Five Practical Rules for Using AI to Refactor Code Without Breaking It

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A software developer has shared a structured approach to AI-assisted code refactoring after a failed attempt where Claude over-refactored a 500-line service file, forcing a full revert. The core advice is to feed AI small, isolated code chunks with clear, specific instructions rather than entire files or vague prompts. Developers are urged to supply relevant context such as language, framework, and performance constraints, and to use AI for pattern recognition tasks like deduplication or async conversion rather than architectural decisions. Every AI suggestion should be tested on a dedicated Git branch, and the resulting diff must be reviewed line by line to catch unintended behavior changes or hidden dependencies. The method was validated on a 330-line payment handler that was incrementally reduced to 45 lines through repeated, targeted AI prompts on isolated logic segments.

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