To The Moon

When I was growing up in the 1980s, we had a set of Britannica encyclopedias on the bookshelf in the living room. If I had a question about an animal, country, disease, or anything else, that’s where I could go to try to find an answer. Despite being thousands of pages, the explanations weren’t in-depth, weren’t updated, and often what I was looking for wasn’t there. The next step was going to the public library a few blocks away. And I never quite got the hang of searching their catalog system. If you weren’t alive then, it’s hard to explain just how hard it was to find information. Sometime in the late 1980s, we got a computer with MS-DOS. In the early 1990s, that computer could access the internet through a service called Prodigy. Suddenly, you could get the weather 24/7, not just at 5:

Only about $0.05 of every dollar spent on $Uber(UBER)$ ends up as profit or free cash flow for the company. Now imagine an ad-supported version of Uber. What if advertising revenue could subsidize fares, making rides significantly cheaper — or even free in some cases? 👀 Uber already has a massive consumer network and valuable insights into shopping and travel behavior. Advertising could create a higher-margin revenue stream without requiring a proportional increase in rides. The big question is how much of that potential can translate into sustainable free cash flow. A trillion-dollar valuation by 2035 is an ambitious target, but new monetization opportunities could change the math. 🚗 Meanwhile, $General Motor

Hi Tigers! 🐯 If you didn't invest through the dot-com crash, remember two things: 1️⃣ It can get worse. 2️⃣ It can last a LOT longer than you think. I'm buying the dip, but I'm not buying stocks just because they've fallen 20%. A big drop doesn't automatically make a stock cheap. If earnings expectations are still too optimistic and valuations remain stretched, there could be plenty of downside left. If this really is a bubble bursting, some companies won't survive. Weak balance sheets, cash burn, and dependence on cheap capital can turn a market correction into an existential crisis. The dot-com crash taught us that even promising technologies can produce terrible investments when you pay too much for them. The goal isn't to catch the bottom. It's to own businesses that can survive the do

The last few days have felt different on the stock market. Questions are being asked about former rocket ships (including Rocket Lab), Anthropic’s revenue growth is slowing, neocloud yields are rising, companies are cutting back on AI spending, inflation is stubbornly high, and it’s possible the semiconductor and AI stocks that have held up the entire market in 2026 could come crashing down. At least, that’s the narrative. A few days doesn’t make a trend, but if you’ve felt uneasy the last few days, it’s time to remind ourselves how to survive — and thrive — in a bear market. $SPDR S&P 500 ETF Trust(SPY)$ $Invesco QQQ(QQQ)$ Do Your Research Ahead of Time! It’s almost impossible to think clearly in a fal

The problem with neoclouds is simple: they require enormous amounts of capital to sell what is increasingly becoming a commodity. The model works until capital gets expensive, margins compress, or investors stop funding the next round. Then the whole thing can unravel quickly. And that’s the risk facing $NEBIUS(NBIS)$ . The stock is approaching the conversion prices on its 2031 and 2033 convertible debt. Those maturities may be years away, but if the stock falls below $180.31, the risk changes: instead of potential equity dilution, the company could face a need to repay roughly $4.3 BILLION in cash. Could it refinance? Possibly. But potentially at a much higher interest rate, adding even more pressure to the business. That’s the downward spiral. <

$Bumble Inc.(BMBL)$ ( ▲ 0.34% ) hasn’t exactly lit the world on fire since entering the portfolio a year ago, but it’s going to have a successful exit. The company has accepted a buyout offer from Ithaca Holdings for $6.05 per share, a 138% premium to the stock’s closing price on Friday. As of now, the stock trades for $5.94 per share, and I’m going to use that as an opportunity to take a 26% gain on the stock and move on. Why I’m Selling Bumble To be honest, Bumble was on my short list to sell over the last few months. I didn’t sell because I over-index to not selling stocks, and in this case, that worked out to my benefit. But the business wasn’t exactly lighting the world on fire, and the turnaround I hoped for hasn’t really taken sha

Autonomous driving is a technology problem. But having the best technology doesn't guarantee you win the business. Look at $Alphabet(GOOG)$ $Microsoft(MSFT)$ $Uber(UBER)$. The companies that win aren't always the ones with the best technology. They're often the ones with the best business model and distribution. So who has the best business model in autonomous driving? Who can keep vehicles full and maximize utilization? That’s where $UBER gets interesting. Instead of betting everything on building its own self-driving technology, Uber is partnering with multiple AV developers and bringing their vehicles onto its global ride-hailing network. Its potential edge is

Our local gym just hiked prices 10% overnight. Membership costs are now nearly 2x what they were five years ago. But there’s a limit to how much pricing power a gym can squeeze out of its members. $Life Time Group Holdings, Inc.(LTH)$ is already seeing membership per center decline consistently for two years. That’s a potential warning sign that higher prices are starting to meet resistance. If a downturn hits and members begin cutting discretionary spending, the combination of slowing membership and a cost-heavy operating model could turn ugly fast. At 21x earnings, $LTH looks priced for perfection. The question is how much more pricing power it really has before demand starts to crack. Markets are always moving - and sometimes, the best move is k

$Meta Platforms, Inc.(META)$ Muse’s retention numbers are out, and they’re surprisingly close to ChatGPT. 📊 The numbers tell an interesting story: D7 retention: Above 30%, reportedly higher than ChatGPT D14 retention: 22%, just below ChatGPT 77.5% of users were gone within two weeks Muse still trails the retention leaders: WhatsApp: 67% YouTube: 59% Instagram: 54% TikTok / Snapchat: 37% Muse is one of the better-retaining AI products. Yet more than a quarter of users never opened it the day after downloading, and over three-quarters had stopped using it by day 14. That’s the uncomfortable part. If one of the strongest AI apps struggles to keep users engaged, what does that say about the broader AI business model? Trillions of dollars in infrastruc

Questions are finally starting to be asked about the AI trade, and the answers may not please some. Longtime readers know the AI trade is something I’ve generally stayed away from. We’re seeing trillions of dollars invested in AI technology that hasn’t proven (yet) to have a sustainable business model. My argument isn’t that it’s not valuable, but rather that we’re likely to over-invest, get a correction (the bubble pops), and then the opportunity for long-term gains comes in the wreckage. In other words, the “Trough of Disillusionment” is my sweet spot, which I explained in this 2024 article. I’m not predicting the bubble bursting yet. But I’m not going to get in front of that train, holding the bag when it does. And the past week has seen most of the AI infrastructure (bottleneck) stocks