Here's something I've noticed: AI generates code that runs perfectly on day one. Then you come back two weeks later to add a feature, and you're staring at a 200-line function wondering where to even start.

AI has coding habits, just like any developer. And if you don't catch them early, you'll pay for it later.

What AI tends to do:

Inline everything. Instead of breaking logic into smaller functions, it dumps everything into one place. Works great until you need to change one piece without touching the rest.

Create tight coupling. The code it generates often ties components together in ways that make extending or testing difficult. Change one thing, risk breaking three others.

Skip separation of concerns. Business logic, data access, UI updates all mixed together. Fast to write, slow to modify.

How to fix it:

Prompt for modularity upfront. Don't just ask for a feature. Ask for it broken into small, focused functions. "Build a user auth system with separate functions for validation, token generation, and database access."

Request a refactor. After AI gives you working code, ask it to refactor into smaller pieces. "Break this into separate functions" or "Separate the business logic from the data layer."

Review before moving on. Scan for functions longer than 30-40 lines. Look for mixed concerns. If you see them, ask AI to split things up now, not later.

Set architecture rules. Tell AI your structure upfront. "Follow a service/repository pattern" or "Keep controllers thin, move logic to service classes."

AI is an incredible tool. But like working with a talented junior developer, you need to guide the structure, not just accept the output.

Treat AI code like any code review. If you wouldn't merge it from a teammate, don't merge it from AI.

#softwaredevelopment #ai #codequality #devcommunity #FireInTheCircuit