6-Step Playbook: Closing the Gap Between AI Agent Adoption and AI Agent Security
A practical framework for closing the distance between how fast AI agents get built and how fast they get secured, before the gap becomes a breach.
This playbook exposes exactly where that gap opens, and what’s already slipping through it.
It explains why after-the-fact inventories and written guardrails can’t close the gap on their own, and lays out a practical, six-step framework for governing AI agents at the same speed the business builds them without becoming the team that says no.
What You Will Learn
Why an inventory isn’t the same as visibility
See why a list of agent names and owners still leaves security blind to what each one can actually do.
Where over-permissioned agents create hidden risk
Learn how a single broad data connection can turn a low-risk agent into a data-exposure incident.
Why prompt injection is a real attack surface
Understand how untrusted inputs like email and documents can manipulate an agent into acting against its own instructions.
Why written guardrails aren’t a security control
Discover why an instruction a model can be reasoned around isn’t the same as an enforced boundary.
How to put enforcement where it actually works
See how to move the rules that matter out of the prompt and into controls the model can’t override.
How to keep agents safe after they ship
Learn why runtime monitoring, not a one-time review, is what keeps agent behavior safe as it evolves.
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