🔮 Ten things I’m thinking about AI | Part 3

What happens when capital markets don't know exponentials

Hi all,

This is Part III of a four‑part, members‑only series Ten things I’m thinking about AI as we approach the third anniversary of ChatGPT.

The series connects the dots with a view to the past and to the future. From energy and depreciation schedules to capital markets and platform strategy, it’s a unified map for the next 24 months of AI – grounded, contrarian where needed, and practical. Here’s what we cover:

Part I: The Firm [read here, no paywall]

1. Enterprise adoption is hard and may be accelerating

2. Revenue is already growing like software

Part II: Physical limitations [read here]

3. The real scaling wall is energy

4. The inference training loop squeeze

Part III: The economic engine [today’s email]

5. Capital markets struggle with exponentials

6. Perhaps GPUs do last six years

7. Compute capacity is existential for companies

8. The “productivity clock” rings around 2026

Part IV: The macro view [coming up]

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Part 3: The economic engine