When building an AI-native security program, start with outcomes
In my last article, I described the SOC Triangle , the longstanding trade-off among quality, consistency and cost efficiency in security operations. AI is starting to loosen that constraint by enabling certain kinds of work with greater depth and consistency, without requiring a…
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Detection engineering follows the same pattern. A rule that produced useful signals 18 months ago may generate mostly benign activity today. New attacker techniques may also create gaps that did not exist when the rule was written. Continuously evaluating detection fidelity and coverage can make improvement part of day-to-day operations without requiring a dedicated detection engineer for every environment.
Threat intelligence has an even shorter useful life. Teams may subscribe to high-quality sources and still struggle to translate new reports into hunts before the information loses…
