I've seen this exact process play out in my own work. The AI generates code and tests that pass with high code coverage and honors invariants set by spec. I look at the code and find a rats nest / ball of mud that will cost 10x more tokens to enhance should I ever need to add a feature.
So, I think you're on to something, but I think the process might be discounting extensibility and resilience under change.