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The AI Pilot · № 18

Eval Designer

Created a rigorous evaluation framework for an AI task that others have adopted or cited.

The idea

Evals matter more than models in the long run. The kid who can rigorously evaluate AI output is more valuable than the kid who can fine-tune. Have them pick a task, define what good looks like, build a test set, document the methodology. If someone else adopts the eval and cites it, the eval was real. Most AI work fails at the eval, which is why we keep arguing about whether models got better.

Steps
  1. Pick a task. Define what good looks like.
  2. Build a test set: real examples, varied difficulty.
  3. Document the methodology reproducibly.
  4. Publish where others can find and use it.
What counts

A published evaluation framework adopted or cited by someone outside your family. The framework plus adoption record is plenty.