alt Hacker News> LLMs are super useful but currently, the primary use case is teaching, not doing.
For code? Autocomplete on steroids is the killer-app.
The other things the LLMs give me are prone to be over-engineered/overly verbose code or similar.
I went through a lot of "Why are you also doing $FOO then $BAR? Doesn't seem necessary if we skip them and do $BAZ which will make one or both of those redundant" and it responding "You're right! Lets use $BAZ instead".
And giving them code to make a small change to was pointless - they would often, but not always, make an incidental change far from the point where you asked for the change.
But autocomplete? That works just great and because I've already got context of the code I am writing I can check it in (at most) two seconds and move on.
I think you're missing the value of rubber-ducking with the chatbot on a fairly well-defined/well-known problem in a somewhat specific/novel scenario—this is the vast majority of software development being done today.
Depending on the situation this can be invaluable. If you're experienced in the domain you probably know generally what you need to do but you might get a better result by reasoning through the best solution with the constraints and requirements you have. Or maybe you missed something obvious when you write out the full context—which is a required step for getting a good output from the chatbot, and generally isn't a required step if you aren't explaining your approach to someone else and you don't want to be rigorous.