Why AI Pilots Never Reach Production
The demo worked. The team still cannot explain what changes on Monday, who owns the exception cases, or what evidence would justify keeping the system.
The recognizable symptom
A pilot produces a persuasive example but no operating contract. The next step becomes another demo, another prompt revision, or another request for more data. Confidence rises while adoption stays at zero.
The mechanism underneath
Most pilots optimize the model response instead of the decision loop. There is no named user, no baseline, no review budget, and no stop rule. Without those, success cannot survive contact with ordinary work.
What we built to contain it
We freeze the question before the experiment: what decision is changing, what counts as a useful output, who reviews it, and what would make us stop? The artifact is a receipt-backed continue, redesign, pause, or stop decision—not a prettier demo.
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