Dynamic Agent Context
Dynamic agent context is an access model in which AI agents receive the specific tools, data access, and permissions they need at the moment they are needed, scoped to the active task, and released on completion. It describes the full lifecycle of how an agent's access changes in real time, from task start to task end.
Why It Matters
Zero standing permissions describes where an agent starts: with no access. Dynamic agent context describes what happens next. As the agent works through a task, it receives just-in-time access to the specific tools and data the task requires. When the task completes or the session ends, that access disappears.
This is not a theoretical distinction. In practice, an agent working on a code review needs read access to a repository and write access to a PR comment. Five minutes later, the same agent working on a different task needs access to a project management tool and nothing else. Dynamic agent context means the agent's permissions are a function of the current task, not a static role assignment.
The term positions the governance layer as an enablement mechanism, not a restriction. The agent gets more context (and therefore more capability) precisely because there is a system managing what it can access and when.