Experimenting with graph-based semantic memory for AI agents
The article discusses Graft, a local-first agentic memory system designed for AI coding agents. It aims to help these agents retain knowledge across sessions, preventing the loss of important insights and decisions. Graft is not a vector database but a tool for persistent reasoning that enhances the productivity of AI agents by allowing them to build on their past experiences.
- ▪Graft provides a persistent memory for AI coding agents that survives session resets and machine switches.
- ▪It captures decisions, gotchas, and root causes as agents solve problems, allowing for reusable knowledge.
- ▪The installation process is straightforward, requiring only a single binary and an SQLite file.
Opening excerpt (first ~120 words) tap to expand
graft Local-first agentic memory for AI coding agents. Stop solving the same problems twice. Give Claude Code, Codex and any other agent a persistent memory that survives sessions, context resets and machine switches — locally, with no cloud and no API key. C11 · SQLite + sqlite-vec + FTS5 · llama.cpp + BGE-M3 · MessagePack · AF_UNIX socket · optional REST + 3D viewer Made for Claude Code · Codex · ChatGPT · Claude Desktop · Gemini CLI · Open Code · and your own microservices. Why Graft? AI coding agents are productive — but they forget everything when the session ends.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.