The Exchanges, every show

Q How do you decide when a business is ready to take on some leverage?

A It's a combination of two things. One is, what is the depth of the G&A line? Do we have a CFO, a controller, a head of treasury and cash management? Are all of the warning lights that we touched on earlier in place so that we're able to spot things in real time if something isn't coming to fruition in a way that we underwrote it? So that's the people side of it. And to a size and scale, we have found that the credit markets are far deeper Cheaper, more flexible, less covenant-laden, and friendlier to consolidations that are, let's say, 15 to twenty million of EBITDA in size and scope versus something that's five. What does that mean in terms of practical timing for us? That's usually 12 to 18 months after we invest in a business. We've typically deployed the preponderance of the equity we've allocated to that roll-up. The team is fully formed. We have all the warning lights in place. And it's at a size and a scale where we can then go to the market and get a number of term sheets and create real competitive tension around that financing.

AI assessment note: “It's a combination of two things. One is, what is the depth of the G&A line?”

Q Which two people have had the biggest impact on your professional lives?

A For me, I would say number one is my wife, Annabelle. She's allowed me to spend the time, effort, and energy traveling around the world with Alex the last 13 years doing the things we need to do to build the firm, and she's picked both of us up off the ground from the lows over the last 13 years. But equally as important, she actually suggested that Alex and I worked together while we were in business school, so GSP is Very much her brainchild. Her and Alex have actually known each other for longer than I've known either one of them. They went from preschool through college together. We both give her and Alex's wife, who's also named Alex, a ton of credit for helping us in the early days of figuring out our partnership. Two is Royce Yudkoff, who we mentioned earlier, who's our HBS professor for me, and I'm sure Alex agrees, has been our most impactful An important mentor and thought partner over the last 13 years. Even to this day, almost 15 years later, whenever we have a serious problem, our first phone call is to Royce, and just an unbelievably thoughtful, smart, humble individual who we owe a lot to.

AI assessment note: “number one is my wife, Annabelle... Two is Royce Yudkoff”

Q So, you know, I think, I look at a necktie. I haven't worn a necktie. I can't remember the last time I wore a necktie. But, uh, it doesn't seem from the outside like a particularly complex product. Piece of, of apparel. Like, it's just a, you know, it's the shape, and am I wrong about that? Is it a lot more complex than people realize?

A It's not. I mean, it's a pretty basic item, but the components really matter. One thing that, uh, most guys will tell you is they like the way a tie ties, or they don't. And a lot of that has to do with what's inside it, the interfacing, which we cut apart all the ties that we had, what we liked, what we didn't like, and why. The other thing that you people notice is, um, how the silk feels, you know, what the finish is on there. Is it gummy? Is it not gummy? And as you pull the tie tighter, a lot of people would like a little bit of a contour, like a little curve to the surface of it. And we discovered that that had to do with the way in which you cut it and which way the, the weave was going. Um, and we found that a lot of the ties that didn't tie well We're all done one way and the more expensive ones were done the other. So we emulated what we liked and walked away from what we didn't.

AI assessment note: “It's not. I mean, it's a pretty basic item, but the components really matter.”

Q years, and he's like, he's maybe not impolite, but he's probably looking at you guys and thinking, what do they know about this business? And, and he might even have an, uh, an opinion About, about the designs, and he might even say, you know, this is really not, these are things that just aren't going to sell. Like, is, did you, do you remember coming across anyone like that?

A We did for sure. We had one guy who said, you know, we were very pedestrian. We have one, a lot of people say, you know, we're just not selling ties. And you're totally right. We had no experience in this industry. And, you know, a lot of brands were started by people who were in the industry, you know, and had an idea and they, they acted on it. So for us, what we had to do was to show them that we were eager to learn. And by spending time in their stores, like stocking their shelves, helping sell on the floor, just by hanging out and learning through osmosis, we earned their respect, and with that respect came their willingness to give us a chance.

AI assessment note: “We did for sure. We had one guy who said, you know, we were very pedestrian.”

Q I read, well, I'll get to this question in a sec, but I read that within three years, you guys are doing a million dollars in sales, which is kind of crazy. Before we, before I ask you about how you got there, just, can you just give me the breakdown, like roughly, of what the margins were? I mean, what did it cost you guys to make a tie?

A So the ties, I mean, just the cost of the tie itself, the physical tie and the components was probably somewhere around 12, 13 dollars, something like that. And we didn't realize it at the time, but it was a very high profit margin product. It also had quite a long runway in terms of apparel. It was less seasonal. Like we could make the same print. In fact, we still make the same print, some of the same prints we did 20 years ago. So they, the pro, the inventory lasted longer than typically for apparel. And it also took up a very small amount of retail space. You could hang, you know, a bunch of ties on a wall, and it didn't take up much space. Uh, and there's also no sizing.

AI assessment note: “physical tie and the components was probably somewhere around 12, 13 dollars”

Q Have you been surprised by how price sensitive people are around security and code reviews?

A Not in our segment. I would say in the engineering segment, um, And we, we have some engineers use Replit, but the 75% are non-engineers. Engineers are more price sensitive because they have a lot of options. They can use a lot of different products on the, on the market. Now, when, when you're an operations manager using Replit, And you just saved 10,000 dollars on a SaaS software. You've gained, you've saved another, you know, 200,000 dollars on, on headcount. And you're spending an additional thousand dollars to just make sure that the software is more secure. That's like a no brainer. The ROI has been a hundred fold for, for, for companies we work with. On the consumer side, there's more price sensitivity, especially if I'm an entrepreneur just dipping my toes, which is why we reduce the price on our core plan. So I think there's going to be, and you, you, you hinted at that earlier, there's going to be this different models for different use cases or different parts of your journey. If you're just starting out, you don't want to be hit with a thousand dollar bill. You want to be able to play around with 20, 30 dollars before you commit.

AI assessment note: “Not in our segment. I would say in the engineering segment”

Q I'm going to do a quick fire round with you. Uh, you have to go and be a public company CEO, I know. Um, so what have you changed your mind on in the last 12 months most significantly?

A I do think that, that I've, I've become more convinced that software is headless in the past year than I was maybe three years ago. And it's because of the, the level of agentic capabilities on tool calling and searching across systems and the accuracy of that. Uh, and that, that has happened faster than I, I would have, uh, perceived. So two to three years ago, if you were to kind of You know, wire up an agent and tell it, hey, go work inside a box and find a document to work with and do some process. It would, it would basically almost always find the wrong document and it wouldn't be able to handle actually like cracking open the file and reading through it. And so thus, you know, going headless wasn't sort of the, the most urgent priority, uh, from an agentic standpoint. And in the past year, those capabilities have just absolutely accelerated. To the point where I'm fully convinced that you just, you have to be, you know, headless first as a software platform.

AI assessment note: “I've become more convinced that software is headless in the past year”

Q Irrespective of the benchmark you used, for a long time we've had shrinking number of public companies, particularly in the U.S. How do you think about what that means for the future?

A I'm not sure we know quite yet what it means for the future. The shrinking number of companies from a peak in the U.S., six, 7000 securities, about the time we graduated business school, down to about 4000 U.S. companies is just a fact. When you go and you dig into it, you discover what we lost was a lot of really small companies, a lot of micro cap securities, a lot of small cap companies, and for long-term returns, it's not clear you lost much. We are seeing companies stay private longer, which does mean there may be less return in the public space. It's hard to know. There's SpaceX and others sitting out there waiting to come public. I would love to have had them in my index fund. Back when they were a hundred billion dollar company before whatever trillion is, I still believe the best place for companies to grow their business is the US public markets. There's no place that trades as well. There's no place that has as much liquidity. There's no better place to raise capital. What I don't know is whether this staying private for longer is a permanent phenomenon or not. Let's find a way to get some high quality private assets into retail investors hands over time.

AI assessment note: “which does mean there may be less return in the public space.”

Q With that money that's gone into some of the successful large private companies, should they go public? And there's some noise that some of the bigger ones will this year. How do you think about integrating that into your index products?

A The minute a company comes public, it belongs in an index fund. We've had that belief for a long time. You might need a few days for it to get trading and figure out price discovery. Our best indexes add those securities in day three or day five. That's the best practice. Why should they not be an investor's portfolio from there? They should be float adjusted. Most companies come public, only bring five to 10% of the company public. We only want to buy five to 10% on the day of the IPO. Many years ago, Yahoo came public with a small float. Indexers bought a lot of it, and the price went up. The demand was greater than the supply. Gus Sutter and Mike Buick, people long before me on this desk, pushed really hard for all of our indexes to be floated, just in which they are today. That reflects what's available in the marketplace, and therefore, an indexer doesn't oversize the amount of Shares brought to the market, but get them in there quickly, have it be part of the investment return.

AI assessment note: “The minute a company comes public, it belongs in an index fund.”

Q I'd love to ask you about the business of Vanguard, some of the decisions along the way. You weren't the first mover into the ETF space, now one of the biggest. How did that decision process play out in your organization?

A All of that, Ted, started before I got to the investment side of Vanguard. We did launch ETFs after I was at Vanguard two years. At that point, I was working the four and K operations. It had nothing to do with the original couple of ETFs we brought to the market. The history goes back to Jack Bogle talked to the American Stock Exchange about the spy product, and he said, what are you crazy? Trading intraday is the worst thing for investors. In the early days, Jack Bogle was highly opposed to this. Forward probably a decade or so, Gus Sauter came to Jack Brennan and said, we should offer these. Gus pitched it to Jack Brennan and said, this is an alternative distribution vehicle. Intraday trading is not what we're about. It does open the aperture of getting our products to more people, making indexing better. Jack Brennan threw him out of the office the first time, Gus was tenacious and went back in and said, you really should. This is a way for us to take our business from being just a direct place where we sold mutual funds to putting it out there on a brokerage platform that today advisors can use it. It's widened the use of index funds. Jack Bogle still hated him. He would still talk to him. I got an earful on a number of occasions from Jack as to why would you give someone the ability to trade interday? No one ever needs it. They need to buy it once today, sell it again in …

AI assessment note: “Gus pitched it to Jack Brennan and said, this is an alternative distribution vehicle.”

Q Why don't we start with your background and path to joining Vanguard a quarter century ago?

A It's been a heck of a 25 years since I joined right out of business school. I grew up in a small town in Delaware. My parents didn't go to college. My mom took a job at the University of Delaware as a secretary so that I could get free tuition to the University of Delaware. I got exposed to some folks who were looking at other schools. I was fortunate enough to get into the University of Pennsylvania, but it was a little bit too pricey for my parents. I looked and remembered that I really enjoyed My dad's story's from the Navy. I put the two things together, a chance to go to Penn with a Navy ROTC scholarship, which paid the Penn tuition and got me to go to a great school where I studied engineering, and then I owed the Navy. Five years of service, which I turned into six and a half on a submarine out of Grodden, Connecticut. That was a fantastic experience where I got to see a little bit of the world. I got to see some great leaders and learn about leadership. From there, I went to business school at HBS and Where I met you for the first time. Part of the reason I went to business school because I didn't know what I wanted to do. I tried a summer in consulting, and it turned out that I like doing things a lot more than giving advice on how to do things. I went back to school second year looking for a place to work that had a great mission, a great value set, and was Philadelph…

AI assessment note: “It's been a heck of a 25 years since I joined right out of business school.”

Q As you look at the equity index business today, what's the range of products and asset size across it?

A We have about eight and a half trillion of index fund assets. That would include our fixed income index assets, which a colleague of mine runs on behalf of investors along with the active fixed income space. That's one big business for us. Within equities, we have two teams that run assets today. One is the team that reports to me, the global equity team. We run about five trillion dollars of assets. They range from total stock market broad exposures to global broad exposures to value and growth exposures and country exposures. We're running Australian and UK. There's a wide range of outcomes along with running target date suites. Over on the other side, our SE team, or strategic equity team, they're running size and value growth sector funds for U.S. investors. They're close to what you would see in Morningstar, nine box type things, along with sectors, maybe some unique sectors like dividends, country exposures for non-U.S. investors.

AI assessment note: “We run about five trillion dollars of assets. They range from total stock market”

Q Yeah, it's like playing poker with Alan Keating. It's just like, how is this guy solvent? He's literally playing every hand of poker, he's losing tons of money, and then all of a sudden, by the end of the night, he hits two big pots, and he's got the nuts both times, and he pulls out of the stall. What's your take on the market today, Chamath?

A Yeah, I mean, I'll just do it again, but I think the, the Shiller PE, Nick, I sent it to you, shows near all-time highs. Then the second is the Buffett Index, which is the sum of all, uh, U.S. equities divided by GDP, is also at all-time highs. So this would generally mean that you need to be increasingly a little bit more risk off. But then the opposite side of that, and I sent you a third one, and this is why it's so confounding, is you have signals showing everything, which is, which typically doesn't happen. And this is this dispersion point where when you see this performance and it's up five percent in the first, you know, half of April, typically the market is up almost 32% on average for the rest of the year. And we were already up, as Sac said, you know, Seven and a half percent already.

AI assessment note: “you have signals showing everything, which is, which typically doesn't happen”

Q bunch of checks as we have done for the last 10 years, and a next generation, or to your point, a back to the future era of venture capital where you co-found the business side by side? Can they run side by side? Or are we actually entering an era where we're back to the future era, as you say, where value accrual is in the co-founding and incubation side?

A Um, I, I think it's very hard for them to coexist inside of one person, and it's very hard to coexist sometimes inside of even one firm because, you know, the reason I'm sitting here at Periodic Labs, I work here three days a week. Every day from eight a.m. to 8:30 a.m. for the last year, Liam Doge and I have had a stand-up every morning where we go through the priorities of the company, and then we, we make them, we prioritize, we go and execute. I mean, the compute team of AMP is sitting upstairs, procuring compute for, for the periodic guys. My role models have always been the Arthur Rocks and the Bob Swansons and the Mike Marcola, personal computing. Effectively, the first CEO for the first year of Apple was Mike Marcola. He was an angel investor, and he was the one doing all the CapEx, you know, supply chain and capital and all of that stuff that allowed Steve and Jobs and Woz to focus on the product and the engineering. And, and that kind of deep partnership is what I get really excited about.

AI assessment note: “it's very hard for them to coexist inside of one person”

Q Yeah. So, I mean, so given all of that, how, how were you actually going to become a real business? Like, how are you going to come up with a sustainable model?

A The breakthrough for us actually was a business model that we discovered. We would come up with a, a way of working together where I would work at cost. I would work at break even, but since I wasn't making any money, We would split the value that we ultimately created. For this big company, this is nearly free. They were getting MIT engineers working on a problem that they cared about at a third the price, and they only had to care about this value sharing thing if something good came out of it, and they would own the IP they brought to the party. We would own the IP that we brought to the party at any IP That was jointly developed, was jointly owned.

AI assessment note: “The breakthrough for us actually was a business model that we discovered.”

Q Dragons in every Sunday. Brad, you're, uh, sorry. Brad, you're an investor in this company. Is this virtue signaling or is it reality? Is this a good move by them to not release this model and be thoughtful, give it to a handful of people, and just find all the bugs it can before releasing it to the public? And we've got a lot more issues to discuss about this.

A I mean, I, I, I actually think they deserve A ton of credit here, and let me walk you through why, right? They, the company could have just released Mythos, broken a lot of core things on the internet. Oftentimes in Silicon Valley, we say move fast and break things. In this case, it means just releasing the model to move further ahead of your competition, but here the company realized it would wreak havoc. They ran their own vulnerability testing. They saw that it would allow offensive hacking and people to expose browsers and browser history, expose credit cards, you know, on, on the internet. You know, what I like about this is they didn't need government to hold their hand on this. We have plenty of government regulations. They know it's in the best long-term interest of the company and the industry, you know, so they set up Project Glasswing. It's an AI-driven, you know, kind of cyber coalition. Apple, Microsoft, Google, Amazon, JP Morgan, 40 of the most important companies, and their goal is very simple. Let's spend a hundred days, use advanced AI, To find and to fix and to harden these software vulnerabilities before hackers exploit them. Now, what I think this represents, Jason, is a threshold that we're crossing. Mythos and Spud, which is going to be out from OpenAI any day now, which is the first Blackwell-trained model at OpenAI, they represent the beginning of what I…

AI assessment note: “I actually think they deserve A ton of credit here, and let me walk you through why”

Q When you think about that, is continuous learning the next breakthrough that you're most excited by?

A I think there's quite a few things that are missing. There's, there's continual learning. I think there's a lot of, uh, I think a lot of mileage in looking at different memory systems. Um, at the moment we have these long context windows, which are kind of a bit brute force. You just put everything in them. Um, I think there's, there's, there's a lot of, uh, interesting, probably architectures to be invented there. Um, and then there's stuff like, uh, longterm planning, you know, hierarchical planning. These systems are not very good at planning at long time horizons, you know, many years into the future, uh, which we is, you know, with our minds we can do. So, um, there's quite a lot of, uh, problems I think that are still left to overcome. Maybe one of the biggest is consistency. So, you know, I sometimes call these systems jagged intelligences because they're really amazing at certain things, uh, when you pose the question in a certain way. But if you pose a question in a slightly different way, they can actually still fail at quite elementary things. So a general intelligence shouldn't be that sort of jagged.

AI assessment note: “I think there's quite a few things that are missing. There's, there's continual learning.”

Q fetal DNA that naturally exist in the mother's blood, and that this would someday be universally adopted. This was a radical idea at the time. Before Billion to One, most genetic abnormalities could only be detected via amniocentesis, an invasive procedure that is only used in high-risk pregnancies. How is the key insight that enabled you guys to do this when no one else was able to do it before?

A We have realized that DNA that is coming from the fetus and the tumor is both very dilute and rare, right? So you might only have a few molecules among billions of other molecules. So every molecular diagnostics approach here requires In the lab using a process called PCR to amplify this DNA billions of volt. The problem is that this DNA amplification process can add tremendous noise so that the small signal that you have can be lost. So what we have done is to add a synthetic DNA into the patient sample that we get before any amplification happens. These synthetic DNA Allow us to know how much amplification happened at different genomic locations. You know, what are the errors that are being introduced by the amplification process? So then we can remove those errors from the sequencing data, the data that we get at the end, so that we know what was in the sample to begin with. That converts a difficult biology problem to almost a simple mathematical problem.

AI assessment note: “what we have done is to add a synthetic DNA into the patient sample”

Q So what was the motivator then for change in the construction of the landscape of defense contracting? Was it software that takes us from the old primes to the new primes? Is that really what kind of triggered this?

A Consolidation. So in 93, having won the cold war in 91, or I think more accurately, the Soviets lost the cold war, you know, by 93, we expected as a nation, a kind of peace dividend. We don't have an adversary. Now we should be able to spend less on defense. And, uh, the department had this famous dinner where they brought 15 of the 51 primes together and said, this is gonna happen. The budget's gonna get slashed. We're not going to save you guys. You have our permission to consolidate. Some of you are going to go out of business. Some of you should try to make a commercial business, which didn't really work. Uh, and that's what led down to five. It was actually, there was going to be, we were going to go from five to four and 99, the justice department put their foot down and said, we're not going to let Lockheed and Northrop consolidate.

AI assessment note: “Consolidation. So in 93, having won the cold war in 91”

Q people are saying that Silicon Valley is taking over Defense and Silicon Valley is the next story of the American war machine. This has become sort of a popular narrative. Can you just respond a little bit to kind of where we were coming out of World War II from a defense industry perspective, where we find ourselves, where Silicon Valley seems to be at the center of this today?

A You know, the industrial base that won World War II and the early Cold War was not a defense industrial base. It was an American industrial base. You know, Chrysler made the Minuteman ICBM. They were the prime contract on it, and they make minivans, so missiles and minivans. General Mills, the cereal company, had a mechanics division. Everything they learned doing R&D to process grains, they actually used to build torpedoes and inertial guidance systems. Ford built satellites until 1990. So the entire economy was invested not only in economic prosperity, But also underwriting the freedom that allowed us to have economic prosperity. It's really a consequence of the end of the Cold War. So when the Berlin Wall still stood in 1989, only six percent of spending on major weapon systems went to pure play defense specialists. 94% of it went to what I call as dual purpose companies. You know, yeah, a missile is single use. It's not a dual use product. You're not going to buy it at Walmart, but that actually these companies were invested in both parts of this. That figure today is 86%. Goes to defense specialists. So we have a very different structure of the U S economy as a result. And I think it leads to very perverse narratives of what would it be like to mobile? If things got really bad, we'll just flip a switch and our auto factories will magically turn into enabling us provide for…

AI assessment note: “the industrial base that won World War II and the early Cold War”

Q When you start out that portfolio and you're looking at the world, there are probably some similarities, differences. Competitive advantages you wanted to lean into. Walk me through the design of this and how you've implemented it. What's similar from other pools and what's different?

A What's similar is we have equity-centric portfolio. Just like any other endowment, we need to generate a five percent plus real return. You can't do that any other way than investing in equities. We use primarily outside managers. Those two key tenants are pretty similar. What's different are a couple of things. One is we are resource constrained. It's been a team of mainly five investors since day one. When there's just five of you, you can't do everything. You have to make a choice about things to leave out. Because you're leaving out a lot, you really have to be focused on picking the right things to lean into. Our portfolio probably looks a little bit different in that there's a lot of things that we've decided to not spend our time on. Because we believed we'd be better spent spending time elsewhere. Things like private credit, China, Latin America, Africa. We decided to keep focused on other areas of opportunity. The other real difference in our portfolios that's significant is we have less illiquidity risk. We only have about 20 to 25% of our portfolio in private assets. Some of that is a structural constraint that we have, which is that most of the assets that we manage are actually not true endowment assets. They're balance sheet assets. There's not a statutory constraint. Elroy Demson is a researcher. He wrote a paper a few years back. One of the things he looked at w…

AI assessment note: “What's similar is we have equity-centric portfolio... What's different are a couple of things.”

Q It feels like today there's either a lot of simmering or a lot of burning across a lot of areas, private equity, private credits, and emerging markets, U.S., Where are you thinking about diving in to do research?

A Some of it is in our own kitchen. India right now is going through a very difficult period. It's got a double whammy now of being in the crosshairs of AI because of IT services and the huge part of their economy that that sector represents. It's got the risk that it's facing from the Iran war, where it's so dependent on Middle Eastern oil, gas, and fertilizer. That's a place where we're spending a lot of time to underwrite what we have, to be ready as dislocations there might increase. We have been positioning our credit portfolio to better take advantage of dislocations. We've done a fair amount of work to be well positioned for what's happening in private credit. We recently reconfigured that part of the portfolio, added a new manager. We have capacity to add there. That's where there'll be tons of interesting opportunities. There will be indiscriminate selling in private credit. There's good reasons why many of those companies will be sold, but there'll be many reasons where it's just liquidity that's driving prices down. We're excited about opportunities coming from there.

AI assessment note: “That's a place where we're spending a lot of time to underwrite what we have”

Q What was different for you in what you saw from the years spent managing fixing portfolios with those two bookends of Columbia at the beginning and then Virginia afterwards?

A I came at it from a quantitative background. My interest in this all was fixed income was easy because you had closed form equations that could solve the pricing. When I got to UVA, I understood how so much alpha was generated by being able to have a more creative thought process about asset pricing. This was when the Tiger Cubs were at the height of their powers. Being able to look at the Lone Pine portfolio and see how Steve Mandel and his team could see into the future about What these high quality businesses would be worth was eye-opening. It was a completely different model for making money than I had understood in the past, and it was so much more potent. It lit a fire in me as far as thinking more creatively about investing, which fit my personal background really well.

AI assessment note: “It was a completely different model for making money than I had understood”

Q decided advantage. That's why customers call it miraculous, game-changing, and an awakening. If that's not how you would describe your investment management tech, request a demo at ridgeline.ai. And now back to the show. I'd love you to dive into the concept of limited time, limited resources, have to focus on the things that are most interesting. How do you go about deciding where to spend your time and energy?

A Primarily, that has come from our relationships with our managers. Some of that has also come from our own research. An example of the latter would be When we started, if you looked back on the last 10 years of our peers and where overseas they had generated all the returns, it really was in China. From the beginning of the admission of China to the WTO to 20 15, that was where the golden years of both the China economy and investing in China. That's right when we started, and we look back, you could see some of the political winds changing in China. You could see some of the political winds changing in the U.S. in regards to its relationship to China. It was also clear to see that that opportunity wasn't the same as it was in 2005. We then started to think about where that opportunity might be. We spent a lot of time in India. Since 2018, India has been Our largest overseas allocation of any region or country. That was primarily driven by an internal iteration of our own research. We've been fortunate to work with some managers who, this is a rare skill set, can see where economic value creation over the next 10 years will be. There was an individual named David Mock, who had done an amazing job at Hill House riding that China wave. We backed him day one when he launched his own fund, Composite Capital. Within two years, he had stopped investing in China and pivoted his portfo…

AI assessment note: “Primarily, that has come from our relationships with our managers. Some of that has also come”

Q If I told you today, hey Bruce, it's time to sell the entire portfolio again, take out liquidity restraints and things like that, but you could rebuild it tomorrow. How different do you think it would be from today's portfolio?

A One of the big changes would be in our private portfolio because we have such a limited private allocation. We try to focus on where the most asymmetric return opportunities are. I do think our venture portfolio has many great managers in it. I don't think we've leaned hard enough into the asymmetry. We should have more managers who are at that smaller level of the fund sizes, two hundred million and below, where their outcomes could be a 50 X or an 80 X. There's good reasons to invest with established managers. You end up paying a lot in fees for returns that might be available in public markets. Might be a better fit for our portfolio to just have a little bit more of that emerging manager risk or smaller fund risk Because the payoff when it works can be so much greater. That's probably the biggest change we would make.

AI assessment note: “One of the big changes would be in our private portfolio”

Q So what I'm thinking as we start, just kind of give us like a brief history lesson of just like what happened in November and where are we today? What's possible now?

A Well, let's, let's talk about all of twenty-twenty-five very briefly. Um, twenty-twenty-five was the year that especially Anthropoc and OpenAI realized that code Is the application. Like being able, having these things generate code. I think partly because, um, Anthropic came up with Clawed Code back in sort of February of 2025, and it took off like crazy, and a bunch of people started signing up for 200 dollar a month accounts. And so suddenly, wow, it turns out people are willing to pay a lot of money for this stuff, for that specific field. Both Anthropic and OpenAI spent the whole of 2025 focusing all of their training efforts on coding. If you look at what they were doing, it was all the reinforcement learning stuff. The reasoning trick, the thing where the models say they're thinking, that was new in late 2024. Like OpenAI's O-One was the first model to exhibit that. And now all of the models do it. So that was the other big trend of last year was these reasoning models. Turns out reasoning is great for code. It can reason through code and figure out the root of bugs and all of that. And so the end result of this, the end result of these two labs throwing everything they had at making their models better at code Is in November, we had what I call the inflection point where GPT, 5.1 and Claude Opus 4.5 came along and they were both just, they were incrementally better than…

AI assessment note: “in November, we had what I call the inflection point where GPT, 5.1 and Claude Opus”

Q If you can recall, You know, roughly. Which year did you cross? 50 miller and which year you crossed hundred miller?

A Yeah, yeah. So I believe we crossed fifty million. So I started with Cloudflare in early 14. I think we crossed fifty million in I think end of 16, 2016 in three years. And then in, then at that time we were more than doubling the business. So then we must have crossed the hundred like within the next nine months. Uh, so we went public in 2019 and at that time we were doing about three hundred million. So, so if you know, in our case, I think, uh, we went from like a couple of million to three hundred million in, in a, in a matter of, uh, five years. And, and then after, after going public, we, we actually accelerated over growth, because, you know, as a public company, we were, we, we were able to have bigger awareness, and then COVID happened, and then we went from three hundred million in 2019 to a billion in 2023, basically.

AI assessment note: “crossed fifty million in I think end of 16, 2016 in three years”

Q Alright, let's start by having you give me a walkthrough of the, uh, uranium fuel supply chain, the nuclear fuel supply chain. So, like, take me from soup to nuts. What do we start with, and what do we end with?

A Yeah, happy to. Um, I mean, the, the background is that every, every reactor needs fuel, as, as most people know. And we can talk about types of fuel, but, but all fuel in reactors in the U.S. today is made using a five-step process. So, step one is you mine uranium out of the ground. You then convert it to a gas. That's called the conversion step. Um, you then enrich it, which is really a refining separation step. You then deconvert it into a solid, back into a solid. And with that solid, you then make fuel, fuel fabrication. So fuel pellets or trisoparticles or whatever that is. So five steps total. Um, the US does all of the steps. The US does not do the middle step at commercial scale. So that's where the bottleneck is, which I'm sure we'll talk about today.

AI assessment note: “all fuel in reactors in the U.S. today is made using a five-step process”

Q over time as the U.S.-Russian relations have moved? Like, I get the sense it's one of these areas that, like, We kind of don't like to talk about it because we're sort of reliant on Russia to some extent right now, but we need it, you know, and so we're sort of unwilling to sanction it or stop buying from Russia. Is that, do I have that sort of right?

A Well, in, in twenty-twenty-four, there was a Russian uranium imports ban passed by Congress, and so there's a waiver process, um, that's, that's ongoing right now where the Secretary of Energy can waive, uh, the ban. If a utility needs it and there's not another source, which has been the case, um, that waiver process expires January first, 20, 28. And so the setup today is yes, it's still three quarters Europe, one quarter Russia. Um, most of that Russian uranium is coming in. It's all coming in under those waivers. Um, I think it's gone from about 25% to 20% as utilities look to diversify and get ahead of the full 20, 28 ban. But That is currently the breakdown. Um, a lot of people have asked, how, how do we even get here? How is it the case that we're still importing from Russia? You have to go all the way back to the fall of the Berlin wall, the end of the cold war. So eighties, the U S was the leader in global enrichment, something like 86% at the peak. Um, and then the Berlin wall fell and we entered a treaty with, with Russia, which was called Um, the megatons to megawatts program, and in that, in that trade program, we imported Russian, uh, warheads. We downblended them and used, used that downblended material to run our reactors. Um, we then, you know, sent the depleted uranium back to Russia, uh, to be, or the, we sent the depleted uranium back to Russia to be enriche…

AI assessment note: “in twenty-twenty-four, there was a Russian uranium imports ban passed by Congress”

Q And is it, is it like a replacement ROI that you're selling? Like you don't need air specialists anymore, or do you like enhance, like what's the positioning?

A Yeah, it kind of just depends on the company. So, you know, we sell to flyover state businesses. I'm from Michigan. So think like industrial manufacturing distribution, those types of companies. And we really augment teams. Some people are like, you know, we might want to move accounts receivable back to sales. You know, sometimes there's people in like warehouses that do it as a part-time job, or even like our larger enterprises like Honeywell, they just don't have the account penetration. You know, think like somebody in accounts receivable can probably cover like 200 accounts a month. Uh, with AI, now you're able to cover like 5000. And so, and most companies actually are losing about five percent of their revenue trying to collect payments and matching up all the cash and handling with all the bullshit.

AI assessment note: “And we really augment teams.”