you will get the economic return, but it just happened slower than you would have thought.” Enterprise adoption just didn't take off as quickly as you thought, and therefore the problem is that when you are this capital-intensive as a business, it introduces financial leverage and operating leverage to a degree you don't see in normal businesses.

You don't have the luxury of 2 or 3 years of things going slower than you otherwise would expect. The scaling laws, the returns on capital, and the speed at which these tools and AI are adopted throughout the economy are the questions.

Is there anything that Netflix or something like that could teach us? That's another business that comes to mind where a crazy amount of capital was spent to build an asset, and then it gets amortized over a bigger and bigger user base. That's turned out to be a great stock, and one that I know you've owned a lot.

Yeah.

Is there any analogy between those two that's interesting to you?

When I was speaking to the executives at the LLMs, the way I framed this was, “Look, I think your business is some kind of combination between Netflix and Spotify.”

Netflix, in that, unlike other tech companies, you are spending a ton of money upfront to train these models. Once these models are trained, you go sell them at extremely high incremental margins. You don't know what the revenues are going to be from that fixed asset that you've built, but to the extent that you've built that asset, you want to sell it as much as possible so that you can get the cash flows to build the next model, and so on and so forth.

That's very similar to Netflix. They invested in content, and when you're an early mover in this kind of fixed-asset business, you invest heavily, you get the capital to invest heavily, you get the revenues, and you spread it out over an increasing number of people. You invest more in that fixed asset, and that just has a flywheel effect of generating more revenue, more content, more revenue, more content. Eventually, you get to the point where it's almost impossible to compete.

It's just a first-mover advantage, right?

Yeah. If you were to say what an important difference between Netflix and these models is, Netflix's content was differentiated. The models are more similar than they are different. At any given time, OpenAI may have a better model, or Anthropic may have a better model, but a lot of the expertise and innovation gets disseminated pretty quickly. These models are not terribly different.

That's where the Spotify analogy comes in. I think if you're Google or OpenAI, the differentiating factor will not necessarily be that Google gives you a better answer. If we were just to query Gemini or ChatGPT on something, I don't think it's the case that we would say definitively that one will give you a better answer over time.

However, the personalization matters. The more that these models know about you—how you live your life, your health, and all the things that are important to you—you build up this history with them, and it becomes very sticky. The music on Spotify is no different from Apple Music or Amazon Music, right? Theoretically, it's a pure commodity. What makes Spotify have pricing power? What makes it differentiated? Why would people be incredibly upset if you said they had to stop using Spotify? It's because it's personalized. They've tailored the service to take a product that is a commodity and personalize it to the point where you're willing to pay a premium for that commodity.

If you were giving advice to the executives at these companies and telling them what to lean into and what to look out for over the next 5 years, I'm curious what you would say. The scaling laws are so interesting in the sense that the models keep getting unbelievably better, and that probably means the revenue available is—who knows how big it could be? It could be the whole world. But the cost keeps going up by orders of magnitude. The Colossus 2 data center is this unfathomably big thing. It's like 2 gigawatts of power. It's crazy. What advice would you give them based on everything you've learned about these big, massive businesses?

The really interesting and challenging aspect of these businesses, the LLMs, is that the models they are building now, and especially in the future, can be applied to almost any aspect of the economy. You can take these models and make consumers' lives more efficient by having them be personal assistants. You could solve physics problems, help with drug discovery, and make enterprises more efficient. The TAM is certainly not the problem.

Focus is going to be a question mark. On the one hand, the more end markets you go after with a fixed asset, the better, right? You're spreading that cost over more end markets and having more revenue, which can then be reinvested. I think the flip side of that is that I rarely have seen any company succeed trying to go after multiple end markets at the same time.

Usually, you have an A team, and that A team is focused on one thing. Your culture as a company is oriented toward either consumer or enterprise. They just have different focuses. Even Amazon, which you'd say is the example of a consumer company that got into enterprise, got into it 7 years later, after they had even gone public.

Trying to do everything at once is tempting because, if you're successful, you're effectively advertising that fixed asset over more revenue streams. At the same time, you risk not being the best at any one thing. That is the trade-off, and I'm not sure we have the final answer.

Right now, the market has gone through periods where people thought Anthropic and OpenAI were Uber. Up until recently, the sentiment on OpenAI was more negative. I think OpenAI is taking the strategy of, “Let's do everything. We're going to go after Apple hardware, robotics, enterprise, consumer, and science.” They've been very successful in a lot of ways, but that's hard. I'm sure there are companies I'm not thinking of, but I can't think of many examples where that's been successful.

I understand the temptation to do it. Obviously, the difference versus history is that the smartest people in the world are all going to work at these companies.

So if anyone’s going to pull it off, they will. Anthropic took a different approach and just said, “We are going to focus on enterprise.” They tried consumer early on, but it became clear they didn’t have traction. So then they just went all in on enterprise, and they’ve had a lot of success with coding in enterprise.

Because they’ve now taken a market-leading position, generally sentiment is that Anthropic is winning, and they’re kind of now the Uber, if you want to use that analogy. I think this is going to go back and forth over time, and people like most things to watch.

Yeah, people probably get carried away in both directions, but I think those are the biggest differences. I would probably err on the side of focus, but I do understand the economic rationale for trying to do as many things at once.

The only thing is, early on when we invested in OpenAI—this is probably a year and a half ago—I said to them, “You have to do ads.” I said, “Yeah, you have to do ads.”

I understand. I’ve seen it so many times: people in Silicon Valley are allergic to the idea of ads. “I had this amazing pure technology product, and you want me to paint it with ads?” You see Anthropic’s Super Bowl commercial.

That being said, even the companies that were the most adamant about never getting into ads, like Netflix—if you go back and just listen to what Netflix was saying even 15 years ago, getting into ads, even Reed would have been like, “You are out of your mind. We would never do that.” Ultimately, they did it.

To me, it’s like, if you’re going to do it ultimately, you can’t really compete against companies that are using ads if you’re not. It’s very hard. If you’re ultimately going to do it, you might as well start earlier because you have to build a culture around it. It just takes time.

I don’t think it’s a big deal that OpenAI waited. But I was probably, rightly or wrongly, pushing for ads sooner than they’ve chosen to do it. I think now they’re probably going to get it right.

I’m so curious what you think is going to happen to the hyperscalers now. I saw this news report the other day that Anthropic is considering securing 10 gigawatts of its own power, which just makes me think, okay, they’re going to have the power. Why don’t they just create their own clouds, effectively? The hardware might be different, more focused on inference, et cetera.

Does that jeopardize these business models, which I think people have thought of as pretty damn good, at the hyperscalers? Do you think the future is different as a result of AI?

I do. I’ve thought this for probably about a year now, and I wouldn’t say there’s anything conclusive, but I am more confident in it. I am more confident in the thesis that the hyperscalers are a worse business model going forward.

2. The Future of Hyperscalers

It’s interesting because usually when you say something is a worse business model, you’re implying that growth is going to slow and margins are going to contract. I actually think you’re going to see the opposite. I think AWS and Azure—I maybe think Azure doesn’t accelerate, but certainly GCP. I think these businesses are going to accelerate for a while, just because their customer bases, Anthropic and OpenAI, are growing at an enormous pace. As they become a bigger part of the business, the growth accelerates.

The problem is that you went from a dynamic where AWS, Azure, and, to some extent, GCP had a customer base that was every corporation in the world. Therefore, they had fragmentation and the benefits of massive economies of scale that no single company could get. It was a very good business.

The problem going forward is that I think it’s highly likely that LLMs are going to be very concentrated in the hands of 4 or 5 companies. Those companies right now, as we discussed, are investing a ton. They’re cash-flow negative, and therefore they’re looking for compute anywhere they can get it.

But if we’re correct, and if anyone who owns these companies is correct, at some point in the next 5 to 10 years they will be generating enormous amounts of free cash flow. When that happens, I think they are likely to insource the compute.

Every year, AI is going to be a bigger percentage of the workloads at any hyperscaler. If you look out 10 years from now, I think the majority of the workloads will probably be AI. The LLMs will probably be providing a lot of those workloads, and I think it will make economic sense to take it in-house.

Yeah.

Right now, I think they look at the hyperscalers as more of a financing mechanism. These are well-capitalized companies with big balance sheets. But I don’t think these companies are better than them at building data centers.

Building CPU clusters is different than building GPU clusters. Running inference on GPUs is very different than workloads on CPUs. I think the LLMs are actually better at inference than the hyperscalers. Then you have this whole dynamic of neoclouds.

I think the initial view from most public investors was that this was pure overflow capacity. There weren’t enough GPUs, and these things would be dead as soon as Microsoft got theirs. I certainly would not make the case that they are fantastic businesses, but I don’t think they’re going away like people thought, because I think they’re better at running GPU clusters than the traditional hyperscalers are.

I think there’s a lot of interest from NVIDIA and other chip companies to make sure that the customer base is diversified. NVIDIA has a very big balance sheet, and they want to keep these players in business.

Over the next 10 years, I think these hyperscalers—AWS and Azure—will grow fast. My guess is that the margins will be challenged, both because the businesses are getting a lot more capital-intensive, because AI is capital-intensive—more capital-intensive than traditional workloads—and also because the customer base is getting more concentrated.

Meta is not a hyperscaler, but they insourced all their compute, because why would they pay? They’re just too big to use somebody on the outside.

If you think about the last couple of years, probably the best thing you could have done is just be long the AI buildout in all its various forms. Maybe that will remain true going forward, but it seems like the market is starting to think ahead to the other implications of AI.

Software—we’re talking about the week after software got absolutely decimated in the market, and everyone thinks, because of Claude Code and the amazing experiences they’re having with Claude Code, that software businesses are just screwed. I’m curious how you’re starting to think now beyond just the AI buildout.

It seems like AI is a thing. It’s going to be here now. The rest of the world has to start to absorb this technology. How are you thinking through that? I’m super curious what you think about the software sell-off, but even more broadly, the real economy now has to start to swallow this new technology. I’m so curious how you think that’s going to happen.

3. AI's Impact on Traditional Software

It is incredibly difficult to know, and I don’t think that’s because I don’t have perfect information. I think it’s just that these models are improving at a rate which is exponential, and understanding how that makes its way into the real economy and the implications is difficult.

I think you probably want to use a few frameworks. It really comes down to which companies you think will have a moat. In most circumstances, it’s fairly straightforward to identify moats that are protected from digital LLMs—just the proliferation of digital intelligence.

Once you get into robotics and other areas, you start to have to question the moats around some other traditional industrial companies, and also just the moats of globalization. How do countries that were arbitraging labor do relative to developed economies?

I think there are going to be phases of this. The first phase is with software, and that’s really because Claude Code entered the zeitgeist. All of a sudden, people see Claude Code, and all of a sudden they see on Twitter that people are saying, “Oh, I created a CRM system in a day.” I was like, “Oh my God, this isn’t good.” That’s kind of where people are now.

We wrote in our letter at the end of the year, and I said, “Look, the buildout is still going to be a thing in terms of places to invest in the public markets, but it’s increasingly going to become about which companies are affected.” There haven’t been any shorts in AI. There were basically no shorts prior to 2026, really. If you want to just say, “I’m going to short something because of AI,” you didn’t make a lot of money doing that.

In our letter, I said there are going to be a lot of shorts and some longs because of AI, and software is the first one. The market tends to swing to extremes. My guess is that software will have to evolve and will probably be a worse business model going forward.

But I think it’s the same way that Walmart evolved with e-commerce. Would they all have preferred that e-commerce never happened? Probably, at least at the beginning. It required an enormous amount of investment, their margins took a hit, and they had new competitors.

I think that will be the case with software too, where companies that have really great distribution and great business models, and are systems of record for companies—one of the things I did was ask the LLMs, “Are you designing your own ERP system?” And they said, “No, we’re buying a new ERP system from this company.” [Laughter] If they’re not doing it yet, at least you’re protected for a few years.

So I think systems of record are going to be difficult to displace. I think it’s neat to create software for small productivity enhancements, but if you really want to run your entire business on something like an ERP system or a CRM system—

I think it's going to be quite a while before people are just going to be vibe coding an ERP system. But I don't think you can just sit back as a software company and say, “We're a system of record. We'll be fine.” You're going to have to integrate AI and find ways, the same way Walmart integrated e-commerce into its business model. It was painful for a long time and probably is on the other side of it now.

This is fairly low conviction, because everything about AI's impact on the economy is inherently low conviction. I think everyone is likely underestimating how much these models are going to improve. To really think about what's going to happen, you have to almost not think like an investor. You have to think like somebody who's into science fiction.

Can you imagine a version of the story where this is all just overblown? Is there any coherent potential future where, 5 years from now, we're just like, “Actually, these things weren't that big of a deal,” or they were much less of a big deal than we thought they were going to be sitting here today?

The only way that would be the case—and even this argument, I think, wouldn't hold—would be if scaling laws just totally stopped. But even if scaling laws stopped, even if these models got no better, I think you probably have 3 years of just people learning how to incorporate AI into their daily lives or their companies.

Certainly, it wouldn't be good for the businesses if scaling laws stopped, but I still think you'd have pretty profound changes within the economy. Betting that scaling laws are going to stop is a really low-probability assumption. There's just nothing to suggest that's the case. In fact, everything suggests the opposite.

I think it's difficult to really get your arms around what that means, because we went from, “This is an interesting chatbot that's like Google,” to, “Oh my God, these are going to be solving problems that humans can't do.” We're already almost there.

I have a 12-year-old son who's interested in investing. I think your son's interested in investing, too; we've talked about that before as well. What do you tell him about the future of this profession given these tools? Surely it applies to us, too.

Elon Musk says—I think a line he's used is—it's better to go through life being an optimist and be proved wrong than a pessimist and be proved right. To be young and to be interested in something and be dissuaded because you're operating from a self-defeating mindset seems wrong.

It is likely that, at some point in the future, everything that we do is arbitraged away by AI. I think it would be naive of me to say no. Do I think that's happening anytime in the next couple of years? I don't.

What do you tell someone to focus on? First of all, unless someone is really interested in something, they're not going to be good at it. It might be the case that being a plumber or being an electrician is the most lucrative job in the world, but if you don't want to be a plumber or electrician, it doesn't help very much.

It's hard to tell your kids, “Don't do this” or “Don't do that” because it's going to be irrelevant. I saw a podcast recently with a Google researcher who left, and he said, “I don't even tell my daughter to study. It's just like, go out and have a good time.” I think that's a very destructive way of going through life.

You should go through life thinking that you want to achieve things, that you're interested in things, and that you're curious, in the same way as if this doesn't exist. If it turns out that whatever job you envision having no longer exists, then you'll have to adjust.

I talked with John and Daniel about the GameStop story. We can touch on it here, too. I'm curious what you most learned about yourself during that period of time when, lore has it, in February of 2021—so, GameStop was in January—you went to your team and basically said, “Look, the way we're going to calculate your comp this year is not going to include January. That was just a completely insane period of time.”

You took certain steps to create stability in the business or whatever, but in such a stressful period of returns, I'm curious what you learned about yourself or what it was like emotionally to go through that time.

It was incredibly difficult. I never want to come across as too exaggerative about my experience, because there are people who go through a lot worse things in life. But as an investor, I'd say that was about as bad as it gets.

We went from being top of the world—everyone thinks we walk on water—to everyone thinking we're going to go out of business. I have a lot of pride in what I do. I don't need to be celebrated, but I also really did not like having our firm and our performance dragged through the mud. Granted, it deserved to be treated that way, because the performance was very bad.

4. Surviving the GameStop Short Squeeze

It also is a bit lonely. During GameStop, there were probably a couple—1 or 2 other people—who were going through the same thing we had. I found it helpful to go back and read and listen to Ken Griffin's interviews in 2008 and to people that I respected.

It's lonely. It's a matter of testing your resilience. First of all, we never came close to going out of business. That was just nonsense. I was never going to quit, because even though we had made some mistakes, I deeply believed that we were still good at what we do, that we had something to offer the world, and that we could be excellent again. I was confident in that.

GameStop changed things. It was the beginning of a change in the market structure and on the retail side, so I knew we had to adapt to that. I didn't know exactly how that would play out. By 2021 or 2022, I'd been doing the job for 20 years, right? I never really had severe adversity, probably because at some point Andreas was just very quick to risk-manage. But I never really had that.

I thought to myself, “Am I really going to be the guy who quits the first time there's a severe bump in the road?” The analogy that people gave was “one day at a time.” Bill Ackman was like, “Look, every day, try to do something that makes things a little bit better.”

It's not something that changes overnight when you have that kind of a drawdown. Even if I hit the ball out of the park for 3 months, investors would say, “He's just volatile and crazy.” If I slowly and methodically did it, some people would just give up because they'd say, “This was just too crazy. We don't believe in him.”

It's impossible to disprove the negative narrative in the short term. It takes a lot of time—years. Acknowledging that this was not going to be something that you changed overnight—people's perception of you as an investor, people's perception of D1 as an attractive place to invest capital—was important. That was not going to change overnight, no matter what I did.

It was really about looking inwardly at the team, making sure that we were all on the same page about what we were trying to achieve, and that no matter how many people outside might doubt us, we were going to do it—or at least we were going to try very, very hard.

Was there a specific moment in the whole experience that most stands out in your memory as particularly salient, whether it was on the difficult side—emotionally difficult—or on the resilience side, like a decision that you were going to forge ahead? Does any one moment stand out?

The moment that stands out is—I mean, there are different moments that emotionally just hit you in different ways: news articles and friends calling you, saying, “Are you going out of business?” A lot of that was painful and something I had never had to deal with before. I'd never tried to be a public figure, and all of a sudden it became very public.

I think the most important moment was our semiannual investor dinners with our LPs. That's our primary form of communication. We write letters periodically, but we do these semiannual dinners where, over a period of 4 nights, we meet with all of our LPs.

Four straight dinners.

Yeah. It was June of 2022, at the beginning of June. The peak of our drawdown—the trough of our drawdown—was at the end of May 2022, and these dinners were scheduled for June 3, 2022.

Jeremy, the president of our firm, said to me, “We can't do these dinners. This is going to be a bloodbath.” To me, it was really clear. I said, “No, we have to do these dinners. This is the most important time to go out there and speak to our investors.”

The message was that we were going to do things differently—not in that the stock selection, all of that, was going to be the same, but the portfolio construction was going to be done in a way that was much less risk-prone.

The analogy I gave was that we were going to hit singles and doubles. It might take us longer to get back to the high-water mark because singles and doubles are not fireworks. But we felt that what we had gone through in 2022 was tough enough that, even if the right positive NPV thing would be to keep taking a ton of risk—and obviously, usually the best time to take a ton of risk is when you've lost a lot of money—emotionally, I would not be able to go through this again.

So we just said, “Look, we're going to run the business differently. We very much understand if this is not what you signed up for here.” Although I think at that point people were not saying, “Yeah, I really signed up for them to take on more risk.” They were [laughter] kind of like—I think most of them were happy to hear it, even if they didn't believe in it.

We really went about managing the firm differently. That was a pretty pivotal moment, just looking in the eyes of all the investors and feeling pretty horrible in every way. But there is something invigorating about a turnaround, and when you're going through something like GameStop, where the world is collapsing and there's nothing you can do, that's a very uncomfortable position. When things are really bad but you have a plan and you believe in that plan, it changes the perspective entirely.

I really did believe in the plan, and I believed in the team. All of a sudden, I felt like, “Okay, everybody else may doubt us, but I believe it.” We were now at the start of a mission to dramatically improve our returns, improve our firm, and earn back our reputation as great investors.

Assuming some did, what do you think of the people who redeemed from D1 during that time?

I don't harbor any ill will. Look, I think that the act of redeeming is, to some extent, something we deserved, right? Obviously, I appreciate it much more when people stayed.

I always start out these dinners, even in the worst times, by saying, “Ask me anything. Criticize me. It is my job to deliver for you. If I don't do it, it's on me.” Ultimately, I think that when you screw up in business, capital follows returns, and when you deliver poor returns, capital will leave.

We had a lot of great investors who stuck through it, and I deeply appreciate that more than I resent people redeeming. It's pretty asymmetric.

Can you do great investing, in your experience, meeting others, without having a pretty narrow band of excitability versus despondency?

For better or worse, I've always, from the first day I got the job, had a lot of confidence in what I was doing. I never stepped in and said, “I'm just better than everyone else. I'm going to be the most important hedge fund manager.” That was never it. But when it came down to looking at a company and making a decision, I felt confident in it.

When I feel confident in the analysis, I generally am pretty balanced. Is it possible for somebody to have a very volatile personality but train themselves to deal with the ups and downs of markets? I think the answer is yes. I think there are some hedge fund managers who have been truly, generationally great. You hear the stories that early on they were just throwing things at people on the trading floor and yelling, and ultimately they ended up being great. But you have to be able not to let that emotion influence your trading.

Yeah. If you think about the future of the world, given the crazy changes in technology, we haven't talked about SpaceX yet. That's a whole different dimension of an incredible technology curve that's going on, and that's a huge position for you. You mentioned earlier the importance of being optimistic. Where are you the most optimistic, and what parts of the world and its progression give you the most pause—things you have your eye on to be, if not worried about, at least keep an eye on?

I'm most optimistic about economic growth. It has to be the case that if you believe in scaling laws and you believe in AI, economic growth will be very powerful. This is the ultimate productivity tool, and what productivity does is allow you to grow while having disinflation, which is nirvana for markets. So I'm very bullish on that.

There are implications that flow from that, which are more macro, which is something we don't do, but that can cure deficits. Economic growth does a lot of great things for everybody, from hedge fund managers and CEOs to people who are in lower-level jobs. If a country is not growing, it's hard to have a better standard of living.

The part that makes me more uncertain is that I think we as humanity—I just think we've never encountered something like we're about to encounter. With that kind of profound change, we're going from the smartest animals on the planet. We were never the fastest or the strongest; we were just smarter than other animals. We're no longer going to be the most intelligent beings on the planet.

And so what are the implications of that?

I'm not really sure. I think there are a lot of negative externalities in that. As much as people like Dario, whom I respect a lot, might say, “Well, we're just going to give everybody a check, and everybody will just live off universal basic income,” I just don't think humans are wired to collect a check and go around and play sports all day.

Humans are wired to create relationships, create value, work, coordinate with other humans, and achieve things. I just don't think you're going to have a great society if it's just a bunch of people living off checks that come from the government as a result of this massive economic boom.

5. Big Private Bets: Rivian and SpaceX

One of the most interesting stories you've told me before was this time when you made similarly sized investments in Rivian and SpaceX at the same time. Can you tell that story? Both were big, big bets. Obviously, SpaceX is—you've got this huge position now.

I loved that story of this style of big-bet private-market investing in exciting technologies, and then the way things can go. If you could bring us back to those moments of decision—those were huge checks that you wrote into those companies—I would love to hear that story.

The thesis was that EVs were going to dominate the auto market, and that EVs were an entirely different kind of automobile, in that they were software. It was the equivalent of the iPhone versus Motorola and Nokia.

In the same way Motorola and Nokia were not able to move into smartphones because that was hardware and not software, there would be a few companies that would be able to do this successfully. Ultimately, autos are a bad business. Whether they're software autos or hardware autos, it's a bad business and a really tough business to scale.

And it was very capital intensive. The manufacturing didn't go as smoothly as it could have. The cost of delays in manufacturing, when you're ramping up and burning a lot of cash, is quite significant. The technology, I think, was always good, and not getting up the manufacturing curve very quickly meant you didn't get to scale fast enough.

I really believe that scale in EVs is going to be important, which is why Tesla kind of won. The IPO was great. It looked like a great investment. Ultimately, I don't know what our ultimate return was on Rivian, but it wasn't what we planned for when we made the investment.

The bad ones tend to be more obvious faster. The great private tech investments, I think, are sometimes slower to prove how great they are.

Because you have these amazing founders who are constantly making decisions that take the business in one direction or another, and ultimately the compounding of those decisions takes time but leads to great outcomes. It was pretty obvious to me that the launch business, at a minimum, was going to be a very good business. What they had achieved, I thought, was, from an engineering perspective, insane.

So to me, if I could buy a company that had achieved the most amazing engineering feat I'd ever seen at some multiple of revenue, with very little cash burn at that point, I didn't know what was going to come; I just knew that the skew was very good. Because if they achieved that, then who knows what they could do in the future?

What do you think about that business today? So much has changed since you first invested. What's your updated prognosis for it, or your thoughts about it?

The initial prognosis was always that they were going to be a low-cost provider of launch. I think the success of Starship—and I wouldn't say we're fully there, but I think we're pretty much goddamn there.

Yeah, you caught a skyscraper with chopsticks. It's pretty good: proof of full reusability and scale. Yeah, okay, there's more to come. Starship is a game changer, which we knew about fairly early on but didn't know if it would work. What that means, very simply, is that the cost of launching everything goes down dramatically.

The engineering that they've done with the satellites to harness solar power and be able to deliver really high-speed bandwidth has surprised me to the upside. There's a lot of software that goes into that, too, given that these networks of satellites are all communicating. The ramification of that, I think, is that the telecom market globally is now the TAM.

Whereas before it was like, okay, you live in whatever and you don't have cable to your home, so you get this Starlink thing. There are boats and planes, and there are people living in the lower 48. I think the cost—they've come so far down the cost curve—that in a relatively short amount of time, months or a few years, they are going to be dramatically cheaper than any other form of delivering broadband.

You just said how much you love shorting stocks. What is it about it that you like? You just don't meet that many people who are focused on this or really that good at it anymore.

6. The Art of Short Selling

My wife begs me all the time to stop shorting stocks. Anytime she looks at me, she's like, “Uh-oh. This is a short. It's a bad business.” So you have to be intellectually stimulated by it. Most people in the market are just not fundamentally based, period. Even if they are fundamentally based, they're not interested in shorting, or they pretend like they're shorting and kind of short indices or whatever.

Very few people are doing it. There are tons of people investing in things that are just based on stories because of social media and Robinhood, and so there are just endless amounts of shorts if you have duration and if you take a fundamental view.

Why do you think markets are less efficient now?

I think it's just the people transacting in the market, or the nature of the institutions transacting in the market. If you go back 10 or 20 years ago, mutual funds and long/short hedge funds were a big part of the market. Now it is a lot of passives, a lot of retail investors, people who are making investment decisions that are not based upon long-term considerations of intrinsic value, quants, and even multi-manager long/short funds.

While they are focused on fundamentals, they are, by necessity, short-term oriented. The majority of the time, the moves you see in the short term exaggerate the true change in intrinsic value of the company, which makes for a less efficient market.

One of the things that interests me a lot about you is—I'll use the word “loyalty.” Jeremy's been your partner. He's one of your best friends from growing up. The guy runs your family office and is your director of research. Lots of your key partners you've known for a really long time and are good friends of yours. I think you met your wife in college. I did, too, so that always perks me up when I hear that example. Can you say a little bit about how you feel about loyalty?

I know these people the best, and I've dealt with them through so many different things in life. I have a lot of confidence in their confidence. To me, there are a lot of people that I love in life who, for different reasons, are wonderful people and would be loyal, but they have to be really competent for the job. This is a very intense job, so the bar is extremely high, and the people that I've hired who have been friends of mine forever, I am just confident they've cleared that bar by a lot.

But when you're able to find people that you've known for a long time who liked you before you had any money or any signs that you'd ever have any money, that is a different kind of relationship. For me at this point, I don't like most people I meet. I don't know: are they nice to me because they think I can do something for them? There is a group of people in my life that have always been there, and they will be close, close, close to me for the rest of my life. To the extent I can work with those people, great. Now, as I said, they have to be excellent.

One of the things that you do for your portfolio is host this group chat that's just full of your thinking on what's going on in markets. One of the things that struck me the most about this is just how prolific you are in it. You're thinking and writing about this at all hours, all the time. Clearly, this is the thing that you just love and are passionate about.

What has been the impact of that—constantly communicating with the people that you care about, about markets? I ask the question because I just want to encourage and give examples to encourage other people to do the same, because I think it can be so powerful.

Look, when you're investing in a company privately, there is obviously a financial aspect to it that's the driver, but there's also a relationship part of it, in that you are signing up to hopefully help that person grow their business, be with them through ups and downs. When you're doing the initial investment, you spend a lot of time together, but then it's very easy for me to go months without communicating with the CEO on the private side if nothing's happening. I don't like that.

I like to be—if we have something that we can offer people, and they can just opt in, they can either read the stuff I write or not read the stuff I write—it is a way to broadcast-communicate with people that I want to be in touch with and that I want them to know us better as a firm, know me better as a person. I find that now, even if I haven't spoken to a CEO in 3 months and I call them, it's almost like they feel like they talk to me every day.

It's the same way when you meet someone on Zoom during COVID: you don't really—you never met that person in person. I know that being a founder is lonely. You are going through all kinds of issues, and so being around other founders—almost universally, the feedback I get is that founders like to be around other founders because they're the only people who can sympathize with and understand everything that they go through.

By having a bunch of them together in a chat, it's helpful for us from a business perspective. But I think it's also just—group therapy would be too strong of a word—but I think it's nice for them to know that these other people are part of this community that they're in. If they want to reach out to these people, they can, and they hear these people's perspectives. Some of these people are world-leading experts in areas like AI that are going to be impactful to companies that are not experts in AI.

Just getting that input, I think, is really helpful. We have a network of a lot of companies and a lot of industries. Being able to share the insights—not just my insights on markets, but having companies share insights with each other—and seeing how the world is impacting companies is, I think, useful.

Do you care whether or not D1 has enterprise value as a business? Is that something you think about? It's something I've started to think about more recently.

I think the answer is no.

Look, money to me is a scorecard. I want to have the best score. It is a really great positive externality of being a good investor, but maybe I will just be so intellectually interested by the idea of being a CEO that I want that to go from being 10% of my job to 30% to 40% of my job. That's how you would create enterprise value.

I'm just not there right now, and I want to deliver amazing returns. I think that'll be financially more than compensatory. Maybe one day, but I don't think hedge funds are a good business. Our business is horrible. It has amazing cash flows; it cash flows really well, but it has no terminal value.

I tell this to the companies I invest in. I'm like, "You have no cash flows and tons of terminal value. I have tons of cash flows and no terminal value. So we're good together. We can kind of arbitrage that." I think there are other businesses within asset management that have value. I definitely do not ever aspire to having hundreds of employees or something like that. That's kind of what you need to do to have enterprise value.

Why do you care so much about the scorecard? Where does the competitive drive come from?

This is what I've devoted my life to, right? Anything you devote your life to, you want to be great at, or at least have an impact that is tangible and measurable. I could be a family office right now, and there are plenty of positive things about being a family office. The drawback is that you're not in the arena.

I'm very collaborative with other investors. It's not like I'm sharp-elbowed, but being out there and being able to prove that we can be great—not just me, but our firm can be great—is invigorating. I think I'd be kind of bored if I was just investing my own money.

Going back to some of the history, I want to start with something I've never heard you talk about publicly, which is the early writing you did on Value Investors Club, and specifically the Orthodontic Centers of America short case that you wrote about. I'd love to hear the origin story of how you found VIC and why you started doing it.

I'm very interested in this idea of how much can come if you do some great posting online, which is a very early version of this. Maybe just tell us the story of VIC and that early passion for stocks.

It was 2002. I was working at a private equity group within Bear Stearns. I always had an interest in stocks, but I didn't have the toolset to analyze stocks until I got there. I deeply understood accounting and finance, and so I started just looking at stocks of my own.

The only way to really get exposure to investment ideas written up by hedge fund managers or investment managers was this site called Value Investors Club. I applied; you had to send an idea. Every week, you'd have tens of ideas posted by people anonymously, and you could read them. I would just consume everything. It was reading about merger ideas, long ideas, and short ideas. Every week, they paid $5,000 to the best idea.

I just got inspired by all the stuff I was reading and decided to try to find some of my own ideas. I did a few that were probably not particularly successful. Some were, some weren't. They were really deep value, trying to buy cigar butts—trying to buy a dollar for 50 cents.

After maybe 6 to 12 months, I had a portfolio of things I'd written up on Value Investors Club, and I decided I wanted to go work at a hedge fund. The first thing hedge funds ask you to do is talk about an investment idea, and so I had all these investment ideas.

7. Early Career

One of the hedge funds I interviewed at was a spinoff of SAC that did healthcare. I had no particular interest in healthcare, but it was just where I got an interview. Back then, hedge funds weren't as big of a thing. They said to me, "We want you to do a case study for the interview, and the company is called Orthodontic Centers of America."

For me, this wasn't a task; it was something I was really excited to do, because I had never had my work shown to or given to somebody who was a professional. I went home and spent hours and hours going through the financial filings and trying to build a model with it. I was pretty good at accounting. It was like a puzzle that just made sense.

I really tried to get deep into the financial statements, and nothing reconciled. Nothing made sense. I couldn't figure out what was going on. I kept going through it. It hit me that what they were doing was the simplest form of accounting fraud: capitalizing expenses that should have been expensed, in a big way. There were other things too, but that was the most egregious.

I was able to effectively prove that. Obviously, it wasn't incontrovertible proof, but it was pretty close, just by building up all the unit economics as they said they were and comparing them to the unit-level economics that you could actually decipher by going through their financial statements. It was clear. I did a write-up that was about 6 pages long before I went back to the follow-up interview, where I presented my case study.

I thought I was onto something. I thought, "Let me post it online first, and I'll get some feedback." I wasn't allowed to trade stocks because I was working at an investment bank, so I wasn't short the stock. I wasn't allowed in the stock. Value Investors Club was done anonymously with a tag name.

I posted online, and within a few hours, the stock started to go down. I was like, "That's cool. People are noticing." There were a couple of comments online. The market closed a few hours later, and I was watching online. There were more posts saying, "This is really interesting. Has anyone double-checked these numbers?" People were commenting.

The next day, the stock started to crater. The stock was down 20% to 30%. I started getting calls from people working at mutual funds who owned the stock, because even though it was anonymous online, I had told friends of mine at hedge funds, "You should look at this stock and short it. I think it's a fraud." They had told other people, and so I started getting calls at Bear Stearns from people at T. Rowe Price and Fidelity saying, "What's going on?"

I wasn't supposed to be doing that. You're working at an investment bank; the last thing you're supposed to do is post about companies that are frauds. I didn't even know if they were a client. The stock just got hammered.

I went back into the interview to present the case study, and at this point they were just like, "What did you do?" I was like, "Look, you told me to look at this. I thought it was a fraud." They were like, "Did you tell anyone that we told you to do this?" I said, "No." They were like, "You sure?" And I'm like, "Yeah. Nobody knows." They were like, "Okay."

They basically thought I was going to come back and tell them if the company was going to miss earnings. I didn't want to do healthcare, so I didn't work there, but I now had this write-up that could go around to different hedge funds. Most of them already knew about it because they shorted it after the write-up. That's how I got my job.

So you go and end up at Viking. You're there for a long time. You're the CIO, and you've got an incredible track record while you're there. If you think about the moment that you decided to go start D1, what was it like? Bring us back to that moment when you decided to go hang your own shingle and build this thing.

I started out as a banks analyst. That's what I did for the first couple of years. I still had a value bent. I think most investors who love investing start out with a deep-value bent because, if you want to read about great investors historically, most of them were deep-value investors: Ben Graham, Buffett.

I was working for somebody named Tom Purcell, who's an amazing investor. I realized that Tom was an awesome mentor, but I also realized that he was very well equipped to generate returns in financial services for Viking. If I wanted to grow in my career, I had to move into other areas.

Gradually, I took on other sectors, starting with healthcare, industrials, and TMT. The nature of those companies was different from banks. That was a learning process. There were years of covering different companies and different industries, and the deeper you got into it, the more you saw that what created value in TMT was different from what might create value in industrials or healthcare.

To me, if you love investing, my time at Viking was amazing because I was able to get exposure to every industry. Almost by 2016, I was managing just over half of Viking's capital, somewhere around 55% of Viking's capital. I'd started out in 2002 as an analyst with no portfolio, so I'd gone from no portfolio to a portfolio to eventually CIO, managing more than half the firm's capital, which was an abnormal percentage historically for Viking.

Viking is usually more diversified, but it was pretty clear to me that, from a business perspective, it was not in Andreas's best interest to have 1 person manage more than half the capital.

I don't think that would even be good for LPs. I recognized that I had pretty much achieved what I could achieve at Viking. Over time, I'd probably be managing a smaller percentage almost regardless of how well I did. I've always had a mindset of wanting to grow, get better, and achieve new things. I felt like there wasn't that much more for me to achieve at Viking, and I was 40.

I started a fund relatively late in life. I recognized that at some point, you just wouldn't have the energy to go do something like starting a fund. Starting a fund is obviously a big endeavor, and I felt like I had the energy. Everything came together.

What interests you about art? It's something that obviously you care a lot about and have devoted some time to understanding. What is it that attracts you?

I've always had more of a leaning toward the humanities than STEM, which is unusual, certainly in tech and somewhat in finance. That is why I perhaps look at my job as more art than science. The science is very simple. DCF I could learn how to do 25 years ago, and it hasn't changed. The humanities side interests me, and art is certainly one aspect of that.

I'm particularly interested in aesthetics. I like design, architecture, and art. To me, it's just beauty. You go to the beach and watch the wave; that's beauty. There's beauty in the world, and art is one example of beauty.

There's usually a story behind it, and there are people behind art. Art is important because it is created by people. I think the bull case in art would be that, as everything else is automated and in infinite supply because it's being created by AI, art created by people reflects emotion and often what's happening in the moment in the world when they're making that piece of art, or what's happening in their life.

If you apply the same aesthetic idea—the beautiful idea—what is the most beautiful business you've ever seen, or just the best business you've ever seen?

I think the best businesses are usually low-cost producers of something that's very durable. People underestimate the ability to provide a given product or service sustainably at low cost, where there's a positive feedback loop: low cost drives more volume, which drives low cost.

I could say a bunch of businesses that are really great. Moody's or S&P—those are great businesses when you're wrong. But something where the cost advantage is so substantial and so impenetrable, like SpaceX with launches or Costco with groceries, is amazing.

The only way to win in most businesses is to provide a great product at a low cost. The businesses that do that at scale and build a moat around it are amazing. Amazon's e-commerce business is amazing. There are so many amazing businesses, but very few monopolies. When they are a monopoly, what usually happens is they tend to get lazy, and the returns aren't as good.

What parts of the world do you think are underappreciated right now? When I look at your top 10 holdings, I actually didn't recognize a number of the companies. Lots of them are not in the U.S.; they're international. Where's your eye right now that you think the world is not paying enough attention to?

It's hard to say Europe is underappreciated. Europe has stagnated economically, so I'm not sure anyone should pay attention to it other than if you're a pure fundamental stock picker; it's an easier market.

I think there are really interesting things happening in Asia, just as politics change globally. You saw what happened in Japan, and for the first time Japan's probably going to become a military power at some point in the future again. That has all kinds of implications. I think there's a lot going on within defense, and obviously AI.

Geographically, Europe is always the most inefficient. I think Japan and Korea are probably pretty inefficient as well. A lot of retail investors don't recognize some really great companies that happen to be in Japan and Korea. They were not well positioned for the last 20 years because it was just digital companies. But when it comes to hard assets and good engineering, Germany, Korea, and Japan have a lot of companies that have excellent physical assets and engineering.

Is there anything else that we haven't talked about today that you have on your mind or are especially passionate about—things you're thinking about in the world?

The thing that troubles me the most, frankly, is that I think we are on a collision course with China over semiconductors. I'm not sure—I think there are ways to get out of that, but none of them are easy. To the extent that we don't figure that out, I think we're going to have something akin to the Great Depression.

It's very straightforward: Taiwan produces 90-something percent of the most advanced semiconductors, and everything we use depends on semiconductors. I would say it's almost as if you went back 50 years and there were only one country that produced oil, and oil was that important. We went to war over oil, even though you could get it all over the world.

8. Geopolitics and the Semiconductor Collision Course

Taiwan produces the vast majority of the leading semiconductors, and that is what powers everything. That supply chain is fragile. It's not like it's easy to replicate; it's easy to destroy. If that supply chain were to get screwed up or disintermediated, we would have an incredibly bad economy, on the order of a Depression-type economy.

I think probably a lot of people in government understand this. I've heard Scott Bessent talk about it. I think people understand it, but there are some scenarios that are okay for the global economy. There is no scenario I can think of where everybody's happy.

China's happy, Taiwan's happy, and the U.S. is happy. Somebody's going to be unhappy, either because the economy collapses or because their sovereignty is handed over.

What do you hope happens? That we build fabs here?

What I hope happens is that we replicate the supply chain over time in the U.S., and we work something out with China where they see a path to integrating Taiwan. If we replicate the supply chain, the risk is that we're probably less likely to defend Taiwan, in which case China will attack Taiwan anyway, right? Bad for Taiwan, fine for the U.S. China achieves its objectives.

I would like to see the world avoid a Depression, and that's going to require, I think, some understanding that we need 10 to 20 years to replicate this supply chain. Over that period of time, China will not screw up the world economy by being very aggressive with Taiwan. Eventually, there's a path where China feels comfortable that they will be able to reintegrate with Taiwan.

Usually, when dictators say something and they say it religiously, you should believe them. When Putin talks about the glory days of the Soviet Union, he may not always have the capabilities, but as soon as he did, he acted on it. Dictators usually do.

Every time Xi makes a speech that's of any importance in China, he emphasizes Taiwan. We can pretend this is going to happen at some time that's not relevant, but it's so important that AI just raises the stakes so much that it would affect everybody.

Zach told me to ask you what you've learned or what you like about the Real Dictators podcast.

Oh.

Basically just this. [laughter]

I like history. I like history and these things—sometimes just listening to what's happened in history, how many horrible leaders there are, and, as Charlie Munger said, “Tell me where I'm going to die so I never go there.” Learning about bad things so you don't go there, to me, is interesting, whether it's communism or fascism.

All of these things are still possible and relevant in the modern day, and we see seeds of them. Just understanding how things have played out in the past—and it tends to repeat itself—is interesting. Communism starts, but communism without dictatorship doesn't work, because eventually people realize it's not good and then want to change. The only way it doesn't change is if you have a dictator who's really benefiting from all this.

To me, that's interesting because a lot more things have gone wrong in the world than right. In our lifetime, things have gone right technologically and geopolitically, but over history more things have gone wrong.

Good leadership can be as impactful as, or more impactful than, bad leadership. You've worked with and invested in a lot of great leaders. I'm wondering specifically around CEOs, but broadly about leadership: What are you looking for in a leader?

Real passion, a strong competitive streak, and a desire to win. Somebody deeply engaged in the business, somebody who knows the details when you talk to them, and somebody who people want to work for.

9. Traits of Great Leadership

That could be because they like the person personally, or it could be because they don't necessarily love the person day-to-day. Like Elon Musk, I'm sure in the factory is not all giggles, but people are like, “I'm going to learn more by working with this person.” Business is more important than the leader because, eventually—although I kind of disagree with that—if you look over 30 years, sure, but over any medium period of time, businesses are just people. If you have amazing people, they make great decisions and bring great people, and my investing time frame is more like 5 to 10 years at max. I think people are more important in that time frame, especially in technology businesses.

I think it's come through today that you are clearly one of the most passionate stock pickers, stock people, markets people that's active today. Mostly, I like these things just to be inspirational to other people that might want to do the same thing. So it's been so much fun to do it with you. I ask everyone the same traditional closing question: What is the kindest thing that anyone's ever done for you?

My wife, right now. I was a pretty bad boyfriend in college. I was busy doing other things, and I was not very attentive. I was not somebody that you'd necessarily want to marry.

We broke up, and I remember I sat down with her. We went to get a drink just to catch up as friends, and I said, “I got a job at Bear Stearns.” I just remember she started crying, because it wasn't the easiest thing for me. I got it—I was fine—but it wasn't like Goldman Sachs was knocking down my door to get me to go. I didn't really work for the first 3 years of college.

10. The Kindest Thing

She started crying tears of joy, and I was like, wow, this person who I really didn't properly appreciate—how much they cared for me, how devoted they were, and how much they were rooting for me. To me, it wasn't an act that was kind; it was just a gesture that I was kind of taken aback by. Immediately, I walked out and I was like, “I'm going to marry that girl,” because I'm going to be better. I'm going to be a better boyfriend and husband going forward.

I love that story. I haven't heard a specific moment quite like that one in all the 500 times I've asked this question. So, an awesome place to close. Thanks for your time.

Awesome. Thank you.