Designing and assessing power grid resilience policies under climate stress is challenging due to cascading failures, rapid operational dynamics, and uncertainty in extreme events. This paper proposes an agentic AI framework that integrates large language models (LLMs) with validated power system simulators to autonomously support policy-informed resilience decisions under severe heatwaves.
