Building With AI Without Letting It Drive
A practical look at where AI coding tools accelerate software work, where they distort judgment, and how to keep ownership intact.
6 min read
AI coding tools are strongest when the human still owns the shape of the work.
They can move fast through boilerplate, test scaffolds, refactors, and implementation variants. They can also confidently produce code that looks plausible while pushing the system in the wrong direction.
The leverage comes from giving the tool a narrow lane:
- gather context before asking for changes
- define acceptance criteria in plain language
- keep edits small enough to review
- test behavior, not vibes
- stop and re-plan when the output starts hiding complexity
The more I use these tools, the more I value ordinary software fundamentals: clean boundaries, readable tests, stable interfaces, and the discipline to say no to a bad abstraction.