Sometimes it does... sometimes.

I recently had a nice conversation looking for some reading suggestions from an LLM. The first round of suggestions were superb, some of them I'd already read, some were entirely new and turned out great. Maybe a dozen or so great suggestions. Then it was like squeezing blood from a stone but I did get a few more. After that it was like talking to a babbling idiot. Repeating the same suggestions over and over, failing to listen to instructions, and generally just being useless.

LLMs are great on the first pass but the further you get away from that they degrade into uselessness.

Yeah, when I first heard about "one-shot"ing it felt more like a trick instead of a useful heuristic but with time my experience mimics yours, nowadays I try to one-shot small-ish changes instead of going back and forth.

I've had some luck in these cases prompting "your context seems to be getting too bloated. summarize this conversation into a prompt that I can feed into a new chat with a fresh context. make sure to include <...>".

Sometimes it works well the first time, and sometimes it spits out a summary where you can see what it is confused about, and you can guide it to create a better summary. Sometimes just having that summary in its context gets it over the hump and you can just say "actually I'm going to continue with you; please reference this summary going forward", and sometimes you actually do have to restart the LLM with the new context. And of course sometimes there's nothing that works at all.

I’ve had really good luck with having gpt generate a todo list that’s very, very detailed. Then having Claude use it to check items off. Still far from perfect but since doing that haven’t run into context issues since I can just start a new chat and feed it the todo (the todo also contains project info).