Paul Wilczewski

Kalshi founder on institutional adoption: "Block trades are already live on the platform...Right now a trade that we're seeing a lot is in the $20-30 million range for payroll hedging"

every professor I talk to that uses AI says the college system is about to collapse

Gundlach on private credit: > “Next big crisis in financial markets” > “Garbage lending” > “Only two prices: 100 or zero” 😂 His recommendation: 20% cash, stay away

Over 100 languages are spoken in our great city and it’s actually a pretty amazing part of being an American. If you are humiliated by America and the diversity that powers our nation’s Nobel Prizes, Olympic Gold Medals, and breakthrough innovations and culture, that’s on you.

To put a slightly finer point on this, our "most productive workers" are pretty much all able to live in NYC, SF, and LA. You can get a Studio or place with roommates for <$2000/month in almost every neighborhood of every US City That's affordable for a nurse at any downtown hospital The REAL crunch occurs if/when those workers want to move into the next stages in life: marriage ... and especially having kids. Unless you've joined the right startup, made huge gains in finance, or come from family money, many of these cities just aren't affordable for the long term Thus we have a situation, where a large portion of workers are forced to choose between delaying having kids and staying the City That's obviously a huge problem. For companies, for cities, and for people.

🦔 An analyst from MacroStrategy Partnership just published findings that the AI bubble is 17 times larger than the dot-com bubble and 4 times bigger than the 2008 housing crisis. Using economist Knut Wicksell's analysis methods, Julien Garran calculated the scale based on investment levels versus actual economic returns, revealing a bubble that dwarfs previous financial disasters. The Debt Connection We Missed While many assumed AI companies were growing through equity financing, making the bubble isolated from the broader economy, Goldman Sachs found that $141 billion of this year's $500 billion AI capital expenditure came from corporate debt. That's more debt than the entire industry spent in all of 2024, meaning at least 30% of current spending is debt-financed. The Hidden Leverage Problem Companies are increasingly using Special Purpose Vehicles to raise debt off their books, making the true leverage impossible to calculate. Meta alone is looking to raise $26 billion in debt through an SPV by year-end, representing 5% of the industry's total annual capital expenditure in just one deal from one company. Why This Matters More Than 2008 The 2008 crash devastated the global economy through debt interconnections, causing 27 million job losses worldwide and triggering a suicide spike. But that bubble developed over years while this AI bubble has grown faster and larger, with debt connecting it directly to major banks, pension funds, and the broader loan market. My Take This analysis continues to confirm my concerns about circular financing and impossible economics in AI, but the scale is more severe than I anticipated. When an industry burning hundreds of billions annually while generating minimal profits is funded through hidden debt structures, it creates systemic risks that extend far beyond tech companies. The combination of unrealistic revenue projections, massive infrastructure costs, and leveraged financing creates conditions for a financial disaster that could make 2008 look manageable by comparison. Hedgie🤗

Campbells Tomato Soup. When money dies.