I think the "answer" to users that anthropomorphize their LLMs is to create for them an environment where they are on both sides of the LLM: give users the ability to create their own contextually limited, purpose driven AI Agents where they control the "personality" of the agent, because what the agent is doing is context-wise something the user understands intimately (its their career) and they actually understand the problem space better than a software engineer (occupant of a different career) could and would care to deeply understand at the same level.

I've actually set up an environment like this. It requires contextually positioned agents with a limited scope and purpose. Imagine something like a creative writing agent that understands the literary genre of its user, and the user is able to change the focus of the literary agent, or create new ones that provide a counter-point perspective. As the user operates their word processor, the agent(s) can be asked for opinions, advice, and so on. But the point being: when the user is on both sides: they authored the agent, and that authoring was entirely purpose focused, nothing technical unless that what the user instructs them to understand. With the user on both sides, dangerous anthropomorphism is largely erased, their agent is only doing what they told it, and when it does something unexpected they an easily reason why. Magic AI no more.