A Reinforcement Learning AI agent learns to inhabit and move a quadruped body. The performance optimisation process takes several days and includes millions of steps, as the model progresses from incapability to competence. These behaviours are then transferred onto 3D scans of real people, which are ‘re-skinned’ with metal, stone and other materials. Finally, a second RL agent analyses the behavioural performance and re-orders movement in real-time according to abstract aesthetic goals. This results in the breakdown of performance - instead a disjointed and sometimes impossible sequence of body motion appears. A live deconstruction of goal-seeking at once relatable and alienating. The real-time dynamic artworks can run in perpetuity.