The Agentic Shift: A Structural Redesign of Human–Machine Experience

The emergence of agentic AI systems—software capable of interpreting intent, planning actions, and executing outcomes without step-by-step instruction—creates a structural break in user experience and organizational governance. This paper introduces the Supervisory Coherence Model (SCM), a framework linking autonomy anxiety, the undo contract, negotiated interaction grammar, interruption budgeting, and episodic interface architecture as a causal system governing human–agent collaboration. Drawing on supervisory control, calibrated trust, situational awareness, and sociotechnical systems research, the paper proposes design primitives—reversibility, provenance, progressive disclosure, risk-tiered approvals, and escalation routing—that maintain supervision under autonomy. It further argues that agentic systems redistribute decision authority within organizations, creating governance and accountability gaps that require explicit institutional design.

Version: v1.0 (February 2026)

DOI: 10.5281/zenodo.18624567