Habitat as the Missing Layer in Physical AI Deployment

Physical AI deployment, autonomous systems that perceive, decide, and act in the physical world under real consequence, is failing at the pilot-to-production boundary at non-trivial rates across multiple industrial settings. One underlying reason this paper examines is that existing integration disciplines, developed over decades for deterministic software and traditional industrial systems, are structurally under-fitted to the distinct demands of probabilistic, learning-based agents operating where errors are irreversible and institutional acceptance gates scaling.