It's a zero sum game. AI cannot innovate, it can only predictively generate code based on what it's already seen. If we get to a point where new code is mostly or only written by AI, nothing new emerges. No new libraries, no new techniques, no new approaches. Fewer and fewer real developers means less and less new code.
Nonsense indeed. The model knowledge is the current state of the art. Any computation it does, advances it. It re-ingests work of prior agents every time you run it on your codebase, so even though the model initializes the same way (until they update the model), upon repeated calls it ingests more and more novel information, inching the state of the art ever forwards.
Current state of the art ? You must be joking .. I see code it has generated, some interns does better.
Obviously, you are also joking about the thing that AI is immune to consanguinity, right ?
If you have had interns who can write better code than Opus 4.5 I would very much like to hire them.
Nonsense. LLMs can easily build novel solutions based on my descriptions. Even in languages and with (proprietary) frameworks they have not been trained on, given a tiny bit of example code and the reference docs.
That's not novel, it's still applying techniques it's already seen, just in a different platform. Moreover it has no way of knowing if it's approach is anywhere near idiomatic in that new platform.
I didn't say the platform was the novel aspect. And I'm getting pretty idiomatic code actually, just based on a bit of example code that shows it how. It's rather good at extrapolating.