Every week, Kristen and Jen (best friends since the second grade) have smart, funny. and honest conversations about investing, tech, and business. From Princeton and Brown to Morgan Stanley, as former investment bankers turned entrepreneurs and podcasters, Kristen and Jen take the most complex deals, market moves, and tech breakthroughs and distill them into stories you care about.
From conversations with the biggest names in investing to deep dives people can’t stop sharing --- not to mention the occasional HBO Industry red carpet --- this is the show Wall Street is obsessed with.
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Anthropic's S-1 Explained: Everything You Need to Know
mercredi 28 octobre 2026 • Durée 31:35
Anthropic’s S-1 is finally public, giving investors their first real look under the hood of one of the most anticipated IPOs in years. We dig into the numbers behind the rumored $2 trillion valuation, Anthropic’s growth and profitability story, its massive AI compute commitments, and what the filing actually tells us about the economics of the business.
But some of the most interesting details aren’t sitting neatly on the balance sheet. We break down the nearly $800 billion of disclosed commitments tied to compute and infrastructure, why Anthropic may need the public markets more than people realize, and the very unusual assumptions investors may have to make to justify a valuation this large. Plus, we get into what the S-1 still doesn’t tell us, and the numbers we’re watching as Anthropic gets closer to an IPO.
Then we zoom out to what Anthropic’s IPO tells us about the broader AI trade: the neocloud selloff, CoreWeave, Meta’s latest capital-raising strategy, and the extraordinary amount of money required to fund the AI buildout. And because we can’t help ourselves, we get into Anthropic’s unusual share classes, the ticker $ANT, and why Instagram’s latest moves might tell us something much bigger about where Meta thinks the value of content really lies.
02:00 How Do You Value Anthropic at $2 Trillion?
03:00 Anthropic’s Business Model Is Changing
04:00 The Strange Metric Anthropic Wants Investors to Use
05:00 The Nearly $800 Billion Question
08:00 The AI & Neocloud Meltdown
10:00 Why Anthropic May NEED This IPO
11:00 Meta Is Raising Even More Money for AI
13:00 Anthropic’s Very Unusual Share Structure
15:00 Why Anthropic Chose the Ticker $ANT
17:00 Meta’s Latest Instagram Move
18:00 Is Content Creation Basically an MLM?
20:00 Why YouTube Pays and Instagram Doesn’t
22:00 The TikTokification of Instagram
24:00 How Social Media Algorithms Hook Creators
26:00 Want to See Someone’s Instagram? Unfollow Them
28:00 The Real Reason Meta Wants More Content
"You Can See Everything" EXPLAINED: Were We All Just Willing Participants in a Social Experiment?
samedi 24 octobre 2026 • Durée 01:10:19
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Nathan Fielder’s You Can See Everything is the most talked-about documentary of the year, and after sitting through all three hours of it (there is exactly one acceptable bathroom break, and we tell you when), we came out more divided than when we went in. The film asks us to decide who Elizabeth Holmes actually is: a liar who knew the truth and deceived people anyway, a woman who lied to herself so thoroughly she no longer knows the difference, or a useful idiot who has been handed from one controlling man to the next. One of us walked in firmly in the second camp. The other changed her mind three times before breakfast. So we start by asking whether those are even the right three options.
To get there, we recap what Theranos actually was: the Enron connection, the Stanford dean who never bought it, Rupert Murdoch’s $125 million, the Pfizer logos pasted onto “independent” reports, and the diluted blood samples telling Walgreens customers they’d had miscarriages they hadn’t had. Then we walk through what Fielder does with it, and why the second half of the movie turns into something closer to a heist. Why does Amanda Seyfried go from hired reenactor to wanting to break up a relationship? What does Billy Evans have power of attorney over, and why does he carry a gun? Did Elizabeth know her boyfriend had negotiated a cut of the documentary when she looked into the camera and said she had no economic upside? And when two people watch the same scene of Nathan Fielder asking a convicted fraudster about the word “can,” how do they come away with opposite conclusions about whether she’s being literal or being clever?
That last question is where the two of us really split. One of us has known the other since age seven and has some things to say about how literal minds actually work, including a detour through medevac helicopters, SEC testimony, and whether a woman who quotes Yoda in her interviews gets to claim she doesn’t understand figurative language. The other wants to know why Adam Neumann, Elon Musk, and half of Silicon Valley never saw the inside of a courtroom for the same fake-it-till-you-make-it playbook. Is Elizabeth Holmes a mastermind, a product of the zero-rate era, or just the one who got caught? And after three hours of getting closer to her than anyone ever has, do we know more about her than we did before, or less?
Timestamps
0:00 We’re in costume2:00 The three ways to judge Elizabeth Holmes2:50 Where we each land going in5:30 Theranos recap: the Enron dad, Stanford, the pivot9:00 Murdoch, the Waltons, and the $9 billion valuation11:00 The voice, the turtleneck, and fundraising as a woman14:40 No diligence: fake Pfizer reports, diluted blood, Walgreens16:50 The whistleblowers and what she was actually convicted of20:20 The documentary, part one: the month before prison and Billy Evans24:30 The economic upside question: did she know?27:00 Amanda Seyfried joins and wants to break them up29:30 Confronting Billy: power of attorney, the X account, the rage30:30 The kids, and whether we’re being manipulated31:50 Dead man switches and a gun33:30 From The Rehearsal to the reenactment35:20 The prison visit: two questions37:00 Did Nathan fall for her?39:20 Three things at the end: the contract, the swim, the New York Times quote42:00 Why Billy? Rich versus wealthy45:40 Does she believe her own lies? Who’s on first50:30 Figurative language and the medevac helicopter testimony56:30 Why Nathan Fielder? The “you picked me because I’m incompetent” confession59:30 Will the public give her a second chance?1:02:30 Is she any different from the rest of Silicon Valley?1:04:50 Where we actually agree1:06:40 ZIRP, AI promises, and what everybody does1:08:00 Do we know less than when we started?
AI Stocks Just Tanked. Why Is Wall Street Talking About Enron?
jeudi 15 octobre 2026 • Durée 01:01:44
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0:00 Why Enron matters for the AI conversation right now
5:00 Origins: the gas bank, Lay, Skilling, and Fastow
9:00 Mark-to-market accounting and booking 20 years of profit on day one
13:00 Growth targets, exec comp, and regulated vs deregulated energy
15:00 SPEs, the 3% rule, and Fastow's LJM
19:00 Circular earnings: the dark fiber swap and disguised loans
24:00 Earnings games, leverage ratios, and why cash flow matters
28:00 Every deal was a stinker (and Netflix before Netflix)
29:00 The collapse: Chanos, debt puts, the commercial paper run, Dynegy
35:00 Broadband, Blockbuster, and the $8 business valued at $60 billion
38:00 The fake trading floor
40:00 Take-or-pay, leases, and off-balance-sheet debt in AI today
44:00 Meta's Project Hyperion and thinking about risk holistically
50:00 Accounting is imperfect: pensions, EPS maximizers, and the AI lesson
55:00 California, the Raptors, Arthur Andersen, and who called it
Why is Enron suddenly back in the conversation about AI? This week, we revisit The "Smartest Guys in the Room" to unpack what actually happened in the Enron scandal. While there are some similarities, a lot is different. Enron hid debt, manufactured earnings, and convinced Wall Street to buy a story that even many professional investors couldn’t explain. From a fake trading floor to financial structures backed by its own stock, we break down what actually happened behind one of the most infamous corporate collapses in history.
Then we turn to the financing behind today’s AI boom: off-balance-sheet obligations, circular financing, and the gap between reported earnings and actual cash flow. We dig into Meta’s Project Hyperion, the long-term commitments funding the data center build-out, and why a chipmaker booking revenue today while its customer spreads the cost over years matters when evaluating the boom. Along the way, we explain mark-to-market accounting, special purpose vehicles, and why “it’s not on the balance sheet” doesn’t mean “there’s no risk.”
To be clear, we’re not accusing today’s AI companies of Enron-style fraud. The point is understanding where the comparisons hold up, where they fall apart, and what investors should actually scrutinize. A technology can change the world without every company funding it earning a return. Revenue isn’t profit, profit isn’t cash flow, and a rising stock price isn’t proof that a business model works. Before you call something “the next Enron,” you need to understand the first one.
Also if you want to learn more about accounting, valuation, M&A etc. Kristen spent 13 years teaching this to analysts and associates at bulge bracket investment banks and business schools and then spend two years creating the most comprehensive course out there. https://www.thewallstreetskinny.com/investment-banking-private-equity-fundamentals
Use code: VIPCUSTOMER for 20% off
NEOCLOUDS EXPLAINED: Your ULTIMATE Guide to AI’s Least Understood Business
dimanche 11 octobre 2026 • Durée 35:57
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How do Bitcoin miners end up running the infrastructure behind AI? This week we break down neoclouds like CoreWeave, Nebius, and Lambda. What makes a neocloud different from AWS, Google Cloud, Azure, and the hyperscalers? Why were crypto miners, sitting on warehouses, power contracts, and a business model with a built-in expiration date, so well placed to pivot? And if these companies don’t have the cash flows of a Google or a Microsoft, how are they paying for billions of dollars of chips? We dig into chip-backed financing. How can a junk-rated company borrow against Microsoft’s AAA credit? Why are lenders comfortable with 95% advance rates? What happens when the compute contracts are only three to five years long and customers like OpenAI aren’t profitable yet?
Then we get to the NVIDIA of it all. NVIDIA invests in the neoclouds, backstops their unused capacity, and sells them the chips. Is that savvy, or is it circular financing? How does it compare with Lucent in the dot-com bust? What about the take-or-pay obligations that never show up on anyone’s balance sheet? Plus: OpenAI’s revenue miss, how media bias shaped the coverage, and whether Starbucks and Chipotle should merge (pumpkin spice burrito, anyone?).
0:00 Market-Moving Headlines: OpenAI’s Revenue Miss
3:27 Starbucks & Chipotle M&A
6:29 What Are Neoclouds?
9:12 From Crypto Miners to Neoclouds
13:40 Hyperscalers vs. Neoclouds
17:21 Chip-Backed Financing
23:30 The NVIDIA of It All
29:56 Circular Financing Risks
Is Anthropic's $2 Trillion IPO in Jeopardy? What We Learned from Leaked IPO Prospectus
jeudi 1 octobre 2026 • Durée 46:31
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We're back at the intersection of AI and high finance!
Anthropic is reportedly targeting a $2 trillion IPO valuation. So what did Reuters find when it got an early look at the S-1? Kristen, our resident investment banker, walks through the numbers: $4.6 billion in 2025 revenue, a $42 billion loss (and how much of it was an accounting charge on a convert), $20 billion in cash against a reported $518 billion compute plan, and a quarter of revenue coming from just two customers. Why don't those compute contracts show up as debt when the neoclouds on the other side are borrowing against them? And with open-weight models closing the gap, is it time to get nervous about this IPO?
Then we turn to the off switch. After a summer of OpenAI agents breaking out of the sandbox, a paused model, and a scrapped GPT-6.1 Astra release, who is actually reaching for the brakes? We cover Dario Amodei's "We Must Pace the Frontier" essay and the cynical read on it, the AI Kill Switch Act and the AI Emergency Button Act stalling in Congress, the executive order rebranding AI as "super intelligence," and the White House Accord on Super Intelligence, typo and all. And why did the industry name its newest products after the villains in The Matrix?
Finally, NVIDIA swore off kill switches in 2025, citing a 1993 government fiasco called the Clipper Chip. So why did it just announce a two-part system called OpenShell and Sentry, and what would it catch inside a private equity data room or on a trading desk? Can any guardrail keep up with something built to be smarter than us? Plus the trolley problem, Iain Banks' Culture series, and whether we should just give up and let the robots win. Make sure you're subscribed to our Substack so you don't miss our more in-depth coverage on these complex topics: https://substack.com/@thewallstreetskinny
How Nvidia's Recent Acquisition Changes the AI Game Feat. Morgan Stanley's Head of US Thematic Research
dimanche 27 septembre 2026 • Durée 59:43
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NVIDIA just agreed to buy Hugging Face, and the deal won't add a cent to its earnings per share. So why do it? In this episode we dig into what NVIDIA really gets from owning the home of open-weight AI, and whether this is a threat to OpenAI and Anthropic that the market hasn't priced in yet. What's the actual difference between open source and open weight, and why does almost everyone (yes, even us included) mix them up? If Amazon, Google, and the frontier labs are all building their own inference chips, where does NVIDIA's next wave of customers come from? And if the free "Temu version" of AI gets good enough for most people, who keeps paying for the Prada bag?
Then we bring on Michelle Weaver, Head of US Thematic Equity Research at Morgan Stanley, to ask the questions everyone in finance is worried about. Which companies are actually seeing AI show up in their margins, and which are just burning tokens so they can say "AI" on the earnings call? Is AI already showing up in the jobs data for young workers? What happens to the traditional Wall Street analyst class if the org chart stops being a pyramid? Does the Jevons Paradox of economic theory help or hurt the frontier model companies? And why are American companies nervous about building on Chinese open-weight models?
We also get into the growing fight over AI data centers. Why has this become one of the few issues uniting voters on both the left and the right? What do power bills, water use, and old brownfield sites have to do with it? How big is a 57-gigawatt power shortfall, really? And what does Oracle declaring force majeure on its New Mexico Stargate site tell us about where the AI build-out is headed?
00:00 Intro: Revisiting our early episodes
03:00 Life updates: Flying, dogs & kids
06:10 Our Yahoo Finance Market Hang recap
07:50 Why NVIDIA bought Hugging Face
11:10 Training vs. inference: Where AI compute is headed
14:15 CUDA and NVIDIA's software moat
15:50 Open source vs. open weight, explained
19:20 Is NVIDIA a threat to OpenAI & Anthropic?
21:25 Meta's Muse and why easy AI wins
25:00 Why companies struggle with AI adoption
27:20 Oracle's Stargate force majeure (Ground News)
28:45 Michelle Weaver joins: What is thematic research?
30:15 AI enablers vs. AI adopters
35:05 Open vs. closed models and Jevons paradox
37:25 The risks of Chinese open-weight models
39:45 Pricing security risk in AI adoption
42:15 Token budgets and the end of token maxing
44:00 Is AI already costing jobs?
46:55 What AI means for Wall Street analysts
49:25 Data centers: People, power & politics
53:00 Tax breaks, brownfields & state moratoriums
55:35 The 57-gigawatt power shortfall
57:35 US vs. China: Chips, power & the AI race
59:20 Where to find Michelle's research
Why Stocks Could Drop 10% Before Year-End: feat. Wellington Macro Strategist Mike Medeiros
vendredi 18 septembre 2026 • Durée 36:37
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The first Fed rate hike since the summer of 2023 hit today, and we went LIVE from New York City to cover it. Minutes after Chairman Warsh wrapped his press conference, we brought on Wellington's macro strategist Mike Medeiros to make sense of the 25bp hike, the unanimous vote, and a statement that leaned unmistakably hawkish.
We asked Mike everything we've been dying to know: Was this hike a nod to the political pressure campaign coming from President Trump, or would cutting in this environment have been, in his words, "clinically insane"? Are Warsh and Treasury Secretary Bessent working together or against each other, with the Fed pushing financial conditions tighter while Treasury intervenes in the long end? How does Treasury actually fund those interventions next year — bills, buybacks, or the TGA — and does the debt ceiling take one of those off the table? We also dug into what the hike means for the coming wave of corporate issuance financing the AI buildout, whether the midterms change the policy calculus, where positioning is most offsides, his S&P target for year-end, and what the death of forward guidance means for volatility in the front end of the curve. Plus: what nickname does Trump give "No Cut Kevin" now?
Thank you to our sponsor, Ground News — our go-to news aggregator for getting all the headlines moving markets in real time, gauging bias across the political spectrum, and seeing what's factually accurate reporting and what isn't. Go to https://groundnews.com/skinny to subscribe for 40% off their unlimited access Vantage subscription — whether you subscribe yourself or send it as a gift — and use our link so they know we sent you.
I got to ask Scott Bessent ONE QUESTION. His answer shocked me.
dimanche 6 septembre 2026 • Durée 57:13
Everyone in the financial media is telling you the same story: Scott Bessent's surprise Treasury buyback announcement is a thumb on the scale of the bond market, and it's making Kevin Warsh's job at the Fed harder. But what if the headlines have it exactly backwards? What if the Treasury Secretary is actually running interference for the one thing the Fed Chair can't do himself? Fresh off asking Bessent this question face-to-face at the Charlotte Economic Club, Jen breaks down why she thinks there's a stealth rate hike hiding inside what looks like yield suppression, and why the best way to understand it is a three-act magic trick straight out of The Prestige.
To get there, we have to answer the questions most coverage skips entirely. What actually happens at a quarterly refunding, and why does the Treasury auction schedule matter more than almost anyone realizes? What's the difference between an on-the-run and off-the-run bond, and why are aged long bonds from the COVID era trading below 50 cents on the dollar? When the Treasury buys back 30-year paper and funds it with T-bills and short-dated notes, is that QE, or is it something closer to the opposite? And why would Bessent make this move right before the AI hyperscalers flood the corporate bond market in September?
Then things get weirder. Why did the US just participate in the biggest coordinated yen intervention in decades, and what does it have to do with Japan's Treasury holdings? How do stablecoins, a resurgent crypto market, and a shaky dollar all fit into the same trade? And what do Bessent and Warsh, supposedly at war, have in common through their shared mentor Stan Druckenmiller, whose AI-generated op-ed became its own scandal?
Is a Private Credit scandal brewing behind the LA Lakers Sale?
mercredi 19 août 2026 • Durée 36:54
The LA Lakers --- a prestigious basketball franchise that didn't change hands for 46 years --- just sold twice in ten months, the second time for $2.5 billion more than the first. The seller is Mark Walter, CEO of Guggenheim, owner of the Dodgers and part of Chelsea FC, and the man whose laptop and phone the FBI seized off his private jet just as the Lakers deal was coming together. Since then, one of the insurance companies in his orbit has revised its reported related-party investments from $1.4 billion to $17 billion. Quite the rounding error.
In this episode, we get into the questions everyone on the Street is suddenly asking. Why would anyone sell the crown jewel of American sports a year after fighting to buy it? What do a bunch of boring life insurance companies most people have never heard of have to do with the trophy assets of the billionaire class? Why do private equity and private credit firms keep buying insurers in the first place — and what happens to that entire model when the disclosures around "related parties" turn out to be, let's say, incomplete? And why did Josh Kushner and Bob Iger, who spent months chasing a Las Vegas expansion team, pivot to the Lakers over a single weekend?
The bigger question hanging over all of it: this structure — asset managers selling their own loans to insurance companies they control — underpins a massive share of the boom in private credit. If regulators start pulling on this thread, how many other portfolios look like this one?
By way of disclaimer, no charges have been filed and no wrongdoing has been established nor is implied here; our research merely summarizes reporting from Bloomberg, the FT, the WSJ, and the LA Times.
OpenAI's Lawyer: How Big Tech is Winning the AI Race in the Courts
mercredi 12 août 2026 • Durée 51:10
We got to sit down with John Quinn — the "Quinn" of Quinn Emanuel — one of the most powerful litigators in the world, and the man whose firm is defending OpenAI right now. What does someone at the very top of the legal food chain see coming that the rest of us don't? And why does he think one of the oldest concepts in law is about to become the most valuable weapon in tech?
Here's what pulled us down this rabbit hole. The most valuable companies on earth are pouring hundreds of billions into inventions almost none of them can legally protect. So how do you build a moat around something you're not allowed to own? Why are Apple and OpenAI trying to destroy each other in one courtroom and sitting on the same side in another? And what does any of this have to do with a viral park bench kiss that blew up one of the big law talent poaching deals?
We get into all of it: why the patent wars fell by the wayside, what actually replaced them, and why every giant pay package in tech, finance, and now law is really a fight over the one thing no company can lock in a vault. Then John tells us where he thinks this is all headed — for the AI giants, for the lawyers, and for anyone thinking about the profession at all.
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