"find every function in this codebase" is rarely a thing imo. Why would you want to do that, for some statistics? In many cases, what you want to do is find "al

"find every function in this codebase" is rarely a thing imo. Why would you want to do that, for some statistics? In many cases, what you want to do is find "all classes that implement some interface" - of course depending on the language. And reasonable languages allow agents to find that reasonably efficiently ("implements Foo") - a bit slower than specialized interfaces, but in a way that don't require you to maintain a giant index. And yes, agents writing chunks of code or scripts to accomplish tasks is already what they do, when they determine it's efficient. >And there is a lot missing in the actual harnesses frankly that isn't about more parallel agent ninjutsu. Like why isn't there a 'move this function from this file to this file' tool (copy/paste char range) and we have to see Claude/Codex/etc flail around rewriting huge chunks of code in token space I think if we had agent-specialized languages that you would modify by directly changing AST or some other structure it would be more efficient. But, otherwise, it's way more efficient to train on existing corpus - like PRs - which is the same reason that internal LLM thinking is not binharic, but regular English (or Chinese).