An AI agent can accelerate software development, but it does not reliably produce high-quality code without direction. It tends to mirror the surrounding code: expressive code encourages better results, while tangled code can reproduce its flaws. Human supervision remains necessary because the agent lacks the system context, business constraints, and long-term perspective behind design decisions. section 1.2.2
Use an AI agent as a guided collaborator rather than an unquestioned implementer:
- Provide explicit design intent instead of repeatedly asking an incorrect first draft to be fixed; successive corrections can become patches on the wrong solution. section 1.2.2
- Review generated code for comprehension, not only compilation and tests; working code can still create comprehension debt when nobody understands the complete solution. section 1.2.2
- Ask for reasoning about purity, side effects, mutable state, and transformation clarity rather than requesting a generic functional rewrite. section 6.4
A more useful prompt
“Review this code and identify opportunities to improve purity where appropriate. Favor functional style when it makes the code clearer, simpler, and more predictable. Look for hidden side effects, mutable shared state, mutating operations, and imperative transformations that could become readable pipelines.” section 6.4
The practical measure of an agent’s value is not speed alone. Generated code should remain understandable, safe to change, and aligned with the surrounding design; otherwise faster production merely compounds technical and comprehension debt. section 1.2.2
