Hi everyone,
I’ve been analyzing the performance challenges, high token costs, and memory overhead caused by excessively long AI chat histories. I would like to propose a hybrid architectural concept to address this:
Hybrid AI-Driven Auto-Pruning (Reducing Cognitive Load): Instead of manually managing text or risking total context loss, the system intelligently suggests low-priority text or redundant parts for pruning based on relevance. The user just gets a quick, clean prompt to approve, avoiding any manual burden.
Unified File-Cache Storage (Solving Synchronization Complexity): To avoid RAM synchronization issues and cache fragmentation, core ideas and key summaries are stored directly within the chat’s designated file/folder structure rather than separate volatile caches.
Safety Mechanism: A mandatory 10-second “Undo” window whenever pruning actions are executed, giving users total control and peace of mind.
From a software and UX architecture perspective, how efficient do you think this hybrid approach would be for scaling long conversational contexts? I’d love to hear your technical feedback!