Shifting Ground: Architectural Maneuver and Economic Deterrence in the Era of Autonomous Cyber Adversaries

The proliferation of autonomous, agentic AI in offensive cyber operations has fundamentally altered the offense-defense balance. As evidenced by recent reporting on automated intrusions achieving marginal costs of approximately $50 per successful breach, the traditional defensive cycle(detection, alerting, and human-gated response) is outpaced by machine-speed execution. This paper proposes a structural framework, termed "Shifting Ground," for defending networks against autonomous adversaries. Drawing on systems thinking, organizational theory, and recent literature on moving target defense, we argue that static fortifications are inherently obsolete against learning agents. Instead, defense must prioritize the invalidation of the adversary's world model at the moment of commitment, paired with economic attrition models. The paper further delineates the boundaries of this framework, utilizing a typology of adversarial threat models (bounded versus unbounded budgets, in-battlespace versus out-of-battlespace vectors) to prevent the scope overreach common in commercial security postures. Finally, it addresses the necessary institutional architecture, arguing that technical postures are insufficient without independent verification, sustainable defense economics, and organizational cultures that institutionalize dissent.