The emergence of Anthropic's Claude Mythos has significant implications for security teams, as it accelerates AI-driven vulnerability discovery and exploit development. This shift is exposing critical gaps in asset visibility, patch management, and security operations across both IT and operational technology (OT) environments. According to Rik Ferguson of Forescout, the rapid development of exploits is outpacing defenders' ability to respond, highlighting the need for improved visibility and more efficient security operations. The increased risk surface created by large language model (LLM) developments like Claude Mythos demands a proactive approach to vulnerability management and incident response1. As a result, security practitioners must reassess their strategies to address the expanding threat landscape and prioritize investments in technologies that enhance asset visibility and automate security workflows, so they can effectively counter the heightened vulnerability risks posed by AI-driven exploit development.