AI is useful in development because it reduces the cost of trying things. It can draft code, explain unfamiliar APIs, generate tests, summarize errors, and help move through repetitive work faster.
The risk is not that AI writes code. The risk is that developers stop deciding. A faster output is not automatically a better implementation.
Taste is the ability to say no
Engineering taste is not only about beautiful code. It is knowing when a solution is too clever, too broad, too fragile, or too disconnected from the product. AI can produce confident answers that still do not fit the system in front of you.
That means the developer still needs to read the surrounding code, understand the constraints, and make the final call.
Use AI for momentum, not ownership
- Ask for options when the problem is still blurry.
- Ask for implementation help when the direction is clear.
- Ask for test ideas when the risk is behavioral.
- Ask for a review when the code touches shared boundaries.
In each case, AI helps create momentum. It should not replace ownership. The person shipping the change still owns the tradeoffs.
The best AI workflow is conversational
I get the most value when I treat AI as a collaborator I can challenge. “This feels too abstract.” “Use the existing pattern.” “Show me the smallest change.” “What test would catch the regression?” That kind of interaction keeps the work grounded.
The goal is not to produce more code. The goal is to produce better decisions faster.
Craft still matters
Users do not care whether a human wrote every line. They care whether the product is clear, reliable, and useful. Teams care whether the code can be maintained. That still requires taste.