Basically, we use AI to do a lot of formatting for our manuals. It's most useful with the backend XML markups, not WYSIWYG editors.
So, we take the inputs from engineers and other stakeholders, essentially in email formats. Then we pass it through prompts that we've been working on for a while. Then it'll output working XML that we can use with a tad bit of clean-up (though that's been decreasing).
It's a lot more complicated than just that, of course, but that's the basics.
Also, it's been really nice to see these chat based AIs helping others code. Some of the manuals team is essentially illiterate when it comes to code. This time last year, they were at best able to use excel. Now, with the AIs, they're writing Python code of moderate complexity to do tasks for themselves and the team. None of it is by any means 'good' coding, it's total hacks. But it's really nice to see them come up to speed and get things done. To see the magic of coding manifest itself in, for example, 50 year old copy editors that never thought they were smart enough. The hand-holding nature of these AIs is just what they needed to make the jump.
Did you have any scripts or other explicit “rules-based” systems to do this before? Is it a young company?
It sounds like a pretty old and common use case in technical writing and one that many organizations already optimized plenty well: you coach contributors to aim towards a normal format in their email and you maintain some simple tooling to massage common mistakes towards that normal.
What prompted you to use an LLM for this instead of something more traditional? Hype? Unfamiliarity with other techniques? Being a new company and seeing this as a more compelling place to start? Something else?
Basically, we use AI to do a lot of formatting for our manuals. It's most useful with the backend XML markups, not WYSIWYG editors.
So, we take the inputs from engineers and other stakeholders, essentially in email formats. Then we pass it through prompts that we've been working on for a while. Then it'll output working XML that we can use with a tad bit of clean-up (though that's been decreasing).
It's a lot more complicated than just that, of course, but that's the basics.
Also, it's been really nice to see these chat based AIs helping others code. Some of the manuals team is essentially illiterate when it comes to code. This time last year, they were at best able to use excel. Now, with the AIs, they're writing Python code of moderate complexity to do tasks for themselves and the team. None of it is by any means 'good' coding, it's total hacks. But it's really nice to see them come up to speed and get things done. To see the magic of coding manifest itself in, for example, 50 year old copy editors that never thought they were smart enough. The hand-holding nature of these AIs is just what they needed to make the jump.