The author argues that world models—systems that represent environments, predict outcomes, and plan actions—are where AI is heading, evidenced by Yann LeCun, Demis Hassabis, and Fei-Fei Li all pivoting toward this approach. They're using it as a new editorial lens to track how AI systems will move from generating text to making consequential decisions.

• Three major AI researchers from different backgrounds are independently converging on world models, suggesting this is where the field's momentum is shifting
• Companies investing billions in AI aren't chasing better text generation—they want systems that can predict consequences, test scenarios, and choose actions in real environments
• The practical applications span software development (agents that understand codebases and predict edit effects), robotics (agents learning in environments with consequences), and business (moving from analyzing past decisions to testing hypothetical futures)