Good, you achieved a 10% speedup for a particular workload that some users said they care about. But how do you find out that was really the feature that should have been built next? How do you prevent adding badly factored code? How to make sure you don't pile on top of existing tech debt in the codebase, that you are solving the most fundamental issues first?
I think a sufficiently smart non-competent developer can still do this to great effect, but it definitely helps if someone is both a competent developer, smart, and a seasoned user of LLMs.
Just because AI is not yet a god that is better than all humans at creativity and product decisions and design does not mean it is not a huge accelerant right now.
