I can see this being important if you only care about the results as evaluations of AI progress, but if what you care about is the math itself why should you care about the prompt or anything other than the proof?
Pure math is relatively outside my domain, so I find it difficult to grok the exact relevance of the various published discoveries beyond that they are not insignificant, and LLM competence is expanding quite steadily across the field. If this trend continues to the point of LLMs being able to competently expand pure math, it seems somewhat predictable to expect there to be a number of people aiming to find ways to try to keep human mathematicians in the loop.
I've no idea what I think about this one way or the other, beyond that it's certainly a phenomena and one that's going to drive motivated reasoning that may not be entirely sound.
My perspective is more like a FOSS philosophy for math. Even if a closed version has the same immediate effect, it's just better for everyone if everyone can look under the hood and tinker with it.
I would've thought pretty much the exact opposite. "Prompt engineering" was somewhat important in 2023/2024 when the models were much weaker, it doesn't seem at all necessary anymore (unless just "clearly stating your requirements" counts as prompt engineering). Most of the discussion I've seen seems consistent with this?