The amount of garbage it spits out in autocomplete is distracting. If it's constantly making me 5-10% less productive the many times it's wrong, it should save me a lot of time when it is right, and generally, I haven't found it able to do that.

Yesterday I tried to prompt it to change around 20 call sites for a function where I had changed the signature. Easy, boring and repetitive, something that a junior could easily do. And all the models were absolutely clueless about it (using copilot)

I'd say that those details that vary tend not to vary within a language and ecosystem, so a fairly dumb correlative relationship is enough to generally be fine. There's no way to use logic to infer that it's obvious that in language X you need to do mylist.join(string) but in language Y you need to do string.join(mylist), but it's super easy to recognize tokens that suggest those things and a correlation to the vocabulary that matches the context.

Rinse and repeat for things like do I need to specify type and what is the vocabulary for the best type for a numeric value, This variable that makes sense is missing a declaration, does this look to actually be a new distinct variable or just a typo of one that was declared.

But again, I'm thinking mostly in what kind of sort of can work, my experience personally is that it's wrong so often as to be annoying and get in the way of more traditional completion behaviors that play it safe, though with less help particularly for languages like python or javascript.