I'm pretty enthusiastic about LLMs and use them on my 8 year old codebase with ~500kloc. I work at a hedge fund and can trace most of my work to dollars.

I dunno if I’d fall myself “enthusiastic” but I successfully use AI on a large production monorepo. The onus is on the user to break down the problem into llm-sized bites. How to do this effectively is a skill that takes time to develop. You’re not crazy: if you go in and ask it to do things in broad strokes it won’t work.

I'm quite sure "loading the project" isn't putting every single line of code into the context. Probably just a huge CLAUDE.md or something.

Either that or this author is completely out of touch with reality.

should have been clearer here. by "loading the project" I meant the initial context claude builds like CLAUDE.md, directory structure, etc... not literally putting every line of code into context. 7M tokens would obviously not fit in a 200k window

I’m not clear what “just loading the project” even means here - if that’s how many tokens are consumed by system prompt plus Claude.md and MCP tools well that has nothing to do with the size of the project

I think the agent mode stuff only works well on trivial projects. But the top tier models can be very productive with carefully constructed prompts and manually curated contexts for large mono repos.

You obviously don't have any idea how any of this actually works.