I think i’ve only once flat out told one it was wrong about a specific assertion I quoted and it immediately was able to find its way to what I knew to be the correct claim.
I just wonder what would happen if i was in fact mistaken and I told it confidently it was wrong without elaborating
I think that’s a good approach. Personally I find LLMs quite fascinating but they’re deeply flawed. They can barely be used in production environments, especially unsupervised. The workflows regarding LLMs are very esoteric with specific prompting techniques etc and while all LLMs have similar flaws each model and model version behaves differently. It’s super weird and unreliable. Like one big workaround that has so much investment that it keeps improving every month but still stays shitty at it’s base.