Release System detail
AI release metrics track whether the release path is getting more dependable: readiness, evaluation pass rate, route accuracy, intervention rate, approval latency, incident rate, rollback rate, time to release, cost per successful workflow, and learning-loop closure.
Plain-language definition
AI release metrics track whether the release path is getting more dependable: readiness, evaluation pass rate, route accuracy, intervention rate, approval latency, incident rate, rollback rate, time to release, cost per successful workflow, and learning-loop closure.
Example before the midpoint
| Field | Example |
|---|---|
| Readiness | Workflows meeting ownership, evaluation, and support criteria. |
| Route accuracy | AI actions routed to the correct class. |
| Intervention rate | How often people must step in and why. |
| Incident and rollback | Escapes, severity, recovery, and rollback behavior. |
| Learning-loop closure | Production findings converted into updates. |
Failure modes
Activity hides whether the workflow is closer to dependable use.
Leadership misses risk pockets that should block or change release.
Faster release increases operating burden without showing whether reliability improved.
Claims outrun evidence and make learning harder.
Measures of effectiveness