Comment by dyauspitr
3 days ago
I still don’t get it I can dictate a prompt and sometimes I do it so quickly the text looks like a drunken parrot dictated it and it still always gets exactly what I’m asking for. I’m just going to attribute malice to the naysayers.
Some people are really bad at specifying what they want to ask for. Or they already start prompting with the attitude that it can't possibly work so they don't even really try, or stop at the first failure to point and say how bad it is.
People are really, really bad at specifying what they actually want. I've worked in IT for my whole career, starting in help desk (now an IT manager). My days in the service desk was enough proof that people have no idea what they actually want, or at least, they really struggle to articulate it into words.
It's the famous "email broken, fix pls" but in the form of an LLM prompt.
Well, today's multimodal llm agents with tools would at least have a good chance to do something with even such an underspecified query. Because fixing things is simpler to specify, the agent could look at config, network settings, send a test email, take a screenshot etc and get a good idea of what's broken. But when you want some new feature or new app, you can't do without actually asking for specifics, or at least you shouldn't complain if it didn't read your mind correctly. Or at least accept that you have to iterate. I think many average people can get this if they are motivated, and they can incrementally say what they don't like even in vague terms and it can get better. But some just stop without trying to ask for changes.
It can be frustrating to observe people interacting with these things. But it was just as frustrating 20 years ago, so maybe it's just a constant.
Similarly, doing service desk, the thing that makes me flip the table is how people start by explaining what does not work, instead of explaining what they are trying to do.
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Or maybe people see how complex the code is and all the failure points, and don’t feel it’s ethical to use the output. In most of the comments, the most relevant point is that the poster is not an expert in the domain they got helped. While they can observe the result, they don’t have a causal model of the situation.