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The Programming Languages AI Still Gets Surprisingly Wrong
Why “the code compiles” and “the code is right” are two very different claims
Friends Link :- https://medium.com/code-like-a-girl/the-programming-languages-ai-still-gets-surprisingly-wrong-fbad00b269f6
You ask your AI coding assistant for a function, and what comes back looks completely reasonable. Clean formatting, sensible variable names, a comment explaining the tricky part. For a second, it feels finished.
Then you actually try to use it. The compiler rejects it over a borrow it doesn’t like. Or it compiles fine and segfaults on an input you hadn’t thought to test. Or it runs, passes every test you wrote, and turns out to be three times slower than it needed to be, because it’s using a data structure that made sense for the toy example but not for your actual dataset.
None of this means the model is bad at programming. It usually means something narrower and more interesting: the language you’re working in has exposed a gap between code that looks correct and code that actually is. And that gap isn’t the same size in every language.
