N Refactors Later: Human-AI Playbook for Big Rewrites
Claude Code large-refactor SOP: plan.md → lock-replace-verify → post-mortem loop. 100% behavior-safe.
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When you first start using Claude Code, you throw in your requirements, code gets generated at lightning speed, and efficiency skyrockets. But once the codebase grows, the code becomes messier and messier with each modification.
I’m sure you’ve experienced the despair of having AI break your project and having to repeatedly roll back changes.
For example, just last week, I used Claude Code to optimize a core order processing logic. The code looked much cleaner, but when it went live, it directly caused the order status to lock up in a certain edge case. I spent an entire day locating and fixing that bug.
This was a typical case of code hallucination—it imagined a better logic while ignoring real-world constraints.
Three fundamental reasons why AI fails at large-scale project refactoring:
1. AI is a genius at local optimization but mediocre at global architecture.
AI’s attention is limited.