OpenAI's GPT-6 Astra is days old, so Graham and Debs put it straight to work against Claude Fable 5.1 on a real job: write a private credit memo for the same hospital deal Claude analyzed from the equity side last week. Same document, same prompt, live on screen, with Astra still generating when the recording started.
The two models read the deal completely differently. Astra proposed $155M of sponsor equity to fund future cash burn and a tiny $4M revolver, a credit memo in form with no actual credit in it.
Fable went the other way: a $30M term loan, an undrawn ABL revolver and a delayed draw term loan, a classic private credit structure for a business where CapEx is outpacing EBITDA.
One of them is arguably overlevering the deal and the other is arguably underlevering it, and neither explained the one thing that might justify a loan here at all, the hard asset value of the hospital real estate.
That gap becomes the lesson. Graham walks through how a credit investor actually thinks: your upside is capped at a contractual return, so the whole discipline is downside protection, and at a 1.3x gross underwrite it only takes a few losses to wreck a fund.
The pair dig into the EBITDA bridge ($4.5M actual to $9M normalized, with the usual sell-side aggressiveness in between), why cash flow and not EBITDA is what a lender lives on, how structure prices perceived risk, and why even a lender's memo should show the sponsor's equity returns, because deals only get done when they work for everyone. Both AI memos missed that too.
Topics covered:
→ Fable 5.1 and GPT-6 Astra writing the same private credit memo, live → Two wildly different structures for one deal → Why neither model spotted the real estate lending angle → How credit investors think: capped upside, downside protection → The EBITDA bridge and why cash is what lenders care about → Structuring around risk: leverage, pricing and protections → Why credit memos still show equity returns → Which model you should trust (neither, yet)
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