Refactoring JetBrains AI Code for Production

JetBrains AI may generate code that doesn't follow your team's specific architectural conventions — using field injection instead of constructor injection, creating service classes that mix layers, or bypassing your domain model with direct repository calls from controllers

Use JetBrains' built-in refactoring tools in combination with AI assistance. AI can suggest the refactored structure, and the IDE's safe rename and extract method tools can execute it reliably. Code review should enforce that AI-generated code follows the established layering pattern

Not all JetBrains AI code needs refactoring. If it works, is secure, and you don't need to modify it, leave it alone. Refactor when: you need to add features and the current structure makes it difficult, bugs keep appearing in the same area of code, or onboarding new developers takes too long because the code is hard to understand.

The golden rule of refactoring: behavior stays the same, structure changes. Before refactoring any code, make sure you have tests covering the current behavior (or add them first). Refactor in small steps — change one thing at a time and verify the app still works. Use version control (git) to commit after each successful change so you can revert if something breaks.

A well-organized project has a predictable structure where anyone can find what they're looking for. Group files by feature (not by type), keep related code together, and use clear naming. Every file should have a single clear purpose. If you can't describe what a file does in one sentence, it's probably doing too much and should be split.