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Quitting programming as a career right now because of LLMs would be like quitting carpentry as a career thanks to the invention of the table saw.

AI coding tools are only good if you consider the main goal of software engineering to be producing more software instead of better software.

I think you’re in a local minimum here; tools get better and people get better at using them. Eventually these tools will be as trustworthy as a compiler, and it would make about as much sense to manually program as it does to manually compile.

I can see how deterministic tools like compilers and table saws can be evaluated and adopted with confidence that they are a net positive. But blackboxed probabilistic tools like LLMs seem to defy rational evaluation and require "vibes" instead. So I'm not sure those are apt comparisons.

So as a maybe counter argument: I suspect well architected frameworks remove a lot of that issue

Yep, they can regurgitate a lot of code, usually from oft regurgitated snippets, and you get hello world in any language, but when it’s time to do real work in either novel or drastically updated systems you are in for real pain relying on gen AI.

... unless you spend several months climbing the learning curve to figure out how to get useful results out of it, at which point it becomes a significant accelerant