Copilot for Docs

I'm so used to links not being underlined, I tried clicking the orange 'Copilot for docs' about 4 times !

Love how 3/4 reactions are engineers from GitHub rather than customers.

Is it possible to teach llm to read issues and answer questions such as how do I get angular 17 to output to dist instead of dist/browser with you can't do this with angular. However, in your CI CD pipeline, you can do a mv or robocopy or bla bla bla depending on context?

https://github.com/angular/angular-cli/issues/26028

It would be very useful because there are so many edge cases that aren't covered in the docs but are probably available in some kind of WON'T FIX issues.

Love how the AI hype went from "it's going to write code for you!" to "oh okay, maybe just boring boilerplate" to "it's basically a glorified search" (and it probably won't be great at that, either).

Great, all I ever wanted was a hallucinated manual.

So how do you actually use this? Or is it just a design/proposal?

I switched to Cursor (VSCode fork) a couple of months ago. It does this already and I haven’t looked back since. Especially as the copilot extension (along with all my others) work out of the box.

It has full knowledge of your entire codebase rather than being limited to currently open files (I assume embeddings with RAG) and will index documentation (or any other URL).

I find it especially useful for things like Swift/SwiftUI APIs given how quickly they can evolve, not to mention copilot’s other limitations when it comes to languages beyond JS/TS, Python, etc

Who made this website? I feel like I am in a vegas casino and having trouble focusing.

It was unclear in the quick pitch but I am wondering if they essentially throwing RAG/search on top of a GPT model? I am guessing so because I cannot imagine you could train the model on such a limited source and get meaningful information. If thats the case perhaps this will be interesting but I think there are other interesting angles to this approach than focusing on a single library/codebase.

This is an excellent idea, but it feels like an obvious application of RAGs (or a trivial agent to build with OpenAI’s latest ‘GPTs’ tool). Not dismissing the necessary and valuable work—it’s “obvious” in the way sleeping after a long day is obvious.

What I’d love to see is such an agent *learn* from the interactions with people asking:

* What questions they ask more often than other framework, and how can the documentation clarify that (explicitly or not);

* Can you detect when questions betray a naive grasp of the problem and when the person asking would benefit from dedicated training, not just a quick answer;

* Can an LLM structure programming concepts and suggest ways to describe a framework that would help people make sense of what each framework actually is?

Is there a way to do the inverse: produce a rough draft of a complete documentation site based on reading a codebase?

What is copilot for docs? This page, rather infuriatingly, doesn’t explain! Is it part of copilot? A product? An experiment…?

Copilot for docs is ___

We're using kapa.ai for this right now, pretty happy with them.

It's an LLM trained on our docs, openapi spec, github issues, and forum posts.

Definitely been helpful to our customers and users to find answers/pointers to docs more quickly.

So another RAG product? I do like the ability to specify your knowledge and qualification level to help steer the output.

I always assumed copilot and ai code assistants were replacing docs, for most use cases. I guess I'd rather just ask the question I have, when I have it, instead of having copilot preemptively create docs for questions it thinks I'll have later on.

I unironicly love the sliders below the search box.

Hate how they announce this product by shitting on the hard work of docs teams.

I get that docs are uneven in quality but there’s also been what I think is a renewed focus on quality & interactive examples. There’s some truly fantastic OSS documentation out there.

The tone of this just didn’t sit right with me.

Ok, so why do we need stackoverflow anymore?

This is a great use of AI