Long-Term Memory

Long-term memory lets agents persist and retrieve information across sessions, maintaining knowledge about user preferences, past interactions, learned facts, and project-specific context that survives beyond a single conversation. Implementation approaches include vector database storage for semantic retrieval, structured databases for explicit facts and relationships, and file-based persistence such as CLAUDE.md files that encode project knowledge in plain text. The primary challenge is retrieval quality: storing memories is straightforward, but reliably surfacing the right memory at the right moment requires careful indexing, relevance scoring, and decay mechanisms to prevent stale information from polluting the agent's context.