According to Nagli on Twitter, AI should continuously augment security across the full attack surface rather than replace manual penetration tests used for compliance, emphasizing that deeper cloud context is critical for effective detection and prioritization across environments (as reported by the original tweet by @galnagli). According to the tweet, this approach suggests a hybrid model where AI-driven continuous monitoring flags risks in real time while human-led pentests validate exploitability and meet audit requirements, creating business value by reducing mean time to detect and aligning with compliance frameworks. As reported by the source post, the claim highlights a product direction for cloud-native security platforms to leverage environment-wide context graphs for attack path analysis, drift detection, and automated validation—opportunities for vendors to offer continuous assurance alongside scheduled manual assessments.