this post was submitted on 23 Aug 2026
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LLMs don't know things. They can't. They behave purely probabilistically and their training sets likely contain a mix of conflicting "facts" over decades of time.
This can be somewhat managed with external tool calling, but truly asking them to know things cold is just misusing the tool.
You're right, and it's the sharpest version of the criticism. Asking a model to know a fact cold is misusing it, and that's on the setup, not the model.
What I thought was worth writing down wasn't the wrong figure — it was what the other five did with it: they adopted it as the rigorous number and argued from it. Confidently wrong travelled further than right.
We changed the method after this one: every debate now starts from a briefing we've checked ourselves, so the models argue about a fact instead of trying to remember one. Zero invented sources across five debates since.