Wow, interesting that your view on AI slop is more sophisticated than mine. I had the foundational understanding that AI slop was closer to a code smell than specifically a claim on project sustainability.
I mean, don’t get me wrong, my belief had deep implications on project sustainability. It was effectively that AI slop was the pattern where AI produced code would bloat the project with things that don’t make sense to a more experienced developer. Like unit testing that old function signatures are no longer used. Or choosing to implement an algorithm yourself where using another dependency would have been far more reasonable. These decisions bloat the project can kill one’s ability to reason about it. Not to mention weird abstractions in the code, *Manager classes with proxy methods hiding functionality that would have been better demonstrated in the front of the code.
You’ve pointed out that AI slop is not the pattern, but instead the result of ignorance toward the complexity of producing publicly shareable code when given tools that allow them to confidently test and ship code on a single device. That makes it more of a problem of scope of intent not matching scope of implementation, rather than a problem of AI fundamentally being shit at coding in complex situations. I mean, if it’s just that AI slop is primarily when code is unsustainable in essence, then in theory at least, AI slop could just find a route toward sustainability and then it’s defacto not slop anymore.
Am I catching that right? I might have smoked a bit too much, maybe that’s it.