> Anthropomorphizing algorithms only serves to impair objective analysis of when they are, or are not, applicable.

Actually, in this case, comparing how we as humans think to how LLM's work is in fact useful. It's hard for us to eyeball a word and say how many consonants are in it, we need to count. I wouldn't ask a human to eyeball a tax return and tell me what the totals are reliably without giving them the tools to add things up. LLM's are the same way.

It's true that anthropomorphizing in general can be a trap, but when working with LLM's it can be a useful guide in pointing the way towards workable solutions.