Detection engineers are drowning in manual toil—triaging alerts, tuning rules, and writing detection logic faster than most teams can keep up. Agentic workflows change that equation, but only if R&D resources are pointed at the right places.

Mark Mager, Head of Adversary Engagement at GreyNoise, breaks down how to allocate R&D toward implementing and refining an agentic analysis pipeline built on frontier LLMs. Attendees will learn how to:

• Identify where agentic workflows remove friction and mental load bottlenecks for detection engineers
• Prioritize R&D investment across an agentic analysis pipeline
• Apply frontier LLM outputs to craft more effective detection logic for critical threats

This session is built for practitioners looking to make agentic AI a working part of their detection engineering practice, not just a proof of concept.