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How to Make Claude Code Improve from its Own Mistakes

A practical guide to enabling continual learning in Claude Code and other AI coding agents. Three main techniques are covered: a 'generalize-knowledge' command that prompts the agent to summarize lessons learned into markdown files (CLAUDE.md, AGENTS.md) after each task; daily reflection via cron jobs that review agent logs from the past 24 hours; and 'skills' — specific markdown prompt files that capture how to handle particular tasks, APIs, or workflows. The approach treats coding agents like new employees who need structured mechanisms to retain and build on past experience rather than repeating the same mistakes.

    #llm#prompt-engineering#claude-code
Mar 24•7m read time•From towardsdatascience.com
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Why do we need continual learningHow to Achieve Continual LearningConclusion
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