You build a perfect model. You simulate a city. You introduce a new policy: a universal basic income, funded by a micro-tax on digital ad views. The model predicts a 12% rise in leisure-based small businesses, a 5% drop in stress-related hospital visits, and a stable economic uplift. It’s flawless. You deploy it.What the model didn’t, and couldn’t, simulate was Mrs. Henderson in 4B. Mrs. Henderson, now freed from her clerical job, doesn’t start a pottery business. She becomes a one-woman investigative journalist, using her free time to uncover the corrupt municipal contracting that built her apartment block. She starts a blog. It goes viral. There are protests. The city council resigns. This is The Law of Unforeseen Reactions—not unforeseen events, but unforeseen human reactions. The model understood economics. It did not understand spite, passion, boredom, or righteous fury.We model humans as rational agents with preference curves. We are not. We are narrative engines. We are vengeance seekers. We are creatures of sudden, glorious, and catastrophic inspiration. A model can predict what you should do. It cannot predict what you will do when you’re feeling particularly alive, or particularly pissed off on a Tuesday afternoon.My controversial take is this: The only way to model this is to deliberately introduce chaotic human agents into the training simulation. Not rational agents, but Shakespearean agents—driven by jealousy, pride, sudden love, or a misplaced sense of honor. You need to train your World Model on ten thousand simulations of Hamlet and Macbeth, not just on census data. Because the future isn’t built by the average. It’s shattered and remade by the outlier, the obsessed, the mad, and the unexpectedly brave.This has been The World Model Podcast. We don’t just simulate actions—we must learn to simulate the human heart, in all its glorious, inconvenient, and world-breaking madness. Subscribe now.