The truth is we're brute forcing some problems via tremendous amount of compute. Especially for apps that use AI backends (rather than chats where you interface with the LLM directly), there needs to be hybridization. I haven't used Claude Code myself but I did a screenshare session with someone who does and I think I saw it running old fashioned keyword search on the codebase. That's much more effective than just pushing more and more raw data into the chat context.

On one of the systems I'm developing I'm using LLMs to compile user intents to a DSL, without every looking at the real data to be examined. There are ways; increased context length is bad for speed, cost and scalability.