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Any popular examples to support your claim?

My claim is supported by the post article and many points there, for example. Another example is my own experience working with python ecosystem and ai/ml libraries in particular. With rare exceptions (like pandas) it is mostly garbage from DevX perspective (in comparison of course).

But I admit my exposure is very limited. I don’t work in ai area professionally (which is another example of my point btw, lol))






pytorch, tensorflow, numpy there are quite a few examples ai/ml has been steadily more commodetized, so it's far from only being developed by mathematicians. Hence every highschools student and his mother has an AI startup now. (And I'm not even mad, it's actually very exciting to see what people come up with nowadays)

Unfortunately when someone says "AI" these days they're not talking about pytorch, tensorflow, or numpy. They're talking specifically about LLMs, which are built on top of those tools but which do show the tendency that OP is identifying to generally appear to be vibe-coded over a weekend rather than designed by a rigorous engineering process like what we've come to expect from foundational tech like web browsers or operating systems (or, yes, pytorch or numpy).

Which LLMs seem to be vibe-coded over a weekend?

Do you perhaps mean small language models?

I doubt Llama or Deepseek were vibe coded..


Sorry, I see that was confusing. I meant tooling for LLMs. Things like Langchain come to mind.

> pytorch, tensorflow, numpy

I would use those as examples of an exception from my generalized point.

Anything else? Just a handful of tools you can call professional of thousands and thousands used everyday?




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