Your AI agent did not fail because the model was weak.

It failed because it made a decision no one had authorized it to make.

Maybe it skipped an escalation.

Maybe it treated a missing requirement as obvious.

Maybe it chose one tradeoff over another because a threshold told it to.

The dangerous part is not that the AI made a mistake.

The dangerous part is that the system allowed the decision to happen invisibly.

This is not a tooling problem. It is a definition problem.

What AI Actually Is

Before designing any harness, we need to agree on what we are harnessing.

My working definition:

AI is a machine that executes the work of structuring information according to a given purpose.

Two constraints follow immediately from this definition:

Purpose is supplied externally. AI does not generate its own goals. A car does not decide where to go. AI does not decide what to optimize for.

Structuring information is not the same as making judgments. A car can move faster than a human.…