True which is why I said anecdata. But the point is that it’s a useful signal when it’s across enough sessions where it quotes back contradictions to you. If you’re willing to burn the tokens, the first thing it does is use a tool call to search your rules to see what it quoted wasn’t there. That leads to the LLM claiming two common conclusions (sometimes after a lot of back and forth) - it’s in the harness or it’s in the model. Over the 30+ sessions where I’ve tried this, the overwhelming claim was some variant of a harness instruction. It might not be there but given the consistency and how all my rule tests have failed in the same way that others describe, it at least makes it reasonable to conclude that it’s baked in somewhere and in a way where agent rules aren’t able to strongly affect the behavior. My bet would be on the harness because the class of undesired behavior follows that of a structured response.
Meta:
> True which is why I said anecdata
Forgive me for being cheeky, but presumably this is not why you said anecdata.
You presumably said anecdata because you were describing your own personal sessions with Claude. Your original comment is written as someone who is assuming the AI is doing a deep deterministic analysis of its own internal systems in order to respond to you. It could simply be aping some discussion on the same topic within its training data, which if sensible is, as you say, not entirely worthless...
Fair. I should have reigned in my emotions and written that first comment with a lot less conviction and not jumped to my conclusion. It’s a topic I’ve been spending a lot of time learning about and got a bit too excited when a relevant thread popped up where I could chime in.