Problem
For users working on multi-session projects, it’s frustrating when ChatGPT forgets recent refinements, reverses prior logic, or loses track of critical constraints.
This is especially disruptive in:
- Complex code refactoring efforts
- Long-running database or infrastructure planning
- Documentation drafts and legacy capture
- Design systems that evolve across many iterations
Having to re-explain goals, context, and decisions repeatedly is both inefficient and error-prone.
Proposed Feature
Introduce a “Pinned Thread” or “Persistent Project Memory” capability with these characteristics:
- User-defined project scope (e.g., “GiftCardList component”, “Ops Schema Redesign”)
- Editable context summary pinned to the thread (like a README for the session)
- Explicit memory control — user can commit, override, or delete entries
- Memory persists across sessions until unpinned
This provides structure and continuity without relying on full recall of all messages.
Benefits
- Dramatically improves experience for power users and developers
- Reduces cognitive and conversational friction
- Prevents logic regression due to AI forgetting prior refinement
- Supports iterative design, code, and planning workflows
Optional Enhancements
- Memory Diff Log: Track changes to project memory over time
- Restore Point: Ability to roll back to a previous project state
- Named Pinned Memory: Multiple concurrent persistent threads (e.g., “Spa Manager”, “China Trip Prep”, “AI-Enhanced Backup System”)
Summary
This would bridge the gap between short-form, ephemeral chats and full long-term memory — enabling ChatGPT to function as a truly collaborative assistant for complex, ongoing tasks.
Submitted by:
MDD
(Full-stack developer, infrastructure designer, and long-term user of ChatGPT for real-world work)