Observer-First Containment for Autonomous AI Systems: A Jar-Wall Authorization Architecture

Evaluating autonomous or agentic AI systems creates a measurement problem: the instrumentation required to observe a system can itself alter the system, obtain excessive authority, or become an unexamined execution path. Conventional sandboxing addresses some execution risks but does not by itself establish that observers, telemetry services, orchestration layers, or recovery mechanisms remain outside the authority of the system being tested. This paper presents an observer-first containment architecture built around a strict activation boundary called the jar wall. The design separates preparation from authority, observation from intervention, and configuration from live activation. An observer may be fully constructed, tested, signed, and staged while remaining incapable of attaching to a live target until a fresh, explicitly scoped authorization event is materialized.