"Humans are often stupid in that way too"—we've said it of bots from GOFAI through LLMs + RLVR; it's always been true but not predictive or productive. I think the temptation arises because we recognize the same failure modes in ourselves and fellow meatbags. But whatever the pathology du jour may be, in us it's never quite so pathological; whereas to the bots it's crippling, the glass that the ceiling is made of.

These pathologies arise for specific reasons that point to real deficits. For each bot generation going back lo unto the dawn of time, you can trace its dominant failure modes to bad or insufficient algorithms, data, compute, or objectives.

For the current generation, the obvious culprits are RLVR (too short-term, stupid objectives, not enough compute for truly complex and long-horizon environments) and absence of continual learning (they are incorrigible dummies because in deployment it is customary to excise the part that allows them to corrugate).