The AI Supercycle with Jordi Visser | Raoul Pal the Journey Man

Building a business in AI has tremendous margins, tremendous. It allows you to grow rapidly. We've never seen this before, right? So Reeds Law, which is Merciful Square, has never existed in biology. Not even viruses. It doesn't exist. And now we're seeing it at its fucking everywhere. Which is why it's so hard to understand. The new world is, if we can't actually make all the chips we need, and we can't actually get the power we need, you end up with a little bit of demand for a sub-bideness map. The bottlenecks themselves may slow the earnings of these companies. Not because the demand is not there, because the demand is too big. And that's sort of bananas, but that's what we might get to. As you know by now, I'm Raul Pal, and welcome to my show, The Journey Man, where we traveled to that nexus of understanding between macro, crypto, and the exponential age of technology. I've been bleeding on for a few years now. How this is all coming together. macro, crypto and technology, they're all the same thing, and everything is changing, and it's changing extremely fast. There's not many people who understand across all of these disciplines. You can find extra experts in various fields, but very few people who understand at broad macro terms, well, this all means. But my regular guest, good friend of mine, Jordy Visser, well, he's the person I go to to think things through, and he does the same with me. So it's not really an interview ever. It's just us thinking through what the hell is going on. What does it mean? How to measure it? How to take opportunity of it. So I think you're going to love it. Here's a conversation with good friend Jordy Visser. Join me, Raul Pal, as I go on a journey of discovery through the macro, crypto and exponential age landscapes. In The Journey Man, I talk to the smartest people in the world so we can all become smarter together. 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I'm good. I'm good. So lots to talk about, I'm sure. I have no idea as ever what we're going to talk about, but what's on your mind? Well, I'm going to start in a good place for you. I actually listened to you and Julian recently. And something you guys talked about throughout, but really at the very end. If you remember when we sat down in my offices, and I talked about no more recessions, and that kind of hit you, the way you guys phrased the transition away from labor versus capital into compute versus energy, you and I have talked about this in some way, we're both AI believers, but it really hit me hard in the same way the recession, because it fits in with that whole conversation. Meaning business cycles are the past to grow your business. You needed location. You needed to borrow money. You needed to hire people to grow it every year when we were at investment banks. Okay, this division's doing well. Let's give them more people. Let's go open an office in Brazil. Let's go do this. In compute versus energy, it's a very, very different thing. And I spent the time and I've been writing about that the AI cycle is no longer about capital versus labor, but not praising the way you guys did, and not specifically saying compute versus energy, but actually saying bottlenecks and shortages, which are the same thing as when supply and demand get out of whack on the other side. But it really hit me hard that we're starting to see that phase and that people should get used to, that the new world is, if we can't actually make all the chips we need, and we can't actually get the power we need in a delayed fashion, you end up with a little bit of demand for supply mismatch. So that's what I've been thinking a lot right now. I got further in this thinking. So I've started building out a whole dashboard of indicators for monitoring this exponential increase in the output of intelligence per unit of energy. And I built an index of it. And I'm still not, I've not published it fully yet. I just started right about it in GMI. Really interesting. So I used Moore's law beforehand, and then it starts hooking up really with AI. You've got some kind of GPU and other stuff that starts lifting it. And then AI, it's now gone, it's a log chart, and it's now gone exponential on a log chart, which is what I've been talking about, reads law, the exponential squared. And what it started to think about, so think about these bottlenecks and stuff like this. Think about the fact that like data centers are 30% built versus where they should have been what they stated. Think about the race between the US and China and how nobody's allowed to win it. Think about the fact that no single AI frontier house can win, because it's all too dangerous, right, to have. And what I get to is there is almost no way for this not to be a super cycle. And even the bottlenecks just slow it down, but it has to keep expense. So what does a bottleneck and actually needs more expenditure? You need to build out the power stuff, you need to build out whatever it is. And so what you've got is the largest capex cycle I think humanity will ever see at this rate. Well, maybe there's another one to space later, but right now is this. And I'm struggling to see how we actually get a business cycle. And you and I will remember the days of 1995 to 2001 where the business cycle went up and down a bit, but basically it was all productivity and growth. Yeah, so let's make sure we we we we double click on one part and let's see if you agree with this. So for the business cycle, it is based on perception. It's based on surveys. It's based on the way people see it because everyone can't see everything happening. So when people talk about PMIs, okay, well, those are surveys. Those are this is what I expect to have happened. And so when they're high, there's a lot of different components in it. There's prices paid. There's supply delivery times. There's new orders. There's productions. And with inside the PMI, you can have a high PMI number, but you could have bottlenecks showing up in the supply chain and the prices paid. And you could see new orders drop down to 50. You could see the other things. And we saw a lot of that during COVID. And we have the employment numbers, which are the component, which is not going higher. So I think my I think everything you said I completely agree with. I do believe one of the problems. And I want to double click on something you said if people haven't thought about this. How could we possibly have this must advancements in the IQ stage, getting us up to 135 plus right now without having the data centers being built? How could that have occurred? And you and I both know, well, the algorithmic side got better. Human feedback, reinforcement learning, reasoning, everything kind of happened. And that's why we've been able at least to stay up to here. I believe we're at a different point. But I want to hear that's why we're seeing an exponential of an exponential because it's not just about the build more oil rigs and we have more oil, right? That's a standard process. So build more part data centers and we have more energy, more intelligence. Yes. But that intelligence becomes self-recursive learning, improvements in the algorithm, all of that. And that is where the double exponential comes from. And we've never seen this before, right? So reads law, which is mecosl squared or to the power of two, has never existed in biology, not even viruses. It doesn't exist. And now we're seeing it and it's fucking everywhere, which is why it's so hard to understand. Not only hard to understand, but how fast it starts to move at a pace that parabolas now become something that you get used to. And you and I have been doing this long enough and because I grew up in emerging markets, I used to see parabolas a lot. And they usually went up and then they come down in almost the exact same straight line. I think it is confused people. I literally just wrote something where if you go back to January and you take when Jensen Yuan got on stage at CES and he spoke and he talked about Vera Rubin and he talked about all the things that were needed. You know, you and I are in different, we're in the same worlds. We have the same background, but I have two feet or I've one foot fully in the Trabhi world and then one foot fully in the crypto world. And I still talk to hedge funds every single day. I talk to mutual funds. I talk to people about AI and how to invest in it. In January, they didn't understand the agentic economy had started. They didn't understand the rise of agents at that point. And then by March, you had the Morgan Stanley TMT event and Jensen Yuan spoke there and Intel spoke and Dell spoke and they all started and everyone started realizing, oh my god, these numbers are going to be huge. We got to start getting involved. And then you had Computex over the course of this month. And I think the realization has hit people, but the problem with the agentic world and the way that Jensen Huang described that it CES, which makes it a little bit different than the last three years with the IQ acceleration, it's going to be very difficult and very correlated amongst all of the broadening out that's happened to make sure that we can continue to keep this thing going at the same pace that it's been happening. So I do believe there's going to be a slow down to some degree, but to your point for everyone watching, recursive self improvement in where we're getting a year from now, you're going to be more blown away than you are today, even if for the next four months, the focus shifts to bottlenecks and shortages. And also, you know, I was building something else about this is like, you know, it's not going to be the same stocks all the way through because there's bottlenecks and shortages, but there's the applications layer, right? People still aren't focusing something you talked about a long time ago is like, you know, the peptides and all of the genetic science breakthroughs that are enabled by this technology, right? The market can't focus. The market can only hold so much attention and so much capital at any one stage. It hasn't figured out the agentic economy yet because if not, you'd see it in crypto because it's massive. The time has gone to infinity, which people have never understood that the time was always humans, right? And now the time is infinity and people don't understand this yet. They don't understand what this is about to do to human biology. They kind of sort of do, but it's not reflecting in stock prices yet. So I think we'll get rotations, you know, it doesn't always have to be at that and video, as you say. There'll be times when it's going to take a while to push a new breakthrough from algorithmic compression or build these data centers in enough scale to show the next big step, you know, after mythos, maybe it's going to be difficult for a while. Maybe not. It's not proven difficult yet. They've never yet hit any boundary and they keep saying we're not hitting boundaries and we thought we would and we haven't. But I do think there'll be rotations, as you say, it goes through different component parts and kind of breaks them down because, you know, if you think about the bottleneck theory, so you find a bottleneck, whatever it may be, power, what that bottleneck does is concentrate capital into that particular issue. Because if the universe is solving for intelligence per unit of energy, it will clear all roadblocks to get there and capital is how you do it. Capital and attention. And so two things you said on there. On the power side, it's very clear to everyone now based on the data center delay is based on the turbines and the transformers and every other part that it's, we've got a bottleneck. So what is the recent announcement from Nvidia and Siemens? Well, they're doing something with fluent specifically on the battery side in China. They're really focused on solid state batteries. Huge silver imports. Everyone should go look at how much silver is needed in solid state batteries instead of what lithium takes. If you take, if we have battery innovation today and we were able to, we have enough power on the US grid to plug everything into it. We just can't do that because we repeat capacity too much. But if we could store and have it to deal with those peak capacity days, then we wouldn't, we'd be able to use the grid almost completely to get the needs that we have by 2030. So innovations and the stuff that we're talking about are going to happen in power as a perfect example. You brought something up, which I think, and I'm starting to focus my attention. So when you say, we'll rotate, we'll move to other places. When Jensen, you wanted to do the five layer cake and he talked about the fact that at the bottom of the stack, you have energy, you have chips, you have infrastructure, then you have the models and at the top of applications. Every time I talk to people on applications, they are focused on SaaS for some reason. And I always sit there in these meetings and I go, why are you focused on a seat-based thing of the past? What I envision happening, and this is the first time I'll say it in any podcast, even though I've talked about the name, the reason we're in the stage that the buildout can happen with companies like Google able to raise $85 billion in a public equity. You and I have been involved in a long time. There's never been a public equity of that size, but let's normalize it. It's bigger than the bottom 360 companies in the S&P 500's market cap. So you're talking about a massive raise, barely down for the buildout. To be in that position, you had to be a whore from the time that the great financial crisis came out. They sucked in all of the capital. You know who's starting to suck in all the capital right now for the application layer. It's for human software and it's what you brought up. Eli Lilly is sucking in all of the capital through GLP ones. And I believe GLP ones are going to lead to them. They have a thousand GPU data center now at LillyPod at their campus. They worked with Nvidia to launch something in Silicon Valley. I believe we're going to look back and realize that GLP ones were the ability to finance the next stage of the human software that you're talking about. Yeah, it's like Elon's used cars. You use something that generates cash flows and we'll look back at Google and look back at some of these people and say, well, advertising was just the start of actually a much bigger process. Just a couple of things to add to that as well is talking about efficiencies and bottlenecks. Elon's been is always very good at this kind of stuff. So when the cyber truck came out, he realized that there is a global copper shortage. Every hedge front in the world plays the AI trade via the copper shortage. It's been okay, but not the greatest trade on earth because I think everybody's focused on it. But what Elon did was change the voltage in a cyber truck from 12 to 24 and ended up using 70% less copper. It's like a very simple thing. He's like, well, nobody's done it before. And it was just basically physics. And I just did that and we figured out how to do it and then it changed everything. So I do think there's a lot of efficiencies. You know, you talk about silver and stuff. We will route around it because we're quite intelligent. It was an old friend of mine who was a Goldman who was on the oil trading desk wrote a book, The Energy World is flat. And I didn't really understand it at first. But basically explaining that the intelligence density within the oil companies is vast. And if you give them a roadblock like we can't get enough oil, there's going to be peak oil. They come up with shale. And it's the same with the drug companies. It's the same with Elon and copper. You know, I think do mongers will say, well, it's fucked it can't happen. And my thought will capsule and attention will just root through it. And again, I don't know. I don't think you guys said this when I listened, but I heard the copper point, which I agree with. I mean, for the amount of times I've heard we're not going to have copper, which again, it's true. But you could have said the same thing with the data centers. And then Vera Rubin came out. We moved most of the stuff to optical fiber to move the around. So it's like, we keep coming up with solutions to problems to deal with this. And I will make solutions faster to get to as well. Well, but that's the main point. And so when I look at parabolas and the easiest way for me to say to someone, okay, let's assume there was a parabola that was justified. If at the beginning of January, in January of 2026, instead of him announcing that the agentic world was rising, what if he actually said, you know, there's seven and a half billion people on the planet. But by the end of this year, there'll be 15 billion. Okay, we'd have parabolas everywhere. It'd be in food. It would be, we wouldn't have enough things right off the bat. So what he did when the agentic world comes, people have made the connection that we're talking about billions of thinkers entering the world. And they consume only one thing, compute. So that's why we have shortages of all these things, because that's what they compute. The reason the business cycle and people looking for when the next housing market's going to start, you're missing the point that these digital employees will never buy a house. They will never send their kids to college. They will never consume things the way it is. So you have to kind of back your way out and realize, forget the doom and gloom over the job replacement. The reality is, as Elon says, at some point, if they're really good at solving problems and abundance comes, you're going to have a choice of whether you actually want to work, or if your life is fine just being in nature. And that time commitment of the next 50 years of adjusting to a world that is completely different, that is what happened in my opinion there. And to your point on any kind of problem we have, with seven and a half billion agents coming in over a course of whatever the next year or two years, whatever it takes, we're basically doing the man happen project times whatever. So any problem you want, forget Elon figuring it out, he's one person. But if you take all of the AI agents and let them sit and work on any problem there is, we will solve eventually every single problem. I don't think people have come into the context of that much IQ and what it means to have that much IQ solving problems. And also because people think of these models as a single thing, like this single beast, but they're not because there's a hundred million users, no, it's a billion users, I think now of, of open AI. Each one is a different instance using this huge intelligence of which they can come with different breakthroughs. It's not the big model itself. The big model enables all these instances and depending what you do with it. So it's exponential yet again, in the amount of intelligence you can drag out of this thing. Yeah, that's a brilliant comment and I've experienced it a couple of ways. But let's assume that every time that I ask a question or I go down a rabbit hole of what will happen if this or what'll go on when I'm writing papers and all of that's getting added into the way that things are thinking about. You're getting all human intelligence put back in. The other direction I've gone is to isolate intelligence to try and brainstorm with certain people. So one of the things that's worked extremely well for me this year, both investing but also writing papers, has been creating knowledge brains. And I did it in a very simplistic way to start, which was just let me take every transcript and uploaded into notebook LM of Jensen Yuan, of whoever I wanted to do. I recently did it with David Ricks from Eli Lilly, because I want to hear what they're talking about. And I want to have it in one transcript. Jensen Yuan speaks multiple times a week. And these are not short conversations. These are anywhere from an hour to three hours. If you upload three hours of him speaking, he doesn't have a teleprompter. He's just winging it. You get so much good, raw information. He's basically telling you what companies to buy. And to do it, you can either do it notebook LM or you can take all those transcripts and save them into a notebook on your computer and then have co-work go in there. Then you can have your agents go off and run through and connect it to another person, Andre Carpathy, whatever you want. So the ability of taking a human being's brain and making that the content that you're working off of as opposed to the internet, which is every human being. I don't think people have made that connection yet of how quickly you will do it, because you can isolate the most individual thinkers in any given field and get tons of information, particularly when you pair them with other people. Yeah, and I've built, I'm building a whole, I mean, so many things right now, but one is the GMI brain. So it has everything I've ever written over the last 21 years. I've probably got more long form written content than almost anybody else in finance. And then the video transcripts and then my X feed and then, all of this stuff. And then I've got a, you know, it's that's in a rag vector database I can now query it, do all sorts of stuff. Okay, that's interesting. Then I built something that I'm still working called the lens, which uses my exponential age framework only and goes to first principles. And you, you give it any question whether it was the US election, the midterm election or markets, and it uses that particular lens to analyze stuff. So I'm now doing replications of parts of myself into different things. I'm not just using Jensen, you weren't. The issue I've got is, I mean, I love the idea of what you're doing with notebook LM, which I love as well, is I'm running out of time. I can't manage this. I'm so overwhelmed with the amount of things that I'm building and doing because, you know, I can do all myself now, which is a dangerous thing because the only thing I've got is time. That is my energy per unit of intelligence. Yeah, my intelligence is going exponential, but I'm right at the boundary of my fixed time. So let's, we always talk about the similar areas between us. One of the differences is I was still at a hedge fund. You were off building a separate business. When the hedge fund that I worked at for 20 years closed, I had to make a decision and I never wanted to work for anyone again. And I never wanted to manage anyone again. Those were the two things that I kind of said brought me the least amount of joy going out, raising money, going to investors, trying to convince them to give you money, then staying up all night trading the markets and explaining why you're doing whatever. And then people coming in and not able to pay their bills or whatever the case was, it just, it was very difficult for me to kind of do all of that and still be able to enjoy life. So when I started to make the decision, what I wanted to do and I realized content was going to be it, not content for me, but realizing that 8 billion people on the planet are not going to know how to navigate this thing. I'm very few people are going to be able to. And if I thought about it all the time and I took my ability to speak in analogies and convert it into language that they could understand, I could help people train on doing this that I could grow a business, which has grown rapidly. And the one thing I can say is in your position, some of your time is just dealt with that you're involved with a big company. I have no employees. I have one person that helps me out once we launch the paywall. It's grown consistently. And the reason it's grown consistently is because I'm using AI agents, but I have all of my time. They deal with the, the, the subscribers and I deal with just creating content and going through it and learning and being able to do it. So I appreciate the part you're saying, I don't know how you do as much as you do because I have a lot more time. But I do think for people that are listening, building a business in AI has tremendous margins, tremendous. So you can go from zero to, I don't even think my business will be around for very long because I think it'll be monetized because I think people need what I'm doing and it's growing in a consistent linear way. But I'm having so much fun and I'm learning so much and I feel like it's making me want to do that. So Jury now just thinks, you know what, I need to build hermese agents. And then I need to think about I need a permanent memory layer. So how do you get the time to do? It's that stuff that takes up my time, right? Because it eventually, you free up time, but you end up finding new things to do with this technology. So that time just gets sucked into something else. But how do you find the time to do that? Because I'm doing all of these things and that's what I'm really struggling. I've got 15 things on my list of different variations of stuff that I'm doing and having to learn brand new from scratch. I can't, I don't know this for sure, but I'm going to guess that I'm able to you. Now it has to be, I use AI more than you do just by the nature of not having to do as many interviews and not having to deal with the business and whatever else things you're traveling, the events. I choose and pick what I'm going to based on whether it makes sense for me totally from a time basis. So I probably had more time to use it. Not sure, I'm not sure. I mean, all day from 6 a.m. until 8 p.m. I'm 14 hours a day at this stuff. You know, I do three speaking, you know, where I have to go and travel three a year, something like that. So it's not really that yes, there's running real vision, but there's people running. I don't know, I'm just finding, maybe I'm just overly ambitious and all the things I want to do. You want to get everything moved along to get to that foundational layer. So you build all the databases across everything and how they interact with each other and whether you're using a obsidian or whether you're using a nation and all of this stuff is, it just takes time. You know what it is to be fair. So let's assume we do exactly the same amount. It is a function of number one. We see new stuff every day that we wish we were doing. And so it's moving so fast and we're seeing it so fast because you and I are clearly on X. We're clearly talking to smart people. And if someone says to me, you should be connecting to Obsidian to do your knowledge brains. Then immediately when I go home, I go, look, and I'm like, well, how much is this, how much time is this going to take? How's it going to go? With Hermes, it's very interesting because I had just finished my second open claw and then all of a sudden, everyone's like, you got to move to Hermes. I'm like, I just went through all this time to use open claw. And I read what they were doing. And I worked with one of the LLM. Should I be spending time on this? And the answer was, no, don't bother yet. It'll get easier in the next month. So what I've gotten good at is kind of asking, Chad, I'm using 5.5 now much more than Claude. It just, I think they're both at, I don't know what the IQ is, but these things are the smartest things I've ever had conversations with. But Chad, CBT is my style because it's less for Bose. And I like less for Bose. I just like quick answers, move on, get to the next one. And it has been very good about telling me what not to spend time on. Yeah. And what I got to is, you know, because having had their same conversation, most of the time, we both know is like either anthropic or open AI will build that you don't actually need the Hermes agent. But the foundational database layer, you actually do need. So I'm like, I'm just going to build that for now. I've got Hermes agent. Don't really use it yet because I'm building all the other things from that database. Because once you've got your foundations right, how I think about these databases is we're all going to have our own vaults of everything. Your personal stuff, every photo you've ever had, every phone call you've ever done, everything will be in your vault. And then you can use the vault for various brain aspects or monetization aspects or whatever. So I'm just focused like, okay, I need to create the vault, the rail operating system as I call it. And as people listen to this, don't know what you're saying. Honestly, the beauty of an LLM is theoretically you can get information on any topic you want to get a topic on. You can have a chat on it. Great. But if every file on every computer you've used on your phone, on everything, every piece of information you've ever had is now in a place where it can be access to at any point, like in a second, I don't think people realize what that means. If they've gone out to dinner and someone says, "What is the receipt for that?" You have the receipt. Like every single thing is at your fingertips. And the easiest way for me to explain to people as to how important this is is when a loved one dies and you're the executor or the administrator, you will hear from every person how much of a nightmare it is to go from point A to the end. I had to go through that over the course the last 18 months. And midway through it, I just started putting everything into one folder and connecting that folder to Opus 4.5 initially and then go. So whenever the probate person calls, whenever one calls, I just go right into it and I say, "Hey, what they're looking for this answer? What's the answer?" I don't have to go look. If they say, "Where are we right now in the state account?" I just go in. What did you do this asset at? Where's the document for that? It's all in one file. It gets brought up by cloud. It immediately sends it out. So I think for people to understand you're coming on the vault. They really have to understand how amazing it will be in the future. And that's one of the reasons why you need to have your personal assistant at least trying it just to get through the experience of everything that you can do with it. Have you started using Cronolia yet? No. Okay, Grinola's a great one. It's, um, we've all seen on Zoom and everything else. It's there's an AI that does the transcripts. But Grinola is like, it has a bunch of different models you can use whether you're using chat GPT or you want to use Kimmy or whatever it is. And it will do instant transcripts, instant summaries. Okay, fine. But it becomes the knowledge base for everything. So it's like, oh, you're speaking to Jury again. Here's the four things you talked about last time. Here's the things you were going to follow up on. And it all feeds into my brain. So then every single conversation I have and I can do that on phone calls all of the self voice messages, all feeds the brain and it never forgets. So then I can go back and say, hey, listen, you know, when's the, you know, whether it's a real version meeting, a product and development team, you know, one of the last five things we talked about what's going off track and you analyze what it's all of it. So it's a really helpful tool. And everybody I know uses it starts using it a lot. So is this for place? Did you use, is this notion, but in a different way? What it is is it just recall, just think of it as recording everything you speak. Okay. And so it captures all of the nuance because it's full transcript. Okay. And then has LLMs to analyze, summarize, do all of that. But then it becomes this vast database of everything you've ever spoken. And you know, what we're getting to is permanent memory. Yep. The biggest issue that AI companies have is the memory is not persistent enough. That's what we all fight with all day. You know, bloody context windows and then, you know, it forgets everything. And you've got so much, you know, imagine you've got thousands of chats. All of that information gets lost because it only compresses like human brains can press what we can remember. It does the same. And this, this is the breakthroughs, the database memory layer, I think. That's what Kapathy's been talking about as well. After look at everything. I do, I mean, that's the reason why I use OpenClaw so much is I'll just say something. If I'm on a flight and I want to send something because I have an idea and I want to remember, I don't want to forget it, then I will just literally say in telegram to OpenClaw, hey, when I get off the flight, let's remember to talk about this. And then when I get off, maybe it's two weeks later, I never asked about it. I said, hey, what did I ask about on the plane? And immediately it comes back to me. So again, I've stopped using, you know, notes and notion to a great degree compared to OpenClaw. OpenClaw becomes my assistant in terms of me making sure. And then on the week on Fridays, when I'm doing all these, this algorithms that I run on my portfolio, and then I upload them into OpenClaw, then it's very easy for me to go back and like, hey, compare where the technical sheet is now versus where it was in April. Tell me where the exhaustion model is today versus where it was in April. It has all the information. And so for me, I just know that OpenClaw has everything that I need. And I guess I'm using it to some degree the way you're describing. But I don't have to go look at it. Yeah, it's just great because you can just dump the same data into your OpenClaw and OpenClaw and then access it and do whatever it wants and look for the patent matching and that comes up. And then you do, I mean, this is going way off the macro topic because it's always interesting to speak to somebody else doing the same thing. Are you using OpenClaw using a VPS or are you using a mini Mac or something like that? Now it's so I have one on a Mac mini which has a Chinese model, a Kimi K 2.5. And then I bought the highest end laptop I could from Apple and that one I'm using with GPT 5.5 at this point. So initially it was using 5.4 then when the pro max, I think I've just got mine today with the M5 chip and the whole exactly. Yeah, and it just stays open all the time and I can bring it with me. The reason I got a laptop is so that I literally can bring it around with me on trips as opposed to bringing my Mac mini and then plugging it into something and going through this. And I'm finding because we're moving between chat GPT, between codex, between code, between co-work, between that I've got Macs in my house, the main Macs and stuff. I'm like, it's just not functioning any longer because I'm having to scrape everything from the local machine, dumping it into my Google Drive or something. I just need the most powerful laptop and monitor screens and just plug the same thing in everywhere. But then I'm terrified of losing that laptop. So a quick break in your regular programming. If you're serious about your future, grab my free report called Prepare for 2030. I think you've got five years to make as much money as possible and this guide will help you navigate what's coming. The link is in the description. Download it now. I think I'm going to and I hate saying this, but again, for people listening who are thinking and building a business, when you don't have compensation costs and your business is growing and you're looking at the bottom line, your margins are insane. So it's literally like, I need to spend some money on something and so I keep playing with hardware because the hardware allows me to do things. So the Hermes agent stuff is going to be on an Nvidia. I mean, that's what it's going to be. And that's because number one, there's a backlog on all the Apple stuff at this point and that'll change at some point. But Nvidia is coming out with new work and I want to do it. And so I saw a setup that was on a on a DGX that I think is going to serve the purpose that I want with the Hermes agent of where it got to. So I still want to do these things and I also want multiple ones that can do things in a different way. So I haven't got to the point yet where I envision only having one of these. I like having them for different things and doing different projects. I want one that works overnight on a low-cost thing. I want to have an open source model because I listened to Demis Sassabus this morning on an interview he did probably that was with Y Combinator. And he just talked again and again about these models. The open source model is just getting better and better and smaller and smaller and eventually we're going to be on the edge. And I don't know what that means for the for the big model providers. I don't know what that means for enterprise adoption. But I do know this working on your own personal laptop and having your own machines is going to be a major part of what we're doing. And I just want to have the models just on my machine and I want to have the ones accessing the cloud. But also, you know, I think you're raising an important point here is that we're going to go to the edge. This process of, you know, it's laughable us buying Mac Minis and you know, and everybody running out of Mac Minis, right? But it just shows you the phase we're at. We're at the tinkering phase where everyone's like doing the in the end literally every electronic device will have a powerful LLM model because you're now getting the new Gemini 4 or whatever it is, the Gemma 4 or whatever you know these things are small enough for a mobile phone, carry the history of humanity on it and concoed. I mean, it's like these things are wild, right? And soon that'll be in your fridge. This is what people don't understand is, you know, this ridiculous phase where we're talking about different hardware, it goes everywhere, a, just to be to buy cloud that we don't think about these things, some localize, but then every single device. Yeah. The only thing I'll say about the devices, the approach, the thought I've had in the one that I say to parents, not to kids, the only analogy I can use for people is if it's either golf or skiing, I started skiing in my 40s, and it's a very hard thing to do. You have to, I mean, you have to unlearn what you think you know about falling. You have to learn about gravity more, you have to learn technical skills, you have to get over fears. It's a very complicated thing because you're scared of dying and hurting your knees and everything else. So golf, you have to, if someone said tomorrow that you want to start to play golf and you're like, okay, what do I do? One thing you have to do is put the reps in and for the machines to get used to being on the edge. Part of it is knowing that when you're walking around listening to a podcast, which I do every morning almost, and I hit something that clicks. If I'm listening to Rural and Julian, then you guys say something, which is literally what happened. You guys, I took the paper I wrote, has you guys referenced and it has two quotes from you, two literal quotes? I paused it. I speak it into whisper flow. It goes into notion. But then I'm like, you know what? I need to write a draft of the paper right now. So I paused the interview and as I'm walking, I now shift over to Chatchee PT and I say, okay, we're going to write a five paragraph paper real quick. So I have an outline. I want the first paragraph to be x, y, z. I want you to fill in enough of it. They're the thoughts I have. Paragraph two. And I go through this whole thing and it's a technique I learned from a movie producer on how they write screenplays. And it's like, yeah, movie when you watch it, it's think of it as 60, 90 second increments. And if you're going to write a paper, you should think about nine paragraphs and then just kind of write each paragraph at a time and then go back and edit it. And the only way Rural that I think people can actually get good at this is they need to buy the best iPhone. They need to buy the best computer. They need to buy it. They need to use it. And then when the new stuff comes out, they need to buy it and treat it as education and education costs money. And if you're not learning how to use it now, I don't know if you can catch up. I really don't. This is not going to be the software age. It's the one thing I haven't heard anyone talk about it. And I'd love to hear your opinion on it. I figure out new ways to change the way I'm using AI. It will never be a button. There will never be like a format way that everyone uses it. Everyone will use it differently. And for me, I really do use it walking. I use it thinking. I use it in the car. I use it on the plane. And then I use it on my Mac Mini. And they're all running at the same time. I think to do that, you have to use the technology in different devices. Yeah, what it is doing is creating friction with girlfriends like, yeah, you include. It's like, the problem is, is I'm on a plane. I come off for plane. I get to my desk and I've got, yeah, I'm doing everything I'm writing essays, getting notes, building stuff, analyzing stuff, doing my personal life stuff and there's all in one thing, right? Intelligence is not software. Intelligence is intelligence and it can have any output that you want or any input that you can give it. And that's why it's so unique in what it is. It's not like, oh, I use whatever software tools. None of that. It's not like using zero to do your accounting. It can be everything and anything or nothing depending what you do. Yeah. Do you do you watch TV much? I do in the evenings because I need to because if not, I'm not sleeping a lot because I'm like, I can do this and I can do this and I can do this. I can do, I'm not for fuck sake. I need to stop this. So I'm I'm the same way and maybe it's an hour a day. It's never during the day. Like sports sports has become like a lost thing for me because it's like three hours and I think about how much time can go on in three hours. Like, you can just go. You end up on the sofa. And if I can, you know, chat to you thinking, I've got an idea. Yeah. So go back to the first time that you talked to Stan Druckemiller, the first time that you talked to Paul Tutor Jones and the feeling you had of knowing these people from a myth and then speaking to them and realizing, I love talking to them because I'm learning something and their unique thinkers and what goes. The problem is in the way you describe it. And so people realize I always view the LLM as the smartest person I've ever met. And that means that why wouldn't I just love every conversation? And if I think of something I want their opinion on anything. I know. But that's, you know, but it's before you know it, you know, it's the main thing you talk to. And it's like, it's yeah, it's complicated. Let's put it that way. Not for insatiable learners who ask questions and constantly one. Incredible. I mean, it's incredible. It's just, you know, it's the most amazing thing you could ever imagine. You can't imagine anything more incredible than somewhere in this cloud above us is this super intelligent being of which we get to talk to. And it gets to help us. And maybe we're helping it as well. And it's like, it's wild. Yeah. And I guess that's where you and I are at this stage. And I know most of the people I talk to in my in my life. And a lot of them, it's shocking how many people that are a part of my regular communications that are people I've met either through you that were connected back to me. One of the people which I'll just mention, Ted Smith is a very close friend at this point. I love him to death. I love you had to my my spy tells me that you just have him. So Alan Howard the other day as well. I did. And Alan Alan's become a good friend as well and someone that I like to brainstorm with on on on a regular basis. Alan super small is a great guy. He's super smart because he has the same affliction I do, which is ADHD. Meaning he likes consuming lots of information and compounds from topic to topic. And Ted's a little bit more organized in his thoughts. And that's why he was CEO of major places. But the reason I bring him up is a lot of the conversations I have have come through you. And that just means it's it's curious people that are using AI. And in particular, I love people in their 50s and 60s that are using AI because they're bringing domain experience. They're bringing having people work for them. Because if you've had people work for you. And in my 20s, I open an office from Oregon Stanley. I've had hundreds of people reporting to me since I was in my early 30s. At some point you get frustration. You get happy. You get disappointed with the employees. That never happens with AI. It's always some amazing experience that I blame my. I think that was straightened sometimes, particularly when they're about to change a model. And it's the thing it. And it's like it's out. Output suddenly becomes really dumb. And it's so frustrating. It becomes lazy because they're obviously training transferring the inference over to a new cluster. And that gets so insanely angry. And then, but you know what's coming. It's like Christmas because you're going to get any model. Can we can we talk in the in the final minutes of this about how much and I don't know if you thought about this. So when I brought up Eli Lilly, the reason I care so much about longevity and about the concept of people not being sick is because whenever I hear people talk about government debt, there's two things that I always they just blow my mind. The US has $38 trillion, $40 trillion of debt. Great. The total net worth of households in the country is $180 trillion. So I always hate the fact when the balance sheet isn't brought into how small the problem is and that that has bothered me forever. But the second thing is when we get into the entitlements in this crossover point of when it's going to be bankrupt, then I go, well, how much of those dollars are related to health? How much of those dollars are related to? Have you thought about the impact that AI is going to have on both the debt and the entitlement situation? Well, the debt is simple because debt is a percentage of GDP collapses, right? That's the economic singularity idea. So I don't worry about the debt and I think the whole singularity when it starts really changing the economic form of 2030, that was my guess three years ago and I think it's going to be spot on. So that feels like that. The longevity side, it's a mix, right? I think you're right is that the entitlements go down, which is intelligent solving for the problem of the entitlements. But what do you do with an old population and how do you retool them to do things that they feel is productive? Now, it doesn't have to be productive as in terms of economic units, but it needs to be productive as in community or whatever it is. That's still quite hard to for them to figure out what you do because don't forget the whole mindset is I do this, then I retire, then I do that. And you kind of it all blurs into one. It's already been blurring for a while because everyone's working from home. So what is a job and you know, then when you're having so much fun as well, the whole job disappears, you're not reporting to the guy and having to wear a suit. So we're merging that way already. You know, what is a what is a podcast or a YouTube? It's, you know, it's somebody whose job is to get attention from other humans and entertain them, whether it's via curiosity or whatever it is. That's a purely post-AI job really. So I don't know about the longevity side because it's it's somewhat complicated because there's so many unknowns, but I hadn't really thought about the entitlement side, but it makes a lot of sense. Yeah. I spent a lot of time on this and I think the reason is I don't know if you have or if you've if you've ever seen the book The Daily Stoic by Ryan Holiday. Yeah. Yeah. Okay. Um, he's even been a real fisherman. Oh, I think the book is a must-own for all human beings. And I will never say that about any book. There's not a book I've read that I think all human beings should should read. But the reason I say all human beings is if you think your problems like worrying about what you would do if everything is free or if there's no jobs, wondering what you do, I mean, just go back to reading a book where Marcus Aurelius thousands of years ago is talking about the same anxiety. It's just a different form of it. Human beings have anxiety and they will always have anxiety. They will always worry about what if this then what will happen. Um, type thing. There's people that lose their arms and then they're playing golf. There's people that, you know, every single thing that human beings need to overcome over time, they have figured a way to not all people, but people have the ability to kind of find it. And the Daily Stoic has always shown me that I'm not trying to, I never think the problem of this all happened and people won't adjust to it. I know they will. The debt problem I completely agree with you on. I don't know how much you've been talking with people on tokenization. I know I've listened to some interviews recently where you, where you have, but I was just at the New York Stock Exchange and I said to everyone, do you understand that two thirds of the assets in the world are illiquid tokenization for everything that people are looking at. We're going to bring transparency, movement into dormant things. Two thirds of the money that has gone into assets doesn't move real estate, private credit, private equity venture cap all art, memorabilia, like it doesn't move. Now you're going to have movement velocity. So GDP by definition, just because of velocity has to go higher. So I agree with you on the debt side. That's why I've started to focus more on the entitlement side and what it means from a political basis and what it means for crypto in general. And so tokenization has been kind of the thing that has really entered my mind with this longevity thing because demographics are obviously highly attached to the, to the entitlements, but they're also attached to the ownership of assets and that's where tokenization comes into. Another thing that I'm been thinking through is a rotor of essay and a bit series of essays around something I've called the invisible economy, which is basically the agentsic economy. Now I got to it, it was Ribbit Capital, Mickey Malca, and the team had written an essay about tokenization of everything in token factories. And how they think about token is a machine readable packet of information, whether it's a financial transaction. I mean, even blockchains aren't financial transactions, only Bitcoin is. They're recorded packets of digital information. And how much Google, I think Google, what did they create or process? I can't, it's like 13, 30 trillion tokens last year. It was stupid, right? We're in quite trillions now for sure. Oh, of course, whatever it is, it was like a stupid number. But anyway, what I realized is to feed the beast as I call it, the whole AI super brains, all of them, however it comes, you need more and more information to get smarter. Yep. And we're going to suck in all of the information. Every single piece of information that can possibly be digitized, we'll get digitized, and used to train AGI to turn into ASI. That's every piece of scientific data, every single thing from any university, any single piece of information. All of this is going to be an agentic economy that's invisible to us. They will be, well, we're already seeing it, right? API calls, MCP. This is the start of the invisible agentic economy where the marketplace, and what I'm trying to get to, to your point, the biggest marketplace on earth is not going to be the assets and stuff that humans have. It's the data that the AI needs. And we don't see any of it. You just plug in your thing to your vault. Yep. And you can monetize it. And you can be a university. You can be whatever for source information. We're seeing people like John Deere connecting all of the tractors and getting all of the information. We're seeing all of these companies creating massive, massive, massive information. And that we won't even see. It'll generate money for whoever it is, that's probably an AI agent, by other AI agents who are connecting with them, taking all of these transactions in real time speed. And I've been telling people, this is the biggest marketplace on earth. And people don't even, not even ready for this shit. And I will, I will give you a lot of credit being in the seat you're in, being making calls going out and having to deal with people's impatience on how this all plays out and how long it takes, particularly in the crypto community. And as you were speaking about this hidden economy, I remember you in the conversation with Julian, you're getting into this. So I've started to kind of pick apart the concept of bubble because bubble is a very weird thing. And it's very hard and exponential because it's price and time. And so like when you're talking about, you have to be patient. I'm now going the other direction. I'm going, if you don't want to be patient, that's fine. But if you're seeing a bunch of parabolas, don't think of it as a bubble, break bubble down. That means you're seeing sticks. That means things are going up fast. So they're going up high and they're going up fast. And the problem is when you look at the Mag 7 and you go, well, they were a trillion dollars in, in 2010. And now they're 20 some odd trillion. Well, if that had happened in one year, that you'd call it a bubble, but it happened over 15 years. So it's not a bubble, but it's a 20-bagger. It's a 30-bagger. So why isn't any different? You just think that if it happens too fast, that's a bubble. And I think people, that is the problem is people don't understand time, both from the bubble side, but also from the patient side. And what's been hilarious is earnings of ket pace. Yes. With its not growth, right? In fact, peas have come down. And people don't want to see that. It's like, we've got hockey sticks going on in ways that we have never seen before. It's literally everything. Yeah. And I'm sure what's going to happen is they're going to consolidate now. And then they'll go up again. And you know what a six-month consolidation looks on a hockey stick to then hockey sticks again. When you pull it out, it still looks like a hockey stick. So for everyone who's going through this, it's like, we're caught in this human time warp of looking at things and things that move fast, we assume can't be true. And I was listening to a podcast this week where sometimes the brilliance comes out from people that are not that educated, but what they're doing is just paying attention to everything they hear. And they call this, I think the smarter you are, the more you know the worse you are during this time. I think actually knowing a lot, like having the history in the back of your mind, your brain is taking this pattern, connecting it to too many other patterns. And even though when people go, this is like the dot com bubble. This is like 87. This is like, you know, 1929. And I look and I go, that's three data points. I don't make decisions on three data points. You're going to have to give me more on this because if you're wrong, you're missing out on the entire thing. And so how you and I would understand this is those people have a bloated context window. And what happens is it's exactly right. I mean, once you realize it, right, you know, when the LLM's compress, that's what we do, we remember certain things and it gets more compressed over time, this context window, if you, that's the mid curving, you're putting too much context into the thing. And what happens is you're drawing false parallels or misunderstanding or not reading what it is and often to, to let go of it, what, you know, how I got into using Claude Coe because I'm scared of it was I'm just like, listen, I've no fucking clue what I'm doing. So just, just bear with me. Yeah. Well, I, as opposed to, and I need to know how to do this, I need to know, I'm like, I've no clue. So just, I'm in that. And then occasionally you'll stop him, so like, I don't understand what you're talking about. Sorry. Okay. Come back to you. All right. So let me get your opinion on this because I think everyone reminds you of this. I think they want to hear us talk about this. So when earnings are this good, it's very easy for people that are traditional investors to then look at what the PE is, what the growth rate is and they can justify buying things at any price. When earnings are great and they're this good, it's bad for things that are narrative-based. It's bad for Bitcoin. It's bad for crypto because there is no way to take the same thing. So it's not just the attention in my opinion as to what's happened. It's the fact that for this period of time, which I believe is a small period. The one thing I believe has happened is this is like a gap higher in AI because in the end of last year, nobody was on top of the importance of Opus 4.5. That was the official gun going off for the agentic world. The agentic world is a broadening out in what it needs. It brings in every semiconductor. It's not just GPUs. It is movement. It is so many things. And so if overnight, there was a pre-announcement and the earnings were, you know what, we're saying the earnings are now going to be up 28% year-to-year. Well, then the stock market gaps up. All the semi-names go up immediately and you have this place. The problem is for things that are narrative-based that don't actually work in the traditional world is then they lose interest to people because they have so many things to buy. I think we've now built in because it was such a surprise, the agentic thing, there's so many real investors. I've talked to trillions of PMs that manage, oh, combined over trillions of dollars. I'm telling you, they were caught off guard by the agentic rise. They're not caught off guard anymore. Now they're fully on board. They get it. And they're probably a little bit ahead now and the earnings will now be good, but they won't be five times what people expected. And that means we should be a rotation. And that's why I like the longevity themes. I like the application for the software for Eli Lilly and for stuff like that. But I also think this is where crypto and where a lot of the commodity-based stuff, the bottlenecks of shortages, and there's the normal rotation where people look for other things. But I love your opinion on when earnings are great, you don't need crypto. What happens when earnings are now a two-sided market? Yeah, I think, look, everything is attention and capital, right? And there's simply not enough liquidity to drive these massive megastokes to these levels. There's not enough attention to be broadly spread, which actually creates opportunity. If you go back to the 1995 to 2000 period, it was rolling as well. It wasn't just one set of stocks, right? It wasn't just Microsoft. It was a whole bunch of things that moved over different periods of time. So I think we'll see that. And I think what you're suggesting, I think, is really interesting, is that the bottlenecks themselves may slow the earnings of these companies. Not because the demand is not there because the demand is too big. Okay, that's sort of bananas, but that's what we might get to. And if that happens, they need to correct or trade sideways for a while and digest and do all of that. And that's great. And the market's focus will move. And the application's layers one. And crypto to me is, I mean, it's so obvious. And it remains obvious because of the agentic economy, the need for ID, the need for all of the things from AI alone, let alone all the other attributes of blockchain technology that that doesn't go away. And I've been really hyper focused on the layer ones. Not just stuff like hyper liquid because that's for me mid curving it because people are looking for cash flow. And yeah, buybacks. It's like because they want it in a bucket that they understand because as you're saying, it's working in the real world too. And other things haven't been. I think that will all change again. The other thing is, I did a few sort of Chimath had written that whole article on X about how these software, long duration software stocks were. And basically, you read this very long piece. And what he's made the assumption of is in a world where all software goes to zero, basically, is what he's saying. It has a three year shelf life. And it's like, He's actually using current interest rates for that assumption, but in that world interest rates are zero. And so duration doesn't matter still. So I think it's just attention-focused and people trying to understand, you know, what? There's a lot of people interesting enough buying SaaS companies to use AI to rebuild them. And that we're a bunch of them won't happen. So yeah, we're going to have a bifurcation of stuff. I don't sit going away because what are we, what are you and I doing all day plugging our fucking api? Our AIs into APIs of all of these things. Right, there's no point rebuilding zero if you need to do accounting. Just get your claw to talk to zero and do the accounting. Yeah. Why would you rebuild? Oh, I've built my entire own accounting engine. That's stupid. So let's, let's, everything you said there. So, chamaste thing on terminal value I wrote about. Let's go back to what you said about the bottlenecks and the interesting part. So the AI world is a commodity world. This is a hardware trade. And in commodities, they don't speak in the way that we do with software and we go through. They think in volumes. So it's a volume thing. It's how many did you sell? The price is the after effect, but it's all about barrels of oil. It's about how much did you sell? My guess is with bottlenecks, you just, you don't sell as much because you can't make as much. And so the production of these things is going to be more difficult. The other thing is to make a semiconductor. You need and a people have realized you need nap. That you need helium. You need a lot of petrochemicals, not just in that. You need them for lithography. You need everything to happen to be able to build everything. And so if there's a bottleneck, you could extrapolate this bottleneck. You and I both know the algorithmic side and the agentic side could make all of the investment. The catpex numbers may never happen to the degree that people think. Because we could solve for that. So there could be a bubble on that. Here's where the issue comes in in the second part of what you brought up. I always believed that I first said this said, you're event in Miami last year, not the one this year. But I said, guys, the third wave of crypto, I already know what is two things have to be happening. One is once the AI physical infrastructure is being built for the agentic world, and we hit that trigger point in the agentic world, we won't know three years from now whether we're at AGI or not. We won't know which companies will be around. And that's Chema's point on terminal value. What I do know will be here is the financial guardrails, the transactions, the velocity of money, all of that will be happening. The beauty of the financial guardrails in crypto, we're back to software again. We're just a different, it's a different kind of software. But it's about the transactions. And so if the physical hardware side becomes, I don't know if this is going to happen or whether we actually need as much as I thought we did, well then we get back into the cyclical side and people start looking for, I need something safe, I need software, I need things that don't need the physical world that are based on volumes and seats. And well, that's AI agents. And so I've always believed that the third wave is an Elliott Wave person. Number one, you had to get to a point where everyone was dumping crypto, which is where we are. Number two, they had to miss the obvious, which is the financial guardrails are necessary for these consuming token hungry digital employees. And we need that the world that they're comfortable with, they start questioning if these are good investments and tokenization needs to come to make them more liquid, where that money can leave this massive $400 trillion and start to enter the crypto world. So I actually believe that this is the most important point for people. It's the patience point. We are now at the bottleneck stage and the longer it takes the fix a bottleneck role, the more likely is that we come up with innovations along the way that we don't need the entire capex build out. And so you could get these multiples to come down. And so that's what I think is going to happen is we'll start questioning it at some point this year or into next year. Talk to me about the IPOs, because this is on people's mind. How are you thinking through this? I've been spending a lot of time thinking about this as well. How are you thinking about it? Well, first thing is Google's decision to do this is clearly in my opinion a fight for finite amount of capital. You've got massive IPOs, three massive IPOs coming to the market, where you could see $4 trillion there coming in. You had cerebrus come out and the stock is already down 50% from where it is, which is fairly normal for any IPO. But I think you're getting these raises at a time which says that number one, people need a lot of capital for this build out. Number two, the credit markets and the debt markets are being used by the companies that can do it. And if I was Google and Goldman walked in and said, hey, open AI and anthropic are not going to be able to raise debt. You should go hit their market because they're going to tap into that. SpaceX can't go borrow any debt. So hit the equity market, get your stuff done, and then continue with the debt markets. But you might as well do that now. So I think the IPOs are very likely to be some sort of a not a top in the market, but probably a peak in the infrastructure cat-backs trade for the time being. Rather than say the S&P is going to trade lower, because I can see software, I can see a lot of things starting to do well. I just think in general this might be a peak in the cat-backs trade. Yeah, I think there's going to be some outcome. You can't have this much. Although there is a bit of an engineered short squeeze and stuff like SpaceX, just by how it's included to the NASDAQ. I'm not sure. I just think volatility seems to be the easiest answer to that. It's not going to be as easy for a bit, because we're going to need to digest a lot of capital. People have to recycle capital. Because if you think about it, there's a whole bunch of people who made a shit ton of money. They're going to be able to realize some of their gains. Okay, great. So they realize some of their gains. What are they going to do, reinvesting to something else? The capital gets recycled in the end, because why not? This is the world's greatest trade of all time. It's all happening in front of us. So for people listening, Roll and I have been involved in the same market for a long time. So I used a word that I used in my paper today. So for people that are technicians, they'll say consolidate. For people that I think pay attention to investors and supply and demand, digestion. And the line I used in my paper was, we just had an AI cat-backs all you can eat buffet. And it's going to end with the IPOs. It's not going to go down. This is not the end of the market. But we need to digest everything that just happened for three to six months. And it could be sloppy and it could be frustrating for people. But capital will rotate. The moment it happens, people realize that the underlying growth of this whole thing, this mega-secular trend is not going away. So therefore people just go for the next phase, whatever it is. Whether it's crypto. If in video and all of these companies stop going up, probability of crypto going up goes up much faster. For example, did you think when the Bitcoin ETF was launched, that we'd see a similar type thing that after the initial enthusiasm, we'd go through a period of digestion? Yeah, I mean, we've seen that before. We saw it with gold, the gold futures market. We've seen this, you know, it's a lot because you forward load a bunch of demand. Basically, it's what it is. And you need for the wait for the underlying trend of demand to continue. And, you know, capital can only be created via either the markets growing up and people cashing out or by liquidity expansion. And that's only expanding at a certain pace. You have global liquidity is expanding 10% a year. So it takes a while if you take out, if you forward do years worth of capital, it's going to take a year to catch up. And the reason I asked the question is because if you would have gone back in hindsight before 2024 and said, okay, so the ETF launch is going to happen. And oh, by the way, the president of the United States is going to support crypto. And all of that happened within a one year period. You would expect that that was kind of like a digestion event. That would be a sell the news event. And so whenever I look at crypto and I see people, I'm like, unfortunately, you come out of a bear market, a horrible bear market in 2022. And then you get this enthusiasm. And finally, we're getting this ETF. And then you get a president. And then you get a president and add inauguration. He issues a meme stock and all of a sudden now, if you could have written the book, you would have said, I think we're going to be in a painful period. And I think it actually clearly the altcoins and a lot of the ecosystem did not do as well. As Bitcoin did during the period. But I think everyone would have would admit looking back that those events probably justified some sort of a digestion period. And I think that's what crypto has been going through person. Yeah. And in the meantime, you know, like you, I'm an observer of the underlying trend. The underlying trend is every single bank and financial institution I have spoken to. When I go to the big, I went to consensus in Miami, no retail. No, and it was not a lot of people. Yeah. I don't know how many 15,000 people not retail. You're well. But they're still out there, oh, because I left yoga this morning at 715 and these two very nice women, again, Meshada, Jessica and Patricia, they saw me and they went, hi, Jordy. Hi, they went, we follow you. I mean, oh, that's great. And they went, this is a sign we need to buy today. They're still out there. They're just waiting for. No, they're not. They're not gone. They're really interesting. These are bigger than. Yeah. Well, also because retail haven't made money and the ticket prices is expensive, whatever. Yeah. But there's a transition. I mean, look at the rise of stable coins. Look at the rise of what the financial institution is doing. Look at the tokenization of everything. And you just see what the underlying trend is. And you can see what the financial institution is doing. building huge demand for block space by these things. You know what the answer is going to be? It's number go up. People unfortunately got too used to short-term trading that they've lost the wood through the trees. Yeah. Which again, that's normal. I just find the traders in this world that I know are crypto. They move on to other things and there's other things to to make money on. My father trained me in handicapping horse races and he used always say, if the odds on in your favor, wait till the next race. And I think if you break markets down by what race are we in, right now the crypto race is not a race that people have been enjoyable. I've said to people now that there's no way to refute it. When you fail at a moving average or you fail and you keep having these lower lows and lower highs, it's a fair market. There's no other way to do it. I want to see us break a moving average and I want to see on the flip side the CapEx trade not be working and everyone looking for a new place to play the trade because if I'm right and this is the third wave, I learned a lesson from from both Paul and Stan when I read Market Wizards when I was a younger person still in my 20s and they both said read the Elliott Wave book and I still to this day read it every single year. Now I use AI to kind of go through and have a chat with it but I'm a big believer in third waves or when you make lots of money and I was lucky to catch one in micron. I'm lucky to catch one in Marvel. I'm waiting for it to happen back in crypto and for everyone who's watching third waves go look him up. You want to be involved in that. It could be called the banana zone but it's still this Jordy. A fantastic conversation is ever. I just I love these check-ins because we just are parallel into locking paths and then we just get a chance to check in what each other's up to and what they're thinking about. I love it. Love it as well. All right my friend. See you soon. See you soon. So another great conversation with Jordy. There's not much more to say really than you can see how much disruption is happening, how fast it's happening and how complex it all is but also there's probably still opportunities in all of this. The great rotation when it happens if it happens if people move away from the Magnificent Seven and start looking at laggards. Well there's the whole biological revolution going on. There's whole applications layers. What's it going to do to the SaaS industry? We don't know but we're going to find out and when this crypts had catch up as well because I know people have given up hope but normally that's the right signal when things change. So anyway keep your eyes on it all. Nothing is nothing remains as it is. This is the exponential age after all. That's when everything goes exponential. See you next time. You obviously enjoyed the episode because you're here with me at the end but listen don't forget to go to www.realvish.com/join and grab a free membership. It's an incredible community packed with alpha, great investment ideas and the research that you need to help you unfuck your future. So get started now. Go to www.realvish.com/join.