A news summary on AI-native email security highlights the need to transform security workflows from manual rule-writing to natural language-driven systems. The article argues that defending the inbox currently requires engineers to translate human intuition into regex, debug rule sprawl, and handle manual ticket routing, while software engineering has evolved to use natural language prompts for coding agents. To be genuinely AI-native, an enterprise email defense must re-architect the human workflow across three vectors. First, a detection engine should rely on natural language policies rather than manually hardcoded YARA or Sigma rules, allowing security teams to define policy rubrics in plain English, such as flagging messages from executives requesting urgent out-of-band tasks. The system then translates these parameters into semantic vectors and system prompts, with reasoning-based agents evaluating text intent, relationship context, and infrastructure metadata. Second, handling the feedback loop when an email slips through or triggers a false positive should not force teams into submitting support tickets or untangling conflicting manual rules.