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Felix Prehn - The AI Stocks Palantir Wants You To Buy + Stock Market News 29 October 2025 (Goat Academy)

• Felix Prehn

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What if I told you that one of the smartest investors in the world just revealed exactly how he thinks about AI investments? And that guy is the co-founder of Palantir, a chap called Joe Lonsdale. Now, he didn't just co-found Palantir, the company that helps governments in Fortune 500 companies make sense of massive data. He also runs a venture capital firm that invests hundreds of millions of dollars into the next big tech companies. And he literally just published his complete framework for understanding AI investments. Breaks AI down into six different tiers, like levels in a video game. Each tier represents different ways to make money from the AI revolution. And here's the crazy part most investors are focusing on the wrong tiers. By the end of this video, you will know exactly which stocks to research for each tier, including current prices, what they actually do, and why they matter, whether you have$100 or$100,000 to invest. Now smash the subscribe button because you know we're going to be diving deep here. And to make this video most valuable for you, I'm also going to give you completely for free all of my research in a presentation to a research document so you really understand this. Because we're going to cover so much ground here, you're going to want to be able to reference that material because I'm going to give you all the stocks, all the sectors. There's going to be a lot of stuff in there, and that's completely free. It's in our free community at foodexpense.org slash resource. Grab that so you get the most out of this. Before we jump into the specific stocks, you need to understand Joe's framework. Think of AI like building a house. Now there are six tiers. I've actually added a seventh because it just makes a lot more sense. One of his tiers was kind of covering two things. So we've actually got seven tiers, but he started with tier zero to kind of make this make sense. First of all, you have tier zero. That's your energy infrastructure sector. That's powering the entire ecosystem. It's the power plant that keeps everything running. Then you have tier one, your semiconductors, then the bricks and the concrete, they're the physical chips. Tier two are your data centers. That's the house itself where all the computing happens. Tier three are your foundation models. They're the architects, they're companies building Chat GPT-style AI. And then you have tier four, the software infrastructure. Think of these guys as the plumbing, the electrical tools to deploy AI. Tier five, that's the furniture, that's the applications, useful products people actually use. And then the last tier here are old houses getting renovated with AI. Your traditional companies. And the key insight here is what Joe says. Most of the best opportunities are in what? Tier five. AI applications. Almost all of these companies are private, though. You can't buy stock in them. So we're going to show you the best publicly traded companies across all of these tiers. And this way you can potentially invest in the AI revolution today, not in five years when those companies finally go public. Why AI? Why now? Well, it's going to be like a$5 trillion business by 2033. So that will be bigger than the GDP of Germany, which is where I hail from. Hence the strange accent. But make no mistake, this is the biggest wealth creation event of our lifetime so far. So let's dive into it. We're going to go through each tier. We're going to give you stocks for each tier. Doesn't mean you should run out and buy them blindly, but it's a great start for your research. You'd want to dive a little deeper than download the full research document that I'm giving you for free at FelixTrans.org slash resource. So, first of all, we have energy infrastructure. Well, AI needs a massive amount of electricity. We're not talking about running your laptop. A single AI data center can use as much power as a city. So as AI grows, energy demand explodes, and these companies are basically selling, well, they're like selling water bottles during a marathon. They win no matter which AI company becomes the champion. That's the beauty of it. So I've selected two stocks here for you. CEG, Constellation Energy, as the top pick here. What it does, well, it runs the largest nuclear power fleet in America. Nuclear power runs 24-7. It's perfect for data centers, because data centers never sleep. They have contracts with Microsoft, with Meta. And we're expecting their revenue to grow 10% per year until 2028. And guess what? More data centers are going to get built. More power will be needed. The second stock is VRT Invertive Holdings. What does it do? It makes cooling systems for data centers. Why does that matter? AI chips get really, really hot, hotter than regular computers. They make the cooling systems. It's like a car radiator, but for chips essentially. And they work with NVIDIA. They work with Microsoft. These guys know what they're doing. AI chips are like athletes. They need cooling to perform their best, or like cars, perhaps maybe the better. A bit of a random analogy there, isn't it? VRT is often called the real AI darling by analysts. Now, what if you don't want to buy individual stocks because that scares you? Nothing wrong with that. One thing I'd say to you is you might want to learn Wall Street's system for picking those stocks. You can learn that in 15 minutes. I'll teach it to you for free. Not in this video, because it'll make this video unnecessarily long. But you can go to felixfriends.org slash get free. FelixFriends.org slash get free, and you can watch a 15-minute video I made just for you. So if you want to not buy stocks, well, you could buy some ETFs. Let me write some ETFs on the screen here for you. That stuff's also in the in the research doc. XLU is one, it's a big one. It's basically the utility sector. It's a basket of utility companies. So you will own 28 companies instead of just the one. So if you're in a conservative chap or lady, then that could be that. They also pay a decent dividend. So energy is your foundation. These companies benefit no matter which AI companies win. Lower risk, more steady returns, dividend income. Not saying there's no risk. There is risk at all investments. I'm not telling you what to buy, being hopefully the beginning of your research so you can make smarter decisions. Section number one, because we started with zero. Sneaky, wasn't it? Sneaky. These are the actual chips that power AI. So it's like the engine running the race car. The better the chip, the faster AI can think. So why does it matter? Well, every single AI model needs these chips. They're in short supply, companies are waiting for them, the market is growing at 40% a year. Write that down. Who's the market leader? Well, I think you probably know it's Nvidia. They have a 92% market share. Then you have AMD. That's sort of your value play. Hanging behind it a little bit. Earnings are growing at 43%. If you want to diversify, you've got TSM. They make the chips for everybody. They are sold out till 2026. They can't make any more chips. So if you don't want to pick Nvidia or AMD or Broadcom or any of the chip design companies out there, well, TSM makes all their chips. So that could be an interesting alternative, right? Doesn't matter which chip wins, they will make them. It's very simple. So what's the takeaway here? Semiconductors are the engine of AI. Nvidia dominates, AMD offers value, TSM offers diversification. There are some other ones you could look at for custom chips like Broadcom or for Memory Micron. But let's focus on the main ones here. Now these stocks are volatile. They're gonna swing up and down a lot. Bear that in mind. Tier two. Data centers. What is it? They're the massive buildings filled with computers. They're like giant warehouses but for servers instead of boxes. And AI models need somewhere to live and run. Data centers sign three to ten year leases for tech companies. That means stable, predictable revenue. As AI grows, demand for space will grow too. So who have we got here? We've got the market leader, Equinix, EQIX is the ticker. They have uh 220 data centers in 26 countries, pay a nice dividend of 2-3% as well. So Equinix is basically the landlord for AI companies. The second stock is a realty trust, DLR. They own 290 data centers globally, pay a similar dividend to EQIX. Last time I checked. Nicely diversified across the US, Europe, Asia, long-term contracts for cloud providers, pays a dividend. It's basically not a landowner option, different locations. If you want an alternative, if you want an ETF, if you're an ETF hunter, there is one called DTCR. Write that down. They basically own multiple data center companies. So it's diversified across the whole industry, pays about, last time I checked about a 1.7% dividend. So data centers offer more stability, but growth potential. These are REITs. They pay out most of their profits as dividends. It's a lower risk than chips or software, but it is sensitive to things like interest rates. Lower interest rates good, higher interest rates bad. Then we have the foundation models. These companies build the actual AI brains, think ChatGPT, think Google's Gemini, think Meta's Lama, the architects of artificial intelligence. And these guys are at the core of AI. Every application needs a model underneath it. But most of these companies are private. You can't invest in them. So what are our publicly listed options? Well, we've got Google. They're a nicely diversified AI leader. They do Google search, YouTube, where you're watching this probably. Google Cloud, Gemini AI. And funnily enough, they actually made my uh my buy list this week. Doesn't mean you should run out and buy it, by the way. They compete with ChatGPT. Google Cloud also offers AI services to businesses. They have DeepMind, their research arm, and they are spending about$75 billion on AI infrastructure just this year. So Google is integrating AI into everything search, ads, cloud. And the advantage is these guys are already profitable. They have massive cash flow to fund the AI, and you get YouTube, Google Search, Android thrown in for free, basically. The second one is Microsoft, because they're basically an open AI proxy. Of course, they have Windows and Office and Xbox and Azure Cloud and everything else thrown in as well. But they're the main cloud provider for OpenAI. They have Copilot, which is an AI tool and Word and Excel and PowerPoint and so on. And 65% of Fortune 500 companies use Azure OpenAI services through Microsoft. So Microsoft is basically the closest you can get to owning OpenAI without it being public yet. Thirdly, we have Zook's little plaything, Meta. Meta is Facebook, it's Instagram, it's WhatsApp, it's RayBen Smart Glasses. This isn't one of those. This is for the bright lights. They have a Chat GPT competitor called Lama. Doesn't spit at you, but you know you get the idea. It's open source. Meta AI is a billion monthly users, and they use AI to improve ads, which is their main moneymaker, their main business. So Meta basically gives away AI for free, but uses it to make their products better. So the advantage is massive user-based to test improve AI. These foundation models are massively expensive to build, billions of dollars. So only the giant tech companies can afford to build them. Microsoft gets you indirect open AI exposure, but all three companies here are profitable now, not just some AI promise. So these companies are so big, they move a little bit slower than startups. That's the risk here, but you get a bit more uh safety in there, right? Still risk in every stock, obviously. You're getting some value in this? Put a V or a value in the chat and crying out loud, make sure you download the research and learn the brutals on how to actually buy stocks. Links are down below. Tier four. What is software infrastructure? They're the tools that help companies deploy and manage AI. Think of it like the tool belts of a construction worker. They make AI easier to use for businesses. Now, Joe Lonsdale wants, but the problem with tier four is foundation model companies, OpenAI Google, they're building their own infrastructure. And it makes it hard for pure infrastructure companies to compete. But there is one exception, and that stock is Palonte Technologies, which happens to be Joe's company. No conflict of interest there. What do they do? Data analytics, AI platform for governments and big businesses,$450 billion market cap, something like that. Now they started as a defense contractor. The Foundry platform now helps companies organize their AI, their data. So it lets businesses deploy AI without being experts. They just got a billion-dollar contract with the US, with the UK's Ministry of Defense. US commercial revenue is up 93% year over year. Just joined the SP 500. We've been talking about them for years, since we're trading at like$20. And Joe basically says Palantir succeeds because they understand the ontology of their customer. Ontology is just deeply understanding how work actually gets done. It's very hard for their customers to leave because there's no real alternative out there. So Palantir is like a translator between your company's data and AI. Now it's trading at a fairly hefty valuation, but if growth continues at 90%, well valuation could actually make a lot of sense. Start by joining the free community. I should mention that this is obviously higher risk than some of the stuff we talked about before, right? It goes without saying. Now, tier five, five chink, these are the AI products that do actually work. They replace jobs, like having a robot employee. Now, Joe loves these. Their venture capital firm spends most of their money here. So what do these guys do? They're like AI software engineers that write code, AI recruiters that find and screen candidates, AI researchers that conduct interviews, AI legal assistants that handle contracts. The problem, almost all of these companies are private. You can't invest in them unless you're a venture capitalist. But there are some publicly listed alternatives I dug out for you. The first is Soundhound. What does it do? Voice AI for real-time conversations. So think about it this way: an AI drive-thru, ordering at restaurants, in-car voice assistance, customer service bots. They're already doing 100 million daily interactions. So wherever you talk to an AI for the drive-thru, it might be Soundhound. So the opportunity here, it's a pure play AI application. The risk is it's a small company. They're not making any money yet. Could be very risky. So I'm going to give you one that is a little bit less risky, which is good old Adobe. You probably think of Photoshop or Illustrator or some sort of other design software. Well, they also have Fireflight, which generates images from text descriptions. Three billion images have been created so far. It's built into every Adobe program. So Adobe lets designers use AI to create images and designs faster. Now they're already profitable, they have millions of paying subscribers, and designers already use Adobe, so it kind of makes sense for them to stay there. Third play is CRM, Salesforce. Customer relationship management. That's what that stands for. Basically a sales software. They have a product called Agent Force. And that AI handles 50% of customer service conversations automatically. Automate sales follow-ups and data entry. So Salesforce is basically teaching AI to do sales and customer service jobs. Now, none of these are perfect. Adobe and Salesforce are established companies adding AI. They're not AI native, but they're the best public options right now, in my humble opinion. So this is Joe's favorite tier. But as I say, the public options are limited. Soundhound is probably the highest risk, highest potential. Adobe and Salesforce are safer, more established companies. The best companies will eventually go public. We'll talk about them on the channel here once they do, so make sure you are subscribed. Tier 6. We're getting there, aren't we? Well done. Well done for still being here with me. What are traditional companies? Well, old companies are using new AI technology. It's like teaching an old dog new tricks, manufacturing, retail, banking, traditional industries. And these companies are already making money. AI just makes them more profitable. So it's a lower risk investment than a pure AI player. Let me give you a couple of examples. Rockwell Automation, ticker symbol ROK, what does it do? Well, they make factory automation equipment. Now they've released a free AI software for factory design. It helps factories run smarter with AI, makes programming robots easier. So Rockwell is bringing AI to manufacturing floors, and every factory will need to upgrade eventually. There are some other examples we could put in here. Google and Meta, for example, they're using AI to improve their core business, search and ads. Walmart is using AI for supply chain and inventory. Banks are using AI for fraud detection and customer service. This is the lowest risk AI exposure you can get. Big companies that are already profitable before AI, AI will improve their margin, it'll improve their core business. So it's good for more conservative investors who still want to participate in the potential AI upside without all that AI risk. So let me give you three ideas of how you might structure a portfolio. I'm not telling you to do it. This isn't financial advice, this is educational. I just want to give you some guidelines that you might want to think about. You've got to come to your own conclusions. We teach skills, not the answer. You have to come to the answer yourself because only that way you'll be independent and you'll be able to do this again tomorrow. But before we get into those three tiers, let's look at ETFs first. So there's some alternatives here. There's AIQ, Global X AI in technology. It's uh an ETF. AMD, Meta, Microsoft are in there, 88 stocks, pretty diversified. We have RT, which is a little smaller, 48 stocks, a bit more concentrated. Think Nvidia, Broadcom, VRT, stocks we talked about. Or maybe you want to focus on more on robotics, which in the case you have NVIDIA, ABB, FANUK in there. Instant diversification, one button, but it may underperform the hyper growth stocks, but it's probably less risky. Now, alternatively, we can build a whole portfolio around this. So say you're a conservative chap, lower risk, right? Still risky. I'm not saying there isn't any. You could get some energy and data center exposure. You could focus on some AI ETFs, perhaps with some of that money. Um I give you the tickets here. Uh, and maybe you want to go into some of the big tech stocks, Google, Microsoft, relatively reliable. They give you some dividend income, they give you relative stability. Now, if you're a little bit more um, you know, that's meant to be fire, but you get the idea. Your mindset is a little bit more uh rocket, then um maybe something a bit more balanced might appeal more. The time horizon should still be 10 years plus if you're picking these kind of stocks for the long run. Semiconductors diversified across Nvidia, AMD, TSM, maybe an AI ETF like AIQ, and some of the foundation model owners like Google, Microsoft, Meta, and then somewhat infrastructure, which would Parliament here. So you get growth and you get diversification, medium risk. Now, if you want to be really, you know, the to the moon shop here, then high risk would be what? If you're very young, you have a very high risk tolerance, or it's just a very small, small, small portion of your portfolio, you go into the individual stocks. Nvidia, AMD, AVGO, Palantir, Soundhound, maybe the chat ETF. Now, these can drop 20 or 30% quite easily in a bad market, but you do get maximum growth potential. You need good stomach lining, you need good risk management, you need to know what the heck you're doing. Just to give you some options about what to think about, not telling you which one to do or what to do any of these. Now, you're gonna want to think about risks. There's an argument, there'll be an evaluation bubble. Um, there could be antitrust action, especially against the Googles and the Microsoft, the big boys and videos. And technology changes. So today's leader could be tomorrow's loser, right? Someone else might come along and just do it better. So competition is gonna increase. So you're gonna want to diversify. You might want a dollar cost average, never invest more than you can lose, and definitely always keep an emergency fund. Don't leverage, don't ever borrow money to invest. That would be my advice. What financial advice do you own research? Consult a competent financial advisor. Focus on competent. But the real data, that's just facts. The AI market is expected to be$4.8 trillion according to McKinsey, but that's a fact or not to different story. We expect a 10x productivity gain. Chips are expected to grow about 40%. We expect massive margin improvements, and therefore, potentially there is a lot of money to be made here. So to summarize where we are at here, maybe take a screenshot of this. I also put a little bit like the risks here for you so you can see where they are for each of these tiers. So you have some takeaways. Yes, yes, yes, yes, yes. All right, move on. And now you're gonna want to take action. This is just the beginning. This was just you learning something. Now you need to turn that something into actual skills. For that, I'd highly recommend you go to FelixTrans.org slash get free and learn some actual skills so that you can take this and apply it. I hope you got some value out of this. If you did, share it with a friend who might get some value out of this. And I hope that you take action and learn some more. All the best.

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