What the Data Shows

In the summer of 2025, doctoral student Xingqi Maggie Ye and Associate Professor Aruna Ranganathan of UC Berkeley's Haas School of Business began what would become the most rigorous empirical study of AI's effect on work thus far. They embedded themselves in a 200-person technology company for eight months and focused on observation and qualitative work. They sat in the offices, attended the meetings, watched the screens, talked to the workers, and documented what happened when generative AI tools entered a functioning organization. Before you read further, it’s important to note that this experiment predated the rubicon of the “orange pill” I describe in this book.

Their findings, published in the Harvard Business Review in February 2026, confirmed some of what Han's philosophy predicted. They also complicated it in ways that Han's philosophy cannot easily accommodate.

Finding One: AI does not reduce work. It intensifies it. Workers who adopted AI tools worked faster, took on more tasks, and even expanded into areas that had previously been someone else's domain. The boundaries between roles blurred, too. Designers started writing