Fleet-Mem Shared Code Intelligence

Example Use Cases

• 1

  Semantic code search returning meaningful code units instead of string matches.

• 2

  Share discoveries and knowledge persistently across sessions and among multiple agents.

• 3

  Automatic git-aware file locking and coordination to avoid merge conflicts and stale context.

Description

fleet-mem enables multiple AI coding agents working on the same codebase to share context and avoid conflicts by providing AST-aware semantic search, persistent shared memory, and automatic file locking and coordination. It runs entirely locally by default using Ollama embeddings, ensuring zero data leakage, and supports incremental indexing and branch-aware overlays. This improves efficiency by preventing duplicated work, merge conflicts, and stale context among agents.