Once AI improves its cost/error ratio enough the systems you are suggesting for humans will work here also. Maybe Claude/OpenAI will be pair programming and Gemini reviewing the code.
That's exactly the problematic mentality. Putting everything in a black box and then saying "problem solved; oh it didn't work? well maybe in the future when we have more training data!"
We're suffering from black-box disease and it's an epidemic.
Every time something new the same thing happen, people start exploring by putting it absolutely everywhere, no matter what makes sense. Add in huge amount of cash VCs don't know what to spend it on, and you end up with solutions galore but none of them solving any real problems.
Microservices is a good example of previous $trendy_dev_pattern that is now cooling down, and people are starting to at least ask the question "Do we need microservices here actually?" before design and implementation, something that has been lacking since it became a trendy thing. I'm sure the same will happen with LLMs eventually.
And you’d have to assume that the errors LLMs make are random and independent.