Good analogy. I’m gonna steal that :D

I don’t doubt that it is possible to create good code when focusing on programming best practices etc. and taking the time to check the AI output thoroughly. Time however is a luxury most of the devs in those companies don’t have, because they are expected to have a 10x code output. And thats why the shit hits the fan. Bad code gets reviewed under pressure, reviewers burn out or bore out and the codebase deteriorates over time.

This approach to coding is exactly what creates the problem. They will find out the hard way if they can continue to be productive when something breaks and AI is not available for whatever reason. Does anyone know how to fix it? Is the documentation sufficient to understand what the AI did?