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I agree there is a spectrum, but we at least have to be honest with ourselves: are we really sure AI generated code is following the spec? On the other hand, with progress in proof automation, it is now feasible to formally verify AI generated code, and that allows us to specify program behavior formally, and a formal specification is again a program in itself.

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I think with the AI it's not only question about following the spec, but about the completness of the spec. Before the AI, if specification wasn't complete, then program would lack of a feature, won't start correctly or crash. Nowadays, agents will happily fill any missing specification parts with random stuff, often looking reasonable at the first glance. This random content can be different with every iteration of the LLM work.

To find the right position in this spectrum, I think we need to find a level of specification that we care about.

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