The Wall Street Skinny

What took Situational Awareness from a $45bn hedge fund down to a $10bn hedge fund in less than a month? Two years ago Leopold Aschenbrenner was a researcher at OpenAI who wrote a 165-page essay about superintelligence. Since then, he raised $225 million seed funding from Stripe co-founders, Jane Street, and GitHub's CEO, which he proceeded to turn into an AI hedge fund called Situational Awareness worth about $45bn as of the beginning of July. He did this with no prior trading experience, 4-5x leverage on a concentrated bet in AI names. By Thursday the fund was down to about $10 billion. Neither Millennium nor Jane Street were willing to step in to catch a falling knife. Ultimately Citadel stepped in to buy the flagging portfolio.

Here is the crazy part though: Aschenbrenner wasn't wrong. He is reportedly still up around 80% on the year and "he only sold enough to cover his losses". But what caused a massive drop in the global markets was that a prime broker does not care what happens in 2030. And because half the market was crowded into the exact same names, his exit was everyone else's problem. SK Hynix and CoreWeave cratered. Korea's Kospi tripped circuit breakers. Over a million retail accounts got margin called. All of July's violence, the moves that had traders questioning their own sanity, was one book being taken apart in public. So the question this episode actually asks is whether this was one overlevered fund or the first crack in the AI trade itself. Because the market's answer this week was a shrug. Microsoft just posted the largest single-day market cap gain in history and credit spreads snapped back tighter, as if the whole thing was somebody else's accident. Kristen and Jen have both traded through cycles that ended this way, and they have seen exactly how comforting that shrug feels right before it stops being true.

*Note: This episode was recorded before news broke of Situational Awareness' unwind, which gives us much better insight into the pace and magnitude of the move in the Korean markets specifically.*

Chips, China, and credit. The three forces tearing through the AI trade right now, and we called it last week. In this episode we break down why the bond market cracked first, what widening credit spreads on Nvidia, Meta, and Oracle are actually telling you about default risk, and why the Nasdaq is bleeding while the S&P barely flinches. We walk through Alphabet's first negative free cash flow after twenty years of printing money, the CapEx numbers that keep getting revised upward, and the moment the market stopped rewarding spending and started punishing it. If you have ever wondered how to read a credit spread, we show you the math live.

Then we get into the China story that moved markets this week. CXMT went public in the largest mainland Chinese semiconductor IPO on record, oversubscribed 212 times, and the Korean stock exchange took the hit because the KOSPI is essentially a memory-chip index wearing a trench coat. We explain why memory matters in an AI data center, why Samsung, SK Hynix, and Micron controlling 90 percent of the market was the whole moat, and what reports of domestically produced DUV lithography machines would mean for US export controls. We also unpack Nvidia guaranteeing borrowing for a 10-gigawatt OpenAI data center in Ohio, and whether circular financing between chipmakers and model labs is clever structuring or an accounting Ouroboros.

Finally, the philosophical hangover. We react to Elon Musk's Economist interview and his claim that money stops mattering within a decade, pressure-test his deflationary argument against MV equals PQ, and ask why every science fiction author who ever imagined artificial superintelligence wrote a horror story. Plus Anthropic's positioning ahead of a possible IPO, the distillation and copyright fight with publishers, the rare books being unbound and shredded to feed training data, and where value actually accrues if models commoditize. Energy and molecules, or something else entirely. Subscribe for weekly deep dives on AI infrastructure, credit markets, semiconductors, and the money moving underneath the entire AI build-out.

Short interest in the S&P 500 is sitting near its highest level since 2010, Jamie Dimon says he won't touch US stocks or Treasuries at these prices, and SpaceX is the ninth-most-shorted stock in the market ahead of its very first earnings report. So this week we're asking: why is everyone so bearish when the market is up more than 15% from the March lows? What did Alphabet's first-ever negative free cash flow quarter reveal about the real cost of the AI buildout? And when the five biggest hyperscalers are planning to spend nearly as much as the US military in a single year, who's actually going to fund it — and at what price?

That last question took us straight to the bond market, where things look even scarier. Why are Meta, Oracle, and SpaceX's 30-year bonds trading 40-60 basis points wider just weeks after issuance? Why have 30-year Treasury yields held above 5.00% for the longest stretch in two decades — and is 5.00% the new floor instead of the ceiling? With a Fed meeting days away and Chairman Warsh's hawkish instincts colliding with the biggest negative CPI print since 2020, we dig into what the rates market is telling us about risk premiums across every asset class... and whether anyone wants to own anything right now.

We're talking about the buzziest --- and most controversial --- book of the summer: "Yesteryear" by Caro Claire Burke. It poses a question no one's brave enough to answer: are trad wives and career women fundamentally at odds? Or are they two sides of the same coin, minted by a bigger system that profits from their fight?

As two Wall Street veterans recently profiled in Bloomberg for our new career as "finance influencers", we HAD to talk about the novel everyone is calling "rage bait", and we've got quite a lot to say. Fair warning: we spoil everything, INCLUDING the plot twist that has readers and critics alike up in arms.

Why is a finance show covering a book about a trad wife influencer? The biggest names in this space, like Ballerina Farms and Nara Smith, are pulling in millions every year. The raw milk industry is a multi-billion dollar megalith expected to double in the next few years. And all of this is fueling a vertical of the creator economy that is growing in size (and scandals). What happens when a woman builds an empire by performing traditional acts of subservient domesticity on the most modern machine ever invented? We also turn the lens on ourselves, as moms, influencers, and educators --- where's the line between education and performance, and what responsibilities come along with influence?

Whether you loved this book, hated it, or refuse to read it on principle, we want to know what you think! Let us know in the comments...

With hyperscalers like Meta, Google, Amazon and SpaceXAI burning through cash, we decided to answer the question underneath all of it: what is this money actually buying?

In this episode we start high level with a primer on the AI ecosystem or what Nvidia's CEO Jensen Huang calls the "five-layer cake" of AI — energy, chips, infrastructure, models, applications. We get into the vocabulary everyone uses and nobody defines: what a hyperscaler actually is, how it differs from a frontier model company like OpenAI or Anthropic, why Oracle only plays in one layer while Google plays in all five, and what a NeoCloud like CoreWeave is really doing when it borrows against its own chips. Then we get into the grid — all three of them — including how power prices get set, the difference between regulated and deregulated states, why Meta's $200 billion Project Hyperion campus in Louisiana needs enough electricity to power half of Manhattan in the summer, and why the new rule for data centers is essentially "bring your own electrons." We also dig into the tax incentives driving the timing of all this spend, and why states are competing so ferociously for projects that employ almost no one once the construction crews go home.

Then we bring on an extra special guest: power expert. Ron Kelly, who spent 50 years in power and energy — as an engineer, at Calpine, and developing natural gas-fired power plants and solar plants all over the United States the country. He also happens to be Kristen's dad.

His take is bracing: he's seen this movie before. Between 1995 and 2005, roughly 300 gigawatts of power projects were announced on the promise of the internet. 168 got built, 130 were canceled, the rest died, and Enron, Mirant, NRG, and Calpine all ended up in Chapter 11. Today's data center pipeline is about the same 300 gigawatts. Ron explains risks that could complicate the build out necessary to get all the needed power infrastructure online: the interconnection studies, transformer backlogs — plus what he really thinks about the security of the largest machine humans have ever built.

Connect with Ron at / ronald-kelly-pe-mba-3587a718