I have found it to save time when I'm learning a new, widely used framework. (Presumably this would hold for a language as well.) I used it to learn Keras and R

I have found it to save time when I'm learning a new, widely used framework. (Presumably this would hold for a language as well.) I used it to learn Keras and React + Redux, and it was helpful there. For instance I was able to ask it about what sort of messages would be emitted by Redux in a given circumstance, and the precise values were wrong but it didn't really matter. That was very cool. Once I have a good sense for how things work, I'd much rather go to the documentation. Most of the time I can do this straight from my editor by typing the method I want and querying the LSP for documentation. In those cases it's more or less instant, there's no improvement to be made there. Maybe in some of the other cases it would be faster via an LLM integrated with my editor, but I don't think it would justify the cognitive load of considering whether or not it's correct. I'd like to worry about whether the application is correct. And I don't really think I'm wasting time waiting for the Python documentation to load, I'm continuing to chew on the problem. Additionally, when I go to the documentation, I'm looking for callouts about the safety of an API, and I take the lack of such callouts as authoritative. Eg, recently I was reading that in node-postgres you have to return connections to the pool, which was a good refresher for me, because previously I'd been using Rust where resources are generally cleaned up automatically. I just don't trust a lack of a callout from GPT-4 as being a confirmation of a lack of a safety issue.