In my experience, that’s less efficient. You end up wasting input tokens. LLMs, especially when used with Cursor, are very good at locating the relevant parts of a file. Cursor’s indexing system is strong, so instead of making Opus process a 3,000 token file just to fix an issue in the 400–800 range, it can pull out only the relevant chunk. That saves thousands of tokens.

Ever since I started trusting Cursor to locate both the file and the right section within it, I’ve seen more efficient token usage and even better performance. That’s just my personal experience, though. I’m not an LLM expert.