What This Looks Like
A policy, rule, standard, guideline, rubric, or instruction has been updated, but the AI output still reflects the older version. The user may see outdated language, old thresholds, prior approval rules, obsolete categories, or earlier workflow requirements appear after the update should have taken effect.
Why It Matters
Policy updates are only useful if they change the outputs they are supposed to govern. When AI output continues to follow an older policy, users may believe the current policy is being applied when it is not. This creates audit, compliance, and operational risk, especially when the old and new policies lead to different decisions.
Structural Signal
The declared governing rule has changed, but the generated output is still governed by a prior rule state. The issue is not just that the answer is outdated; it is that policy version and output behavior are no longer aligned.
Common Triggers
- The model or workflow still has old policy text in context
- Documentation updates before prompts, tools, or retrieval sources are updated
- The AI retrieves an older policy version
- Cached examples preserve obsolete policy behavior
- The workflow does not declare which policy version is authoritative
- Updated policy is available but not connected to the current task
When to Use This Issue
Use this Issue when a policy or rule has changed and the AI output still follows the older policy state.
When Not to Use This Issue
Do not use this Issue when the policy is merely unclear or when the AI violates a policy that has not changed. Use this Issue when the update itself is central: the output fails to reflect the new governing rule.