self-improving

To capture AI behavior corrections into reusable rules, simply provide explicit feedback during your conversation. The system automatically converts these corrections into actionable rules stored in a rules.md file to guide future responses.

Automating memory management for personalized AI prompts is handled through a three-tier file system. Rules auto-promote or demote between hot.md, cold.md, and rules.md based on usage, with memory audits removing stale items.

To save structured reflections for ongoing conversations, instruct the assistant to reflect on a task. It generates a structured reflection and saves it directly to a dated markdown file in the reflections directory.

This self-improving behavior system requires no external dependencies. It operates entirely standalone, managing its rule formation, tier management, and memory auditing through local files.

AI assistant responses lack consistency over time when behavioral corrections are not captured. This system solves that by generating actionable rules from user reflections to maintain consistent response quality across sessions.

You should not use an automated rule-capture system for one-off tasks requiring no personalization. It is designed for ongoing conversations where accumulating behavioral rules and memory auditing improves long-term consistency.