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AI agents are landing in production faster than most security teams can track them, and the scariest part is how normal they can look. When an autonomous agent runs the same workflow 10,000 times, your SIEM and EDR may see “nothing to worry about” even while the agent quietly drifts outside its intended scope. That is the core AI governance problem we tackle, through the lens of CISSP thinking and real security leadership.

We walk through what is driving the mess: board-level pressure, AI FOMO, and the dangerous habit of treating AI agents like old-school automation. Then we get concrete. We talk about why many enterprises still lack an inventory of AI agents, why traditional security tooling is tuned for human behaviour anomalies, and what it actually takes to be audit-ready. We cover practical governance frameworks like tiered autonomy, why observability is more than collecting output logs, and how to design decision-path tracing with execution records and decision logs you can act on.

To make it actionable for exam prep and day-to-day work, I close with CISSP-style practice questions on the exact scenarios you will face: detection gaps, human approval bottlenecks, least privilege for agents, proving decisions during audits, and architecting platforms that balance operational efficiency with risk management. If you are serious about passing, I also share how my CISSP Sprint cohort is structured to force momentum, including booking your exam date early.

Subscribe for weekly CISSP-focused training, share this with a teammate building AI workflows, and leave a review so more security pros can find the show. What part of AI agent governance is your biggest blind spot right now?

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