Eisman, Daniel & Collins on fiscal strain, gold, OpenAI’s economics and live shorts.
| Show | The Real Eisman Playbook |
| Episode | The Big Short Partners Reunite: Rates, AI, Gold and Two Stock Picks | The Real Eisman Playbook Ep 75 |
| Guest | Vincent Daniel, Porter Collins |
| Host | Steve Eisman |
| Published | 2026-09-14T16:06:00Z |
| Duration | 52 min |
| Fidelity | [partial] |
| Stance | NEUTRAL |
| Listen | Episode link |
Steve Eisman reunites with former Big Short partners Vincent Daniel and Porter Collins, who now run a long/short book anchored in gold. The conversation covers the fiscal bind facing the Treasury — deficits near 6–7% of GDP, interest plus entitlements around a tenth of tax receipts — and why the partners hold their highest-conviction precious-metals position in years. On AI, they walk through OpenAI’s deteriorating economics versus Anthropic, hyperscaler revenue concentration, enterprise cost deflation, and why forced lab IPOs could flood equity supply. The back half explains why shorting is structurally harder now, then works through two live shorts and two idiosyncratic longs. [partial: YouTube auto-captions; ASR artifacts possible]
I think I've had as much conviction in this precious metals trade as I've had in anything in a long, long time.
Why it matters: The conviction statement behind the episode’s gold thesis — highest in years.
I make this joke that whoever buys open AI at out of bankruptcy, it's going to be a fantastic deal
Why it matters: How far the OpenAI narrative has turned: bankruptcy is now a punchline, not unthinkable.
if all of a sudden open AI failed and the whole thing reversed the economy would go into recession almost immediately.
Why it matters: The macro-stakes claim — half of GDP growth is AI capex — stated plainly.
That's that's in 2000 in 1929. That's what killed the market was new supply of stock.
Why it matters: The supply-demand frame behind the forced-IPO warning on OpenAI and Anthropic.
proving that is going to be impossible. that has proven to be impossible for eight years.
Why it matters: The honest tell on the Carvana short: the thesis is right but the payoff needs a catalyst.
Priced in: Fiscal unease, gold’s long run, AI-capex concentration worries, and the difficulty of shorting crowded names are all consensus-adjacent; the episode confirms more than it discovers. Eisman himself pushes back on imminent fiscal doom, and Collins concedes the Carvana–Delaware Life link has been known to shorts for eight years.
What’s new: The concentration math is the variant datapoint — Nvidia’s 10-Q Note 7 puts 70% of accounts receivable with five direct customers; ~70% of hyperscaler AI revenue comes from Anthropic plus OpenAI, or 25–35% of total cloud revenue; and the quarterly split (Anthropic $11.5B, up 100%+; OpenAI $6.5B, up 18%, costs up $3B against revenue up $1B). The pod-leverage mechanics (5:1, 3–5% spread thresholds, weeks-long holding) quantify why squeezes keep happening. Carvana’s gain-on-sale arithmetic (109–110 average vs 102–104 from Ally) and the Delaware Life related-party jump (3% to 30–40%) are genuinely new to most readers, as is the Mr. X cost-deflation anecdote.
The bear case: OpenAI’s narrative could re-accelerate with a product or funding event, making the “in trouble” call look premature; gold is a crowded consensus long after a strong run; the Delaware Life/Carvana connection has been litigated for years without a payoff; FICO’s pricing may invite nothing more than noise; and Bessent’s twist program could pin long yields longer than skeptics expect.
Discount: The speakers are talking their book — long gold and idiosyncratic small caps, short FICO and Carvana (where they admit being squeezed). The Nvidia Note 7 point arrives via Ed Zitron (“Ed Zitron” in captions), an avowed AI bear, though Eisman says he verified it. The Mr. X anecdote is single-source, unaudited, and not for attribution. Auto-caption artifacts (names, percentages) mean any single figure should be checked against the primary source before use.
This is three professional short-sellers arguing that the two risks Graham tracks — fiscal sustainability and the AI buildout’s funding — are converging: a Treasury reduced to signaling games on rates, and an AI economy whose revenue is concentrated in two cash-burning labs while enterprises quietly deflate the unit economics. The episode’s value is in the specifics — the Note 7 concentration, the lab quarterly splits, the gain-on-sale arithmetic — and in the rare mechanics lesson on why fundamental shorts keep failing against levered pod capital. It is a positioning read, not a call: bearish on the fiscal path and on OpenAI’s funding, bullish on gold, idiosyncratic elsewhere.