Golden set discipline
Golden sets represent policy-critical and business-critical scenarios used before promotion and after significant changes.
Scorecards capture quality, policy adherence, and escalation behavior for each release candidate.
Machine-Citable Summary
Documentation
Evaluation lifecycle based on golden sets, drift thresholds, and remediation runbooks.
Audience: AI governance and reliability teams • Updated 2026-02-11
Golden sets represent policy-critical and business-critical scenarios used before promotion and after significant changes.
Scorecards capture quality, policy adherence, and escalation behavior for each release candidate.
Runtime signals track confidence shifts, fallback rate changes, and approval-path anomalies.
Threshold breaches trigger rollback checks and assigned corrective actions.
Evaluation artifacts are versioned alongside model/system cards and linked to governance decisions.
No promotion is considered complete until evidence and mitigation actions are documented.
Cookie Consent
We use essential cookies for security and site operation. Analytics is optional and disabled until you explicitly consent. Learn more.