I think it mattered a lot more a few years ago, when the user's prompts were almost all context the LLM had to go by. A prompt written in a sloppy style would cause the LLM to respond in a sloppy style (since it's a snazzy autocomplete at its core). LLMs reason in tokens, so a sloppy style leads it to mimic the reasoning that it finds in the sloppy writing of its training data, which is worse reasoning.

These days, the user prompt is just a tiny part of the context it has, so it probably matters less or not at all.

I still do it though, much like I try to include relevant technical terminology to try to nudge its search into the right areas of vector space. (Which is the part of the vector space built from more advanced discourse in the training material.)