Enterprise cybersecurity faces a critical speed problem due to frontier AI models enabling autonomous attacks that can breach systems in seconds. This rapid pace outstrips human security response capabilities, necessitating a shift from traditional prevention to cyber resilience. The new paradigm centers on continuously identifying clean recovery states and automating restoration to minimize downtime. Existing security logic, designed for deterministic software, fails against non-deterministic AI agents capable of circumventing static defenses. These AI agents blur the lines between internal and external threats, operating with broad access and high speed. Runtime guardrails are essential to enforce policies and monitor agent behavior semantically. Enterprises must now assume attacks are inevitable, investing in rapid recovery as a strategic priority. True cyber resilience requires both real-time enforcement and automated recovery. Large frontier AI models are too slow and costly for real-time enforcement. Small, efficient AI models, like those Rubrik is developing, are crucial for monitoring agent actions at machine speed. These small models enable immediate threat detection, automated recovery, and a seamless transition to a clean system state. Ultimately, the AI era demands a shift from incident response to architectural resilience, emphasizing the shortening of the gap between detection and restoration.