A Trace-Based Assurance Framework for Agentic AI Orchestration: Contracts, Testing, and Governance
In Agentic AI, Large Language Models (LLMs) are increasingly used in the orchestration layer to coordinate multiple agents and to interact with external services, retrieval components, and shared memory. In this setting, failures are not limited to incorrect final outputs. They also arise from long-horizon interaction, stochastic decisions, and external side effects (such as API calls, database writes, and message sends). Common failures include non-termination, role drift, propagation of unsupported claims, and attacks via untrusted context or external channels. This paper presents an assurance framework for such Agentic AI systems. Executions are instrumented as Message-Action Traces (M...
| Authors | Ciprian Paduraru, Petru-Liviu Bouruc, Alin Stefanescu |
|---|---|
| Primary category | cs.MA |
| Published | 18 March 2026 |
| Last updated at source | 18 March 2026 |
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