memory-tiering

Memory tiering organizes conversational context into HOT, WARM, and COLD memory tiers by automatically redistributing items based on recency and importance to optimize retrieval and prevent context overload.

Pruning and summarizing long-term memory archives involves aggressively removing transient details from COLD storage while creating concise summaries that retain essential milestones for long-term retrieval.

Credential reference hygiene during context compaction replaces raw secrets in HOT memory with secure references and runs verification checks to ensure no critical information is lost during reorganizations.

Automated memory tiering supports periodic context compaction workflows by reorganizing context after long interactive sessions, prioritizing upcoming tasks in HOT and archiving finished projects to COLD.

Memory tiering works without external dependencies, operating as a standalone context-management process that dynamically redistributes and compacts session-based assistant data across multiple storage tiers.

Redistributing context into multiple memory tiers prevents context overload and improves retrieval efficiency by keeping active context small and relevant while persisting stable preferences separately.