self-correction-loop

To make Claude remember corrections across sessions, you can trigger a memory capture process by saying "remember this" after correcting an output. The system detects the correction, generalizes it into a reusable rule, and stores it in MEMORY.md for future retrieval.

Automating Claude memory management involves detecting user corrections, generalizing the lesson, and storing it as a rule in MEMORY.md. This creates a structured workflow with deduplication and audit-ready storage, ensuring Claude's mistake rate drops over time by compounding corrections into permanent knowledge.

Yes, the self-correction memory system triggers on session start to review existing rules stored in MEMORY.md. It also activates when you correct Claude's output or use phrases like "learn from mistakes" or "update memory" to ensure past lessons are applied.

Generalizing a user correction into a reusable AI memory rule involves a structured workflow: detecting the correction, extracting the broader lesson, looking up existing memory to prevent duplicates, and storing the new rule in categorized sections of MEMORY.md.

To keep Claude's memory rules clean and avoid duplicate corrections, the system supports built-in deduplication and auditing. It checks existing MEMORY.md entries during the memory lookup phase before storing new rules, ensuring clean and easily updatable memory.

You should use an automated correction capture system when you frequently correct Claude's mistakes and want to prevent recurring errors. It is ideal for compounding corrections into permanent, audit-ready knowledge rules that improve AI accuracy over multiple sessions.