The tool we use for our docs AI answers lets you mine that data for feature requests. It generates a report of what it didn't have answers for and summarizes them as potential feature gaps. (Or at least what it is aware it didn't have answers for).
People seem more willing to ask an AI about certain things then be judged by asking the same question of a human, so in that regard it does seem to surface slightly different feature requests then we hear when talking to customers directly.
We use inkeep.com (not affiliated, just a customer).
> We use inkeep.com (not affiliated, just a customer).
And what do you pay? It's crazy that none of these AI CSRs have public pricing. There should just be monthly subscription tiers, which include some number of queries, and a cost per query beyond that.
I feel like I should be writing with the goal that the end reader is actually an LLM. The LLM will be the one spitting out the answers to the actual users via things like co-pilot, but I am not sure how that should change my approach to structure or level of detail in docs. Heavier on the number of code examples?
- can also finetune with RLHF or modify the Q-A pairs directly
- then you have a final model finetune once the Q-A pairs look good
- then you use RAG over the corpus and the Q-A pairs because the model doesn't remember all the facts
- then you have a bullshit detector to avoid hallucinations
So the corpus is very important, and the Q-A pairs are also important. I would say you've got to make the corpus by hand, or by very specific LLM prompts. And meanwhile you should be developing the Q-A pairs with LLMs as the project develops - this gives a good indication of what the LLM knows, what needs work, etc. When you have a good set of Q-A pairs you could probably publish it as a static website, save money on LLM generation costs if people don't need super-specific answers.
To add to the current top-scoring comment, though (https://news.ycombinator.com/item?id=42326324), one advantage of an LLM-based workflow is that the corpus is the single source of truth. It is true that good documentation repeats itself, but from a maintenance standpoint, changing all the occurrences of a fact, idea, etc. is hard work, whereas changing it once in the corpus and then regenerating all the QA pairs is straightforward.
You can "Decline optional cookies" and browse without being logged in, at least in Europe. (Just tested in a private window, FB/Meta is only allowed in a separate container on my computer.)
Sure, but I need an Apple account to use an iPad or an iPhone, but I don't need to log into my Apple account to browse hardware on my computer.
I hate Facebook in general, but I like that Meta is investing in a hardware platform. I can live with needing an account to use a piece of hardware, if the hardware is good. I have a quest3, I like it. But they care so much about tracking you that it undermines their hardware and the adoption of it.
https://codepen.io/dsmmcken/pen/WbwYOEQ?editors=0100
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