It is ~a meme on subreddits that developers struggling to get good results out of any given model is a "skills issue."

But I think your comment drives at some authentic take on this. Skill with AI is not only crafting iterative prompts the agent will understand, but also very high domain-specific knowledge of what the prompts explore.

One without the other can result in frustration or worse.

It is a skill issue. Such developers have to take a problem, isolate it and explain it to someone/something else with enough context to be able to work with it.

It is perplexing how many developers lack this basic skill, some of them borderline lack theory of mind and are incapable to understand that other people can't see the unspoken part in their heads.

A naive hope is: you see that the LLM is so good at coding that all you need to do is supply a "yes/no" on what you want.

Turns out that understanding the technical domain is important to getting good results, even if the LLM is more capable at producing output. -- It's still a case of "garbage in, garbage out".

I think for many newbies, they see the LLM is so good at programming and so figure they don't need to learn anything. Apparently not so.

>It is ~a meme on subreddits that developers struggling to get good results out of any given model is a "skills issue."

*GIT GUD* (at prompting)