So this is just delegating certain work to dumber models? I certainly wouldn't use Gemini 2.5 Flash (!!?) for code writing as suggested.

I've never had an issue with Codex or Claude reading massive files, they're really good at precise greps.

> I've never had an issue with Codex or Claude reading massive files

Reading files isn't a problem they want to solve. The idea seems to be using a cheaper model to "scout" for the intended code, instead of an expensive one that reads all the things (and spends more tokens / thinks about them).

I think this might be useful because Opus 5 especially tends to over-read. So this looks like an "LLM Bloom filter", telling "hey this is the code you might want to read".

> So this is just delegating certain work to dumber models? I certainly wouldn't use Gemini 2.5 Flash (!!?) for code writing as suggested.

Why not, though? I started using OpenCode + GitHub Copilot, but I burned through my Claude Sonnet quota in just three days. I switched to GPT-5.4-mini, which uses far fewer tokens, and it’s often just as good as Sonnet. I think optimizing token usage is a good exercise. We often assume a model will be terrible, when it really isn’t.

Yes, this makes little sense. It looks like it's a way to avoid having Claude read or write your code.

And why stop at 90%? I have this one weird trick to reduce Claude Code token use by 100%: use a different harness and model!

This does seem to just be a subagents implementation.