Governing AI agents without slowing them down
Most AI governance is a document. The useful kind is a set of switches in the product.
The objection to AI in delivery tooling is rarely capability. It is that nobody can answer what the assistant did last Tuesday, or who let it.
So the controls are boring on purpose: policy per workspace and per project, credit budgets so usage cannot surprise the account, and a record of every call.
The confirmation boundary
Inside the app, an action that changes data shows you what will happen before it runs. Over a connected AI host there is no such step — a write tool executes when it is called.
That asymmetry is real and worth stating plainly, because a policy written on the assumption of a confirmation prompt is a policy that does not hold over MCP. The lever that does hold is scope: grant read-only unless an assistant genuinely needs to change work.
Review is an interface, not a promise
Owners and admins can see every AI connection and every member API key reaching the workspace, and revoke any of them immediately. Meeting follow-ups are drafted for a human to review rather than created silently.
None of this makes automation slower. It makes the first conversation about automation shorter, which is usually what was actually blocking it.