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I'd like to think I'm reasonably good at coding considering it's my job. However, it's somewhat hard to measure how effective a programmer or SWE is (Leetcode style questions are broadly known to be awful at this, yet it's what most interviewers ask for and judge candidates by).
Code is pretty easy to evaluate at a baseline. The biggest questions are "does it compile", and "does it give you the result you want" can be evaluated in like 10 seconds for most prompts, and that's like 90% of programming done right there. There's not a lot of room for BS'ing. There are of course other questions that take longer to answer, like "will this be prone to breaking due to weird edge cases", "is this reasonably performant", and "is this well documented". However, those have always been tougher questions to answer, even for things that are 100% done by professional devs.
While I'd say the only thing easy to answer is "does it compile", reading your other list I'd say I largely agree with your assesment.
LLMs can be a force multiplier for SWEs, but that doesn't mean they're good programmers. They're not programmers at all.
Looking at the points you made in your other post I'd argue that the biggest force multiplier is your first point and that this is a pretty big deal and bigger than people might first realise, especially non-engineers.
The second one is the issue I'm having with claims about LLM usability. Its kind of like dealing with mediocre Indian resources. You have break down and define the problem to such a degree that you've "almost" written the code yourself. This can still be useful and depending on your role very useful, but it isn't effectively replacing local resources either. Its not a method for solving problems but more of an advanced auto complete.
How useful is this? It depends on the situation and indivual and I'd rate it as moderately useful. Having managed developers, it also seems like something that (for some people) can feel like more of a productivity boost than it is due to time being spent differently (I'm not saying you're doing this).
I also wonder about this. I think in particularly bad cases it can be true, since if something doesn't work it becomes very tempting to just reprompt the AI with the error and see what comes back. Sometimes that works on a second attempt, and in other times I'll go back and forth for a dozen prompts or so. Whoops, there went an entire hour of my time! I'm trying to explicitly not fall into that habit more than I already have.
Overall I'd say it's a moderate productivity boost overall even factoring that in, and it's getting slowly better as both AI models improve and my skill in using them also improves.
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