I’ve identified a flaw in how memory is being logged within ChatGPT’s memory system. It appears that transient debug logs, error tracebacks, and AWS errors are being stored as permanent memories. Additionally, my own celebratory responses when something works are being logged as memories, causing unnecessary memory bloat.
The Issue:
Debug errors and tracebacks (which should be momentary) are being stored as long-term memory.
Iterative improvements I acknowledge (“This works better!”) are also saved, wasting memory allocation.
Memory fills up too fast, affecting reasoning quality and causing processing slowdowns.
The Fix:
ChatGPT’s memory should only log:
High-level insights & preferences (e.g., debugging style, reasoning patterns).
Technical configurations (e.g., AWS setup, preferred workflows).
Long-term improvements & structured workflow changes.
It should NOT log:
Error messages, stack traces, or transient failures.
Repetitive acknowledgments (“This works now!”).
Momentary debugging details that change every session.
This issue artificially reduces reasoning capacity as memory bloats with unnecessary data. Please refine what gets stored as long-term memory to enhance iterative development and efficiency.
Thank you for considering this fix. Looking forward to improvements!