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AI model does not know special insight into how model itself was trained. All it tells you is it's prediction of expected explanation.
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I checked this, and Claude says "it's a real term of art from Michael Feathers' Working Effectively with Legacy Code (2004), where he defines it as a place you can alter a program's behavior without editing in that place."

While I agree the model doesn't have insight into how it was trained I do think the history of the term itself is interesting.

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yeah but I didn't prompt it in a way where I tried to get such an answer, it gave an entire boilerplate rundown just from like me asking "what's up with the 'seams'?"

I might be wrong, but usually it'd be a lot less deliberate, and at least in my mind it wouldn't be surprising if they were heaving training these on these specific "best practices" books/methodologies and thus picking up lingo from them

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