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I study the gap between what's being sold about AI and what's actually happening.

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Everyone's screaming "AI bubble is bursting!" — pointing at Nvidia's inventory piling up. But they're reading the data wrong. I mapped the entire AI money chain and found something the headlines missed: the chips aren't sitting idle because nobody wants them. There's literally nowhere to put them yet.

In this episode, I:

- Break down the AI economy into 3 simple buckets (upstream, midstream, downstream)

- Explain why your neighbor using ChatGPT tells you NOTHING about bubble risk

- Show two competing theories for Nvidia's inventory buildup

- Reveal why Oracle's credit crisis is an Oracle problem, not an AI problem

- Expose the ONE indicator that actually predicts whether AI spending collapses

- Share what I'm personally doing with this information (spoiler: sitting it out)

This is a collaboration with my partner Klaas, a veteran CTO with deep macro economy expertise. Klaas's LinkedIn: https://www.linkedin.com/in/klaasardinois/

📖 Full article with data & sources: https://www.2ndorderthinkers.com/p/why-is-ai-bubble-not-popping-yet

⏰ TIMESTAMPS: 00:00 - Why people can't wait for the crash 00:46 - Who I am 01:13 - The wrong question everyone asks 02:50 - Who's actually spending the money? 03:05 - The restaurant supply chain analogy 03:34 - Upstream: Nvidia (the farmers) 05:05 - Midstream: CoreWeave & Oracle (the dangerous middle) 07:04 - Downstream: Hyperscalers (AWS, Azure, Google, Meta) 08:16 - Theory A: Demand is falling 09:54 - Theory B: The buildings aren't ready 11:46 - The Oracle wrinkle: AI problem or Oracle problem? 13:12 - The ONE indicator you should watch 14:36 - What I'm doing with this information 15:05 - Outro

👍 If this clarified the AI bubble debate:

Subscribe: More myth-busting on AI hype vs. reality!

Comment: Do YOU think the hyperscalers will keep spending? What's your read?

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