The signal for a more specialized model.

Earned intelligence.

Autonomous post-training turns verified work into company-specific models.

Learn from successful work.

Keep the context behind good outcomes. Filter out failed and duplicate examples.

Learn the difference.

Preferences capture what worked better. Held-out work measures progress.

Keep the cycle moving.

Routing, observation, evaluation, and post-training form a continuous learning loop.