How to Decide Whether an AI Workflow Ships, Changes, or Stops

A useful eval begins with the decision the team has to defend. Ship, revise, and stop are different decisions, so they need different evidence thresholds.

A shipping decision needs blockers, warnings, and acceptable residual risk. A revision decision needs a narrow failure explanation and a likely owner. A stop decision needs enough evidence to show that more prompt work is not the next responsible step.

Unsafe actions, missing escalation paths, unreproducible critical failures, and regressions in high-value tasks should become blockers.

A weak score movement without a reproducible failure should not dominate the decision. Treat it as a prompt for investigation, not as the conclusion.

The decision should leave behind an evaluation plan, replay rows, failure taxonomy, release-gate checklist, and a memo that explains the evidence.

That artifact set matters because the next candidate workflow will otherwise restart the same argument with different anecdotes.