Do you use LLMs often?
I get "I don't know" answers from Claude and ChatGPT all the time, especially now that they have thrown "reasoning" into the mix.
Saying that LLMs can't say "I don't know" feels like a 2023-2024 era complaint to me.
Ok, how? The other day Opus spent 35 of my dollars by throwing itself again and again at a problem it couldn't solve. How can I get it to instead say "I can't solve this, sorry, I give up"?
That sounds slightly different from "here is a question, say I don't know if you don't know the answer" - sounds to me like that was Opus running in a loop, presumably via Claude Code?
I did have one problem (involving SQLite triggers) that I bounced off various LLMs for genuinely a full year before finally getting to an understanding that it wasn't solvable! https://github.com/simonw/sqlite-chronicle/issues/7
It wasn't in a loop really, it was more "I have this issue" "OK I know exactly why, wait" $3 later "it's still there" "OK I know exactly why, it's a different reason, wait", repeat until $35 is gone and I quit.
I would have much appreciated if it could throw its hands up and say it doesn't know.
Re:Is the doc bot docs, or not?
by conception on Wednesday July 09, 2025 @02:02PM
(#44513052)
I solve this by in my prompt. I say if you can’t fix it in two tries look online on how to do it if you still can’t fix it after two tries pause and ask for my help. It works pretty well.
In a single request? Oof.
I was benchmarking some models the other day via openrouter and I got the distinct impression some of these models treat the thinking token budget as a target rather than a maximum.
If the training data is full of certain statements you'll get certain sounding statements coming out of the model, too, even for things that are only similar, and for answers that are total bullshit