Assurance-Scoped Reliability for Agentic Networks: Capturing the State That Matters
Agentic networks transform accepted intents into operational services through autonomous reasoning, adaptive planning, tool use, and cross-domain coordination, but these capabilities introduce failure modes that conventional reliability measures do not fully capture. An accepted intent may still be carried out incorrectly, for example because the system acts on stale information, repeats an external action, applies only part of a change, or enters a fallback mode that quietly relaxes policy enforcement. Such failures can leave a service running and apparently healthy while its behavior is unsafe or unaccountable, with too little evidence to detect, explain, or recover from them. This article proposes Reliability Assurance Intelligence (RAI), a general assurance architecture for such systems. From the service description, RAI derives a per-service reliability profile that states what must be checked, recorded, recovered, and audited. At runtime, generic functions use the service profile to retain the durable state needed for recovery and accountability in a context capsule adapted to service conditions. Using an agentic lifecycle manager for deterministic network services as a running example, we design the RAI architecture and propose a methodology for validating its reliability assurances.