Invest Like The Best: Dan Sundheim Interview Transcript — D1 Capital Founder

Guest: Dan Sundheim — Founder & CIO, D1 Capital Partners Host: Patrick O’Shaughnessy — Host, Invest Like The Best Show: Invest Like The Best Duration: 01:26:51 Source: YouTube Analysis: Deep Analysis & Commentary

Table of Contents

1. Introduction: Who Is Dan Sundheim? 00:00:00
2. Public vs. Private Markets in 2026 00:01:43
3. Investing in OpenAI and Anthropic: Pattern Recognition and Conviction 00:05:31
4. AI Business Models: Capital Intensity, Scaling Laws, and Economic Returns 00:09:49
5. Netflix, Spotify, and the LLM Analogy 00:13:58
6. Advice to LLM Executives: Focus vs. Sprawl 00:17:09
7. The Hyperscaler Thesis: Why AWS and Azure Face Headwinds 00:22:27
8. AI’s Impact on the Real Economy: Software, Moats, and Shorts 00:27:40
9. Is AI Overblown? And What to Tell Your Kids 00:31:57
10. GameStop: Going Through the Fire 00:35:01
11. The LP Dinner That Changed Everything 00:39:10
12. Temperament: Confidence, Volatility, and Emotional Control 00:46:07
13. Optimism, AI, and the Question of Human Purpose 00:47:04
14. SpaceX vs. Rivian: Two Big Bets, Two Very Different Outcomes 00:49:46
15. Short Selling and Market Inefficiency 00:54:06
16. Loyalty, Leadership, and the D1 Culture 00:55:50
17. The Portfolio Group Chat and How Dan Thinks About D1’s Enterprise Value 00:57:27
18. Origin Story: Value Investors Club and the Orthodontics of America Short 01:02:27
19. Viking to D1: Building a Fund of Your Own 01:08:25
20. Art, Beautiful Businesses, and What Makes a Great Investment 01:11:31
21. The World: Underappreciated Markets and the China-Taiwan Semiconductor Risk 01:14:21
22. Leadership, History, and Closing Reflections 01:19:40

1. Introduction: Who Is Dan Sundheim?

Time: 00:00:00 — 00:01:42

Patrick: My guest today is Dan Sundheim, the founder and CIO of D1 Capital Partners. Anyone who loves investing in markets has surely heard Dan’s name. You’ll very quickly realize that he is one of the most passionate investors operating in the world today. D1 operates across markets — across sectors in public markets — and having invested in some of the most valuable and important private companies, like SpaceX, OpenAI, and Anthropic, is a testament to how universal Dan’s curiosity is about companies and markets.

I find Dan to be one of the quickest, smartest thinkers about just about any company. When we recorded this conversation in his office in Miami, I spent the next hour talking to him about name after name after name. I could not believe the deep clarity and understanding he had — a small private markets company, then a big public technology company, then an industrial. He could move all over the map. It’s incredibly clear that he spends all of his waking hours studying markets and studying companies. The takeaway for me from this conversation is how good you can be when you are as passionate about what you do as Dan is about investing.

Please enjoy this great and wide-ranging conversation on all things markets with Dan Sundheim.

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 — SpaceX and lots of others. Draw the contrast today in 2026 of the difference in how the two markets feel. I’m curious about how you think about valuation differences, what one tells you about the other, the business of privates versus a public equity hedge fund. What is your feeling on the difference?

2. Public vs. Private Markets in 2026

Time: 00:01:43 — 00:05:30

Dan: It changes over time. It depends where you are in a cycle. Right now I think there are a lot of interesting opportunities in late-stage privates. It’s a moment in time. 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. So this moment is particularly interesting.

For somebody who invests in privates and publics, the synergy between what you see in private markets and what’s happening in public markets is the highest it’s ever been. That just makes you better as an investor in both markets. The valuations in private markets are interesting. In some cases they feel very high. In some cases they’re interesting and high. In a lot of cases, if you believe in the growth and you believe in the business model, they’re quite reasonable. I’d say the inefficiency argument for private markets is more nuanced than it was a few years ago. There are more sophisticated late-stage private investors than there were before and so valuations are more efficiently determined in some cases. But the kind of businesses that are available are just exceptional.

Patrick: If you think about the key companies in your private portfolio today — Anthropic, OpenAI, SpaceX, Ramp, et cetera — what does that group teach you? What do you think you see coming that public markets don’t fully appreciate, not having that same exposure to these great private businesses?

Dan: As long as I’ve been doing private and public investing, at some points in time there is synergy. But if you go back to when we founded the firm, maybe 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 private markets, the synergies are just greater than I’ve ever seen before. If you’re going to take a view on public companies that are deeply connected to AI — whether they’re suppliers, whether they’re going to be disrupted, whether they’re going to benefit — being close to the private AI companies is incredibly helpful.

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

3. Investing in OpenAI and Anthropic: Pattern Recognition and Conviction

Time: 00:05:31 — 00:09:48

Dan: They were very different.

When we first invested in OpenAI — originally in the $125 billion round — I wouldn’t say it was contrarian at all. Whether you invested in LLMs or not was debated quite a bit. There was a lot of uncertainty about the ultimate business models. So that was what we had to figure out.

Anthropic was a different situation. When we first invested in Anthropic, a number of people 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 for me, on Anthropic, was just reading Dario’s essays and listening to him on podcasts. When I look back at my career and the companies we missed — like Amazon in the early days — and I think, what could I have seen? If you looked at their income statement, you’d just see a sea of red. The only telltale sign was reading Jeff Bezos’s 1997 shareholder letter. The clarity of thought and 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. And if I had read that and almost ignored everything else, it would have been a really important sign.

Dario struck me like that. It wasn’t that the models at that point were so differentiated. There were probably five, six, seven players that could ultimately be important. 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. Writing something down means you actually have to go through everything you plan to do and express it in a way that makes sense to everybody. Dario just did that better than almost any CEO I’ve seen since Bezos.

4. AI Business Models: Capital Intensity, Scaling Laws, and Economic Returns

Time: 00:09:49 — 00:13:57

Dan: Back then it was: are these businesses going to ever generate an economic return? 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 another, so returns go down to the cost of capital. We took a different view, but it was maybe 65-35 or 70-30 in terms of confidence. At that point it was more about the skew — if things played out the way 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 the debate. Businesses have taken slightly different lanes and excelled at different things. OpenAI has been great at consumer and has had good enterprise traction. Anthropic has been incredibly successful at coding. There was a thesis that APIs — developers plugging into your model — would be commoditized, a race to the bottom. I think that debate is more or less irrelevant now, because you’ve seen with Claude Code and even OpenAI’s API 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 most businesses. And there’s sufficient differentiation among the models.

The gross margins are quite high. The competitive landscape 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 because there isn’t sufficient talent out there — it’s just that the capital required to get into this business is too great.

The real debate is this: these are extremely capital-intensive businesses. Capital-intensive to a degree we’ve never seen before in the history of business. You’re spending a ton 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? Or are you going to get to a point where everyone looks back and says we raised too much money, spent too much training models, and didn’t get the economic return?

Or — I think equally likely, if not more likely — ultimately you get the economic return, but it just happened slower than you thought. Enterprise adoption just didn’t take off as quickly. And that’s the problem: when you are this capital-intensive, you introduce financial and operating leverage to a degree you don’t see in normal businesses. You don’t have the luxury of two or three years of things going slower than expected.

5. Netflix, Spotify, and the LLM Analogy

Time: 00:13:58 — 00:17:08

Patrick: Could something like Netflix teach us about where this is going? That’s another business that comes to mind — a crazy amount of capital spent to build an asset, then amortized over a bigger and bigger user base. Is there any useful analogy there?

Dan: When I was speaking to executives at the LLMs, I framed it this way: I said, I think your business is some combination of Netflix and Spotify.

Netflix, in that unlike other tech companies, you are spending a ton of money upfront to train these models. Once the models are trained, you sell them at extremely high incremental margins. You don’t know what the revenues are going to be from that fixed asset, but you want to sell as much as possible so you can get the cash flows to build the next model. That’s very similar to how Netflix invested in content. When you’re an early mover in a fixed-asset business, you invest heavily, get the revenues, spread them over an increasing number of people, and invest more. That has a flywheel effect.

The important difference between Netflix and these models: Netflix’s content was differentiated. 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 innovation gets disseminated pretty quickly. That’s where the Spotify analogy comes in.

If you’re Google or OpenAI, the differentiating factor won’t necessarily be that you give a better answer. However, personalization matters enormously. The first-mover advantage is that the more these models know about you — how you live your life, your health, what’s important to you — the more history builds up and the stickier it becomes.

The music on Spotify is no different than Apple Music or Amazon Music. It’s theoretically a pure commodity. What makes Spotify have pricing power? What makes it differentiated? Why would people be upset if you took Spotify away? Because it’s personalized. They’ve taken a product that’s a commodity and personalized it to the point where you’re willing to pay a premium.

6. Advice to LLM Executives: Focus vs. Sprawl

Time: 00:17:09 — 00:22:26

Patrick: If you were giving advice to the executives at these companies — what to lean into and what to look out for over the next five years — what would you say? The scaling laws are so interesting in the sense that the models keep getting unbelievably better, the revenue available could be the whole world, but cost keeps going up by orders of magnitude. The Colossus 2 data center is this unfathomably big thing — 2 gigawatts of power.

Dan: It’s crazy.

Patrick: What advice would you give them based on everything you’ve learned about big, massive businesses?

Dan: The really interesting and challenging aspect of these businesses 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 as personal assistants. You could solve physics problems, help with drug discovery, make enterprises more efficient. The TAM is certainly not the problem.

Focus is going to be a question mark. On 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 that can be reinvested. But 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’s focused on one thing. Your culture as a company is oriented towards either consumer or enterprise — they’re just different. Even Amazon, which you’d say is the example of a consumer company that got into enterprise, went into it seven years after they went public.

The market has gone through periods where they thought Anthropic was Lyft and OpenAI was Uber. Up until recently, sentiment on OpenAI was more negative. OpenAI is taking the strategy of let’s do everything — Apple hardware, robotics, enterprise, consumer, science. They’ve been very successful in many ways, but that’s hard. I can’t think of many examples where that’s been done successfully.

Anthropic took a different approach: we are going to focus on enterprise. They tried consumer early on but it didn’t have traction, so they went all-in on enterprise. They’ve had a lot of success with coding, and because they’ve now taken a market-leading position, sentiment is that Anthropic is winning. I think this is going to go back and forth over time, and people will get carried away in both directions.

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.

One thing I pushed for early on — I said to OpenAI probably a year and a half ago: you have to do ads. I’ve seen it so many times. People in Silicon Valley are allergic to ads. They’ve got this amazing pure technology product, and the idea of tainting it with ads… And yet you see Anthropic’s Super Bowl commercial. Even the companies most adamant about never getting into ads — like Netflix — eventually did. And if you’re going to do it ultimately, you might as well start earlier, because you have to build a culture around it.

7. The Hyperscaler Thesis: Why AWS and Azure Face Headwinds

Time: 00:22:27 — 00:31:56

Patrick: I’m so curious what you think is going to happen to the hyperscalers. I saw a news report that Anthropic is considering securing 10 gigawatts of their own power, which makes me think — they’re going to have the power, so why don’t they just create their own clouds? Does that jeopardize what people have thought of as pretty damn good business models — the hyperscalers?

Dan: I do think about this. I’ve thought about it for probably about a year now. I’m more confident in the thesis that the hyperscalers are a worse business model going forward.

Now, usually when you say something’s a worse business model, you’re implying growth is going to slow down and margins will contract. I actually think you’re going to see the opposite near-term. I think AWS and Azure are going to accelerate for a while because their customer bases — Anthropic, OpenAI — are growing at enormous pace.

The problem is: you went from a dynamic where AWS and Azure’s customer base was essentially every corporation in the world, giving them massive fragmentation and massive economies of scale. The problem going forward is that economically it’s highly unlikely that LLMs aren’t concentrated in the hands of four or five companies. Those companies right now are obviously cash-flow negative and therefore looking for compute anywhere they can get it. But if they’re correct — and if anyone who owns these companies is correct — at some point in the next five to ten years they’ll be generating enormous 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 workloads at any hyperscaler. If you roll out ten years from now, the majority of workloads will probably be AI. The LLMs will probably be providing a lot of those workloads, and it will make economic sense to take it in-house. Right now, the LLMs look at the hyperscalers as more of a financing mechanism.

I also think the LLMs are actually better at inference than the hyperscalers. And then there’s the whole dynamic of neo-clouds. The initial view was that these were pure overflow capacity — there weren’t enough GPUs and they’d die as soon as Microsoft caught up. I wouldn’t say they’re fantastic businesses, but I don’t think they’re going away the way people thought, because they’re better at running GPU clusters than the traditional hyperscalers.

Patrick: If you think about the last couple of years, the best thing you could have done was just go long the AI buildout in all its forms. But the market is now starting to think ahead to the implications for software. The week after we recorded this, software got absolutely decimated in the market. Because of Claude Code and the amazing experiences people are having with it, there’s a feeling that software businesses are just screwed. How are you thinking about AI’s impact beyond the buildout?

Dan: It is incredibly difficult to know. These models are improving at an exponential rate, and understanding how that makes its way into the real economy is genuinely hard.

I think you want to use a few frameworks. It comes down to: which companies do you think will have a moat? In most circumstances, it’s fairly straightforward to identify moats protected from the proliferation of digital intelligence. Once you get into robotics and other areas, you start to have to question some traditional moats.

The first phase is with software. Claude Code entered the zeitgeist, and all of a sudden people see on Twitter that someone created a CRM system in a day. That’s kind of where people are now. We wrote in our letter last year that the buildout is still going to be a thing in terms of places to invest in public markets, but it’s increasingly going to become: which companies are affected? There basically were no AI shorts prior to 2026. If you wanted 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, and some longs, because of AI — and software is the first one.

My guess is that software will have to evolve and will probably be a worse business model going forward. But think of it the same way Walmart evolved with e-commerce. Would Walmart, all else equal, have preferred that e-commerce never happened? Probably — at least early on it required enormous investment, margins took a hit, new competitors emerged. I think the same will happen with software. Companies that have great distribution and great business models and are systems of record for companies are probably okay. When I asked the LLMs, “Are you designing your own ERP system?” they said, “No, we’re buying one from this company.” So systems of record are going to be difficult to displace.

But you can’t 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 the same way Walmart integrated e-commerce. And 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.

8. AI’s Impact on the Real Economy: Software, Moats, and Shorts

Time: 00:30:41 — 00:31:56

Dan: At least you’re protected for a few years if they’re not doing it yet. So I think systems of record are going to be difficult to displace. While it’s neat to create software for small productivity enhancements, if you really want to run your entire business on an ERP system or a CRM system, it’s going to be quite a while before people are just vibe-coding an ERP system.

But 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. 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.

9. Is AI Overblown? And What to Tell Your Kids

Time: 00:31:57 — 00:35:00

Patrick: Can you imagine a version of this story where it’s 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?

Dan: The only way that would be the case today is if scaling laws just totally peter out. But even if scaling laws stopped, even if these models got no better, I think you probably have three years of just people learning how to incorporate AI into their daily life and their companies. Certainly it wouldn’t be good for the AI 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. And it’s difficult to really get your arms around what that means. We went from “this is an interesting chatbot, kind of like Google” to “oh my God, these are going to be solving problems that humans can’t do.” We’re almost already there.

Patrick: I have a 12-year-old son who’s interested in investing. I think your son’s interested in investing too. What do you tell him about the future of this profession given these tools?

Dan: I think a line Musk has used is: it’s better to go through life being optimistic and be proved wrong than to be a pessimist and be proved right. To be young and interested in something and be dissuaded because you think you’re already obsolete — that’s a very self-defeating mindset.

It is likely that at some point in the future, everything we do is arbitraged away by AI. Do I think that’s happening in the next couple of years? I don’t. What do you tell someone to focus on? First of all, people are not going to be good at things they’re not really interested in. So it might be the case that being a plumber or an electrician is the most moated job in the world — but if you don’t want to be a plumber, that doesn’t help very much. It’s hard to tell your kids not to do something because it’ll be irrelevant.

I saw a podcast recently with a Google researcher who left and said, “I don’t even tell my daughter to study. Just go out and have a good time.” I think that’s a very destructive way to go through life. You should go through life thinking you want to achieve things, that you’re interested in things, that you’re curious — the same as if none of this technology exists. If it turns out that whatever job you envisioned no longer exists, you’ll adjust.

10. GameStop: Going Through the Fire

Time: 00:35:01 — 00:39:09

Patrick: I’ve talked with others about the GameStop story. I’m curious what you most learned about yourself during that period. When lore has it that it was February 2021 — January was GameStop — you went to your team and basically said, “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.” In such a stressful period of returns, what did you learn about yourself? What was it like emotionally?

Dan: It’s 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, 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 didn’t need to be celebrated, but I really did not like having our firm’s performance dragged through the mud.

It’s also a bit lonely. During GameStop, there were probably only one or two other people going through the same thing. I found it helpful to go back and read and listen to Ken Griffin’s interviews from 2008 and people I respected. But it’s lonely.

I never came close to going out of business — that was just nonsense to me. I was never going to quit, because even though we had made some mistakes, I deeply believed we were still good at what we do and had something to offer the world.

GameStop changed the market structure on the retail side, and I knew we had to adapt. By 2021-2022, I’d been doing this job for 20 years and never really had severe adversity. 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 people gave was one day at a time. Bill Ackman said: look, every day try to do something that makes things a little bit better. It’s not like something — when you have that kind of drawdown — where even if I hit the ball out of the park for three months, investors would be like, he’s just volatile and crazy. If I slowly and methodically did it, some people would give up because they’d say this was too crazy. I can’t disprove a negative narrative in the short term. It takes years.

So I acknowledged that people’s perception of D1 as an attractive place to invest capital was not going to change overnight, no matter what I did. It was really about looking inwardly at the team, making sure 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 try very, very hard.

11. The LP Dinner That Changed Everything

Time: 00:39:10 — 00:45:56

Patrick: Was there a specific moment in the whole experience that most stands out in your memory?

Dan: The moment that stands out… there were different moments that hit you in different ways. News articles, friends calling you asking if you’re going out of business — those were painful things I’d never had to deal with. I’d never tried to be a public figure and suddenly became very public.

The most important moment: we do semi-annual investor dinners with our LPs. That’s our primary form of communication. We write letters periodically, but these semi-annual dinners over four nights cover all of our LPs.

It was June of 2022, and we were at the peak — actually the trough — of our drawdown. The trough was at the end of May 2022, and these dinners were scheduled for June 3rd. 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 that the stock selection was going to change, but the portfolio construction was going to be much less risk-prone. The analogy I gave was: we’re 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 after what we went through in 2021-2022, emotionally, I would not be able to go through this again. So we said: we’re going to run the business differently. We very much understand if this is not what you signed up for.

And there is something invigorating about a turnaround. When you’re going through GameStop and the world is collapsing and there’s nothing you can do — that’s incredibly uncomfortable. But when you have a plan and you believe in that plan, it changes the perspective entirely. I really did believe in the plan and in the team. So all of a sudden I felt: everybody else may doubt us, but I believe it. We are now at the start of a mission to dramatically improve our returns, improve our firm, and earn back our reputation as great investors.

Patrick: Assuming some LPs did redeem — what do you think of the people who redeemed from D1 during that time?

Dan: I don’t harbor any ill will. The act of redeeming — we deserved it. I mean, obviously I appreciate it much more when people stayed. I always start these dinners 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, when you screw up in business, capital follows returns. When you deliver poor returns, capital will leave. We had a lot of great investors who stuck through it, and I deeply appreciate that far more than I resent people redeeming.

12. Temperament: Confidence, Volatility, and Emotional Control

Time: 00:46:07 — 00:47:03

Dan: 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 was generally pretty balanced emotionally.

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. There are hedge fund managers who are truly generationally great, and you hear stories of how early on they were throwing things on the trading floor and yelling. But ultimately they became great — they just learned not to let that emotion influence their trading.

13. Optimism, AI, and the Question of Human Purpose

Time: 00:47:04 — 00:49:45

Patrick: If you think about the future of the world — the crazy changes in technology, SpaceX, which we haven’t talked about yet — that’s a whole different dimension of incredible technological curve. You mentioned earlier the importance of being optimistic. Where are you the most optimistic, and what parts of the world give you the most pause?

Dan: I’m most optimistic in economic growth. 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 like nirvana for markets. I’m very bullish on that. And the implications flow from there into macro: that can cure deficits, can do a lot of great things. Economic growth does a lot of great things for everybody, from hedge fund managers and CEOs to people in lower-level jobs.

The part of me that’s more uncertain is: I think that we as humanity have never encountered something like what we’re about to encounter. We went from being the smartest animals on the planet — we were never the fastest or strongest, just smarter — to no longer being the most intelligent beings on the planet. What are the implications of that?

I’m not really sure. I think there are a lot of negative externalities. As much as people like Dario, who I respect a lot, might say “we’re just going to give everybody a check and people will 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 achieve things. And you’re not in a great society if it’s just a bunch of people living off checks that come from the government as a result of a massive economic boom from AI.

14. SpaceX vs. Rivian: Two Big Bets, Two Very Different Outcomes

Time: 00:49:46 — 00:54:05

Patrick: One of the most interesting stories you’ve told me before was when you made similarly sized investments in Rivian and SpaceX at the same time. Can you tell that story? Obviously SpaceX has grown into this huge position for you. I’d love to hear about the style of big bet, private market investing, and the way things can go.

Dan: The thesis was that EVs were going to dominate the auto market and that EVs were an entirely different kind of automobile — software, essentially. The equivalent of the iPhone versus Motorola, Nokia. The same way Motorola and Nokia weren’t able to move into smartphones because that was hardware, not software, there’d be few companies that could successfully make the transition.

Ultimately, autos are a bad business. Hardware or software, it’s a really tough business to scale and 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, but not getting up the manufacturing curve quickly enough 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 has won.

The bad ones tend to be more obvious faster. The great private tech investments 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. The compounding of 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. What they had achieved, I thought, was from an engineering perspective insane. So 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, and I didn’t know what was going to come — I just knew the skew was very good.

Patrick: What do you think about SpaceX today? So much has changed since you first invested.

Dan: The initial prognosis was always that they were going to be a low-cost provider of launch. The success of Starship — and we’re not fully there yet, but we’re pretty close — is a game changer. You caught a skyscraper with chopsticks. That’s pretty good. To prove full reusability at that scale — okay, there’s more to come, but 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. And the engineering they’ve done with the satellites — to harness solar power and deliver really high-speed bandwidth — has surprised me to the upside.

The ramification is that the global telecom market is now the TAM. Before, it was like: if you live somewhere without cable to your home, you get this Starlink thing. Now with boats, planes, and lower-income regions — I think that in a relatively short amount of time, months to a few years, they are going to be dramatically cheaper than any other form of delivering broadband.

15. Short Selling and Market Inefficiency

Time: 00:54:06 — 00:55:49

Patrick: You just said how much you love shorting stocks. What is it about it that you like? You just don’t meet many people focused on this anymore.

Dan: My wife begs me all the time to stop shorting stocks. Anytime she looks at me and says “this is a short, it’s a bad business” — you have to be intellectually stimulated by it. And 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 to short by shorting indices. Very few people are doing fundamental shorts. There are tons of people investing in things just based on stories — because of social media and Robinhood — so there’s just endless supply of shorts. If you have duration and take a fundamental view, it works.

Patrick: Do you think markets are less efficient now?

Dan: I think it’s just the nature of the institutions transacting in the market. If you go back 10 to 20 years, mutual funds and long-short hedge funds were a big part of the market. Now it’s a lot of passives, a lot of retail investors. The people making investment decisions are not based on long-term considerations of intrinsic value. Quants, even multi-manager long-short funds — while they are focused on fundamentals — are by necessity short-term oriented most of the time. The moves you see in the short term exaggerate the true change in intrinsic value of the company. That makes for a less efficient market.

16. Loyalty, Leadership, and the D1 Culture

Time: 00:55:50 — 00:57:26

Patrick: One of the things that interests me a lot about you is loyalty. 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 and lots of your key partners you’ve known a long time and are good friends with. Can you say a little bit about the role of loyalty in how you run things?

Dan: I know these people the best. I’ve dealt with them through so many different things in life, and I have a lot of confidence in their competence. There are a lot of people I love in life who for different reasons are wonderful people and would be loyal, but they have to be really competent at the job. This is a very intense job, so the bar is extremely high. The people I’ve hired that are friends of mine — I’m just confident they cleared that bar by a lot.

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

17. The Portfolio Group Chat and How Dan Thinks About D1’s Enterprise Value

Time: 00:57:27 — 01:02:26

Patrick: One of the things you do for your portfolio is host this group chat that’s full of your thinking on what’s going on in markets. What has been the impact of constantly communicating with the people you care about about markets? I want to encourage other people to do the same, because I think it can be so powerful.

Dan: When you’re investing in a company privately, there’s obviously a financial aspect — that’s the driver. But there’s also a relationship part. You sign up to hopefully help that person grow their business, to be with them through ups and downs. When you do the initial investment, you spend a lot of time together — but then it’s very easy to go months without communicating with the CEO if nothing’s happening. I don’t like that.

If we have something we can offer people and they can just opt in — they can read what I write or not — it’s a way to broadcast and communicate with people I want to know us better as a firm and know me better as a person.

Being a founder is lonely. You’re going through all kinds of issues. 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 and understand everything they go through. So by having a bunch of them together in a chat, it’s helpful to us from a business perspective, but it’s also just… “group therapy” would be too strong a word. But it’s nice for them to know that other people are part of this community, and if they want to reach out, they can.

Some of these people are world-leading experts in areas like AI that are going to be impactful to companies that aren’t experts in AI. Just getting that input is really helpful.

Patrick: Do you care whether D1 has enterprise value as a business?

Dan: It’s something I’ve started to think about more recently. I think the answer is no. Money to me is a scorecard and I want to have the best score. It’s a really great positive externality of being a good investor.

I don’t think hedge funds are a good business. Our business is horrible and amazing. The cash flows really well. It has no terminal value. I told this to my portfolio companies: 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.

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

Dan: This is what I’ve devoted my life to. If you devote your life to anything, you want to be great at it, or at least have an impact that’s tangible and measurable. I could be a family office right now, and there are plenty of positive things about that. The drawback is you’re not in the arena. Being out there, being able to prove that we can be great — not just me, but our firm — is invigorating. I think I’d be kind of bored if I was just investing my own money.

18. Origin Story: Value Investors Club and the Orthodontics of America Short

Time: 01:02:27 — 01:08:24

Patrick: I want to start with something I’ve never heard you talk about publicly — the early writing you did in Value Investors Club, and specifically the Orthodontics of America short case. Tell me the story of VIC and that early passion for stocks.

Dan: 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 tool set to analyze them until I got there. I deeply understood accounting and finance, so I started just looking at stocks on my own.

The only way to really get exposure to investment ideas written up by hedge fund managers was this site called Value Investors Club. I applied — you had to send an idea — and every week they’d post tens of ideas from people anonymously. I would just consume everything: merger arb, long ideas, short ideas. Every week they paid $5,000 to the best idea.

After maybe six to twelve months, I had a portfolio of things I’d written up on Value Investors Club and 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. So I had all these investment ideas.

One hedge fund I went to interview at was a spin-off of SAC that did healthcare. I had no particular interest in healthcare, but it’s where I got an interview. They said: we want you to do a case study. The company is Orthodontics Centers of America.

I went home and spent hours going through the financial filings and trying to build a model. I was pretty good at accounting — it was like a puzzle that made sense. I tried to get deep into the financial statements, and nothing reconciled. Nothing made sense.

It hit me that what they were doing was kind of the simplest form of accounting fraud: just capitalizing expenses that should have been expensed in a big way. I was able to effectively prove it without incontrovertible proof — just by building up all the unit economics as stated and comparing them to the unit-level economics you could actually decipher from the financial statements.

Before I went back for the follow-up interview, I thought: I’m onto something here. Let me post it online and get some feedback. I wasn’t allowed to trade stocks because I was working at an investment bank, so I posted it on Value Investors Club under my anonymous tag name.

Within a few hours, the stock started to go down. I was like: that’s cool, people are noticing. The next day, the stock started to crater — down 20, 30%. I started getting calls at Bear Stearns from people at T. Rowe Price and Fidelity asking what was going on.

I went back into the interview and presented the case study. At this point they were just: “What did you do?” I said: you told me to look at this. I thought it was a fraud. They said: “Did you tell anyone that we told you to do this?” I said no. They said: “We basically thought you were going to come back and tell us they were going to miss earnings.”

I didn’t work there — I didn’t want to do healthcare. But I now had this write-up that could go around to different hedge funds. Most of them already knew about it because they had shorted it after the write-up. That’s how I got my job.

19. Viking to D1: Building a Fund of Your Own

Time: 01:08:25 — 01:11:30

Patrick: You end up at Viking. You’re there for a long time. You become the CIO, you’ve got an incredible track record. What was it like to decide to go hang your own shingle and build D1?

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

I was working for Tom Purcell, who’s an amazing investor and a great mentor. But I realized that Tom was very well equipped to generate returns in financial services for Viking. If I wanted to grow my career, I had to move into other areas.

So gradually I took on other sectors — starting with healthcare, industrials, TMT. The nature of those companies was different than banks, and it was just years of covering different companies in different industries. What created value in TMT was different from what created value in industrials or healthcare. If you love investing, my time at Viking was amazing because I got exposure to every industry.

By 2016, I was managing just over half of Viking’s capital — somewhere around 55%. And I’d started out in 2002 as an analyst with no portfolio. It was pretty clear from a business perspective that it was not in Andreas’s best interest to have one person manage more than half the capital. I kind of 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, to get better, to 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 this. Starting a fund is a big endeavor. I felt like I had the energy, and everything kind of came together.

20. Art, Beautiful Businesses, and What Makes a Great Investment

Time: 01:11:31 — 01:14:20

Patrick: What interests you about art?

Dan: I’ve always had more of a leaning towards humanities than STEM, which is unusual in tech and somewhat in finance. That’s why I perhaps look at my job as more art than science. The science is very simple — I learned DCF 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 — design, architecture, 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 it. There’s usually a story behind it, people behind it. Art is important because it is created by people — it reflects emotion and what’s happening in the moment, in the world, when it’s made.

Patrick: If you apply the same aesthetic idea — the beautiful idea — what is the most beautiful business you’ve ever seen?

Dan: The best businesses are usually low-cost producers of something very durable. I think 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 lower cost.

I could say a bunch of businesses are really great — like Moody’s or S&P, those are great businesses. But something where the cost advantage is so substantial and so impenetrable, like SpaceX with launch or Costco with groceries — that’s beautiful. 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. Very few monopolies. And when they are a monopoly, usually what happens is they get lazy and the returns aren’t as good.

21. The World: Underappreciated Markets and the China-Taiwan Semiconductor Risk

Time: 01:14:21 — 01:19:39

Patrick: What parts of the world do you think are underappreciated right now? When I look at your top 10 holdings, I didn’t recognize a number of the companies — lots of them are international. Where’s your eye right now?

Dan: Europe is economically stagnated, so I’m not sure anyone should pay much attention to it — other than for a pure fundamental stock picker, it’s an easier market. I think there are really interesting things happening in Asia as global politics change. You saw what happened in Japan — for the first time, Japan is probably going to become a military power again at some point, which has all kinds of implications. There’s a lot going on in defense. Germany, Korea, and Japan have companies with excellent physical assets and engineering that were not well positioned for the last 20 years because it was all about digital companies. But when it comes to hard assets and good engineering, they’re very interesting.

Patrick: Is there anything else you have on your mind?

Dan: The thing that troubles me the most is that I think we are on a collision course with China over semiconductors. And I’m not sure there’s an easy way out.

It’s very straightforward: Taiwan produces 90-something percent of the most advanced semiconductors, and everything we use runs on semiconductors. If you went back 50 years and there was only one country that produced oil — we went to war over oil, even though you could get it from all over the world. Taiwan produces the vast majority of leading semiconductors, and that supply chain is fragile. It’s not easy to replicate, and it’s easy to destroy. If that supply chain were to get screwed up, we would have an incredibly bad economy — on the order of a depression.

I think a lot of people in government understand this. But there’s no scenario I can think of where everybody’s happy — China is happy, Taiwan is 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.

Patrick: What do you hope happens?

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

I would like to see the world avoid depression. That’s going to require some understanding that we need 10 to 20 years to replicate this supply chain, and that over that period of time, China will not screw up the world economy by being very aggressive with Taiwan.

Usually, when dictators say something and say it religiously, you should believe them. Every time Xi makes a speech of any importance, he emphasizes Taiwan. And AI raises the stakes so much that it would affect everybody.

22. Leadership, History, and Closing Reflections

Time: 01:19:40 — 01:24:00

Patrick: What have you learned from the Real Dictators podcast?

Dan: I like history. And sometimes just listening to what’s happened in history — how many horrible leaders there are — is instructive. Charlie Munger used to say: “Tell me where I’m going to die, so I never go there.” Learning about bad things so you don’t go there.

Whether it’s communism or fascism, these things are still possible and relevant in modern day. We see seeds of them. Just understanding how things have played out in the past, and how it tends to repeat itself. Communism without dictatorship doesn’t work because eventually people realize it’s not good, and then they want to change. And the only way it doesn’t change is if a dictator is really benefiting from it.

A lot more things have gone wrong in the world than right over history. Things have gone right technologically and geopolitically in our lifetime — but over history, more things have gone wrong.

Patrick: What have you decided are the most important qualities you’re looking for in a leader?

Dan: Real passion. A strong competitive streak. A desire to win. Deeply engaged in the business — someone who knows the details. And someone people want to work for. That could be because they like the person personally, or it could be because — like Elon Musk — people think: “I’m going to learn more by working with this person.”

Buffett always says the business is more important than the leader because eventually the business outlasts any individual. I kind of disagree with that. Over 30 years, sure. But over any medium-term period of time, businesses are just people. If you have amazing people, they make great decisions and bring in more great people. And my investing timeframe is more like five to ten years max. In that timeframe, especially in technology businesses, people are more important.

Patrick: I think it’s come through today that you are clearly one of the most passionate stock pickers, stock people, markets people active today. It’s been so much fun. I ask everyone the same traditional closing question: What is the kindest thing anyone has ever done for you?

Dan: With my wife… I was a pretty bad boyfriend in college. I was busy doing other things. I was not very attentive — not somebody you’d necessarily want to marry. We broke up.

I remember I sat down with her just to catch up as friends, and I said, “I got a job at Bear Stearns.” And she just started crying. Tears of joy. It wasn’t like Goldman Sachs was knocking down my door — I hadn’t really worked for the first three years of college. But she just started crying.

And I was like: wow. This person, whom I hadn’t properly appreciated — how much they cared for me. How much they were rooting for me. That gesture — it wasn’t really an act that was kind. It was just a gesture. And I immediately walked out thinking: I’m going to marry that girl. And I’m going to be a better boyfriend and husband going forward.

Patrick: I love that story. I’ve heard a specific moment quite like that one in 500 times I’ve asked this question. An awesome place to close. Thanks for your time.

Dan: Awesome. Thank you.