> With LLMs instantly see "how it's done" for my exact problem case which makes me learn way faster.
No, you see a plausible set of tokens that appear similar to how it's done, and as a beginner, you're not able to tell the difference between a good example and something that is subtly wrong.
So you learn something, but it's wrong. You internalize it. Later, it comes back to bite you. But OpenAI keeps the money for the tokens. You pay whether the LLM is right or not. Sam likes that.
This makes for a good sound bite but it's just not true. The use case of "show me what is a customary solution to <problem>" plays exactly into LLMs strength as a funny kind of search engine. I used to (and still do) search public code for this use case to get a sense of the style and idioms common in a new language/library
and the plausible set of tokens is doing exactly that.
No, you see a plausible set of tokens that appear similar to how it's done, and as a beginner, you're not able to tell the difference between a good example and something that is subtly wrong.
So you learn something, but it's wrong. You internalize it. Later, it comes back to bite you. But OpenAI keeps the money for the tokens. You pay whether the LLM is right or not. Sam likes that.