Tacit Knowledge Is Dangerous
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Tacit Knowledge Is Dangerous
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Re: Tacit Knowledge Is Dangerous
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#5Yes, documentation is important and should be kept up to date. People should consult documentation, and update it if it turn out to be old. But real, up to date, or deep understanding does not exist outside of human brains.
Re: Tacit Knowledge Is Dangerous
#6In my experience, tribal knowledge, which also includes cultural inculcation, can be the difference between success and failure. Sometimes, on the success side, and, sometimes, on the failure side.
The main thing about "tribal knowledge," is that it relies on long-term association/employment, and that is not something we see much of, these days.
Re: Tacit Knowledge Is Dangerous
#7Tacit knowledge is not the same as tribal knowledge. Tribal knowledge is undocumented stuff. Tacit knowledge is about things that cannot be learned from documentation.
Riding a bike is an example of tacit knowledge. No amount of reading about the theory of riding a bike will teach you how to ride a bike. You have to hop on the bike and fail a few times until you figure it out.
In software engineering, tacit knowledge are things like "How to factor a system so 50 engineers can work together without stepping on each other's toes" and "How to structure your files to naturally reduce architectural complexity" and "How do you write a useful test that isn't just writing tests for the sake of tests". You can read about these things all you want, but you can only learn by experience. You have to get it wrong a bunch of times, see how it was wrong, and then you eventually start doing it less wrong.
Learning by example also works to speed up the process.
But that's not the same as undocumented.
Re: Tacit Knowledge Is Dangerous
#8Perhaps such products are in the works, but I would love a private company LLM that slurps all messages, docs, meetings, and becomes an oracle that can be relied upon. Perhaps it could even infer tacit knowledge even when it's not explicit in any docs, since it could abstract principles and concepts from the maze of data.