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.…