Create structured memory blocks with labels like persona, human, or system for organizing information in the Letta system. Link blocks to agents or update content as needed.
Attach a tool to multiple agents simultaneously by filtering them based on name or tags. Use this to efficiently manage tool assignments across your agent network in the Letta system.
Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.
Enables persistent storage and retrieval of decisions, settings, and operational rules across chat sessions, maintaining context continuity and decision consistency for long-term development projects through structured memory management.
Enables AI assistants to maintain persistent conversations and context between sessions through automated saving and global installation across projects. Provides zero-configuration memory persistence with automatic conversation history preservation.