Co-Intelligence: The Definitive, Bestselling Guide to Living and Working with AI

by Ethan Mollick

Take, for instance, the world of classical piano. Imagine two students: Sophie and Naomi. Sophie spends her afternoons playing the same pieces she’s comfortable with over and over again. She might do this for hours on end, believing that sheer repetition will improve her skills. She feels a sense of accomplishment as she gets better and better at this work. Naomi, on the other hand, conducts her practice sessions under the guidance of a seasoned piano instructor. She begins by playing scales and then moves on to progressively more challenging pieces. When she makes mistakes, her instructor points them out, not to chastise her but to help her understand and rectify them. Naomi also regularly sets goals for herself, like mastering a particularly tricky section of a piece or improving her speed and agility on certain passages. The process is much less fun than Sophie’s experience, because Naomi’s challenges escalate with her skill, making sure she is always facing some degree of difficulty. Yet over time, even if both students clock in the same number of practice hours, Naomi will likely surpass Sophie in skill, precision, and technique. This difference in approach and outcome illustrates the gap between mere repetition and deliberate practice. The latter, with its elements of challenge, feedback, and incremental progression, is the true path to mastery.