Models like Anthropic’s Claude Computer Use and OpenAI’s Operator are early commercial examples. Research models like UI-TARS, Agent-S2, and CogAgent are pushing the boundaries further. But training any of these systems requires massive amounts of interaction data generated inside real OS environments — and that’s where things get expensive and complicated fast.
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If you already validate at the boundary and assert at runtime, you know what invariants are. The spec just checks them across every state the system can reach instead of the states your tests happen to visit.
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