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US.Day.Ahead-2026.08.10-Mon.pdf

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🐳 WhalePool Traders Journal

2008 vs 2026: The Same Dominoes Are Falling and it is created by The #JayMartin Show

The machine that broke the economy in 2008 has been rebuilt — and this time it's made of AI. Jay breaks down the $2 trillion in promised future payments that Microsoft, Oracle, Google and Amazon are counting as guaranteed revenue, why those promises come from companies that lose billions every year, and how the same structure powered the housing bubble — which actually died in 2006, while prices were still at record highs. He explains why a nearly free Chinese AI model is now attacking the growth that holds the whole thing up, why Washington's proposed ban could make it worse, and the one number that signals when the machine starts to break.

0:00 The Largest Funding Round in History
1:36 Everybody Remembers 2008. Nobody Remembers 2006
2:31 The Loan That Was Never Meant to Be Repaid
3:41 8% Instead of 15%
5:44 The Machine, Rebuilt
8:05 Take or Pay
9:37 Borrowing Against a Promise
11:30 Thirty Years of Dismissed Dominoes
12:39 Kimi K3
14:48 The Catfish Effect, Run Backwards
16:38 The Third Borrower
18:21 The Stack
20:43 What I'm Not Saying
21:12 The 2006 Question
21:40 What You Can Actually Do
24:36 The Only Number That Ever Mattered

Copyright © 2026 Cambridge House International Inc. All rights reserved.

SUMMARY

This video argues that the modern artificial intelligence industry is built on a financial structure eerily similar to the one that caused the 2008 housing bubble, warning that a potential collapse could follow a similar pattern.

Key Takeaways

The Rebuilt Machine: The host explains that OpenAI, Microsoft, Oracle, Google, and Amazon are counting on over $2 trillion in promised future payments (often from profitless AI companies) to justify massive infrastructure spending. He compares this to the "2-and-28" mortgage model of the early 2000s, where loans were never meant to be repaid but were instead refinanced against rising property values (3:31-5:44).

The 2006 Lesson: The real estate bubble didn't burst when prices crashed, but in 2006 when price growth merely slowed down, making it impossible for borrowers to refinance their loans. The host emphasizes that we should not watch for a crash in AI, but rather for the moment when the speed of growth in AI valuations and revenue begins to falter (3:41-4:50, 20:47-21:12).

The China Factor: The recent release of the Kimi K3 model by Moonshot AI—which is highly capable and roughly 40% cheaper than American alternatives—poses a significant threat to the growth trajectory of American AI models. This competition could force a slowdown in revenue growth for US labs (12:20-13:47).

The Stacked Risks: The host warns that AI valuations support the S&P 500, which in turn supports global savings and the funding of U.S. government debt. If the AI growth narrative breaks, it could destabilize the broader financial system, including the U.S. Treasury market (18:21-20:18).

What to Watch

Construction Spending: Watch for the day a major tech giant announces it is cutting AI-related infrastructure spending and the market reacts positively, signaling that the "race" is over (22:20-22:40).

Funding Rounds: Monitor whether OpenAI's next valuation raise is smaller than the previous one, as this speed is the "collateral" holding the system together (14:01-14:17).

https://youtu.be/Zgbzdk-eqJ0?is=7pZBoK9shKr2CWk2

YouTube

2008 vs 2026: The Same Dominoes Are Falling

The machine that broke the economy in 2008 has been rebuilt — and this time it's made of AI. Jay breaks down the $2 trillion in promised future payments that Microsoft, Oracle, Google and Amazon are counting as guaranteed revenue, why those promises come…

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117 viewsedited 17:42