We describe a research programme aimed at the construction of a single, generally intelligent agent - one competent across all tasks rather than skilled at any one. Such an agent must act in the real world through a rich sensorimotor interface, with sensors and actuators general enough for any task it may face. But that same richness makes any single task nearly impossible to learn directly. We argue that the resolution lies in abstraction, and survey our work towards this goal: discovering skills from experience, deriving compact models from those skills, and transferring both to new tasks. Skills, in particular, can be composed so that new tasks are solved with no further learning. Together, these threads work towards a single agent capable, in principle, of every task its body allows.