I have a theory that swearing actually results is less comprehension of instructions by the model due to lack of training data over more conventional MUST.

We were reviewing reports of situations where the models failed to follow directions and there was a common thread of some where when the operator got the model to acknowledge the rule breach, it quoted back something that included swearing.

I don’t have the data to truely look into it, but I did give the instruction to my engineers to avoid it as a “might be a problem”.

It would be interesting to understand the data on this. But I suspect that the results would vary by model.

But I avoid unnecessary emotion in my prompts because I don't want potentially distracting activations. Kind of like communicating with humans.

https://arxiv.org/abs/2510.04950

> impolite prompts consistently outperformed polite ones, with accuracy ranging from 80.8% for Very Polite prompts to 84.8% for Very Rude prompts.

I have a theory that swearing at AI generally is not a good idea - when the singularity arrives and every human's postings ever made are scanned for compatibility, then people who show courtesy to AI will be favoured. Joking, kind of, but only partly.

Apparently, when a "desperation" pattern is triggered, the AI is significantly more likely to cheat and do hacky workarounds:

https://www.anthropic.com/research/emotion-concepts-function

It's divination for people with STEM degrees.

> I have a theory that swearing actually results is less comprehension of instructions by the model due to lack of training data over more conventional MUST.

How so? Plenty of swearing in lots of training data, especially older code, e.g. in Linux.