I wrote this partly because nobody seems to know about Gödel who is arguably a more important figure than Turing.

The piece follows four threads where formal limits show up in AI practice today: learnable problems that mathematics cannot sort, neural networks that exist but cannot be trained, self-improving systems that dropped their safety proofs for benchmark scores, and the fact that “will this AI cause harm” is, mathematically, an unanswerable question.

The piece is long and the math is dense. I’m curious whether people see the connection as tight or as overextended—whether Gödel’s structural limits actually do constrain what we’re doing now, or whether I’m collapsing categories that should stay separate.