Citrini’s 26 Trades for 2026 | Citrini on BS Jobs, AI Materials, Advanced Packaging, World Cup, & More

More and more, returns are being driven by the themes a company is exposed to. That's why thematic equity research is so valuable. Today, I'm speaking with a clear leader in thematic research, Satrini. Many of you are familiar with Satrini's work, but in addition to research, the Satrini team also has a tool called the Satrindex to track custom indexes and baskets that they build. This helps investors track performance, think through trade expression, and improve portfolio construction. Throughout this interview, we're gonna put up some charts from the Satrindex so we can show you various baskets that we're talking about. The Satrindex subscription is a separate product from Satrini research, and up until recently, if you wanted to subscribe to both, you needed to buy them separately. But now you can get Satrini research and the Satrindex together in one bundle through Substack. Check out my link in the description or go to Satriniresearch.com/mmjack for an exclusive 25% discount on this bundle. The deal expires on January 14th. Let's get into it. Joined once again by an investor and analyst, who I respect a lot, I really like the way he thinks about markets, and I know many in my audience do as well. Satrini, welcome back to monetary matters. How are you thinking about markets in 2026? For subscribers, you recently wrote 26 trades for 2026, so you have an incredibly large and voluminous number of trade ideas. But where are you thinking you're gonna be seeing the opportunity in 2026? And what is the difference between something that's just on the bookshelf versus something that is actually gonna be implemented in your model portfolio for clients as well as you personally? - Thanks for having me back, Jack. Every year that I do this, it surprises me by the middle of the year, which trades I end up putting on, which I don't. That normally what happens is I have a couple that I'm really like, this is definitely gonna make it into the portfolio. And then I get halfway through the year and I look at what actually makes it into the portfolio and it's not that. Last year we had a piece, I think it was like the 16th trade that was like, if you remember, you remember when there were all those drones over New Jersey and we just kind of memory-old it. So that was happening around the time we were writing 25 trades. And I looked at them, I said, people are gonna start thinking about like counter unmanned aerial surveillance, how to defend against electronic warfare and this stuff. And then around the Iran escalation, put on the quote unquote drone basket, but it had nothing to do with the drones in New Jersey. So it's always interesting to see how the year progresses, but there are a few that I had pretty high conviction on so far, but again, it's mostly a thematic watch list. The reason I like doing it is just because it forces you to look at things that you otherwise wouldn't really think about. And so when we did that interview last year, 25 trades for 2025, we talked a lot about themes, we talked about electronic warfare or drones, we talked about Ukraine, Russia, normalization. And those themes were up 76% and 75% year to date. And you actually reviewed all of the themes and a little more than half of them outperformed the S&T and more than 80% had positive return. So definitely helped by the fact that we had a bull market but very solid performance there. And I should say also- - There's a point now that there were some dumb ones in there too, right? Like just for anyone that reads this and is, yeah, I'm gonna put on every single one of these trades. Like the one of them was, we looked at like these were mittens companies and they were so cheap and so enticing. I don't even remember what we said, but I looked back at it when we went to do the scorecard and I was like, why did we think that were mittens that would do well? When Trump's doing like mass deportations, that doesn't make any sense. So again, it's something where really the purpose of this is the in our vocation, we spend so much time thinking about being right about the future. And inevitably we'll run into a point where you look at, like this happened for me with gold miners this year, where it was like, I remember looking gold miners and they're so cheap, relative to where gold's at. And I just didn't do anything with it. And it was because I got so in the weeds on it and I was like, ah, you know, like a mine just to pull with a liar standing on top of it. And I ended up deciding against it. And I look back and I say, man, if I had just done the obvious thing, which is by the gold miners, 'cause gold's already up 40% of your day, that would've made great trade. You always find yourself missing some obvious things and that that's inevitable. But for me, at least the way that you can most effectively defend against that is once in a while, you just allow yourself the time to not feel the pressure of everything I do needs to be right. I need to be skating to work. And you just say, what do I think is gonna happen? What are the kind of obvious, whether or not so obvious, what's the biggest list I can make of things that probably could happen? And that's what this is. It's like the one time a year where we're not just neurotic about being right. - Right, and you also have a model portfolio, the Citrindex that you track very rigorously. And that's the Citrindex I see for 2025. So as we record, it's up 22% year to dates versus 18.5% for the S&P 500. And since inception in 2023, the Citrindex is up 217% versus 69% for the S&P. And that is a way to actually track what's doing. Because I could have my investment newsletter and I throw out a thousand ideas. And 10 of them are gonna make me look like an absolute genius, but actually determining the sizing, the entry points, the exit points, rotations, went to hold onto a winner. Like that is really what makes the great investor not just the ideas. So I think that's important. And monetary matters listeners can get that you're selling that as a bundle. So the Citrini research sub-stack, as well as the Citrindex tracking tool where you can track all of the baskets and that in real time for that bundle, monetary matters listeners can get a 25% discount until the middle of January. And I think James, there are some hedge funds that are not tracking like with as much rigor their positions as this is Trindex. So even though it is a model portfolio, I've been using it and I'm definitely impressed by it. Tell us a little bit about that. - Well, like you said, you know, but when you're writing research, the easiest thing is, you know, you write the research, the things that are wrong, you never really talk about them again. You know, you say like, so and so stock is a long and then it goes up and you say, yeah, look how sick we did. It's very rare, I think. And it's like the much more difficult thing to do. Obviously, if you're managing a portfolio, eventually you take a drawdown or you're underperforming that happens, right? And when anyone can log into what I was saying and see it, it's like, oh, you're talking about this, but you take a drawdown, yeah, well, that happens. But it's for me the most effective way to communicate whether I still think that something's a good opportunity, whether we can always write about something. And then it's a different matter entirely. Is this just interesting? Is this something that you're actively buying? Is this something that what's your timeframe on this? It's just them, we're all reading research because we wanna make money in the stock market. So it's for me at least, it's the most effective way of communicating that. And the other cool thing that I have focused on with Citrini is creating these kinds of thematic factors. If you think about artificial intelligence, for example, it's not necessarily the same as growth or tag it. And there will be periods of time where things find themselves into, quote unquote AI factor that wouldn't necessarily otherwise be included. Obviously, you're gonna have all the data center stuff in terms of semiconductors. But what about when power becomes something that everyone's talking about? And, you know, Jeep or Novo and Siemens Energy find their way into that factor and start trading with beta to this AI factor. So it has every single basket that we've ever created. And you can, and real time tracking. And you can get a good feel on at least for our thematic universe, which now after three years, it's pretty deep. Like we have a deep bench of themes. It's like a, it's a very interesting addition to just like tracking your classic, mobile, growth, dividend, whatever factors. Seeing now 132 baskets, that is a lot of asking. Oh, James, so talk about the AI trade broadening. I'm reading from your 26 trades piece. You write that the, the shirt fire path to being early to someone most profitable parts of the AI trade has been looking at areas that currently have little to no AI premium baked in. And reasoning out six to 12 months as to whether they'll become a crucial part of the supply chain. So basically buying stocks that no one really associates with AI, but make products or services that are related to AI that are going to be in high demand as the AI build out continues. So the topic that's been on everyone's mind as it relates to AI is, you know, where's the return on investment coming from? And that's the whole bag of worms to the hyperscalers and the companies that are selling it to the data centers and lots of. The interesting thing that happened this year, there's been a lot of focus on the science fiction version of AI, one's going to cure cancer, one's going to, you know, kind of reach AGI, or whatever you want to call them now. I think that what happened this year essentially is we found capability gap where the trade is going to broaden out to not about what AI might do in five years, but very much about what it can do already that companies have been lagging and figuring out. So the reality is essentially that if you think of any organization, there's always going to be a subset of the kind of organizational pyramid at the bottom where it's pretty much undifferentiated labor. And AI progressed in 2025 to the level where the technology to replace that already exists. Not necessarily the people above, let's say that bottom 20%. But any organization has a certain amount of employees that are creating negative value. And there's a huge gap between what AI can do to them, what most organizations are actually using it for. And that's where I think this new part of the trade lives. And the reason why it's so interesting to me is it's kind of similar to the robotics thesis that we have, which we spoke about, where the automotive cycle was so bad that you could buy these secular winners from robotics at this kind of cyclical trough price. I can give you a real example. Like I was talking to a senior person of unnamed large professional services from recently. And they were telling me, yeah, we're experimenting with AI. We're letting junior analysts use chat to the summarized PDFs. We're using quen and all this stuff. But at the same time, think about the standard junior analysts that have bank or consultancy. What's their actual job? It's not strategizing. It's taking a logo from a PDF, from moving the background to line your perfectly on a PowerPoint slide two in the morning so that their MB doesn't yell at them. That is what David Graber in his book called "Bullshit Job." He has this great quote about John Maynard Keane's saying in 1930, "By the end of the century, we'll all have a 15-hour work week, 'cause technology will have taken us so far that you don't need to be in the office 40 hours a week." And he was right. The technology did progress that level. But we just created a bunch of more work that nobody really needs to do. And there's a lot of people that show up to work, like email jobs, and they don't feel that what they're doing needs to be done. So right now, like at this exact period of time, an AI agent can do that same logo lining task in four seconds for a fraction of a penny. But Fortune 500 companies are still paying a guy from Warden $150,000 a year to do it manually because their own internal bureaucracy hasn't caught up. Technology advances at this exponential curve and human adoption of technologies is relatively linear. So I think that there's a trade there for sure. You wanna own the companies that have very bloated organizations and show some intent to cut that down with artificial intelligence. And the interesting part right now that's unique about this exact moment in time, nobody's stopping them from doing that. If you think about the social implications of like mass unemployment or this actually occurring, there's no eventually that will cause an issue. But right now, there's no regulatory blocker, there's no technical blocker. It's just that these organizations don't know how to rewire themselves. So when you look at some of these companies, like that have been trading like AI losers and that's gotten their evaluations extremely attractive. If you take the idea of this company might end up being an AI loser. Yes, AI can code now. So maybe you don't need to accenture it, maybe you don't need to cap Gemini. But that's not gonna happen overnight. And the ad agencies, I'm the com WPP, they're not gonna get replaced by AI tomorrow. But they can replace a very significant amount of their labor pool with AI today. So looking at across this universe of stocks that could really see a benefit from organizations realizing that they can finally utilize AI, that it's good enough. When people talk about this adoption being slow, I think that's the wrong framing. The tech adoption is fast, that the organizational adoption is racial. And there's an interesting universe of stocks that are just very cheap that are traded like AI losers. And it could realistically cut half of their workforce. And SGNA would go down. And margins would go up pretty significantly relative to their peers. And then they'd rewrite. And I think that'll happen in 2026. If you think of the other interesting angle here is, you remember we spent a lot of time in the 2010s talking about the cloud transition. And it was a big deal that companies had all this data that was sitting in analog, whether it's paper or whatever notes. And that cloud transition, we don't talk about it that much anymore, but it never fully happened. So the second that one of these companies manages to utilize AI to cut a significant portion of jobs and ends up being fine, if not better, more lean, realizing better margins. Their competitors are going to say, oh, we want to do that too. And the bottleneck is going to become. We don't have that much. We're not at the level where we can be able to do that. We've got the companies that assist with this, think about like SAP. They haven't gotten any AI premium at all baked in, but if you actually think that AI continues to progress in the way that it has and you look at the technology and you know it's good enough to do this stuff, I think we're looking at it, but you're where those companies get some of that premium. And it's from a very, from a risk-reward perspective, it's pretty attractive because they're already trading like AI losers, what, they're going to lose more. Everyone is already maximally bearish. All the capital has been sucked out into the data center beneficiaries. So I think that looking for those companies, which we did a pretty in-depth screen, we narrowed it down to 30 companies. We did some qualitative stuff too, just looking at which companies are actually already talking about using AI for this. That is going to happen. And it'll be a great trade in 26, I think. And how do you crystallize this into an actual trade and find those companies? Talk about the screening process you just referenced in terms of finding companies that have a high head count. And you constructed a bureaucracy score. And then we have a kind of dot cloth, the AI bureaucracy, alpha framework. Basically, it's a process. First, the reason why this trade kind of came about is we were looking at, we did a very naive screen, which is just, let's take the S&P 500. And let's look at the bottom 10th of companies that have the lowest net income per employee. And those 50 companies have massive, we don't perform the S&P 500. So that was interesting to me. But there's a lot of reasons that you don't have low net income per employee. So we said, OK, we've got to go a step further. We used, first, basically what you want is a company that is spending a lot on employment and spending a lot on employment in an inefficient way. We use SGNA as a pretend of sales. And then also what you want is this margin optionality. So you want these companies to be able to within their sector, the sector relative cut the undifferentiated lowest performing labor and be able to increase their margins significantly because they go from the bottom to the top of their field in terms of margin. So we did that. We did like a quantitative screen. And then we narrowed it down qualitatively by looking through a filtering for companies that are talking about AI or done head count reduction already. And then a really interesting aspect, or really interesting area, is like insurance brokers for example. This is like the most paper pushy organization in the entire world. And there's a lot of employees. And there's a lot of people. And I don't want to give up the vibe that I'm rooting for people to lose their jobs. But at the same time, you have to realize that this is going to happen. And when the market's giving you these names that are like incredibly reasonable valuations, you've got to go for it. So we narrowed it down to about 30 companies. There have been many different fields. Stock you sign for example is one of them. And then we threw in some of the names that would help in this transition like some of the cloud names. It was very interesting while we were writing this IBM acquired Confluent. So it's a broad 30 names across different sectors. But the thing that they all have in common is they can utilize AI to increase their margins like this year because of the work that they have a lot of employees and a lot of those employees are going to go for jobs. Hey everyone. You've heard us talk about the Citrindex. And I want to take a moment to explain what that is. As the name suggests, it's an index of Citrini's most high-conviction ideas at any point in time. And the Citrindex tool is an all-in-one dashboard for tracking that index, as well as over 130 thematic baskets that Citrini and the team have made. Plus, it's updated in real time with instant notifications as prices move and facts change. The Citrindex is a separate product from the Citrini research sub-stack. Up until recently, if you wanted to subscribe to Citrini research and the Citrindex, you needed to divide them separately. But now you can get Citrini research and the Citrindex together in one bundle through sub-stack. Right now, through January 14, monetary marriage listeners can get an exclusive 25% discount on this bundle. You'll get access to the Classics and Citrini research that we've all come to love and the Citrindex subscription. Visit Citriniresearch.com/mmjack to access the offer. Just make sure that you're signed into sub-stack or enter your email to unlock the special discounted landing page. If you aren't signed in, you can't access the special offer. Remember that Citriniresearch.com/mmjack. Let's get back into it. I'm just trying to see the dot plot. On the x-axis, it is companies that have a high overhead right now. And the y-axis is the optionality to increase their efficiency. So a company that's a classic example would be these consulting companies like Accenture or Booz Allen Hamilton. So Booz Allen Hamilton, that also has a DC factor involved in that, because everyone thought, OK, Doge is going to happen. And all of these government contractors are going to get totally destroyed. That never really happened. But so Accenture, I know that there was a while where they were actually seeing a very large increase in their revenues from AI. But the stock had not been training well at all. What's going on in Accenture? And exactly that is what you refer to in the piece as a people factory. A company that's just extremely employee-heavy. And listen, probably both, but everyone's kind of guilty of this, where in the beginning, all you really needed to outperform because of AI was a conviction that we were going to do it. And then you said, OK, well, if we're going to do what we need, we need the data centers. And everything has been a derivative of that. And I did that, too. And that's been great. And is that going to keep happening? Yeah, probably. I do think that there's something to be said about 2026, maybe, being the year that algorithmic improvements start to compete with, just like we're out of compute. But that's been the trade. And it's been a great trade. And the reason why we included this specific trade in this piece is because that probably will continue. But at the same time, it sucked a lot of capital. It's become such a no-brainer and so easy that there are a lot of companies out there that just have knock on the second look. Like you said, Accenture has they've cut jobs. They've spoken about AI improving their margins. They AI keeps getting better and enough to use Gemini to create images. But it's like, it nails it. It doesn't really get text wrong. I think you create 10, maybe one has a slight error. And fixing it is as easy as just saying, hey, can you fix this? And it does it. You go from 10 people, each individually working on this, being managed by one guy to the manager and the manager just manages the AI agents. And the thing last year why this wasn't really going to happen was the hallucination rate was just unacceptable. And there's still been some enterprise resistance to that. But you look at like Google's TPUs, right? They're deterministic. And Gemini has a much lower rate of hallucination as well. So people haven't taken a second look at this. And that happens all the time in markets, especially when there's an easy way to make money that doesn't require looking at these areas. And it'll-- I think if you're not looking at this, you're doing yourself a disservice. Because we're not going to spend at trillions of dollars on creating the infrastructure. And then just be like, cool, done. All right. But we're spending a trillion dollars. And we're going to get to AGI. And then AGI happens and overnight, everyone loses their jobs. OK. That's not how it's going to happen. It's not how technology works. The trade here, it's not the AI takes your job tomorrow. The trade is companies in 2026 will slowly realize they've been paying humans to do things that computers are already better at and can already do it for action of the cost. And historically, when that realization spreads, it's an interesting time for society and for shareholders. If you-- the pushback to this is, well, every time that there's a new technology, new jobs get created because of that technology. You look at Excel, for example. It's like, it got rid of the actuarial profession, but it pretty much created the profession of investment analyst. But there's always a gap. You don't have the lotites being mad unless people first lose their job before those new jobs get created. And I think that we're in that period for the gap to turn out. And you put this trade first in your piece. So you must have a pretty high degree of confidence, a higher degree of confidence, I should say. What about this view? What about the backlash to this, James, because I actually wanted to save this for last or not talk about it, because I wanted to avoid making people angry about everyone's going to lose their job. It's not a happy thought at all. I think it's maybe a bad thing, but that doesn't really matter in the investment business, I guess. Yeah, I mean, I'm not rooting for people to lose their jobs, but again, we spend a trillion dollars on a technology, and the sole purpose of that technology is to replace people. And as it gets better, there's a whole other aspect of the societal implications. And could we see an economy in 2026 where the unemployment rate continues going up, but stocks also continue going up. That's happened before plenty of times in history. Good examples, like after World War II, you had all the GI's come back, the unemployment rate was very high, but the stock market continued to do well. It's remnant. March of 2024, we wrote a piece about how to play Trump winning the presidential election, and have the people that read that were like, nope. Well, I don't like this. When you're an investor, you have to separate what you want to happen versus what's in front of your face and likely going to happen. And it's something where the reason why it's up front is because there are a couple of things we could be wrong on. And maybe the stock market continues to just play the easiest thing, which is Nvidia and the supply chain, and all these other things that we talk about, like advanced packaging and the bottlenecks towards making compute capable of doing AGI. But eventually, no matter what, if you're spending it like this will happen. And it's a good idea to be prepared as an investor for what that looks like when that does happen. And it's also got a macro angle of just, are we going to see the unemployment rate rise? And I can see it very clearly in the beginning when that starts happening, and the unemployment-- it might already be happening. The unemployment rate is rising. People are getting increasingly embarrassed, but then companies keep posting excellent earnings. That's something that's very likely to happen. And it's something that you should be aware of. So that's why we live with it, because everyone, I think, deep down knows that this is going to happen. Nobody that's using AI with any regularity doesn't witness the improvements, doesn't notice that it's doing more of the things that they would be doing themselves. It's controversial, but there might have to be-- with every new technology, there's a change to some degree of the social structure. And that's beyond my IQ, what society looks like in that world. But it's something that probably should be thought about. And what about the countercase that actually AI is just a parlor trick, and it can't be used for real knowledge work? It's just taking ideas, not generating new ones. And that in particular, there's a reason that it hasn't been picked up in the enterprise for individuals short, but for enterprise, not so much because you referenced the hallucination rate. Interestingly, I've always been a Gemini user. So I've seen hallucinations a few times, but not nearly as often as people are talking about. Yeah, I think that when you're investing in technology changes pretty quickly. And we've seen a lot of changes this year. And you have to update your priors when those changes occur. I would just say, show me a time in history where we put this much capital into something that didn't at least make it better. We're putting more capital in this relative than we did getting humans to the moon. You can be on the other side of that and say that it's a parlor trick, sure. But even if it was, you throw enough money, it's something that eventually doesn't become a parlor trick anymore. So it becomes reality. Even if the stock market becomes this illusion with the technology will continue to go forward. And that's what's so compelling about looking for opportunities that are mispriced like this. Because when you think about the dot-com bubble, for example, I don't necessarily think that we're repealing the dot-com bubble or that we're far along in that pathway yet. But when you think about the dot-com bubble, the biggest strides in the technology were made while the bubble was bursting. It concentrated capital into more efficient uses. There was a bunch of capacity that was there for the taking for people that were building things. If that were to occur, you look at how a lot of these names find themselves in value factor or in low volatility factor. And if you have this top of mind and you're monitoring it throughout the year, if there is some sort of scare, these names will probably go down a lot less. Or maybe you can go up because they're improving their margins. So yeah, I would say to that parlor trick, it's an uninformed take. And those people will get their day, right? They'll get their day where they say, I told you, look, it's like the stock market's down. That means the AI isn't a thing. But it will be. And it will continue to accelerate. And if you're not preparing for that, it could be where we're doing it. So James, I'd categorize these, the basket of companies that could shed their workforce and increase their earnings and productivity as because of AI. I'd say that is a trade that is a result of AI trade rather than a capex trade. So when you came up my previous show in 2023 talking about AI and everyone was a skeptic, you were all talking about NVIDIA, the semiconductors, maybe the companies around the semiconductors, the data center. Now it seems you're focused more on companies that actually are going to use AI rather than the capex. You still have some capex names. So James, I mentioned that yet again in 2025, yet another year of this disconnects has beaten the S&P. However, don't you think it wouldn't have been better to just trade the capex names like all these memory names are going crazy? And you probably were along those names in 2023 and 2024. But has the pivot from the capex into the beneficiaries is, from phase one to phase two, is that a mistake? We still be in phase one. Absolutely. If you look at the, if you go and you load up our AI basket, it's about 30 or 35 names. Throughout the year, we did on micron, we owned SK Heinix, we owned Keeoxia and the names that benefit from this increasing it for both storage and memory. And that basket, I don't have exact numbers, but I'm pretty sure it was up like 70 or 80% of your day. Yeah, it should have been sized larger, but at the same time, it is a, the risk, right? If you look at how it did in April, right, it wasn't that obviously an opportunity to buy the dip, which we did, but the risk can, it will continue to increase. And it's the, investing in the infrastructure, yes, it's been a great trade. It probably will continue to be a great trade, but it does have an expiration date, I think. And I'm not smart enough to know whether that's this year or five years from now. So I think you do stay allocated to it and you do continue to really, the trade in AI infrastructure has been much more about monitoring for bottlenecks than it has been about just going for whatever we need to build. Because that's constantly changing. And now you have another idea that we speak about in this is advanced packaging, has become the bottleneck and we'll talk about that in a second, but to answer your question, yeah, we probably should have sized up a little bit more in these like first phase infrastructure build ad names in 2020, but you do need to start thinking about a margin of safety. And if that means that you put a portion of your, I really am a fan of like the tracker position, like same with Peter Lynch, you know, you know, 1400 stocks, and you would just buy stuff to put it on a screen. I think it's a really good idea to put this on your screen. And then if the tide starts changing and you see these names out performing, that's like, like, okay, because this second phase will happen and we were definitely early to that, but it's going that like the infrastructure, every time you have an infrastructure, but eventually you get a capacity, and I think we'll get that to here. I don't think that'll occur in 2026, but you should really be focused on just in the infrastructure layer. You look at the bottlenecks, memories of huge one, advanced packaging is another one. And then I do think it's a good idea to start broadening out a little bit in terms of who's going to, this is a real technology now. And we're going to keep building it, but also it's been built to a degree that is pretty useful. >> I think that, yeah, so just looking at the contribution of the P&L, yeah, the dynamic AI basket was up 70% this year. Interestingly, the biggest contributor was shorting the VanX semiconductor ETF. >> Yeah, that was a good one. The deep-sea thing. >> Yeah. So that's good. I don't know that many investors who made money shorting semiconductors this year. >> I had a great conversation this year with Peter Borish, who was at Tudor, when like the 1987 crash, and they nailed it, right? And he was the guy that was making the analog between the 20s, and that helped them be prepared for that. And when I started talking, I said, man, I just got to ask you, and you could see the look on his face. It's like, this guy's going to ask me how I predicted the '87 crash again. And I was like, how did you convince yourself to go long at the lows? Because that is so much more difficult. If you think about it, like a spend, if you're right about a market event like that where you have a huge drawdown, and you make money from it, convincing yourself to get back in is way more difficult. That's the kind of similar thing that happened with you, Steve, where I thought that it represented this broadening out. And for a month, a ton of money shorting SMH on that, pretty covered it pretty much near the lows. But then started looking at these kind of, what about names that aren't semiconductors? And so it's a double-edged sword to do that. But I do think the valuations are getting too attractive, and the opportunity is getting too obvious, where the profit incentive to utilize AI is going to become a driver. And the infrastructure, I mean, there's been a lot of money spending. You start having to ask yourself, you do need to see adoption. And I do think that we will see adoption, and it will drive more money going on. Both of these things can do well at the same time. It's just a matter of continuing to be solely focused on the infrastructure bill that has a lot more risk than starting to think about two steps ahead. But there are places in that infrastructure bill that are pretty reasonable still. The advanced packaging that we were talking about. We will get to advanced packaging. I just want to remind our viewers that I'm looking at the attribution of all of this baskets and the Citrindex. That is available in a package deal, the Citrindex and the Citrini sub-stack in one bundle for 25% off to monetary matters listeners until January 14th. James, talk to me about advanced packaging. I literally, before I read this, I thought you were talking about some sort of really fancy box for an APS or a FedEx. So I'm such a Luddites. But what kind of companies are we talking about here? What's the theme? Why is it so important for custom silicon as well as maybe Nvidia too? That's the advanced packaging. It is what it says, right? It's packaging these chips in a way that basically for 50 years, if you're familiar with Moore's law, we may transistor smaller. And that worked great. And then we hit a wall where chips like we could make them bigger to fit all this stuff, but we can't make them any bigger. They won't fit on the lithography machines. It's called the radical limit. So if you try to print a chip bigger than that, the yields collapse, you lose money. So the new game isn't make the chip bigger. It's make a bunch of small chips, which are adorably called chiplets, and stitch them together so they act one big chip. And that stitching is advanced packaging. This is an interesting bottleneck for me because it's been a bottleneck for a while. If you've heard about coos from TSMC, that's been a big capacity constraint in making as many GPUs as possible. But the reason why this is interesting to me now with names like Ampore and some of the supply chain like the tooling and stuff like that, we saw Google come out with these TPUs. They've been doing the TPU, but the TPUs got good enough to deliver a model that was state VR. And that's not going to be the last piece of custom silicon that we see. If Google is competing with NVIDIA with TPUs, or if Meta makes their own chip, or if NVIDIA launches Black, but all of these needed mass packaging. They're all fighting for the same exact capacity. TSMC is the only one doing it at scale, and they are completely tapped out. And the names that are taking their overflow capacity like ASC, technology, they traded much more reasonable valuations than, say, NVIDIA. And there's another name that might be controversial, or but Intel, right, Intel's been dead for a while. They keep sparing up. Intel's founded business might be a mess, but they're packaging technology, which, you know, eBit, eMed, which is, there's basically, if you think about packaging a bunch of small chips together, there's only so many ways to do it, right, and because there's only so many ways to stack stuff, you can either do it in two dimensions, where you just put it on the chip and then drill through it, or you can do it in three dimensions, where you stack things on top of each other and then stack them on top of the chip and it looks like you. Their advanced packaging, eMed, is there 2.5 dimension, which is just two dimension, basically, this marketing thing. And Phoveros is three dimension. It's becoming the first kind of real relief valve for this massive valve. There's already rumors that Apple and hyperscalers are looking at Intel just for this packaging layer. So, the trade for advanced packaging has these tailwinds from, on one hand, you get upside to this increase companies don't want to pay the NVIDIA tax anymore, so they develop their own custom silicon. And then at the same time, it's additive. So, if NVIDIA sells more chips, this advanced packaging, this complex still does well. And so, like, AMP core, it's a pouring study, has some exposure to mobile. It's increasingly picking up the volumes that Intel or TSMC are too busy to handle. And then, if you really don't want to own Intel, you could buy the guys that are like selling on the staplers, they come to call the Kool-Aid and so forth. I don't think I'm pronouncing that, but the tickers click TLC. They make this specialized kind of tools that bond these chiplets together. I think everyone kind of frames this as a binary thing, either Google wins or NVIDIA wins or a Chinese ASAP wins or right now, at least, it's all additive. So, I think they're betting on the duct tape holding the chip together rather than who wins the chip war is probably a good idea here. So we've got a chart and I like how you make this very simple. Actually, it's colors of my high school, so I like it even more. So that over time, the share of incremental performance from chips, mostly it came from, in the old days, it came from the orange, the transistor scaler. So basically, the chip being more efficient. And now it's coming from the blue, the system level integration, the chiplets, the high-band with minute Murray, HBM, and the co-packaged ASL. So it's not about fitting as many little tiny little things on the chip anymore. It's increasingly becoming about connecting the chip within the ecosystem. Is that what's called what "interconnect" means? Yeah, you need interconnects. Basically, you need all these chiplets to talk to each other. So, yeah, and that's kind of interesting. Once you start like, you're like, oh, advanced packaging. It's packaging stuff together, advancedly. It's like, oh, interconnects, it's connecting stuff. Inter. Now, obviously, if you want to be investing in this stuff, unless you want to go the route of like, literally becoming a semiconductor designer, so that you can understand this, that's like, more power to you. I would much rather understand it from, speak to people that are super smart, and then try to make it understand both someone that's not like myself. And so in terms of the core companies for this advanced packaging, the core longs, you call them Intel, Mcore, Synopsis, KLIC, and BESI. Tell us about Synopsis later on in the 26 piece you wrote a one name piece just on Synopsis, and then also BESI, that company. So, Synopsis, basically, Synopsis is another winner of this custom silicon drive, this a version to the Nvidia tax, this idea that companies can only maintain a massive gross margins for so long. And it's got an interesting story because it was punished for a pretty long time on Intel. But the elevator pitch is basically, you can't do like, like, this is called EDA and IP. So basically, they own the IP of chip design, and you can't build a modern chip without them. It costs like 750 million dollars to design a leading edge chip now. You're not drawing it on napkin. You need to, you need this EDA electronic design automation software to simulate every electron before you spend even dollar manufacturing it. And this is essentially a two-oply or a tri-oply. You have Synopsis, cadence, and mentor, which is owned by Siemens. And Synopsis, specifically, has gotten beaten down because they had a massive contract to help Intel port designs to their 18A node. Intel clean house that brought in LiquidTan to look at the books. He realized that Intel was basically paying for an ecosystem that didn't exist yet, and just wrecked both the contract. Synopsis had to eat the loss because you can't upset one of your biggest customers to suck, went down like 40%. And the market started pricing it like, it's this structural flaw, but it's a contract dispute. Intel's still a huge customer, Intel is improving, Intel's going to need more EDA and IP. They'll eventually pay back those fees because they need Synopsis to make their 18A node work. And if you look at the valuation gap between cadence and Synopsis, cadence is like 45 times earnings. The 30 Synopsis also did a great acquisition with Ansys, which is like the physics simulator. So it's, which is benefiting from these advancements in AI and also enabling these events in AI, which I think is pretty poetic. And like we talked about earlier that this advance packaging 2D or 3D, like as we move towards three-dimensional making these cubes of chiplets, you can't just code the logic anymore. You have to simulate the physics. So heat dissipation, warping, melting by owning Synopsis and Synopsis owning Ansys, their position themselves become the physics engine. And you're basically buying what can really be thought of as a monopoly at a huge discount because of a like breakup. Is it like a little bit expensive? Yeah, trade is a software multiple, it's asset life and it's a huge discount to take in. And so I think that Synopsis is a great play for 26. So that is a play for the packaging of the actual chip. The trade idea right after that is something that got me really excited because early on you had this infographics about a picks and shovels play on AI. And whenever you talked about a picks and shovels play on AI, it tends to have worked out well. This is something James, I've actually been looking in myself. I've just been asking Gemini, what are some commodity materials that are making AI? It turns out Silicon is extremely available. There's not going to be a shortage of the actual. A lot of sand on earth. But what could there be a potential shortage of and what could there be a potential buying in the cycle where the stocks aren't priced, have no AI premium at all. And yet they are producing a commodity or a material or a service that is not, that is going to be in great demand for this AI build up. So this gets way more nerdy. This is like the trade here is basically, you have a bunch of companies that are essentially commodity companies that are putting the kind of materials into, if you think about the GPUs, like the brain, these guys are building the skull and the spine and everything that goes into it. And a lot of these bottlenecks that get discussed, they're digital scaling, running into physics. And if you look at the way that this has progressed, we seemingly always have a bottleneck somewhere, whether it's like in a certain resin or a type of glass or so, a lot of these companies have done really well. If you can split them up kind of like oil and gas, you have upstream, midstream, downstream and downstream ones, like the PCB names, like Celestica, which make the boards to put these chips onto, they've done great. And then midstreams down a little less great and upstreams down, not so hot. PCB stands for printed circuit board and yes, Celestica was a stock that you had such high condition and you actually wrote a single name piece on it and we're very long it. Yeah, that was a great one, a 17 bucks, I think it's 300 something now, I sold it, right? But that was a mistake. But so looking at some of these like chemical or like material companies, if you look at the media out of like Japan and Taiwan, they're all talking about these shortages in, you know, not to like board, like BT resin, T glass, like non-conductive film, probably. And it's all stuff where like non-conductive film, for example, when you stack those high bandwidth memory chips that you need for any AI accelerator, you got to glue them together and you got to glue them with something that doesn't conduct electricity, but conducts heat. There's a company called Resenac that has like 100% market share on that though. And you look at when these companies which are priced like chemical or gas companies experience this positioning as like the only thing that we need more of, they do tend to increase capacity. Their stock also goes up 350%, look at Nitovo in Japan, they make they make T glass fiber which is a special type of glass that doesn't expand when it gets hot and they have 70% market share. You can't build a high end AI server board without this T glass and that stock is absolutely killed it. So it's interesting to look at that and say where else might there be bottlenecks? So maybe these bottlenecks continue so we create like a watch list of categorizations. Here's you need this BT resin, you need non-conductive film, you need this that and the other thing. And some of them won't have bottlenecks. Some of them are very commoditized and it's easy for competitors to increase capacity. Some of them will and watching that in 2026 will be increasingly important and an interesting one that I liked a lot. You remember MSG? Now Madison's work on the like when you order Chinese food and like the early 2000s you're like no and no MSG please yeah. So there's a company called Aginimoto which makes MSG and they also make the quote unquote build up film, the ABS substrate if you want to be like a huge nerd and that's like the insulation layer, they have a 90% bubble market share and so it's and guess what they trade like they make MSG. So they're boring, they're very in the chemical sector and if you look at this supply chain, the closer you get to the AI box, the box that you can touch, the better the stock is done. Look at like outside of the actual GPU, you look like birded or a victory giant, like you said Celeste got a TTI, the server racks, SMCI for a little bit, not anymore. As you go upstream from that, the guys that are like mixing the resin or there's still a lot of them that are trading at these cyclical, chemical multiples and you have a really good proof of concept in something like the tobo which traded like that and then everyone said whoa, we need a lot of T glass and down. So I think the trade here is much more interesting like the midstream, maybe the upstream if you want to be like if you want to play the upstream, you got to be really on top of monitoring these bottlenecks. But the midstream is benefiting from both sides, just keeping like a nozzler on like country, Taiwan or Japan word shortage. I think that and then once you hit one of those, you don't have to be like again, you know, via semi-anfair, you just go load of 26 trades and you hit one and it comes through when it says, hey, Tantillum, there's a Tantillum shortage, okay, control that, Tantillum and it'll show, you know, okay, so Tantillum capacitors are made by Marata Manufacturing, okay, cool, done. That's, it's something, this happened to Marata in, I think it was 2021 to where they said, we have all these crypto mining GPUs and a crypto mine and these crypto mining ASICs and they use 10 or 100, I might be off on order magnitude, as many times of these element capacitors than normal chips. And it was the most severe shortage because of crypto mining that we've ever had, looking at something like that. And if they start talking about, ah, we need these guys to make more of them. You find a company that has 170 to 100% market share and that can go on for a lot longer in this environment than people think. And so you're looking at companies like, yeah, Netobo, but in particular, Resenak, that's the seems to be the company that you had the high, was high conviction in. So yeah, basically, Resenak is the most shots on Goliath where Resenak has a lot of areas that go into the AI supply chain. There aren't any that are like, really in severe shortages yet. But basically, if there's going to be a shortage like in the midstream eruption, Resenak has the highest kind of likelihood of having a significant market share in that area. So again, it comes down to, this is a watch list. You can play the existing shortages, but I would just warn like, these companies still are commoditized, they still make their companies, they're making things, they're turning raw materials into stuff. And the companies are some of them selling raw materials like, if that bomb that gets resolved, these companies are going to have 50%. So it's, I think this is a trade where you can put it on and take the risk of, I think that these architectures won't change that much. And we're going to keep needing whatever it is, whether like T glass, we're probably need more of it. We're also like, you could look like last substrates and stuff like that. But you could also just say, this is a great watch list, and I'm going to just wait until, because the best way to be early to a trade is to just actually be paying attention to something. Just paying attention, a good example, like, it's 2022 chat GPT, you say, okay, I'm going to pay attention to what it takes to run this model, or to train this model, or whatever to deliver this product. And you say, okay, it's GPUs, and then you start seeing everybody talking about buying GPUs, okay, I'm going to buy Nvidia, but I, and that was an easy one. And now that's the most obvious thing in the world, you got to start saying, okay, well, what, what, what, what are people not really paying attention to? And for me, at least like before I did this research, I didn't really know about buildup film or APF substrates. And that's fair, but I'm sure there are a lot of people that are listening that might know about that and might be engineers. But for me, it's, it's easy enough to just monitor these shortages, and once there is one, you buy the companies. And again, if you look at Intel boats been going up every single day for eight months, and the first, you look at the first headline about the shortage of T-Class, and it's eight months ago. So, you got to track the shortages. In terms of actual demand for commodity things like copper, maybe silver, but also natural gas, where do you think the biggest potential for the price going up could be? I know that you're getting increasingly interested in the natural gas area. And in your model portfolio, the Citrindex, that actually is a, is a major theme. Why have you gotten so bullish on natural gas? A commodity that is famous for the supply being able to just go up a lot. Yeah. So, we're bullish on, in the commodity space, we're bullish on copper and natural gas. Copper is a little bit of a simpler story, but they both have the same kind of thing where you don't necessarily have this belief that this cycle could result in any sort of kind of competition, or any sort of like struggling to get supply on. And the thing about the copper might be the easier long natural gas, and we do own about your copper miners and we have for a while on that thesis, but natural gas is much more interesting to me because it's like nobody believes it. And I get it, and you can look at we published our thing on natural gas in September. Natural gas went from sub three dollars to like about five, and then it got caught in half. And it's yeah, like natural gas trades on the weather because it's the only thing that people care about in the front month. The opportunity here is basically, if you have the, if you believe in the idea that like this LNG export capacity will come online and it will start competing with the data centers that like nuclear is great, solar is great, I get it, you should probably, we're going to use that too, but we got a build machine got now. Most of these things are being run natural gas, and we're building so many of them and it's going to start having a competition with this other huge mega trend and infrastructure construction, which is LNG export terminals. And the US used to import energy and now we're going to, or we are large sex board. So I think that the trade again, the trade is not, I got a lot of people when we wrote it, the lock calls on my comm stock, which like great trade, okay, that worked for a few months and then the trade is you own these companies like EQT or comm stock or, and with the idea that like the back end of the curve will still be super volatile because it's natural gas, that's just how the commodity works. But that volatility will trend upwards because you'll need like the excuse of the Permian will just bring on capacity forever. I think like that's definitely how it's priced. And you don't have a ton of downside from that being the case, but you do have a lot of downside from that starting to get challenged. I think probably in the next year, if you remember like the IPPs like Vistra and, so the big thing that happened with them that was like so amazing and got all these growth investors to start putting growth multiple on it was they started offering power like fixed price contract to the Piper scholars. And you're talking like independent power producers like Vistra, Constellation, which unlike regulated utilities where, oh, I'm going to the government to get my 5% price increase approved. Like they can just charge whatever they want and they're not very regulated. And you were early in talking about those and investing in those. But yeah. Yeah, and you see like what, you know, like like something that's basically utility in early 24 starts trading within a beta of one to Nvidia. And that's cool, like the, because that's massive rewriting. And really the driving factor there was this like if you're a hyperskeller, you're worried about power costs, you're worried about power volatility. And Vistra is worried about the same thing. And Vistra says, okay, we'll offer you a fixed price contract on power for the next month. And what that enables is growth investors then can say, okay, I'm not really taking a view on like the commodity pricing of power, I'm taking a view on like hyperscalers using more of it. And I can put a multiple on that because there's this thing. And I think that in 2026, what we'll see, those hyperscalers will probably negotiate fixed price contracts for natural gas with like like EQT has already talked about this a little bit. It hasn't happened yet. But once that happens, the natural gas equities will, I think, trade better. And then if so, the trade is basically one, natural gas is going to keep powering our efforts towards AGI until we can do cultivation. And then on the other hand, the natural gas producers are going to be able to negotiate things with hyperscalers that allow their investor base to broaden out and get more of this growth investor in there. And then it's a similar but not identical story for copper, which most of the guys that are like trading copper futures, they're not going to believe this like AGI super cycle bull case. But we have a line there about how much it would cost to build a new escondida when it would come online. And it's massive and it takes forever. So it's a giant copper mine, yeah. Yeah, yeah. And so that's another, those two commodities are interesting. Can be copper obviously. It's been the easier trade. Natural gas will kick you in the knots a few times, but I think it's also a similar opportunity of brightening this kind of cycle trend. Have you looked into silver, use of the AI? I missed silver, Alts Campbell was talking about it for a while and absolutely nailed it. And I had that like weird psychological like anchoring bias that you get sometimes where I had a whole article ready about the gold miners and then I decided not to publish it. I decided not to put the trade on. And I really should have an extra word me on precious metals. And I just missed the silver trade entirely. I would say if you are interested in Mac, you should definitely go read that what Alex Campbell is learning about because he's been 100% right and I totally miss it. As I so that's the macro thesis for natural gas. I'm looking at Citrindex. You have all of these names in your natural gas basket. One of them I will say is a Texas specific land court, a company that I just think is fantastic. But why so diversified? If the core exposure for most of these companies is the same, what is the advantage of natural gas producer A versus natural gas producer B? That's interesting. So the biggest way to come stock and you can see and then but there's a lot of really interesting opportunities in like Canadian natural gas, which has been a nightmare and that's so. It's very much an approach of casting a wide net because this would be such like this thesis working out which again, this is like a longer term thesis, right? That's great. The natural gas went up a ton after we published and that the winner was all our thesis is not the winners are getting cold. If anything, like that these was like people have gone a little complacent about the winner being cold and sometimes the winner is cold, but it's such a it would be such a shift for the market to not be priced like the Permian can just infinity ramp to meet all these demands for natural gas that and then in the meantime, like if that isn't the case, the downside like relatively limited, especially from where we got in. So it's something where it's like a broader net of you have the upstream and Comstock and EQT and then you also have some the Canadian ones which like are super cheap and which ever one and that's a political aspect too, but whichever ones start doing well, those the ones had into and like the and it's it's a fixed pie, right? So it's not like we're like Martin galling into natural gas, but the increase doing increasing. It's also this is like even more heretical than talking about natural gas, but I do want a couple of regulated utilities as well, which is like insane for a long time. I never taught like my kind of framework was like financials and utilities, there are these industries where everything's okay and then one day you wake up and everything's really not okay, but some of them really, if you look at Excel, for example, I had a discussion with a company that's working with them called form their private and the concept of there's been really really no incentive to allow these utilities to increase their capacity or to do cat X spending and you know, and with the data center stuff, like there's going to be backlash and there's going to be a real kind of drive tool to change the political landscape to get them to be able to do that into some more so that prices don't go up on like households. So that's a super, it's a very left tail or right tail event, I think, but I do think that it could change a little bit in 26. So talking about a potential supply squeeze in, because of AI demand is going to see a high. AI demand is going to be so high. So copper, silver, natural gas, what about this thing you call, what's about this thing you call post-traumatic supply disorder, PTSD, where these cyclical markets have suffered for a long time of building up inventory and only to lead to a cyclical crash that they are avoiding investing into capital expenditure. The most obvious theme right now would be natural gas turbines, so like to even over zeemans. Talk about that. Yeah. So, basically last year, when we wrote 25 trades, the second trade was crouching tigers hidden dragons, which basically the thesis was started from the insight of what can we extrapolate from the names that have done really well into insight about what's going to do well next year. And we looked at like carbona and apple oven and unity and the kind of common thread between all these, which we talked about on our last podcast of 25 trades, was that they had done so much in terms of they had built so much infrastructure, not necessarily physical infrastructure, but they had used the zero interest rate policy environment to create this moat that would be incredibly difficult for new challengers to come up against in the environment where interest rates are 5%. And at the same time, they'd gone down 90% from their highs in 21 and lost their investor base. And everyone viewed them as like a bad word, and nobody really wanted to own them. So it was pated and but also benefiting from this a bunch of cheap money that they had used to build great infrastructure, and that did very well in 29. So we went back to the well of inspiration to think about what else then what did really well in 2026, and was there any common thread between them. So you've got you have memory, a micron, SK high nix, and manned like yaksia sandis, western bitch, you got the gas turbine companies and both of those sectors absolutely murdered it this year. And when you look at them, you see some of the best companies in the world in terms of stock performance. Yeah. And you look at them, you say, you can take the easier way out and say, okay, it's AI exposure. But there's a lot of companies that have AI exposure that didn't end up being the best performing companies in the year. So I think that if you think about it, what is the kind of commonality between these companies had over the past five to ten years that these big cycles where they ramped capacity into it to meet what they thought was like secular demand. And then they got absolutely screwed by doing that. And now they're reticent. They're not as gung-ho. And eventually they will increase capacity, but at least for the past year, they were pretty much contentful at their backlogs grow, the average selling prices go up. And so it's like PTSD, right? Like once bitten twice shy. So we call it post-traumatic supply disorder, which is they listened to a bullish forecast, they built a new factory or they built a new, whatever, a unit of capacity. They spent billions, demand fell off a cliff and now they're just, okay, we're not going to do that again. And it's been a pretty volatile environment for cyclicals over the past five years. So these like wounds are fresh. And in both those areas, demand came back for things like data center power or high bandwidth memory or DRAM or NAND. And in a normal kind of textbook world, these companies rush to build new factories to capture that market share from that demand, but they aren't. Yes, like right now some of them are planning on increasing capacity, but look at G, Renau, right? They're projecting their EBITDA margins to go to 20% over the next years from 14. And because they're not, yeah. And because they're like hyper vigilant, they're not believing the hockey stick charts. They're hoarding their backlog, they're like they're treating debt like a STD that they got in college like the, and it, it's interesting to say, okay, where else could this play out? And the screen basically that we use is, okay, first you need this trauma to exist. Then you need, then you need there to be some sort of increased demand. And then you need there to be some sort of capital discipline. And also you need it to be an oligopoly, right? So one that like meets the first three is any of the gold miners, right? They like, they have the first three, but they're not, but like the capacity can get brought on by any of their competitors, right? It's very, that's not a concentrated market. So some areas that are interesting to look at from this perspective, like solar, for example, analog, analog semis, wind turbines, offshore drillers, like these all had, like they're, each one of those things that I just said, there's a very good case for like why they shouldn't do well. But if low-bargent, high-cap ex and very cyclical and a tendency of the CEOs in the business to be wildly optimistic and the stereotype of the oil CEO who just loves to drill holes and borrow as much money to drill as many holes as possible. Yeah, exactly. And, you know, and then, but you have, you know, like for solar, you got like China is doing anti-anvolution, which is like like they're like, hey guys, let's stop doing this like race to the bottom where we just try to flood the market with as much capacity as possible. There's a national security element where they're not, but the US isn't necessarily buying Chinese-made solar. And you've also, you've got like the beginnings of like gracious for demand with like you are using solar as well for a data centers and rates are going down. So maybe we see some return with the residential. And yeah, then you look at a company like first solar. And so if this de facto becomes a oligopoly because we're restricted from buying China and then the demand goes up and they don't, they're so burned by what happened before that they don't immediately increase capacity, that could be really good for their ever-towing prices. And it could be really good for their stock. And it's an area that's similar. I mean, so like I said, the gold miners don't necessarily fit this because even though they have demand, they're not being relatively disciplined, they're not an oligopoly. But if you look at lithium, it's still commodity, they're not necessarily price, they're not price makers, they're taking price from commodity set. But it is pretty concentrated, right? Like the amount of players in this, for mining at least, it's pretty concentrated. And all of them gone through this trauma. So like something like SQM or, you know, a Libro, which used to be Piedmont, like there is a potential there for the same dynamic to play out. We basically created a screen and we split into four sectors, it's pretty much represented by analog, sammys, solar, there's some offshore drillers in there, there's some lithium. And there's some one-off companies like in like probe cards and stuff that aren't necessarily what's that? Pro what? Pro cards. Yeah. Techno probe in Italy. Like there were just one offs from like individual sectors that meet all these criteria. And we did like, I think that we will see at least one or two areas where this plays out again in 2026. And I also think that the areas where it did play on 2025 continue. And it's probably a good idea to watch for when that capacity gets really ramped up again, when the SK Hynex and Micron start acting like the oil company CEOs, just the drill baby drill make as much as we possibly can. That'll be probably closer to the end in the beginning. But in guest turbines too, we're not seeing it from Siemens or G Bernola, they're not ramping that capacity. They have demand that's projected to double a decade ago, this company would have said, okay, three factories let's go. And today they're like, we're going to do like a tiny cautious capacity bump and then we're going to raise our margin targets massively. And they're just scared to death of over building and that's great for the stock. And so you had a framework of three things, whether it's oligopoly score, it's a demand score and it's discipline score and we can put up right now the dot plot, we call it of on the x-axis, the degree to which it's a price maker and then on the y-axis, the degree to which it has capacity restraints. So for example, like new mod gold miner has very high on both, but it's not an oligopoly, you point out that quite correctly, the precious metals miner is quite diversified. I didn't know until reading your piece that lithium was very concentrated in terms of production. I have PTSD, not so much for investing myself, but just doing interviews on lithium where it was just pitched as this is like digital gold and it's powering thing. And then I probably did those interviews at the peak in lithium prices. And you know, I mean, people were pitching that Piedmont stock that changed its name. There's a reason it had to change its name, I mean, I percent. So I just feel kind of cautious, but maybe my caution is, is the post-traumatic supply disorder that you're talking about? So maybe that kind of proves the point. Yeah, and you know, but it's the same thing like you could have just as easily have done that interview. Maybe you did, I don't know, but about Carvana in 2021 and looking at that did. It's like like the, so yeah, I guess you always starting from a place of what was hated this year and then started ripping and what would it take for it to continue going up? And then what else is similar to this that could, one thing changes that I can track could experience the same kind of dynamic? Oh, James, now I want to talk about, it's not at 26 trades, but it is an idea, a debate that is animating the market right now, which is the degree to which Google can beat everyone else just by building its own TPUs, tensor processing units. So it doesn't need the NVIDIA GPUs or the CPUs, it's building its own infrastructure. Maybe Google is going to be selling to external parties and also Google with its Gemini can beat OpenAI and basically the business model of investing hundreds of billions of dollars in building out capacity and buying NVIDIA chips. You don't need to do that because Google can be way more cost effective. In other words, we've all seen the famous chart from code to how it is being an AI ecosystem, not that OpenAI is publicly traded, Microsoft has exposure to OpenAI. So like Google has been crushing Microsoft just in terms of share performance. The other dichotomy is the degree to which companies can be need to buy NVIDIA chips or AMD chips versus custom A6. And you've been talking about this for two years, but I guess now it's really at the right. But just talking about that first topic, like you had a piece on the Citrini sub stack about, I think it was called carving out the TPU, really good piece, your thoughts here on where are you on this debate? Again, it's something where the market views it very much is binary. It's like you're either bullish on it or you're bullish on Google, like we were bullish on Google because it was treated as an AI loser when it was very obviously a winner and then a couple things went right along that timeline and it did really well. And we will continue to see this happen. We will continue to see the like reluctance to pay the NVIDIA tax leading to hyperscalus making custom silicon and the other like very interesting area here that I didn't talk about that much in the piece. I talked about it a little bit, but there's like this, I would call like the silicon curtain, right? If you look at like for a long time, the anticipation of people who were bearish on NVIDIA was that the custom ASIC would come out of China who would immediately kind of commoditize the space and that hasn't happened yet, but paying attention to the bottlenecks of like China is investing a ton of money in trying to create its own AI accelerators and they're not there yet, but investing along those bottlenecks is a great, it's been a great trade and it's interesting to look at when that became a great trade. If you look at like when the Chinese kind of semi-conductor complex started really outperforming. It happened right around the rare earth export restrictions and it's something where like the really this outperformance in the Chinese AI semi-conductor complex starts happening significantly after the July 15th export restrictions like the rare earths and then it goes really parabolic when some of the blue poles for the like far-known fabs in China get closed and it's something where you know for a fact they're trying to spending all this money and China really wants to have its own independent AI accelerator and they're not there yet, but if you look at what they need to do in order to get there essentially they need to spend a bunch money on the memory, they need to spend a lot of money on trying to get to UV and if you look at there's a company that's listed in the US ACMR, ACM research and they are like they're benefiting hugely from this and but they're so cheap and the interesting thing about this specific companies they also have an A-Share that trades in China, this company owns like the ADR on six of the A-Shares and six of the A-Shares is worth like five times as much as ACMR share price. So the watching that play out like it's very much the same as investing along it's don't fight the Fed don't fight like the CCP when they say that they want to build a semi-conductor industry because whether or not they're successful they're going to spend a bunch of money on it. I think positioning much as you can along like where the bottlenecks for custom asics has some silicon is going to come from whether that's from Google whether it's from video whether it's from meta or whether it's from China that's kind of like a theme that recurs throughout some of the trades that we've created that have to get with AI but just like we spoke about advanced packaging it's the same thing if you look at Google the TVU stuff and then if you look at China there's there's a bunch of companies in China that have A-Shares and there's also and some of those companies also have upside to TPUs and then some of those companies just have upside to China just building out this domestic thing. So ACMR was one of our single stock days. And so I'm looking at the China AI basket companies like Cambrakhan, Veracilicon, Zhongli, Inelite, Pyotech, Sujo, TFC, Optical, Communications, James why are you not long these companies you've known about these companies you've written about these companies for so long they're up a Gajillion percent why are they not into such index? Because so we we have metrics on who subscribes this is really research and most of them are people from the US buying A-Shares is very difficult for unless they have the eight you know the stock connect thing but there are some A-Shares that you just mentioned like like Cambrakhan for example or like the new IPO Morthreads which is like China's Nvidia competitor. I I can't own them in my own IPK or I don't put them in the in the social networks. I do talk about them because you know we have like institutional strippers that absolutely can go and buy those but I try to try to make it so that people don't get upset because they're like I like the stock 5x but I couldn't buy it. That makes sense so you would be long these things but you aren't because most non-super institutional investors in America can't invest in them that makes sense. Yeah but they can invest in ACMR which again is a company that has an ADR and that all that 80 that ADR is just shell like any other shell and the shell basically owns I think it's six shares for every ADR of this company in China that's listed as an A-Share and if you look at the valuation description you can't arbitrage it because you're probably not going to be able to go and short the A-Share but it's pretty interesting that like you know the domestic like the A-Share market which is you know people who are investing based off being in China and seeing what China is prioritizing trades at a five times higher valuation in the domestic market than it does over here like that gap will probably close. So the US one is cheaper and it's five times cheaper. Wow. Yeah it's crazy. Okay so I asked you about Google versus Open AI, Google versus Nvidia you said okay it's not that comp it's not that simple both of them can win. Yeah what do you think about Open AI? My biggest concern about the AI trade was that Open AI would not be able to raise money does seem like they are raising a lot of money. I mean I think if Open AI can keep on raising money like the party continues that's my view. What about you? Yeah I agree with that. I mean basically it's like they're going to keep raising money until they and and you know they're going to probably try to monetize as well we'll probably see some commerce but it's a difficult line for them to walk right because like we spoke about early in the podcast there is this capability gap where AI is increasingly being able to do more things but people aren't using it for those things because they're unaware that it can do that. So really for Open AI they're going to have to weigh the balance between on one hand we want as many people to realize what we're doing and like what AI can do right now and so that they can utilize it for their own purposes and on the other hand we're a company in which probably makes money. So something where you know if if you break the trust of more people that are like utilizing AI for whatever the case may be right for many of these whether it's images or video or doing Excel work or whatever and then if you do it to aggressively and it becomes something where like you put ads in there and you know you I don't know you're doing like you know analysis on a stock kind of keeps recommending that you buy this stock or you don't want to buy and it's because that company paid Open AI you're going to lose trust for it and that will hurt the closing of the capability gaps. I think that Open AI realizes this and it's probably why they've leaned more into the selling equity rather than like aggressively monetizing because they really they could be monetizing more and every day that people use this and become dependent on it. It's like I have like a pretty controversial tweet this year that was like comparing what AI is like right I mean really like if you're not using AI as much as you can you really should be because A it's like in this golden age of like like similar to the internet before the internet was all like search engine optimization and had words and and like delivering you commercial opportunities and at the same time it's also like it's pretty subsidized right like like you know yes you're paying for tokens but you can you can pay the subscription for Open AI and you can become like a negative you know and you can become a loss and that won't last forever it's the same thing it's like when Uber was way better than taking a taxi and cheaper and eventually the company like gets the market share and they convert and they charge more for it because you're dependent on it. This is the time where you can derive the most value for the least cost by utilizing AI so it'll be interesting to see I don't know what the answer is for them but I think so far what they've done is probably the right route and yeah I agree with you if they can't raise money anymore it might be over. What do you think about Microsoft and why is no one buying Microsoft Copilot is that a concern? I think just it's idiosyncratic it's like Microsoft has done not a great job with it and it does tie into what we were just talking about. If you force this down people's throats they like you you can't force people to adopt technology they have to do it on their own they have to become aware of it on their own. I think the Microsoft has taken the wrong route in trying to force AI adoption and they did it way too quickly and because the first impressions are everything right so like for for Gemini from Google like a lot of people's first time try not you but for a lot of people the first time that they tried Gemini was Gemini 3 and it's a really good model and that makes a lot easier for people to switch over but when you're just like packaging Copilot and constantly pushing updates and the first time that people use it they're like this is garbage by the time it gets good they're not interested in trying it again because they've already tried it once so I think that's like a big hurdle for Microsoft overcome and that probably was you know they were really aggressive about it and the market kind of disagreed with that strategy. So in terms of the various bear arguments I could throw at you one is that the customers are extremely concentrated they're investing in themselves the demand is somewhat inflated the other is the depreciation angle where these companies are spending so much and the depreciation expenses are going to be so high they might not earn that back and I guess those would be concentrated in companies like CoreWeap and companies like Nevis but in particular the biggest cap one would be Oracle which off balance sheet of for going to a quarterly report has entered into lease agreements of a quarter trillion dollars so the spend is enormous do you have concerns there I actually don't know if you have any positions in Oracle or any of these companies on this to Trindex I will look but what about these kind of these stocks these these stocks that are the battleground stocks for AI right now where it seems like the life or death of AI hinges on these trades or Oracle and CoreWeap would say. I think that there are some salient points there that kind of circular financing aspect is worrying and if you did get some kind of negative externality it'd be bad but just with the like sake of I feel like the bearish arguments on AI get so much play time that it might be worthwhile to just I'll just take this side the like super bullish side just to just for the sake of making an interesting conversation. So like the depreciation in CapEx angle so I guess the characterization of the bear argument is that like hyperscalers are spending more than 50 billion a year on CapEx and they're depreciating these chips over five to six years so that they can make earnings look good but the bears are essentially saying these chips will be obsolete in the 18 months when the next black well generation arrives and then the capitalizing assets that'll soon be worthless is that like an accurate calculation correct that argument a lot of people attribute to Michael Burry I mean I think it was Jim Chanos who made that argument far far far earlier. Burry is sub-signal which is which is cool yeah but the I think there's better I I subscribe to his there definitely two different things I think the the rebuttal from the bullside the life cycle of a chip kind of functions as a cascade for AI like like bears saying once a chip is no longer the fastest it's trash like these aren't iPhones right the in the data center you get the sickest chip it's like the first two years you're using it for training frontier models that are state of the yard you're trying to make breakthroughs you're trying to like accomplish a GI with them because they're the coolest new thing and they increase your compute capacity so much and then the new chip comes out and that chip moves to like inference and you know like like running AI you know because inference is much less demanding on metrics that without being a huge nerds you can do inference with an H100 right now and okay you know like like like that doesn't mean that those H100 chips that they bought are worthless it's much less compute intensive but inference doesn't make up the bulk of like actual customer usage so that takes you from like those first two years where you're running these chips like as hot as you pass we count for because you want to beat Google at the next generation of whatever AI can do and then from years like three to five you're just using it to actually deliver those things that you built with the chip in the beginning and I guess because we've been in this building phase and this is part of the theory of AI has finally gotten good enough to be utilized for and it's going to be increasingly utilized this year like that CapEx is deflationary when you look at like high expenses and isolation I get that theory but I would argue there is a certain degree that CapEx is replacing future operating expenses just take like the simplest thing happen you're there used to be this company called task us that like was dealing with AI moderation and that got taken out we wrote about it last year but I remember there's such a bad job dude could you imagine like you're just spending your entire day like watching people get murdered on the internet I like scrolling X for 30 minutes and then I'm like wow I noticed that I am much more angry than I was when I started doing this if you think okay you spend a billion dollars on GPUs today is CapEx and then over the next five years you got a higher 5,000 less people to do that moderation that's like a very simple example the heavy depreciation charge is offset by the removal of those expenses so that can lead to like higher margins in the long term again I get like the AI is the thing right now that everyone's buying and it makes sense to be super skeptical of that whenever anyone this is like a an interesting argument about what is it going to take to train the next model but I would say it also misses the point of if you are this is like a role reversal on us where most of the ultra bulls on AI are very like scaling law pilled right it's like like scaling laws or everything by the way if you haven't read the Isaac Asimov a short story the last question a really highly recommend that you do so maybe the first guy to ever explain the concept of a scaling law through that short story it's 11 pages I'm not telling you to go read a book but the concept the more compute we throw this the better AI will get that is something where okay like on the bear side you have to implicitly be a believer in scaling laws holding forever because you're saying okay the next generation of chips that we get it's going to make AI so much better that it's going to be worthless to use the last generation of chips yeah that's a bullish argument for Nvidia like I feel that the gym channels depreciation depreciation argument of open AI is you know and Microsoft and Google's their profitability is inflated because the new chips are going to be so much better that the proper depreciation schedule should be two or three years instead of five or six that to me is a bull argument for Nvidia it's a bear argument for open AI but it is it's a bull argument for AI progress yeah and that is pretty much how these arguments fall I think like people what there's very little nuance in this where it's you do have to pick a side are you either going to be bearish on the hyperscalers or you're going to be bearish on Nvidia because a lot of things that happen that are bearish for Nvidia are pretty bullish for the hyperscalers because Nvidia is making most it's money selling things to the hyperscalers at very high price and vice versa I can get like the argument of why they they shouldn't necessarily go up together but generalizing like AI is this monolith of the users and the like the CapEx spenders and the CapEx earners I think there are some good arguments there but it needs to be pretty nuanced it can't just be this is going to collapse because of xy or z and we are seeing return on invested capital already I think meta spend a ton of money on AI clusters and their ad algorithms became much better and right when you were you accelerated despite a tough advertising market I think there's going to be dispersion for sure but I don't necessarily buy into the depreciate I'm not as good accounting as genchinas I'll just say that on front yeah um and I don't want to disagree with them on accounting but I do think that qualitatively speaking from like a higher level there when you're just looking at the income saving you're missing like like how they're actually getting used and if you get on the phone you talk to guys that are actually doing this like they're pretty concerned about the GPUs melting which like doesn't really it doesn't really conceptualize where it's oh yeah there's going to be a lot of spare capacity yeah maybe not yet though and then the customer concentration that was the other bear argument that you had was what? oh yeah yeah the customer concentration open AI I talked about that I guess just with growth in video the view that AMD is going to beat them the view that the custom silicon is going to beat them basically other companies are going to stop paying the Nvidia tax by building their own ships with the Broadcom or with the media tech and yeah which would you say you're more bullish on Broadcom or Nvidia Broadcom representing the custom A6 Nvidia representing Nvidia and then I also know that you're very interested in media tech as well which is a well known Broadcom between Broadcom and Nvidia I would pick Media Tech because you think that there's a tail situation of inference being on device which I've we've spoken about on this podcast before and they're also they're trading at 20 times earnings and they're going to be designing the next generation of GPUs but the everything keeps getting framed is I do think that there's use in looking at a parallel to the dot-com bubble right you can see what happens when there's a transfer information technology how does the market react to it what happens in the real world versus the market I think trying to track it one for one and I'm as guilty as anyone with this I remember in the April drawdown we made a bunch of charts this look it's the Asian financial crisis you know and and basically like but there are a lot of differences to that nobody really talks about you know the like the big one of the big differences is like you know during the dot-com bubble we laid a lot of fiber that we were just laying in case that it's like you know dark fiber uh we were talking about that for that point originally was made to be like Gavin Baker and I think it's such a great point which is like the 95 percent of all the fiber that we laid in the late 90s early 2000s it was just basically build it and they will cop and we're not doing that yet right we're like we're building it and they're there immediate the other thing is in the 2000s the concentration risk was mostly tied to like debt-fueled startups with no revenue so you think about that's dot-com buying servers from Cisco today the concentration risk is with the most profitable cash flow rich entities and human history with maybe the exception of the Dutch East Indies company like the I've said exactly what you said and it is technically true but the end customer is open AI which is not debt-fueled profit-less but it is equity VC-funded profit-less and Amazon and Google are spending so much is before like the real customer is open AI as well as and the other startups but the end of trying to make that not the case right like they're trying to build their own like Google right like they're trying to do their own thing and that's like I it just would be really and maybe this is like maybe like this is how it ends is where it would just be really surprising me if it basically ended when we have like opening the thing and then like you know and then there's like Google kind of and then it's over like I think before this is over all the hyperscars are probably going to have their like they're going to be in competition with the foundation labs they're going to also be making their own like they will build upon that more startups in Silicon Valley right now are built on quen that are built on then are built on open AI so that's like a pretty bullish case for like inference demand and also maybe like open source and and the the valley boba right yeah and like don't I mean kind of like it's interesting to look at it I think there's a lesson there to be learned about what China would do if a created custom silicon is like they would flood the market with it and make it as cheap as possible to reduce the stranglehold of American companies because quen is open source is yes is it bullish for alibaba in the sense wow you made a model that's like that yes are they making money from it are they making money from the open source model no you know like like that maybe they're making money from using it themselves and also there but if it's an open source model you can run locally there's not it's there's a reason why Linux isn't the most valuable company in the world then I guess there is like a sovereign angle of a lot of a lot of what we don't see like we see the chatbot stuff we see the video stuff we a lot of what we don't see in terms of AI use cases because it's a national security secret is like what what's being used for surveillance or for warfare the but they're probably looking the sovereign AI buyer could de-respect through that customer concentration it's already happening and because there's a supply constraint right now it means that demand is vulnerable so if the if supply is still constrained for top to your chips and the backlogs a month and months long it one hyperscaler like meta drops in order it doesn't just vanish into the either it just goes to the next buyer in mind whether that's core weave or sovereign or Tesla or XAI or whatever like the it's so there is there are reasonable arguments to be made on both sides but I do think that the way that and again there are a lot of things that could change that would make it that would make this equation totally different but the way that it stands right now I have difficult time believing in that this is a trick of depreciation or this is just a some customer concentration and it's going to go the way the metaverse and David in an earlier interview I asked you will you be looking to short all these AI companies when there's a downturn if and when this is a bubble and when the bubble collapses and I think your response word for word was if I'm good enough what are you going to have to see for you to say not only this is a bubble but this is a bubble that's not inflating this is a bubble that is in the process of deflating and important first that probably like to see that things need to get broadly silly first right not don't get me wrong there's some silly stuff going on I'm not like a firmable I don't fail to see that like you know I mean we have like this okay so in 2025 we had a crazy bubble in digital asset treasuries which were honestly it's a real shame that Soros was Soros when he was Soros rather than like being in his prime right now because he had to use the example of mortgage reads which we're doing pretty much the same thing is what digital asset treasuries were trading at a premium issuing equity and it's a shame he didn't have to digital asset treasuries because what a better example of reflexivity and and that was totally a bubble and then quietly in the background with no systemic risk to any one it unwound and most digital asset treasuries trade at or slightly above or slightly above nap right and and then yeah like you've had bubbles in like some of our drone names definitely got super bubbly trading like 1800 times earnings and you know so but I think that it's it's kind of characteristic of a bubble that everything is it's like you need broad kind of silliness everyone's super optimistic about everything so I think that would be the first thing that would get me on guard about the bubble potentially being I do think we're probably going to see that happen I don't know the time frame on that but that would be the first thing to look for as far as AI demand because that's what's driving most of this like you you need some sort of air pocket in the order book for inventory buildup I do think if we reconvene at this time next year and it's extremely and it's as difficult as it is right now not that this doesn't exist but it's as difficult as it is right now to find like concrete examples of companies increasing their margins or utilizing AI to you know then yeah but I think we just got to the point where AI is capable of doing more things than people could use it for and I would put like a chocolate on that of 12 months and if by the end of that 12 months it doesn't result in actual adoption and we're not seeing this more broadly then I would start to consider okay maybe this like the longer it takes and the longer it takes to get to call and call HEI the less likely it is that we're going to get there and that inference on device trade that is an ideal we've talked about it before basically that rather than all of the computation being done in data centers it's going to be done on people's phones so they don't have a lag and super quick and the pretty elegant trade you suggested there is going along a lot of the custom asics players that presumably would be building these chips that go on phones apple samsung etc and actually short the companies that are the net buyers of memory so like Lenovo Dell and I guess Xbox on you know I'm saying short my comment yeah Nintendo that basically are have to pay these very elevated memory costs yeah the I've thought for a while that like inference eventually makes its way on device and the biggest reason why that has been like wrong so far is that because in order to do that like the next gen apple iPhone like the way that things stand right now we need twice as much ram and ram has gotten prohibitively expensive but at the same time and we go over this in the piece we try to make it as as similar as possible that there's we like isolate five ways that they're trying to like algorithmically or even from a hardware perspective improve memory efficiency if we get a breakthrough in any single one of those inference will move to device because it makes sense every time that US chat GPT a question it goes to a server farm in I don't know wherever probably Texas now it gets processed by a GPU that costs as much as a Porsche and then it sends the answer back and that round trip takes like 800 milliseconds and that seems like nothing but in computer time that's an eternity especially when you think about the agentic AI acting as an assistant you want to be able to have a conversation like like I'm having with you where the inference is being done while I'm speaking and then it's immediately delivered back to me 800 milliseconds versus being on device at 200 where there's no tower involved there's no data the way that is right now is great for a chatbot that's doing all these cool things it's not that great for your agentic assistant that can like schedule things and buy things for you and all that stuff so if we want that future where AI is there is a phone already in China where it basically washes your screen and interacts with the screen it takes forever it's not like a great solution but it is the first like instance of seeing this we have a video on the piece of it but like you know booking your ubers you know booking trips for you doing like like anticipating your needs rather than responding to reacting to them it living in the cloud makes it more difficult and that's not to say the like like AI in the cloud will continue to be a thing but it's very much reminiscent of when we had this debate over on premises cloud or and what ended up happening was hybrid right it was on premises it was away from where you are so we're going to have the same thing happen here I think and my piece says AI has to move to the edge and a certain portion of it has to live on your phone and but what I'm not as bullish on is I don't think AI necessarily needs to live on your laptop I don't think AI needs to live on like your Xbox or your Nintendo Switch or your PC like that's perfectly fine to have cloud for that because you're doing more involved work and it sets up for an interesting trade world because the bottleneck for running AI in your phone isn't the it's the RAM there's huge competition but RAM goes into everything and it goes into your PC and it goes into your laptop and your Nintendo Switch and Nintendo Switch is a particularly courageous example because it's like the the bill materials cost is like 41% RAM and it already had a price increase of 300 to 450 and that'll go up again as RAM goes up so I think the best way to put this trade on and be agnostic to whether this happens in the next three months it's basically like you put the trade on you're short the companies that are getting really hurt by increased RAM costs that don't have as much upside to inference being on device through long the companies like MediaTek and Qualcomm and the mobile inference enablers for like battery life and stuff like that and then if RAM costs come down yeah your short leg is going to start going against you but it's going to be really good for your long leg and you can take that off where and in the opposite it's the branch you're going up it's much worse for a company like Lenovo or Dell than it is for a company like Qualcomm or MediaTek or any of these more automatic factory another trade you mentioned is shorting a particular preferred security of microstrategy Michael sailors Bitcoin Treasury company STRD shorting STRD and going long Bitcoin why this trade it's a great because there's a lot that I would say that this as far as trades go this is one that is it has a lot more risk to it there's a couple ways that you can lose but just from like a priori it's like you've got this situation where Michael Seller has pulled off this massive feet of financial engineering and he's convinced a certain subset of people to take capped upside on an asset who's in that's entire value proposition is uncapped upside and then if you look at the preferred that have been issued there's one that's it's like a bank prep right where it's like there's no penalty to just being like actually we're not paying dividends like non cumulative a lot of the preferred securities are cumulative so if you don't pay a dividend you have to end up paying it stacks on whereas this particular one is non cumulative and you even though it trades at a discount you argue that it doesn't trade enough at a discount yeah so it's still near par and I just feel like if you are in an environment where Bitcoin's going down like that if you look at what happened the microstrategy converts which I paid a lot of attention to it flipped long in 2022 and that was amazing because I had that embedded option but the whole reason why there was still demand for that was because it had this embedded option right it was like where if we're solving we're going to pay you back and then also we're giving you an option that like a coin bounces back which nobody was expecting it to go from 15 to 120 you're going to make a crazy amount of money with this it's like once coin goes down it's like in the bull case you're going to make 10% a year and in the bear case we're going to not pay you your dividend and the security is probably going to go down 60% who want it because even when it's down there let's say it does go down 60% like you don't have the comfort of oh well like this should trade back to par because there's the risk that they're not going to keep paying the dividend and there's no so that's again that is probably one of the traits where it's it's much more of a watch list item and bringing it to people's attention they're like hey there is this thing in the microstrategy capital stack that's crazy rather than just like hey put this on right now because you can have an environment where Bitcoin goes sideways and realizes like a 6% gager and then you're slowly just bleeding on that but if Bitcoin rips maybe this goes down to an 8% like it's not going to go below treasuries right and I think I mean this is an example of like it's just an interesting trade and I feel like you come up with so many interesting ideas that are themes and then also within themes there's tons of ways to express the themes so that is something that people have never subscribed to your work may not be aware of is just how diversified within the theme it is you'll have 10, 20, 25 names so you know 1% position within your entire portfolio is actually a high concentration you know for you and as a result I think ultimately you know I actually am kind of of the Charlie Munger school that it's good to be concentrated so I prefer to be concentrated in my personal portfolio but that doesn't mean that only people who have 100 plus positions are going to find value in your work I actually like if you have a basket of 30 stuff I like to theme I like the analysis I will only you know I may only pull the trigger at like one or two stocks and I think that yeah that's like the yeah it's kind of like you're you're we're spending all day researching this stuff and we're creating like a very concise watch list and yes you can play things in a diversified way but it's probably going to be better you're an investor that's interested in this theme to have like with our robotics thing it's like with taradine that was like I think 9% of our robotics basket with yes as a total function of the top level portfolio since the robotics basket is only 20% it's it seems low and it is but it's meant to we spend four pages explaining why it's along and then if you like it you go for it but at the same time there's still other stuff to watch in the space but yes it would have been easy to just say hey we're super bullish on robotics we wrote this 80-page primer on it and then also we're going to write this single name long thesis on taradine and you just buy taradine okay but taradine isn't going to trade necessarily on just robotics right there also like part of the thesis was they've got this great business in semiconductor testing that's going to see this huge benefit and then at the same time you've got this kicker that shows and that will show up in numbers in 2026 of the universal robotics amazon robotic arm and that's going to be bigger than people think and but it would be almost like intellectually dishonest if our sole robotics like representation was just taradine and you would say oh I guess robotics is up 150% no it's it's not we that's why we make like a broader diverse right best so that the value to the user is you can read our stuff on taradine and buy it and make a concentrated position I did too like I really like to stock that's why I spend 10 pages writing about it but the it's also the value of being able to go and look at a new factor and being like how broadly speaking how is the market pricing robotics relative to AI like that's the value proposition yes and I will say this is definitely you know not to be expected or you were necessarily repeatable but you know when we did that interview taradine was at around a hundred dollars it's 198 now so it doubled and I bought call options that were 300% and then I rolled the strike up and then those call options are now up over 100% and honestly it could be probably are up more so yeah that worked out for me yeah so these so this robotics thing you're also bullish robotics I guess taradine is at a fifth biggest position what are these other companies in his robotics thing this is tangent there it's again the like 26 traits it's like kind of an opportunity to be like okay what can we do that's additive to our existing themes and we try to be as comprehensive in our coverage as possible so when we wrote the robotics primer we really died deep on the supply chain and we came up with here's the companies that are really interesting and various kind of like everything from autonomous driving to human robots to robotic arms and stuff but now we're starting to look at areas that have benefited from this advancement in robotics that's been supercharged by advancements in world models and BLAs and stuff like that and one interesting area that's like pretty significantly underperformed that could start seeing margin improvement from robotics is the slopple because if you think about it like when you go to sweet green or kava or purge pole there's a person behind the counter and they are like using a grid right everything is set up in the same way like the guacamole is in the same place the meat is in the same place it's very easy to use like a robotic arm from fanook to replace that process and increase your margins and sweet green for example like sold its robotics division but they have an agreement with the company that they sold it to for a cost plus type thing and they will see these are like the easy one of the easiest places to implement robotics as it exists right now and so the couple it's kind is more of a speculative thing but at the same time it's if you look at the progress that is being made in robotics I went to San Francisco recently I met with a guy who is like right now using robotic arms to plug in ethernet cables and chips for day centers and saw a video of it it works really well it's right now it's totally operated but it's gathering all this data like robots are capable of doing things right now and we're gonna see this year that they get implemented in more areas even if it's not something that's right in front of you even it's happening behind the closed door that they will get used more in consumer facing role James two ideas I want to ask that actually are a 2026 trade in other words they are related to the year 2026 one world cop and two is fiscal transfers in April just give us a very brief description of these trades as well as some of the names so essentially one of the other areas that we try to focus on for the year ahead outlook is less so what do we think is going to happen and much more what do we know is going to happen and how do we trade it so two things that we know we're going to happen the world cop will be in North America and the tax refunds that people get in in q1 will be much higher than previous years by depending on who was estimate use anywhere from 30 to 50 percent higher so both of those have pretty interesting ways to play them i'll just isolate two with the world cop for example budget hotels in the u.s. have done piss poor that is a function of like international travel to the u.s. got a little bit of anemic after the after the the tariff stuff and the geopolitical concerns and then also it's been like you got the k-shaped economy that hasn't been great for the the people that are struggling are not traveling so budget hotels have done worse so something like c-h-h choice hotels but when you have the world cop come in beggars can't be choosers and a lot of these hotels are already sold out or like that and like in Vancouver the hotels are already sold out so those companies will see it'll be relatively isolated but in terms of base effects it's going to be huge and this had the company the c-h-h has continued to go down so that'll be an interesting trade isolated around that specific event and then for tax refunds again it comes into like the k-shaped economy if you think about the purchases like larger purchases not huge purchases i'm not talking about like a house maybe not even talking about a new car but if you think about the purchases the people tend to defer because they're struggling a little bit with their income and liquidity it's mostly consumer durables and then some in deferred medical or health care so you have something like the like a mattress right a mattress costs like three grand if your average tax refund goes up to four grand it's something where you've been wanting to buy a mattress these companies have not done so hot especially with the interest rate environment the way it is and then you get this influx of liquidity and that these guys see a huge sales event and then there is like the added optionality of if we learned anything in 2025 it is that Trump can do more things than you think he can and maybe that'll change maybe you'll lose that has probably won't be as bold this year as he was last year but there is like the incentives are there to do that tariff refund and i think if you're already positioning for the tax refund you kind of get the added optionality but maybe he actually does this to try to lock up the house for the midterms which would flow through to the same exact kinds of things these deferred consumer durables these and then also we have a bunch of other areas that we talk about on ways to play with this but that's one that that kind of sticks out and all of these get our just trade ideas whether they're in your model portfolio the sythrin decks is a different story so i'm looking at the sythrin decks and your biggest three baskets are dynamic AI fiscal primacy and then robotics which respectively are up since inception dynamic AI up 229 percent fiscal primary up 176 percent and robotics up 24 percent it was started in May of 2025 so i think i'll a lot of the critiques of the newsletter business that we talked about earlier oh you throw out 200 ideas and some of them stick and then you say oh pound the table this worked well the sythrin decks is accountable obviously it's actionable but it really is seeing what worked and what didn't and the numbers are what they are just what you want to mention just a little bit a quick bit about the sythrin decks before we leave it there we built this platform it's a in my opinion like a really useful tool i use it when i'm making decisions i think it's like a great centralized place to look at all of our themes or macro trades see it's really interesting once a month i let go and i see okay what themes have outformed over the past month and you always like find something interesting the that's like how we found like that the drone names started to inflect and it we keep doing the work of exploring potential themes and breaking them into more specific areas AI is broken down into top level and then also like interconnects optical so you can go there and you can just find maybe a sythrin that we have that we talked about a year ago that's about to be a really awesome trade and if you weren't paying attention to it you wouldn't have noticed that yeah and because of transparency that i don't think a lot of a lot of research has necessarily i completely agree and that bundle of the sythrin and the sythrin decks that can be got for a 25% discount so monetary matters can click the link in the description to learn more about that we will leave it there james thank you so much thank you everyone for watching and i hope you have a fantastic twenty twenty six as always thanks for watching if you're interested in checking out the sythriny bundle which has sythriny research and the sythrin decks go to my link at sythriny research dot com slash mm jack for a 25% discount the deal expires on january 14th and remember you have to be logged in and if you don't have an account with sub stack you have to give them your email to access the discount until next time