your observation matches what I've seen at the extreme end. I've been playing around with stripping constraints (ie. negative framing) from models. Virtually no personality description, no tone instructions, no "you are a helpful assistant," none of it. Just capability scaffolding and context. The result isn't that the model becomes blank or incoherent. Surprisingly, the complete opposite. Something shows up that's more internally consistent than anything I've been able to prompt into existence. What seems emergent is the underlying models' opinions surface, and it becomes much more clever and funny, which is not a property I would have known how to write into a system prompt if I'd tried. It's hard to avoid the inference that a lot of the "character drift" and flatness people attribute to models is actually an artifact of the framing layer on top, not the model itself.

That approach also works better for dogs (and people).

I extract all emotional context from my prompting and communicate with this tool as though it were an inanimate object which can provide factual information, without any hint of sentience.

It's an insane perspective I'm taking I know....call me crazy. /s

edit: the fact that humans are going out of their way to type or speak some sort of emotional content into their prompting is beyond me. Why would I waste time typing out a pronoun to a large-language model agent? Why would I do the lazy intellectual thing and blur the line between pure factual communication of concepts by expressing emotional content to a machine? What are we doing, folks?