From Studying Complex Systems to Engineering Them in the Era of Agentic AI: The Complexity Threshold, Semantic Coupling, and the Governability Boundary

Agentic systems are entering production as compositions of models, tools, and checks. Yet the sociotechnical operational environment that emerges around them is rarely treated as an object of engineering. Cybernetics, the Viable System Model, systems safety analysis, normative MAS, autonomic computing, and layered management of adaptation each supply part of a response, but none combines them into a single verifiable relation between normative meaning and actual behaviour. The object of engineering changes at an operational threshold: this integrative conceptual review defines that threshold for complex agentic systems. The threshold requires the joint presence of semantic autonomy, closed-loop environmental interaction, and systemic interdependence; adaptive reconfiguration distinguishes a narrower subclass. From these conditions, the article derives six systemic architectural failure modes and predicted production indicators. It then specifies semantic coupling as a bidirectionally verifiable relation among normative meaning, coupling-relevant representations of operational structure, and actual behaviour. Six engineering principles and a diagnosis of the governability boundary follow, with a worked illustration. Semantic coupling is necessary to maintain this relation but insufficient for governability: the capacity of the system as a whole to keep externally significant behaviour within authorised bounds through adequate observation, coordination, control, causal reconstruction, and governed change. Governability additionally requires independent access to operational reality, orientation towards the environment, identity, and meta-governance. The work claims neither empirical validation of the failure-mode catalogue, nor automatically correct translation of normative language into constraints, nor recovery of a trajectory-level guarantee. The attainable guarantees concern boundaries, invariants, enforcement points, attributable evidence, and governed change.