videocut:self-evolve

To make an AI agent learn from mistakes, you need a continuous improvement mechanism that traces context, analyzes user corrections, and updates internal methodologies. This Skill records failures and integrates lessons into relevant documentation sections.

Continuous improvement for AI skills works by tracing the context of an error, reading target files, and integrating updates into appropriate sections. It goes beyond logging by actively refining the internal rules guiding the agent.

The best way to update AI agent rules is to analyze the failure context and integrate corrections directly into methodology files like tips/*.md. This ensures the agent refines its behavior rather than just appending to a log.

Yes, you can record user corrections to prevent repeating mistakes by instructing the AI to analyze the issue. It traces the context, updates internal rules, and logs the event to ensure continuous improvement.

No, self-improvement for AI does not just append errors to a log file. It requires tracing context, reading target files, and integrating updates into appropriate methodology sections to actively evolve the skill.