A file that runs perfectly in production can still sit untouched for months, because the fear is not about bugs. It is about not knowing which of the code's quiet choices are load-bearing.
The Details:
- Traditional legacy code announces its risk. Tangled logic, a variable named badly, a function doing five things at once: the mess is visible, so a developer can trace it, own it, and eventually change it with confidence.
- Generated code hides its risk differently. It reads cleanly and passes every test, but decisions like when a string gets trimmed or how an empty value gets coerced were made once, in a conversation that no longer exists, by a model that never has to defend the choice later.
- A docstring cannot fix this because it describes what the code does, which anyone can already see by reading it. The missing piece is the alternatives that got rejected and why, information that vanishes the moment the chat session ends.
- The fix is a short, deliberately unglamorous artifact: three to five bullets capturing only the choices where another path was seriously considered, tagged with a confidence level, written while the reasoning is still fresh and saved next to the code, not buried in a wiki. Over time these notes start citing each other, turning isolated snapshots into a running record of why the system looks the way it does, and developers begin reading the notes before they read the code.
Bottom Line: The dread engineers feel toward clean AI-written code was never really about the code. It was about the missing record of why it was written that way.
