> I am still trying to sort out why experiences are so divergent
I suspect part of it is that there still isn't much established social context for how to interact with an LLM, and best practices are still being actively discovered, at least compared to tools like search engines or word processors.
Search engines somewhat have this problem, but there's some social context around search engine skill, colloquially "google-fu", if it's even explicitly mentioned.
At some point, being able to get the results from a search engine stopped being entirely about the quality of the engine and instead became more about the skill of the user.
I imagine, as the UX for AI systems stabilizes, and as knowledge of the "right way", to use them diffuses through culture, experiences will be less divergent.
> I suspect part of it is that there still isn't much established social context for how to interact with an LLM, and best practices are still being actively discovered, at least compared to tools like search engines or word processors.
Likely, but I think another big reason for diverging experience is that natural language is ambiguous and human conversation leaves out a lot of explicit details because it can be inferred or assumed when using natural language.
I can't speak for others, but it's difficult for me to describe programming ideas and concepts using natural language - but, that's why we have programming languages for this. A language that is limited in vocabulary, and explicit in conveying your meaning.
Natural language is anything but, and it can be difficult to be exact. You can instinctively leave out all kinds of details using natural language, whereas leaving out those details in a programming language would cause a compiler error.
I've never really understood the push toward programming with natural language, even before LLMs. It's just not a good fit. And much like how you an pass specific parameters into Google, I think we'll end up getting to a place where LLMs have their own DSL for prompting to make it easier to get the result you want.
I suspect part of it is that there still isn't much established social context for how to interact with an LLM, and best practices are still being actively discovered, at least compared to tools like search engines or word processors.
Search engines somewhat have this problem, but there's some social context around search engine skill, colloquially "google-fu", if it's even explicitly mentioned.
At some point, being able to get the results from a search engine stopped being entirely about the quality of the engine and instead became more about the skill of the user.
I imagine, as the UX for AI systems stabilizes, and as knowledge of the "right way", to use them diffuses through culture, experiences will be less divergent.