Playbooks overview
A playbook gives an AI agent a job to do. You write down the goal, list the outcomes (tasks) you want, and choose which actions the agent is allowed to run. When someone starts a run inside a space, the agent works through the tasks toward that goal — reading files, searching the knowledge graph, and dispatching actions — and pauses for your approval wherever you said it should.
Playbooks are org-level and reusable. A playbook isn’t tied to one space; instead you make it available to a space type, and every space created from that type can run it.
Playbooks (the definitions) are admin-only. The library lives at Playbooks in the sidebar. If you aren’t an admin you’ll see “You need an admin role to manage playbooks.” Running a playbook, on the other hand, happens inside a space and is open to anyone who can contribute there — see Run a playbook.
Two run types — keep them straight
A space has both a Playbooks tab and an Actions tab, and they are not the same thing.
This page and the rest of this section are about playbook runs (the Playbooks tab). If you just want to run one action over some files, see Run an action.
The playbooks library
Open Playbooks to see every playbook in your organization. The list has these columns:
Use New playbook to start one. See Build a playbook for the editor walkthrough.
The lifecycle
Every playbook carries a status, and it moves through three states.
Draft
Being built. You edit the goal, tasks, and actions freely. A draft can’t be run in a space yet.
Runs are always started by a person
There is no trigger or scheduling system. A playbook never runs on its own, on a timer, or in response to an event. Every run is started by someone from a space’s Playbooks tab.
Where to go next
Set the goal, add tasks, choose actions and approvals, then activate.
Start a run in a space and follow the live timeline.
Approve or reject the agent’s proposals, steer it mid-run, and control the run.
The installable work a playbook’s agent — or you — can run over files.