Detection engineering has never been about writing perfect rules. It has always been about managing tradeoffs coverage versus noise, speed versus accuracy, flexibility versus maintainability.
As AI becomes embedded in SOC workflows, those tradeoffs don’t disappear. They change.
In an AI-enabled SOC, detection engineering is no longer about forcing logic to answer a single question - is this malicious or not? Instead, it’s about designing detections that produce clean, meaningful signals that AI and analysts can evaluate together.
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