I think something people really misunderstand about these tools is that for them to be useful outside of very general, basic contexts, you have to already know the problem you want to solve, and the gist of how to solve it - and then you have to provide that as context to the LLM.
That's what the point of these text documents is, and that's why it doesn't actually produce an efficiency gain the majority of the time.
A programmer who expects the LLM to solve an engineering problem is rolling the dice and hoping. A programmer who has solved an engineering problem and expects the implementation from the LLM will usually get something close to what they want. Will it be faster than doing it yourself? Maybe. Is it worth the cost of the LLM? Probably not.
The wild estimates and hype about AI-assisted programming paradigms come from people winning the dice roll on the former case and thinking that result is not only consistent, but also the same for the latter case.
That's what the point of these text documents is, and that's why it doesn't actually produce an efficiency gain the majority of the time.
A programmer who expects the LLM to solve an engineering problem is rolling the dice and hoping. A programmer who has solved an engineering problem and expects the implementation from the LLM will usually get something close to what they want. Will it be faster than doing it yourself? Maybe. Is it worth the cost of the LLM? Probably not.
The wild estimates and hype about AI-assisted programming paradigms come from people winning the dice roll on the former case and thinking that result is not only consistent, but also the same for the latter case.