Christian Catalini’s central argument is that AI is commoditizing intelligence itself, so the traditional sources of competitive advantage (“moats”) are becoming much less durable. Instead, the scarce resource shifts from *generating answers* to *verifying which answers are actually correct*.

So what is actually left? Today’s guest has spent his career answering that question with models rather than vibes. Christian Catalini co-founded Lightspark, co-created Libra at Meta, founded the MIT Cryptoeconomics Lab, and is a Research Associate and Senior Lecturer at MIT. His answer is uncomfortable and, I think, correct: most of the network effects we treat as permanent are far weaker than they look, and exactly one kind gets stronger every time the models improve. He calls it a verification-grade network effect, and if he is right about it, the money in this industry lands somewhere very different from where most of us are pointing.

I will stay out of the way and let the work speak for itself.

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