Design a Control Stack That Matches the Risk
Explore how to create a control stack tailored to the risks of Generative AI in Department of Defense workflows. Learn to separate trusted from untrusted context, apply least privilege principles, verify authoritative sources, limit output risks, and document provenance and supply-chain dependencies. Understand how to make conditional, specific approval decisions that keep AI tools safe and accountable in sensitive environments.
A supervisor’s question sounds simple because it is phrased as a switch. Can document search be turned on, and can the assistant draft triage recommendations this week? That framing invites a yes or no, but a responsible answer is a stack of constraints that make the workflow reviewable. The mistake is treating capability as approval, as if adding retrieval only changes speed. Retrieval changes what the system can read, and what it can be steered by, so the approval decision is really about boundaries.
The hard line is not between safe and unsafe tools. The hard line is between information the team can vouch for and information it cannot. Trusted context is information the team controls and can verify, like a curated advisory list or an approved internal template. Untrusted context is information the team did not author or cannot vouch for, like arbitrary web pages or an unknown PDF. Once ...