Dan Sundheim - The Art of Public and Private Market Investing - [Invest Like the Best, EP.460]

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This all comes from the fact that Rogo is built by finance professionals for finance professionals, and it's already being adopted by some of the most demanding institutions in the world. To learn more, visit rogo.ai slash invest. Hello and welcome, everyone. I'm Patrick O'Shaughnessy, and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus along with all of our podcasts at colossus.com. Patrick O'Shaughnessy is the CEO of Positive Sum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of Positive Sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Positive Sum may maintain positions in the securities discussed in this podcast. To learn more, visit psum.vc. My guest today is Dan Sundheim. Dan is the founder and CIO of D1 Capital Partners. I've wanted to do this conversation for a long time. Dan is one of those investors who thinks about markets and business constantly and has built a career entirely around that obsession. What makes him unique is that he operates at full intensity across both public and private markets simultaneously, with major stakes in some of the most important private companies in the world, like SpaceX, OpenAI, and Anthropic, while running a global public equity portfolio that spans nearly every industry and doesn't concentrate in the consensus names. We start at the beginning of his career with a story I've never heard him talk about publicly before how a short case he wrote on orthodontic centers of America and posted on Value Investors Club crashed the stock and helped him land his first job. He shares why he backed Anthropic at a moment when many people told him it was the Lyft to OpenAI's Uber, what reading Dario Amadei's essays reminded him of Bezos' letters to shareholders, and how he thinks about LLM business models through the lens of Netflix and Spotify. We spend time on the extraordinarily stressful moment in early 2021 when GameStop hit the firm and what Dan believes is the single biggest tail risk facing the global economy right now. It's hard to spend time with Dan and not come away struck by how much he genuinely loves his work. I hope you enjoy this great conversation with Dan Sondheim. 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 kind of one of the pioneers of this. You've got some amazing, huge private positions. Draw the contrast today in 2026 of the difference in how the two markets feel. I'm curious a lot of things here, like how you think about valuation differences, what one tells you about the other, the business of privates versus a public equity hedge fund. I want to go into kind of all of it. At a high level, what is your feeling on the difference between the two 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. Some of the largest companies in the world by market cap are private right now. And not only are they large and private, they are innovating in a way that's going to change the world. 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 is the majority of what creates value. But there's other aspects of it too. Like oftentimes there's no disagreement among private investors that a certain company is excellent. 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 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. It's still, you have more people in more places looking at information in companies, where on the private side, just by definition, fewer people looking at every situation and less capital. I would say that one difference that equalizes 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 in the short term, or their business model is not consistent with investment. based on long-term intrinsic value, what you have 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 than the public markets. So there's fewer people competing, but they're all doing the same thing. Whereas the public markets, there's tons of people competing, but they're all playing a different sport. If you think about the key companies in your private portfolio today, Anthropic, OpenAI, companies like SpaceX, Ramp, et cetera, what does that group teach you? What do you think you see coming that maybe the public markets don't fully appreciate yet that don't have that same exposure to those 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. in that 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 is the technology now? Where is the technology going? What are the implications of it? And 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 in that 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. So I don't think people were entirely sold on LLMs as a business model. But if you want to invest in LLMs as a business model, OpenAI was the one. Whether you invest in LLMs or didn't invest in LLMs was debated quite a bit. I mean, 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 in that 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 or why you can invest in the second player in most industries. Investing in the second player is not the path to glory. But the way I viewed it was, 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, Ianthropic 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, Amazon in the early days, and I think, what could I have seen? If you look their income statement, you would just see a sea of red. The only telltale sign was reading Jeff Bezos's 1997 shareholder letter, which was like the clarity of thought, his understanding of what he wanted to achieve and how to create value for shareholders was greater than 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 one of probably maybe that 0.5, 6, 7 players that could ultimately be important. There's still a lot of debate around LLMs as a business model, but I felt like he was incredibly skilled and extremely focused. and 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, you actually really have to go through everything you plan to do and express it in a way that makes sense to everybody else. And Dara 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 like, are these businesses going to ever generate an economic return? I think one analogy was AI will be huge, so was air travel. Airlines were not a good business. There's nothing differentiating about one airline from the other, and so therefore, the returns 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 moded would be huge. I think at this point, we're in a different place in terms of the debate that's important. The debate that's important now, if you want to look through a positive lens, which we do, you'd say that the businesses have taken slightly different lanes and have excelled at different things within AI. So OpenAI has been great at consumer and has had good traction 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 plug into your other developers plug into your model would be commoditized. It would just be a great to the bottom. I think that debate is more or less irrelevant because you've just seen with Cloud Code and even OpenAI's API business, these are durable businesses. And yes, can you switch? You can, 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 four or five LLMs that will be relevant in the long term. I don't see that changing. 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. and then you kind of get the snowball of the more capital you have, the more compute, you get better researchers. I think it'd 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 these are extremely capital-intensive businesses, capital-intensive to a degree that we've never seen before in the history of business. And the question is, you're spending a ton of capital and the ultimate return on that capital is unknown. So it's not like a normal business that builds a factory and kind of knows what they're 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, which means that you will 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. Or I think equally likely, 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 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. So you don't have the luxury of two or three years of things going slower than you otherwise would expect. I think the scaling laws, the returns on capital, and the speed at which these tools and AI is 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 there's a crazy amount of capital that was spent to build an asset, and then it gets amortized over a bigger and bigger user base. And that's turned out to be a great stock and one that I know you've owned a lot. 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 it is I said, 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 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 in that they invested in content. And when you're an early mover, this kind of fixed asset business, you invest heavily, you get the capital to invest heavily, you get the revenues, you spread it out over an increasing number of people, You invest more in that fixed asset and that just kind of has a flywheel effect of generating more revenue, more content, more revenue, more content. And eventually you get to the point where it's almost impossible to compete because it's just a first mover advantage is too great. Yeah. The difference, if you were to say like what is an important difference of Netflix versus 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. Anthropic may have a better model. But a lot of the expertise and innovation gets disseminated pretty quickly. So these models are not terribly different. And that's where the Spotify analogy comes in, in that I think if you're Google or you are OpenAI, the differentiating factor will not necessarily be that Google gives you a better answer. Like if we were just like to query Gemini or ChatGPT on something, I don't think it's the case that we would say definitively one will give you a better answer over time. However, the personalization matters. And the first mover advantage is like the more that these models know about you, how you live your life, your health, all the things are important to you. You build up this data history and it becomes very sticky. The music on Spotify is no different than Apple music or Amazon music. Theoretically, it's a pure commodity. What makes Spotify have pricing power? or what makes it differentiated? Why would people be incredibly upset if you said you had to not use Spotify anymore? It's because it's personalized. It's because they've tailored the service to take a product which 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 five years, I'm curious what you would say because the scaling laws are so interesting in the sense that like the models keep getting unbelievably better. And that probably means the revenue available is like, who knows how big it could be. It could be the whole world. But the cost keeps going up by like orders of magnitude. The Colossus 2 data center is this unfathomably big thing. It's like two 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 thing 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 you can make consumers' lives more efficient by having them be personal assistants. You could solve physics problems. You could help with drug discovery. You could make enterprises more efficient. And the TAM is certainly not the problem. Focus is going to be a question mark. And on the one hand, the more end markets you go after with a fixed asset, the better. You're spreading that cost over more end markets and having more revenue, which then can 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. that A-team is focused on one thing. Your culture as a company is oriented towards either consumer or enterprise. Even Amazon, which you'd say is like the example of a consumer company that got into enterprise, they got into it like seven years later after, even after they went public. So trying to do everything at once is tempting because if you successful you effectively just advertising that fixed asset over more revenue streams At the same time you risk not being the best at any one thing So that is the trade And I think that I'm not sure we have the final answer. Right now, the market has gone through periods where they thought Anthropic was Lyft and OpenAI was Uber. And 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. We're going to go after robotics. We're going to go after enterprise, consumer, 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. And 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. Anthropa took a different approach and just said, we are going to focus on enterprise. They tried consumer early on, but it came clear they didn't have traction. So then they just went all in enterprise. They've had a lot of success with coding and enterprise because they've now taken a market leading position. Generally, sentiment is that Anthropik is winning and they are like now the Uber, if you want to use that analogy. I think this is going to go back and forth over time and 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 as once. The only thing I, early on, we invested in opening AI, this is probably a year and a half ago, I said to them, you have to do ads. I understand. I've seen it so many times. People in Silicon Valley, the idea of ads is like, you know, they're allergic because it's like, I had this amazing, pure technology product and you want me to like- Taint it. Taint it with ads. And like, you see Anthropix, 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, it was like getting into ads. Even Reed would have been like, you are out of your mind. We would never do that. Ultimately, they did it. And to me, it's like, if you're going to do it ultimately, one, you can't really compete against companies that are using ads if you're not. 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 just takes time. I don't think it's a big deal that opening. I waited, but I was probably, rightly or wrongly, I was pushing for ads sooner than they've chosen to do it. I think now they're probably going to get it right. As your business scales up, everything gets more complex, especially your compliance and security needs. With so many tools offering band-aids and patches, it's unfortunately far too easy for something to slip through the cracks. Fortunately, Vanta is a powerful tool designed to simplify and automate your security work and deliver a single source of truth for compliance and risk. There's a reason that Ramp, Cursor, and Snowflake all use Vanta. It frees them to focus on building amazing differentiated products, knowing that compliance and security are under control. Learn more at vanta.com slash invest. I know firsthand how complex the tech stack is for asset managers, and seemingly every new tool and data source makes the problem even worse, adding more complexity, more headcount, and more risk. Ridgeline offers a better way forward, one unified platform that automates away all that complexity across portfolio accounting, reconciliation, reporting, trading, compliance, and more, all at scale. Ridgeline is revolutionizing investment management, helping ambitious firms scale faster, operate smarter, and stay ahead of the curve. See what Ridgeline can unlock for your firm. Schedule a demo at ridgelineapps.com. I'm so curious what you think is gonna happen to the hyperscalers now. I saw this news report the other day that Anthropik's considering securing 10 gigawatts now of their own power, which just makes me think, okay, they're going to have the power. The scale is going to be so big, why don't they just create their own clouds effectively? The hardware might be different, more focused on inference, et cetera. Does that jeopardize what these business models would be? 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 kind of thought this for probably about a year now. I am more confident in the thesis that the hyperscalers are a worse business model going forward. Now, it's interesting because usually when you say something is a worse business model, you're implying that growth is going to slow, margins are going to contract. I actually think you're going to see the opposite. I think that AWS, Azure, maybe Azure doesn't accelerate. Certainly GCP, I think these businesses are going to accelerate for a while just because they are, their customer bases, Anthropic, OpenAI are growing at enormous pace. And as they get to be a bigger part of the business, the growth is accelerating. The problem is that you went from a dynamic where AWS, Azure, to some extent GCP, their customer base was like every corporation in the world. And therefore, they had fragmentation and they had the benefits, massive economies of scale that no single company could get. And it was a very good business. The problem going forward is that I think that economically, it's highly unlikely that LLMs are not very concentrated in the hands of four or five companies. Those companies right now, they are obviously, as we discussed, they're investing a ton and they are cashflow 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 five to 10 years, they will be generating enormous amounts of free cashflow. When that happens, I think that they're likely to insource the compute. And every year, AI is going to be a bigger percentage of the workloads at any hyperscaler. And so if you roll out 10 years from now, I think that the majority of the workloads will probably be AI. The LLMs will probably be providing a lot of those workloads. And I think that it will make economic sense to take it in-house. Right now, I think that 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. And I think the LLMs are actually better at inference than the hyperscalers. And then you have this whole dynamic of NeoClouds. Now, I think that the initial view for most public investors was that this was like pure overflow capacity. There weren't enough GPUs and these things would be dead as soon as Microsoft got their GPUs. I certainly would not make the case that they are fantastic businesses, but I don't think they're going away like people thought. So I think they're better at running GPU clusters than the traditional hyperscalers are. And I think there's a lot of interest from NVIDIA and other chip companies to make sure that their customer base is diversified. NVIDIA is a very big balance sheet and they want to keep these players in business. So over the next 10 years, I think that these hyperscalers, AWS, Azure, will grow fast. I think the margins, my guess, 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 the customer base is getting more concentrated. Meta is not a hyperscaler, but they insourced all their compute. Why would they pay? I mean, 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 build out in all its various forms. And maybe that will remain true going forward. But it seems like the market a little bit is starting to think now ahead to the other implications of AI software. We're talking like the week after software got absolutely decimated in the market and everyone thinks because of cloud code and the amazing experiences that they're having with cloud code, like software businesses are just screwed. I'm curious how you're starting to think now beyond just the AI build. Okay. It seems like it is a thing, like 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? Maybe 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. 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 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 that you probably want to use a few frameworks. It really goes down to like, which companies do you think will have a moat in most circumstances? It's fairly straightforward to identify moats that are protected from digital LLMs, like 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 globally, how do countries that were arbitrarging labor do relative to a developed economy? So there's going to be phases of this where the first phase is software. And that's really because like clog code entered the zeitgeist. And it's like all of a sudden people receive a call code and all of a sudden they just see on Twitter that people are saying like, oh, I created a CRM system in like a day. And 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, I said, look, the build out is still going to be a thing in terms of like places to invest in the public markets. But it's increasingly going to become which companies are affected. And it's going to become there haven't been any shorts in AI. There was like basically no shorts prior to 2026, really. If you wanted to just say, I'm going to short something because of AI, you didn't make a lot of money. In our letter, I said, there are going to be a lot of shorts, some longs because of AI. Software is the first one. I think the market tends to swing to extremes. My guess is that software will have to evolve, will probably be a worse business model going forward. But I think the same way that Walmart evolved with e-commerce, and yes, would they have all its equal, prefer that e-commerce never happened? Probably, at least at the beginning. It required an enormous amount of investment. Their margins took a hit. They had new competitors. I think that'll be the case with software too, where companies that have really great distribution and great business models and their systems are record for companies. One of the things I did is I asked the LLMs, I said, are you designing your own ERP system? And they said, no, we're buying a new ERP system from this company. Quite teller. At least you're protected at least for a few years if they're not doing it yet. So I think systems of record are going to be difficult to displace. I think companies, while it's neat to create software for small productivity enhancements, 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 that 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 their business model. And it was painful for a long time and probably on the other side of it. But this is like, I'd say, fairly low conviction because everything about AI's impact on the economy is inherently low conviction because I think everyone is likely underestimating how much these models are going to improve. And 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 five 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? I think the only way that would be the case is, and even this, I think that argument 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 three years of people learning how to incorporate AI into their daily life 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. And betting that scaling laws are going to stop is a really low probability assumption. I mean, there's just nothing to suggest that's the case. And so, in fact, everything suggests the opposite. I think it's difficult to really get your arms around what that means. Because we went from like, this is like an interesting chatbot that's like Google to like, 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. We've talked about before as well. What do you tell him about the future of this profession, given these tools? Surely it applies to us too. And we may be smart now. 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 AI is going to be better than you, I think is like a very self-defeating mindset. So do I think that it is likely that at some point in the future, everything that we do is arbitraged away by AI? for sure. I mean, I think that that would be naive of me to say no. Do I think that's happening anytime the next couple of years? I don't. But it's almost like, 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. So it might be the case being a plumber or being an electrician is the most moated job in the world. But if you don't want to be a plumber and an electrician, it doesn't help very much. So 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 the Google researcher who left and he said like, oh, I don't even tell my daughter to study. It's just like, go out and have a good time. I think that's like a very destructive way of going through life. You should go through life thinking that you want to achieve things and that you're interested in things and you're curious and the same way as if this doesn't exist. And if it turns out that whatever job you envision having no longer exists, then you'll have to adjust. You've talked with John and Daniel about the GameStop story. We can touch on it here too. I'm curious though, what you most learned about yourself during that period of time when lore has it that February of 21, so January was GameStop, that 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. And so you took certain steps to create stability in the business or whatever. but in such a stressful period of returns. I'm just curious what you learned about yourself or what it was like emotionally to go through that time. It's incredibly difficult. I never want to come across as too exaggerative about my experience because there's 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 being like, Everyone thinks we're going to go to business. I don't think I have an enormous ego, but I have a lot of pride in what I do. And 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. It also is a bit lonely in that like, you know, there's during GameStop, there's probably one or two other people who are going through the same thing you had. I found it helpful to go back and read and listen to Ken Griffin's interviews in 2008 and people that I respected. But it's lonely. It's a matter of testing your resilience. First of all, we never came close to going into business. That was just nonsense. But I never was going to quit. Even though we had made some mistakes, I deeply believe that we were still good at what we do and that we had something to offer the world and we could be excellent again. And I was confident in that. But, you know, GameStop, it was the beginning of a change in the market structure on the retail side. So I knew we had to adapt to that. I didn't know exactly how that would play out. By that point, by 2021, 2022, I've been doing the job for 20 years. I never really had severe adversity, probably because at some point, like Andreas, he was just very quick to risk manage. But I never really had that. And so I thought to myself, am I really going to be a guy who quits the first time? I think the analogies that people gave was like one day at a time. It was like Bill Ackman was like, look, every day try to do something that makes things a little bit better. Because it's not like something that when you have that kind of a drawdown, if I hit the ball out of the park for like three months, like investors would be like, he's just volatile and crazy. And 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. So it's impossible to disprove the negative narrative in the short term. It takes a lot of time, years. And so acknowledging that this was not going to be something that you changed overnight, people's perception of you as investor, people's perception of D1 as an attractive place to invest capital, that was not going to change overnight no matter what I did. It was looking inwardly at the team, making sure that we were all on the same page in 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 one moment in the whole experience that most stands out in your memory as particularly salient, whether it was on the difficult side, like emotionally difficult, or on the resilient side, like a decision that you were going to forge ahead? Does any one moment stand out? There are different moments that emotionally just hit you in different ways, like news articles and friends calling you saying, are you going into business or a lot of that. And obviously those things are painful and something I had never had to deal with before. I've never tried to be a public figure. And all of a sudden it became very public. The most important moment was we do semi-annual investor dinners with our LPs. That's our primary form of communication. We write letters periodically, but we do these semi-annual dinners where over a period of four nights we meet with all of our LPs. It was June of 22, beginning of June of 22. Trough of our drawdown was at the end of May of 2022. And these dinners were scheduled for like June 3rd Jeremy the president of our firm he said to me he said like we can do these dinners Like you know this is going to be a bloodbath To me it was like really clear I said no we have to do these dinners And this is the most important time to go out there and speak to our investors. I had a message I wanted to convey. Message was that we were going to do things differently. 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 like, we're going to hit singles and doubles. It might take us longer to get back to the high watermark because singles and doubles are not fireworks. But we feel like what we've gone through in 21, 22 was tough enough that like, even if like the right positive MPV thing would be to just keep taking a ton of risk. And obviously usually the best time to take a ton of risks when you've lost all the 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 like, yeah, they signed up for them to take on more risk. They were 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. And so that was a pretty pivotal moment, just looking in the eyes of all the investors and feeling pretty horrible in every way. There is something invigorating about turnaround. When you're going through something like GameStop and like there's the world collapsing and there's nothing you can do, it's like that's a very uncomfortable position. Even if things are really bad, when you have a plan and you believe in that plan, it changes the perspective entirely. And I really did believe in the plan and I believe in the team. And so all of a sudden I felt like, OK, everybody else may doubt us, but I believe it. And we are now the start of a mission to dramatically improve our returns, improve our firm, and earn back our reputation as being great investors. Assuming some did, what do you think of the people that redeemed from D1 during that time? I don't harbor any ill will. I mean, look, the act of redeeming is like, to some extent, we deserved it. I mean, obviously, I appreciate it much more when people stayed. I always start out these dinners, even though it was the worst time. I say, ask me anything, criticize me. It is my job to deliver for you. If I don't do it, it's on me. I ultimately 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 that stuck through it. And I deeply appreciate that more than I resent people redeeming. It's pretty asymmetric. What's interesting about the story is when you ask around, most people would say that you have an incredibly calm, like your resting heart rate is very low. Like you're always between a four and a six. Like you're never overly excited when things are going well or overly despondent when things are going poorly. And I'm curious how much you think that disposition matters for great investing. Can you do great investing in your experience meeting others without having like 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. That was never it. But when it came down to looking at a company and making a decision, I felt confident in it. And when I felt 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 that have been truly generationally great. And you hear the stories 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 to not let that emotion influence your trading. 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 like an incredible technology curve that's going on. You mentioned earlier the importance of being optimistic. Where are you the most optimistic and what parts of the world and its progression gives you the most pause or things you have your eye on to be, if not worried about, keep your eye on? I'm most optimistic in economic growth. And I think it has to be the case that if you believe in scaling laws and you believe in AI, that economic growth will be very powerful. I mean, this is the ultimate productivity tool. And what productivity does is allows you to grow while having disinflation, which is like nirvana for markets. So I'm very bullish on that. And then there's implications that flow from that, which are more macro, which is something we don't do. But like that can cure deficits, do a lot of great things. Like economic growth does a lot of great things for everybody from hedge fund managers and CEOs to people in lower level jobs. If a country is not growing, it's hard to have a better standard of living. That's my more optimistic take. The part of me is more uncertain, is that I think that we, as humanity, we've never encountered something that we're about to encounter. So with that kind of profound change, like we're going from the smartest animals on the planet, we were never the fastest or the strongest, just we're smarter than other animals. we are 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 that there's a lot of negative externalities in that I don't think humans, as much as people like Dario, who I respect a lot, might say, well, we're just going to give everybody a check and everybody just kind of live off universal basic income. I just don't think humans are wired to just collect a check and go around and play sports all day. humans are wired to create relationships, to create value, to work, to coordinate with other humans and achieving things. And I just, I don't think you're in a great society if it's just a bunch of people living off of checks that come from the government as a result of this massive economic boom. One of the most interesting stories you've told me before was this time when you made, I think, similarly sized investments in Rivian and SpaceX at the same time. Can you tell that story, both big, big bets. Obviously, SpaceX, you've got this huge position now. But I loved that story of this style of big bet, private market investing and exciting technologies, and then the way things can go. And if you could bring us back to that, those moments of decisions, those are huge checks that you wrote into those companies. I would love to hear that story. Thesis was that EVs were going to dominate the auto market and that EVs were an entirely really different kind of automobile, like in that they were software. And it was the equivalent of like the iPhone versus a Motorola Nokia. The same way Motorola and Nokia were not able to move into smartphones because that was like hardware, not software. There'd be few companies that would be able to do this successfully. Ultimately, autos are a bad business. It could be software autos, hardware autos. It's a bad business. And it's a really tough business to scale, very capital intensive. The manufacturing didn't go as smoothly as it could have. And the cost of delays in manufacturing when you're ramping up and burning a lot of cash are 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. And I really believe that scale in EVs is going to be important, which is one of the reasons why Tesla's won. The IPO was great. It looked like a great investment. But 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 just constantly making decisions which take the business in one direction or another. And ultimately, the compounding those decisions takes time, but leads to great outcomes. SpaceX was pretty obvious to me that the launch business at a minimum was going to be a very good business. And what they had achieved, I thought, was just like from an engineering perspective, insane. So to me, if I could buy a company that had achieved the most amazing engineering fee 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 SKU was very good. If they achieve 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 thoughts about it? The initial prognosis was just always that they were going to be a low-cost provider of launch. I think the success of Starship, I wouldn't say we're fully there, but I think we're pretty much there. Approve full reusability and scale, like, 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. And what that means very simply is that the cost of launching everything goes down dramatically, 97, whatever percent. And 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. And there's a lot of software that goes into that too, just given these networks of satellites are all communicating. The ramification of that, I think, is that the telecom market globally is now the TAM. They've come so far down the cost curve. I think that in a relatively short amount of time, months, few years, they are going to be dramatically cheaper than any other form of delivering broadband. You said how much you love shorting stocks. What is it about it that you like? Because you just don't meet that many people that are focused on this or really that good at this anymore. My wife begs me all the time to stop shorting stocks. It's a bad business. You really have to be intellectually stimulated by it. Most people in the market are just not fundamentally based, period. And even if they are fundamentally based, they're not interested in shorting or they pretend like they're shorting and they 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, like because of social media and because of Robinhood. And there's 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 markets. If you go back 10, 20 years ago, mutual funds, long, short hedge funds, they 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. They're not based upon long-term considerations of intrinsic value. Quants, even multi-manager, long, short funds, while they are focused on fundamentals, by necessity, they are short-term oriented. If you're focused on trying to get an edge in the short term, that is extremely efficient. And it's a game I just don't play. You have firms which are incredibly sophisticated using amazing quantitative methods to go through alternative data. There's absolutely no edge there. Once you go beyond any kind of short-term event and you start to think about what is the business worth? What are the long-term cash flows? what are the quarters by forces attributes of the company, that's when the competitive set gets pretty thin. And frankly, the more people focus on the short term, the more opportunity there is to arbitrage that and have a medium term view. I don't think anyone knows it's going to happen past three years for most companies and for the economy as a whole, it's hard to predict. And so I don't consider myself to be an investor that just buys and holds things for five or 10 years. 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Every investment firm is unique and generic AI doesn't understand your process. Rogo does. It's an AI platform built specifically for Wall Street, connected to your data, understanding your process, and producing real outputs. Check them out at rogo.ai slash invest. Ridgeline is redefining asset management technology as a true partner, not just a software vendor. They've helped firms 5x in scale, enabling faster growth, smarter operations, and a competitive edge. Visit ridgelineapps.com to see what they can unlock for your firm. One of the things that interests me a lot about you is, I'll use the word like loyalty. So Jeremy's been your partner. He's one of your best friends from growing up. The guy runs your family office, your director of research, lots of your key partners you've known 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 and kind of the role that all those data points suggest? There's a few things to consider. Like, I know these people the best. And so I've just dealt with them through so many different things in life. and I have a lot of confidence in their competence. So to me, there's a lot of people that I love in life for different reasons and are wonderful people and would be loyal, but they have to be really competent at the job. This is a very intense shot. The bar is extremely high and the people that I've hired that are friends of mine forever, I'm just confident I've cleared that bar by a lot. But when you are able to find people that you know for a long time and liked you before you had any money or any signs you'd ever have any money. That is a different kind of relationship. For me at this point, I don't know. They're nice to me because they think I can do something for them. They're a group of people in my life that have always been there and that they will be close to me for the rest of my life. And to the extent I can work with those people, great. But as I said, they have to be excellent. One of the things that you do is for your portfolio host, this like group chat that's just full of your thinking on what's going on in markets. And one of the things that struck me the most about this is just how prolific you are in it. Like you're just thinking and writing about the shit at all hours, all the time. Clearly like this is the thing that you just love and are passionate about. What has been the impact of that? Like constantly communicating with the people that you care about, about markets. I asked the question because I just want to give examples to encourage other people to do the same. It can be so powerful. 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 I find that 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. 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 I want to know us better as a firm, know me better as a person, know us better as a firm. I find that now, even if I haven't spoken to a CEO in like three months and I call them, it's almost like they feel like they talk to me every day. It's the same way like 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. 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 there's the only people that can actually sympathize and understand everything that they go through. And so by having a bunch of them together in a chat, it's helpful to us for 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 and that they want to reach out to these people they can and they hear these people's perspective. And 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. So just getting that input, I think, is really helpful. We have a network of a lot of companies, 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. 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. Money to me is the scorecard. I want to have the best score. It is a really great positive externality of being a good investor. And maybe I will just be so intellectually interested by the idea of being a CEO that I want that go from being 10% of my job to 30% to 40% of my job. And that's how you create enterprise value. I'm just not there right now. And I want to deliver amazing returns. That'll be financially more than compensatory. Maybe one day, but I don't think hedge funds are a good business. Objectively, our business is horrible. It's amazing cash flows. It has no terminal value. I told this to my companies I invest in. I'm like, you have no cash flows and tons of terminal value. I have tons of cash flows, no terminal value. So we're good together. We can kind of arbitrage that. But I think there's other businesses within asset management that have value. I definitely do not ever aspire to having hundreds of employees or something like that. And 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? And so if anything you devote your life to, you wanna be great at, or at least having an impact that is tangible and measurable. I can be a family office right now, and there's plenty of positive things about being a family office. The drawback is like you not in the arena And I very collaborative with other investors It not like I sharp elbowed but being out there like being able to prove that we can be great and not just me like our firm can be great is invigorating I think I be kind of bored if I was just like investing my own money. Going back to some of the history, something I've never heard you talk about publicly is the early writing you did in Value Investors Club and specifically the Orthodontics of America Shortcase that you wrote about. I'd love to just hear the origin story of how you found Vic, why you started doing it. I'm very interested in this idea of how much can come if you do some great posting online. This is a very early version of this. So 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 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. You had to send an idea. I applied and like every week you'd have tens of ideas posted by people anonymously. You could read them. I would just consume everything. So it was like long ideas, 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. After maybe six, 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. First thing hedge funds ask you to do is talk about investment idea. And so I had all these investment ideas. One of the hedge funds I went to interview at, it was a spinoff of SAC that did healthcare. And they said to me, we want you to do a case study for the interview. The company is called Orthodontics Centers of America. So I, for me, this was not like a task. It was like something I was really excited to do because I had never had my work given to somebody who was a professional. I went home and I spent maybe like hours and hours going through the financial filings and trying to build a model. I was pretty good at accounting. I really tried to get deep into the financial statements and I realized nothing reconciled. Nothing made sense. It hit me that what they were doing was the simplest form of accounting fraud, which is just capitalizing expenses that should have been expensed in a big way. There are other things too, but that was the most egregious. I was able to effectively prove that. It wasn't incontrovertible proof, but it was pretty close. just by building up all the unit economics as they said they were, comparing them to the unit level economics that you could actually decipher by going through their financial statements. And it was clear I did a write-up that was about six pages long. It was good. It was well done. Before I went back to do the follow-up interview where I presented my case study, I was like, I think I'm onto something here. 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 on the stock. Value Investors Club is done anonymously with a tag name. So I posted online. Within a few hours, the stock started to go down. I was like, that's cool. People are noticing. There's a couple of comments online. The market closed a few hours later, whatever. I'm watching online. There's some more posts being like, this is really interesting. thing. Has anyone double checked these numbers? There's people commenting. Next day, stock starts to crater. Stock's down like 20%, 30%. I started getting calls from people working at mutual funds who own the stock. Because even though it was anonymous online, I had told friends of mine at hedge funds, I'm like, you should look at this stock and short it. I think it's a fraud. And they had told other people. And so I started getting calls at Bear Stearns from people at T. Rowe Price and Fidelity. You're working at an investment bank. The last thing you're trying to do was supposed to be posting about companies that are frauds. I didn't know if they were a client. The stock just got halved. I went back into the interview to present the case study. At this point, they were just like, what did you do? And I was like, look, you told me to look at this. I thought it was a fraud. They're like, did you tell anyone that we told you to do this? I was like, no, no. They're like, you sure? And I'm like, yeah, yeah, yeah. Nobody knows. And they're like, we basically thought you were going to come back and tell us that they were 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. And most of them already knew about it because they would short it after the write-up. That's how I got my job. You end up at Viking. You're there for a long time for the CIO. You've got an incredible track record while you're there. If you think about the moment that you decided to go start D1, bring us back to that moment 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. 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 realized that Tom was very well equipped to generate returns in financial services for Viking. And so if I wanted to grow my career, I had to move it to other areas. Gradually, I took on other sectors, like starting with healthcare, industrials, TMT, and the nature of those companies was different than banks. That was a learning process. It was just like years of covering different companies and different industries. The deeper you got into what created value in TMT was different than what might create value in industrials or healthcare. So 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 55% of Viking's capital. And I had started out in 2002 being an analyst with no portfolio. I'd gone from no portfolio to a portfolio to eventually CIO to managing more than half the firm's capital, which was an abnormal percentage historically for Viking. Viking's usually more diversified. It was pretty clear to me that from a business perspective, it was not in Andreas' best interest to have one person manage more than half the capital. I don't think that would be even good for LPs. And so I kind of recognized that I had pretty much achieved what I could achieve at Viking. Over time, I'd be probably managing a smaller percentage, almost regardless of how well I did. I've always had a mindset of like, I want to grow, I want to get better, I want to achieve new things. And I kind of felt like there wasn't that much more for me to achieve as Viking. And I was 40. I started a fund relatively late in life. I kind of recognized that at some point, you just wouldn't have the energy to go do something like starting a fund is obviously a big endeavor. I felt like I had the energy. And so everything kind of came together. What interests you about art? Like it's something that obviously you care a lot about. You've devoted some time to understanding. What is it that attracts you? I've always had more of a leaning towards humanities than STEM, which is unusual and certainly tech and somewhat finance. That is why I perhaps look at my job as more art than science. The science is very simple. The DCF, I could learn how to do it 25 years ago and it doesn't change. The humanity side interests me, and art is certainly one aspect of that. And I am particularly interested in aesthetics. I like design. I like architecture. I like art. To me, it's just beauty. You go to the beach and watch the waves. 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's people behind art. Art is important because it's created by people. And I think the bold case in art would be as everything else is automated and in infinite supply because it's being created by AI. Art created by people reflects emotion and oftentimes like 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? Just like the best business you've ever seen. I think that the best businesses are usually low-cost producers of something that's very durable. And I think people underestimate the ability to provide a given product or service sustainably at low cost and where there's a positive feedback loop of low cost drives more volume, which drives low cost. And I think I could say a bunch of businesses which are really great, like Moody's or S&P. Those are great businesses, don't get me wrong. But something where the cost advantage is so substantial and so impenetrable, like SpaceX with launch or Costco with groceries, to me, it's like the only way to win in most businesses is to provide a great product at a low cost. Businesses that do that at scale and build a moat around it are amazing. Amazon's E-commerce business is amazing. So many amazing businesses, very few monopolies. And when they are a monopoly, usually what 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? Like 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 US. 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 in that like Europe is economically stagnated. So I'm not sure anyone should pay attention to it other than if you are a pure fundamental stock picker, it's an easier market. I think there's really interesting things happening in Asia just as globally as politics change. Like 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. And that has all kinds of implications. I think there's a lot going on within defense. I think there's 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, some really great companies. Japan and Korea were not well positioned for the last 20 years because it was just like digital companies. But when it comes to like actually 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 you're especially passionate about, things you're thinking about in the world? The thing that troubles me the most, frankly, is I think we are on a collision course with China over semiconductors. 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, we're going to have something akin to the Great Depression. Say more about that. How would that come to pass? It's very straightforward in that Taiwan produces 90-something percent of the most advanced semiconductors. And everything we use is semiconductors. It's almost as if you went back 50 years, if there's only one country that produced oil. I mean, oil was that important. We went to war over oil, even though you could get it all over the world. Like Taiwan produces vast majority of leading semiconductors. And that is what powers everything. And that supply chain is fragile. Like it's not like it's easy to replicate. it's easy to destroy. If that supply chain were to get screwed up or disremediated, we would have like an incredibly bad economy on the order of depression type economy. Probably a lot of people in government understand this. I've heard Scott Besson talk about it. I think people understand it. There are some scenarios that are okay for the global economy, but 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. I think that 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. Bad for Taiwan, fine for the US, China achieves its objectives. I would like to see the world avoid depression. And that's going to require, I think, some understanding of 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. And then eventually, there's a path where China feels comfortable that they will be able to reintegrate with Taiwan. Usually when dictators say they say something, and they say it like religiously, you should believe them. Like when Putin talks about like the glory days of the Soviet Union, he may not have the capabilities always, but like as soon as he did, he acted on And so like every time she makes a speech that's of any importance in China, he emphasizes Taiwan. And so we can pretend like this is going to happen in some time that's not relevant, but it's so important. And 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. I like history. Sometimes it's just like listening to what's happened in history and how many horrible leaders there are. It's like Charlie Munger say, 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, it's interesting whether it's communism or fascism. It's just like all of these things are still possible and relevant in modern day, understanding how things have played out in the past. And it tends to repeat itself. Communism starts, but communism without dictatorship doesn't work because eventually people realize it's not good. And so then they want to change. And the only way it doesn't change is if you have a dictator who's really benefiting from all this. That to me is interesting just because the world, a lot more things have gone wrong in the world than right. In our lifetime, things have gotten right technologically, geopolitically, but over history, more things have gotten wrong. Good leadership can be as impactful or more than bad leadership. You've worked with a lot of, invested in a lot of great leaders. I'm wondering specifically around CEOs, but broadly about leadership. Like what are you looking for in a leader that you back? Real passion, a strong competitive streak, desire to win, deeply engaged in the business. Somebody who like knows the details when you talk to them. Somebody who people want to work for. And 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 like all giggles, but people are like, I'm going to learn more by working with this person. Buffett always says like the business is more important than the leader. I kind of disagree with that. I think if you look over 30 years, sure. But over any period of time, like businesses are just people. And if you have amazing people, they make great decisions and bring great people. and my investing timeframe is like five to 10 years max. And I think people are more important in that timeframe, 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 wanna do the same thing. So it's been so much fun to do with you. I ask everyone the same traditional closing question. What is the kindest thing that anyone's ever done for you? With my wife right now, I was a pretty bad boyfriend in college and that like I was busy doing other things and I was not very attentive. I was not like somebody that you'd want to like necessarily marry. And we broke up and I remember I sat down with her and I said like, you know, we went to get a drink and just to like catch up as friends. And I said, I got a job at Bear Stearns. And I just remember like she just started crying. I was fine, but I wasn't like I was Goldman Sachs knocking down my door to get me to go. I didn't really work for the first three years of college. She just 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 devo 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 back for. And immediately I walked out and I was like, I'm going to marry that girl and I'm going to be a better boyfriend slash husband going forward. I love that story. I haven't heard like a specific moment quite like that one in the 500 times I've asked this question. So an awesome place to close. Thanks for your time. Awesome. 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