Policies trained to evolve quantum simulations now generalise to entirely new starting conditions and scale up to systems ten times bigger than those used during training. Previously, approximation errors were considered unavoidable imperfections; this work instead demonstrates how they can be harnessed as correctable resources within long-time simulation. Such orchestration unlocks more efficient use of existing computational power and expands the scope of achievable modelling.