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Comment by fragmede | Hacker News Reader

Plus, it's a generic question; "give a helm chart for velero that does x y and z" is as proprietary as me doing a Google search for the same, so you're not giving proprietary source code to OpenAI/wherever so that's one fewer thing to worry about.

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Yeah, I tend to agree. The main reason that I use AI for this sort of stuff is it also gives me something complete that I can then ask questions about, and refine myself. Rather than the fragmented documentation style "this specific line does this" without putting it in the context of the whole picture of a completed sample.

I'm not sure if it's a facet of my ADHD, or mild dyslexia, but I find reading documentation very hard. It's actually a wonder I've managed to learn as much as I have, given how hard it is for me to parse large amounts of text on a screen.

Having the ability to interact with a conversational type documentation system, then bullshit check it against the docs after is a game changer for me.

that's another thing! people are all "just read the documentation". the documentation goes on and on about irrelevant details, how do people not see the difference between "do x with library" -> "code that does x", and having to read a bunch of documentation to make a snippet of code that does the same x?

I'm not sure I follow what you mean, but in general yes. I do find "just read the docs" to be a way to excuse not helping team members. Often docs are not great, and tribal knowledge is needed. If you're in a situation where you're either working on your own and have no access to that, or in a situation where you're limited by the team member's willingness to share, then AI is an OK alternative within limits.

Then there's also the issue that examples in documentation are often very contrived, and sometimes more confusing. So there's value in "work up this to do such and such an operation" sometimes. Then you can interrogate the functionality better.

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