Comment by mapontosevenths
2 days ago
Compact the context and try again, or switch to the model with the 1 million token context. They all struggle after a hugge task like rying to make sense of a large codebase. Claude is especially poor at knowing when to compact on it's own.
It has 1M context, and it's not a huge codebase, and the context is sub 10% for a thorough task. This is an LLM issue, not a model/harness issue.
I've run copilot/gemini/pi/opencode/etc for a long time, against all major providers. Don't get me wrong, I get good productivity out of it or I wouldn't use it, but it's very different from intelligence.