AI is most useful to me when it behaves less like an answer machine and more like a second engineer at the whiteboard. It can surface alternatives quickly, challenge an assumption, or turn a rough intent into something testable.
Keep the steering wheel
The developer still owns the architecture. Before asking for code, I define the constraints: who uses the system, what can fail, which data is sensitive, and what “done” means. A generated solution is a proposal, not a decision.
Use it where feedback is cheap
AI is excellent for test matrices, edge-case brainstorming, migration checklists, refactoring options, and explaining unfamiliar code. These tasks become valuable only when paired with a fast verification loop.
- Ask for tradeoffs, not one “best” answer.
- Run tests and inspect behavior.
- Check security and accessibility manually.
- Keep the final code understandable without the prompt.
Fundamentals become more important
The faster code appears, the more valuable judgment becomes. Knowledge of HTTP, databases, browser behavior, and system boundaries is what lets a developer identify a convincing mistake before it reaches production.