Robot manipulation is a complex task that requires visual perception, physical reasoning, planning, and closed-loop control. General-purpose foundation models (FMs) have grown remarkably capable of some of these, especially perception and reasoning. Inspired by the growing ability of FM-powered agents to operate software through visual interfaces, we ask whether that same competence suffices to control a robot directly given the right interface. We present VIA (Visual Interface Agent), a framework that recasts robot control as an agentic task where an off-the-shelf agent drives a manipulator directly through an interface. The interface is a virtual workspace of interactable visual components where the agent can probe pixels of interest with mouse-like tools and command a virtual end-effector to set new target poses with a small set of general tools. We show that VIA enables agents of varying capabilities to perform diverse tabletop manipulation tasks in simulation. We also use VIA to drive an off-the-shelf mobile manipulation robot in the real world to complete tasks that require both navigation and manipulation. Both settings are zero-shot, requiring no robot training or additional action primitives. Performance scales well with the size and strength of the underlying FMs. These results suggest that frontier agents already possess skills that transfer directly to robot control given the right interface: your coding or computer-use agent is, in a sense, secretly a robot-control agent.

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