They don't need the entire project to fit in their token windows. There are ways to make them work effectively in large projects. It takes some learning and effort, but I see it regularly in multiple large, complex monorepos.

I still feel somewhat new-ish to using LLMs for code (I was kinda forced to start learning), but when I first jumped into a big codebase with AI configs/docs from people who have been using LLMs for a while, I was kinda shocked. The LLM worked far better than I had ever experienced.

It actually takes a bit of skill to set up a decent workflow/configuration for these things. If you just jump into a big repo that doesn't have configs/docs/optimizations for LLMs, or you haven't figured out a decent workflow, then they'll be underwhelming and significantly less productive.

(I know I'll get downvoted just for describing my experience and observations here, but I don't care. I miss the pre-LLM days very much, but they're gone, whether we like it or not.)