> How do we actually use this in technical writing workflows or documentation experiences? I’m not sure. I was just curious to learn whether or not it would work.
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There are a few easy applications.
* When surfacing relevant documents, you can keep a list of the previous documents visited and boost in the "direction" that the customer is headed (could be an average of the previous N docs or weight towards frequency). But then you're just building a worse recsys for something where latency probably isn't that critical.
* If you know for every feature you release, you need an API doc, an FAQ, usage samples for different workflows or verticals you're targetting, you can represent each of these as f(doc) + f(topic) and find the existing doc set. But then, you can have much more deterministic workflows from just applying structure.
It's nice that you have a super flexible tool in the toolbox, but I think a lot of text based embedding applications (especially on out of domain data like long, unchunked technical docs) are just better off being something else if you have the time.
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