Results for “temporal-memory”

Anchors work at the current moment and places events as spatial distances ahead or behind to improve temporal reasoning.

Retrieve task-relevant project and global memory without loading everything. Load when the user asks what we decided, recall prior context, find memory about a feature, explain past rationale, resume a task, or check deferred ideas.

Merges mature lessons from a domain memory file into its instruction file, preserving knowledge with minimal redundancy.

Transforms lessons learned into domain-organized memory instructions that persist across VS Code contexts, with global and workspace scopes.

Maintain durable session memory across agent disconnects by writing structured checkpoints to the repo's session directory, enabling context recovery.

Stores, retrieves, and curates persistent facts in a structured memory map, distinguishing between user facts and reference text.

Compresses conversation transcripts into prioritized notes using an LLM observer, consolidates them when they grow, and recovers any missed sessions without a database or vector store.

Watches conversations continuously and compresses them into prioritized notes, consolidating and recovering missed sessions with multiple redundancy layers.

Persists and recalls agent knowledge across sessions using four approaches: static KB, company wiki, persistent memory, and session brain.

Structured memory system with domains, decay, and links for AI agents, replacing flat memory files with a weighted, interconnected memory palace.

Indexes document metadata in SQLite and manages ephemeral key-value state in Redis for cross-session context.