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The Liquidity Trap of Capability

The AI-era analog of Keynes's liquidity trap — an economy saturated with productive capability that cannot convert the capability into value because the bottleneck has shifted from capacity to judgment.
In Keynes's original liquidity trap, the economy was flooded with cheap money that could not be converted into investment because firms could not identify investments worth making. Adding more liquidity to the saturated system was, as Keynes observed, like pushing on a string. The AI economy of 2026 has entered an analogous trap operating not on financial capital but on productive capability. The capability is abundant. AI tools have multiplied productive capacity by factors that cluster around the extraordinary. And yet organizations discover, with increasing frequency, that the additional capability does not automatically translate into additional value — because the bottleneck has migrated from production to direction.
The Liquidity Trap of Capability
The Liquidity Trap of Capability

In The You On AI Field Guide

Keynes's original concept described the limit case of monetary policy. When interest rates approach zero and expectations collapse, further monetary expansion produces no additional investment because the constraint is not the cost of money but the absence of profitable projects. The Bank of

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