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This talk proposes the Embodied Agentic Harness, a runtime control plane between foundation models and robot skills or hardware. It combines deterministic task compilation, world-action-model prediction, layered safety checks, long-term memory, and local self-healing to turn open-ended model intent into verifiable, recoverable physical behavior.