Part of a properly functioning LLM is absolutely it understanding implicit instructions. That's a huge aspect of data annotation work in helping LLMs become better tools, is grading them on either understanding or lack of understanding of implicit instructions. I would say more than half of the work I have done in that arena has focused on training them to more clearly understand implicit instructions.

So sure, if you explain it like the LLM is a five year old human, you'll get a better response, but the whole point is if we're dumping so much money, resources, destroying the environment, and consumer electronics market for these tools, you shouldn't have to explain it like it's five.

Seriously what is the point of trashing the planet for this shit if you have to talk to it like it's the most oblivious person alive and practically hold it's hand for it to understand implicit concepts?

You have to have the car there no matter what type of car wash it is.

If the car wash is some distance "away", it means neither you nor the car is at it. Any attendant is not going to walk off-property to retreive your car, especially when most of them you drive up for service. Which is rather the point.

You shouldnt have to. If you ask a person that question theyll respond "what good is walking to the car wash, dumbass," if AI can't figure that out its trash

You know that LLMs provide their reasoning now? You can check why they answered this way and I'm sure it's not because they thought that "maybe there are no available spaces".