Ask HN: How do you keep documentation up to date with AI generated code?
I've seen numbers like 75% of code at Google is AI generated, huge %s of code overall is AI generated, open source projects overwhelmed with "slop" PR requests.
It's pretty undeniable that AI code is here to stay - so on your teams / companies how are you managing staying up on PR reviews, and documentation?
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[ 3.0 ms ] story [ 33.0 ms ] threadIf someone asks about the internals of the projects it is - you want the truth, you can't handle the truth.
1. Update the documentation first, to describe the desired / expected behaviour.
2. Followed by the code changes that implement the documented behaviour.
PRs: for any behaviour change, feature addition etc: patch must include corresponding documentation updates. If not: reject.
Iirc that was (still is?) OpenBSD's approach to keeping docs up-to-date.
any time ai does any work, it ensures the ADRs are up to date.
it is part of the execution workflow.
maintain the todos which are a record of work that was done. ADRs have the latest current documentation.
Anyway, for now we're assisting to either outdated Docs (Coding Agents often don't even look at them), or to over-bloated ones (the slop is not just in the code). We should probably still find a balance between human readable docs (e.g. README.md) and LLM-tailored ones (e.g. llms.txt)
Obviously if you're using cloud solutions who both generate garbage faster and cost money per garbage, this doesn't work.