The experiences reported in these articles are so utterly unlike the ones I have using AI to generate code. It HAS gotten better in the last year, but it is still no where near this capable, for me.
If I give it too many requirements at once, it completely fails and often damages the code files significantly, and I have to refresh from backup.
If I give it smaller prompts in a series, doing some testing myself between prompts, there is usually something I need to fix manually. And if I don't, and just let it successfully build on what it built before, the code becomes increasingly more impenetrable. The variable names and function names are "true" but not descriptive (too vague, usually) and when those mount up the code becomes unreadable. It generates code comments but they are utterly worthless noise that point out the outright obvious without telling you anything actually useful. When new requirements negate or alter prior ones, the AI does not refactor them into a clean solution but just duplicates code and leaves the old no-longer-needed code behind and makes variable names even more weird to make up for it. The performance of the code decays quickly. And on top of all this, it STILL can't succeed at all if you need to do anything that is a little too unique to your business needs. Like a fancy complex loose sort with special rules or whatever. It tries and fails, but tells you it succeeds, and you get code that doesn't work.
Sometimes it can solve surprisingly hard problems, and then get utterly stuck on something trivial. You tell it what is wrong and it shuffles a lot of code around and says "there, fixed" and it is still doing exactly what it did wrong before.
I have good success getting new projects started using AI code generation. When it is just generating mostly scaffolding and foundational feature support code that tends to be pretty generic, it saves me time. But once the aspects of the code that are truly unique to the needs start coming into focus, AI fails.
I still do most of my coding by hand because of this. I use AI when I can but once this stuttering starts happing I drop it like a hot potato because it causes nothing but problems from then on.
I simply don't see how the same solution could reliably make consistent and significant changes to a codebase and produce reliable, performant, or even functional code on an ongoing basis. That hasn't ever worked for me and still doesn't, even with the latest gen AI models.