alt Hacker News>agents need strong type systems and narrow guardrails
I read the second paragraph of linked article as saying close to the opposite of that, particularly,
"the model can often avoid the mistake before the compiler ever sees the code. And as the models get better, the relative value of catching every possible issue at compile time changes."
In other words, LLMs are much less likely than humans to make dumb, fat-finger mistakes, and, when they do, are able to catch and fix them more quickly, ergo the value of type checking has fallen.
Everything in the prior sentence is, obviously, highly debatable. But it felt like part of the premise.
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i read that too, but i am highly skeptical. i wish the author would investigate that claim and provide some actual examples substantiating it.
My experience with Claude and Ruby, Python, Javascript is similar: it's pretty good at finding the array of strings that was passed to a method instead of an array of integers. Think about record ids coming from a JSON API call. Or the single value instead of an array. I don't remember which Python XML parser is fond of returning one or the other according to the cardinality of the sub elements. Anyway, not only it writes the code to handle those cases but it traces the code and it finds the bugs. So type checking at coding time and who cares about writing the type annotations. They would be probably good to speed up the code at runtime but none of my customers use them and none of them is concerned about the current response time of their systems.