AI on Radical Optimist

AI’s Efficiency Trap: When Productivity Destroys Demand

Sat, 11 Apr 2026 00:00:00 +0000

This is the second piece in a series. The first, Marx Was Right About AI, examined the leverage knowledge workers hold over AI deployment — and why mission-driven organizations will capture the productivity gains that extractive ones cannot. This piece operates at a different scale: not the firm, but the monetary system. Not the leverage window, but what comes after it closes. The third piece, The Robustness Imperative, asks what kind of AI infrastructure serves workers, organizations, and states — rather than extracting from them.

Marx Was Right About AI

Sat, 21 Mar 2026 00:00:00 +0000

This is the first piece in a series. The second, The Efficiency Trap, examines what happens to the monetary system when the displacement described here runs to completion. The third, The Robustness Imperative, asks what kind of AI infrastructure serves workers, organizations, and states — rather than extracting from them.

For two centuries, the story of automation has followed a simple script. Capital invests in machines. Workers are displaced. The productivity gain flows upward. Repeat.

When Doing Stopped Being Learning

Wed, 18 Mar 2026 00:00:00 +0000

“What I cannot create, I do not understand.” — Richard Feynman¹

In the age of AI, every knowledge worker faces the same hidden trade-off: use the tool to produce, or use the tool to understand. You cannot fully do both. How you arbitrage that tension defines what you become.

I. When doing was learning

Before AI, the coupling was tight. To ship software, you had to understand it. There was no shortcut. Writing the code was the learning. Debugging was the understanding. The act of production and the act of comprehension were the same act.

The Fast Track to Incompetence

Fri, 13 Mar 2026 00:00:00 +0000

AI, the Peter’s Principle, and the rise of the Senior Operator

I. The principle, accelerated

In 1969, Laurence J. Peter observed that in any hierarchy, people rise until they reach their level of incompetence — promoted based on past performance until they land in a role their skills can’t support. [1] The ceiling was always there. It just took years to find.

AI has changed the timeline. As a capability amplifier — not a capability builder — it makes you faster and more productive at tasks you already understand. The ceiling stays exactly where it was. The elevator just got faster.