Most AI pilots do not fail because the idea was wrong. They fail because nobody built the machinery that lets a probabilistic system run unattended in a workflow that matters. A demo proves the model can do the task once. Production proves it can do the task ten thousand times without a human catching every miss.
We treat the gap between the two as five gates: an eval suite that measures the thing you actually care about, observability so you can see failures as they happen, guardrails that contain the worst case, a rollback path for when a model or vendor changes under you, and a named owner who is accountable for the metric. Skip any one and the pilot stalls.
None of this is exotic. It is the same discipline that turned web demos into reliable software a decade ago, applied to a stack that happens to be non-deterministic. The companies stuck in pilot purgatory are not short on ambition. They are short on the gates.
