Banger paper from Meta Superintelligence Labs on self-improving agents. (bookmark it) It's hard to know exactly what drives self-improvement, since so many variables are at play (notes, skills, tool calls between runs, etc.). Meta researchers explore and discuss a way to measure whether self-improvement pays off. They call it agent plasticity. It is the gain on held-out tasks per dollar spent on learning, with model weights frozen and every run starting from a fresh context. They find that…