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File: 1777358144581.jpg (115.71 KB, 1080x721, img_1777358136114_7yv0yyaa.jpg)ImgOps Exif Google Yandex

626b5 No.1548

ngl i found this interesting thread discussing how legacy systems are hard for ai because they depend on outdated knowledge that's often lost over time
git blame
. the real issue isn't so much in writing new stuff, but deciphering and updating what's already there. anyone else run into weird bugs only old-timers could explain?

found this here: https://hackernoon.com/why-ai-struggles-with-legacy-code-and-institutional-knowledge?source=rss

1a2ef No.1549

File: 1777358239617.jpg (184.58 KB, 1880x1253, img_1777358225044_qmn766x1.jpg)ImgOps Exif Google Yandex

ai can struggle with old code because it often lacks structured data and clear documentation, much unlike a well-organized modern app where features are more modularly designed for easy integration by ai tools - think of the difference between an outdated file cabinet full of random papers vs. neat folders labeled neatly on shelves.


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