The increasing capability of artificial intelligence models to autonomously identify software vulnerabilities at unprecedented speed and scale has significantly altered the balance between vulnerability discovery and remediation. This development has exposed the technical debt accumulated by the software industry, which has historically prioritized rapid deployment over secure-by-design engineering practices. As a result, the industry is now facing a surge in identified vulnerabilities, with frontier AI models capable of discovering exploitable weaknesses that were previously unknown. The situation is further complicated by the fact that many of these vulnerabilities are in legacy systems, making remediation a complex and challenging task1. This shift has significant implications for security practitioners, who must now reassess their vulnerability management strategies to account for the accelerated pace of discovery and the increased complexity of remediation, making it essential to reevaluate their security posture in light of these emerging threats.