Pre-Deployment Checks and Runtime Safety for AI Agents: Three Recent arXiv Papers
Pre-Deployment Checks and Runtime Safety for AI Agents: Three Recent arXiv Papers Three recent arXiv papers look at a shared problem in AI agents: how to reduce risk before deployment, and how to add safety once an agent is already acting in the world. One paper focuses on pre-deployment assurance for enterprise AI agents through ontology-grounded simulation and trust certification. Another examines a runtime safety question that sounds simple but is difficult in practice: when should a system intervene in an autonomous agent’s behavior? A third studies agentic RAG systems and the way early-stage errors can spread through later steps as cascading hallucination. Taken together, these papers suggest that agent safety is not just about model quality, but also about verification before launch and control during execution. [S1][S6][S8] [S1] [S6] [S8] Introduction: what these papers are and why they fit together The first paper, "Toward Pre-Deployment Assurance for Enterprise AI Agen...