Memory & Context
Problems where task state, prior instructions, saved memory, restored context, stale information, or cross-task context affects behavior incorrectly.
Primary Issues
- AI Forgets Earlier Constraints
A constraint, instruction, preference, or decision that should persist through the task stops affecting later output.
- Task Progress Is Lost Midway
The AI loses track of completed work, prior decisions, current position, or remaining steps before the task is finished.
- Context Changes After Restore
Restoring, reopening, resuming, or reloading a task changes the context that the AI uses to continue the work.
- Context Leaks Between Tasks
Context, assumptions, constraints, examples, files, or decisions from one task affect another task where they should not apply.
- Saved Memory Not Used
A saved memory, preference, instruction, or durable context item exists but does not affect the AI output when it should.
- Stale Context Affects Output
Old context, prior instructions, outdated references, or earlier task state continue to affect output after they should no longer apply.
- AI Memory Has No Governance
Saved or persistent AI memory affects output without clear rules for ownership, scope, review, update, expiry, or removal.
- AI Memory Updated Without Asking
AI memory, saved context, preference, or durable state is updated without the user clearly asking for or approving that update.
Also Related Issues
No cross-listed issues in this category.
Ontology Metadata
- Code
CAT-0020- Version
CAT-0020@0.1.0- Ontology release
- 0.1.0
- Updated
- 2026-05-10T00:00:00Z
History
No public history entries recorded.