> The level of performanace of AI solutions is heavily related to the experience level of the developer and of the problem space being tackled - as this thread points out. > > Unfortunately the marketing around AI ignores this and makes every developer not using AI for coding seem like a dinosauer, even though they might well be faster in solving their particular problems.

You're not necessarily wrong, but I think it's worth noting that very few developers are only ever coding deep in their one domain that they're good at. There's just too many things to be deeply good at everything. For example, it's common that infra and CI tasks are stuff that most developers haven't learned by heart, because you don't tend to touch them very often.

Claude shines here — I've made a lot more useful GitHub Actions jobs recently, because while I could automate something, if I know I'm going to have to look up API docs (especially multiple APIs I'm not super familiar with) then I tend to figure that the automation will lose out the trade-off between doing the task (see https://xkcd.com/1205/). Claude being able to hash out those rapidly, and in a way that's easily verifiable that it's doing the right thing, has changed that arithmetic for me substantially.