Sure, but the study is saying something slightly different, it's not that people write bad prompts for artifacts, they actually write better ones (more specific, more examples, clearer goals,...). They just stop evaluating the result. So the input quality goes up but the quality control goes down.

Seems like it’s impossible for output to be good if the prompt is bad. Unless the AI is ignoring the literal instructions and just guessing “what you really want” which would be bad in a different way.

What does prompting quality even mean, empirically? I feel like the LLM providers could/should provide prompt scoring as some kind of metric and provide hints to users on ways they can improve (possibly including ways the LLM is specifically trained to act for a given prompt).