Researchers propose an agentic AI framework for generating edge case scenarios for safety assurance in autonomous systems. The framework uses local LMs, ensuring data privacy and security, and involves think, act, observe, update, and continue loops with lightweight JSON encoding. The system critiques and refines scenarios using domain-specific criteria and post-hoc clustering to create traceable evidence for safety assurance.