tl;dr: AI systems are rapidly approaching superhuman mathematical ability, making the traditional signals of mathematical work (papers, theorems, PhD theses) unreliable indicators of human understanding or expertise. The author argues academic math must adapt by decoupling "producing mathematics" from "producing mathematicians"—shifting PhDs toward rigorous oral defenses of deep expertise, interviewing grad admissions, and rewarding exposition, seminars, and research-program building over paper output. Rather than resisting AI or clinging to current institutions, mathematicians should embrace an explosion of new mathematics while building community structures that cultivate genuine human understanding.