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73 sats \ 3 replies \ @k00b OP 19h \ on: Grinding down open source maintainers with AI devs
I think underpinning the problem is the cost of creating a solution. A human approaching the problem will spend ample time trying to figure out how to be most surgical - what's the best approach to take to make my effort small and worthwhile. When the code generation is easy, folks lack concern for surgical coherence because it makes no difference to them.
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There's an analogous problem in academia, which is that as the cost of compute went down and the ease of statistical programming went up, papers started getting longer and longer. Mostly, they were filled with dozens of "robustness tests" which are basically checking that your results still hold under small alternative assumptions for the model.
But most people now agree that it's gotten out of hand, that these robustness tests don't really add much, and it severely undermines the readability of the papers by being so long
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Good point: in the AI era, developer "laziness" is a feature not a bug.
Laziness - in this sense - is isomorphic to solving for the path of least resistance, which like the traveling salesman problem or other optimizations is actually really hard. Humans probably use heuristics to get close to lower bound solution which is what "good code" looks like.
Personally, I expect the path of least resistance changes with 2025-era coding agents, and so we'll actually end up changing our metrics for what good code is.
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