Self-improving, verifiable memory for AI coding agents. Learns how you work, stops repeating mistakes, models each project, recalls the right lesson at the right moment. Every memory is signed and tamper-evident. Local-first.
Local-first project memory for AI coding agents. Records failed attempts, fragile files, and decisions per repo, and warns the agent via hooks before it repeats a recorded mistake.
Enables AI agents to store, retrieve, and self-improve procedural memories (lessons learned) based on relevance to the current task, pruning unused memories to reduce context load and prevent repetition of past mistakes.
