Production Performance Geometry and Observability for Agentic AI: The SOSM-10 Framework

This paper develops a performance oriented formulation of the Structured Organizational State-Space Model (SOSM), a triadic dynamical framework characterizing organizational behavior across Representation (R), Constraint (C), and Execution (E) manifolds. While SOSM was originally conceived as a structural model of organizational stability, this work reframes it as a computable operator whose residual error yields a unified agent performance score. A single closed form metric is introduced,enabling continuous evaluation of agent effectiveness and efficiency with out reliance on governance semantics. The formulation is integrated into a deployable R–C–E control pipeline with real time observability using Prometheus metrics and Grafana dashboards. The resulting architecture demonstrates how theoretical constructs can be operationalized into production grade monitoring for agentic AI systems.