Even if cognitive work becomes cheap, will housing, energy, regulation, physical production, and institutional capacity limit growth?
Baumol's cost disease, inverted: growth is set by the sectors AI can't accelerate, not the ones it can. The strongest skeptical case catalogues the physical, regulatory, and institutional drags that cheap cognition doesn't remove.
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The constraint argument found its formal version: Kording and Marinescu's intelligence-saturation model, in which physical work complements cognition and caps returns to intelligence no matter how fast AI scales. Sector studies supplied the concrete cases — law, where regulation and adversarial dynamics keep capability from lowering prices.
You can't build a car with computation. You can't cook a meal with algorithms.
The intelligence-saturation argument for a general audience: cheap cognition yields bounded, not exponential, disruption.
Regulation, adversarial arms races, and required human process time keep capability gains from lowering prices in a major service sector.
Slow-adapting institutional sectors hold growth near 2.5%; status adjustment, not joblessness, is the central problem.