I don’t understand why people are so resistant to the idea that use cases actually matter here. If someone says “you’re an idiot because you aren’t writing good, structured prompts,” or “you’re too big of an idiot to realize that your AI-generated code sucks” before knowing anything about what the other person was trying to do, they’re either speaking entirely from an ideological bias, or don’t realize that other people’s coding jobs might look a whole lot more different than theirs do.
We don’t know anything about the commenters other than that they aren’t getting the same results with AI as we are. It’s like if someone complains that since they can’t write fast code and so you shouldn’t be able to either?
> We don’t know anything about the commenters other than that they aren’t getting the same results with AI as we are.
Right. You don’t know what model they’re using, on what service, in what IDE, on what OS, if they’re making a SAP program, a Perl 5 CGI application, a Delphi application, something written in R, a c-based image processing plugin, a node website, HTML for a static site, Excel VBA, etc. etc. etc.
> It’s like if someone complains that since they can’t write fast code and so you shouldn’t be able to either?
If someone is saying that nobody can get good results from using AI then they’re obviously wrong. If someone says that they get good results with AI and someone else, knowing nothing about their task, says they’re too incompetent to determine that, then they’re wrong. If someone says AI is good for all use cases they’re wrong. If someone says they’re getting bad results using AI and someone else, knowing nothing about their task, says they’re too incompetent to determine that, then they’re wrong.
If you make sweeping, declarative, black-and-white statements about AI coding either being good or bad, you’re wrong. If you make assumptions about the reason someone has deemed their experience with AI coding good or bad, not even knowing their use case, you’re wrong.
