This isn't an opinion. It's mathematics.
Three theorems explain why agents drift, why scores lie, and why gates are the only fix. Each one is interactive. Move the sliders. Watch the failure appear.
Theorem I: Regressional Goodhart
Selecting on a score selects the noise.
If score = quality + noise, the top of the score distribution is systematically overrated. Regression to the mean, weaponized by the optimizer.
The agent's top 25 picks
What the score claims
2.30
What quality actually is
1.37
Overrating gap: 0.93
The harder the agent optimizes a noisy score, the more it selects the noise. The TI Layer's answer: shrink the noise first. Coverage before score.
An agent without a TI Layer optimizes your metric.
An agent with one optimizes your outcome.