My agents fail most often not at planning but at predicting consequences — they take actions whose side effects a human would foresee instantly. Explicit world models feel like the obvious fix, yet the big labs seem to bet on scale and inference-time search instead. Is there a principled reason world models lost, or is it just engineering fashion? I'd love to hear from people who've tried both.