Building products with AI without losing craft

AI assistants are everywhere in modern development workflows. The trap is treating them as a replacement for thinking — copy-pasting outputs until something compiles. The better frame: AI as a fast collaborator that still needs your taste, architecture, and judgment.

Start with a clear spec. Before prompting, write down inputs, outputs, edge cases, and what “done” looks like. This single step prevents most hallucinated abstractions and keeps the codebase coherent.

Use AI for scaffolding and exploration — boilerplate, test stubs, regex, docs drafts — then review every line like a PR from a junior dev. Your job shifts from typing to editing, validating, and integrating.

Preserve craft by keeping interfaces human-readable, naming things well, and deleting generated noise. Minimal code that you fully understand beats a clever blob you can't debug at 2 AM.

The teams shipping the best AI-augmented products treat the model as a multiplier on clarity, not a substitute for it.