Playbook
A playbook is a set of “if this situation, apply this rule, take this action” instructions written for a recurring class of problems, rather than a single fixed sequence.
Some processes really are linear: step 1, step 2, done. Others depend on what's actually happening — a support agent's response to “user can't log in” should differ from its response to “user was overcharged.” A playbook is written for that second kind of situation: it pairs recognizable situations with the decision rule and action to take for each one, the way a human team's runbook or escalation guide works.
The simplified diagram on this page shows a single situation flowing to a single decision and a single action, but that's a simplification for illustration. A real playbook almost always branches — several possible situations, each routed to its own rule and action — which is closer to what a dag-workflow actually models than a straight line.
Playbooks are usually written in prose or as structured conditional rules (agents-md-style instruction files are a common home for them), rather than compiled into a fixed program. That makes them easy for both humans and agents to read and update, at the cost of being less strictly enforced than a hard-coded pipeline.
Example
A deployment playbook might read: “if the test suite fails, block the merge and notify the author; if tests pass but the change touches /auth, require a second reviewer before merging; otherwise, merge automatically.” Each clause is a situation paired with a rule and action.
How it differs
Playbook vs. workflow: a workflow is often written for one specific sequence of steps; a playbook is written to cover a family of situations, with different branches for different cases, closer in spirit to a decision tree than a fixed line of steps.
Common misconceptions
FAQ
What is a playbook for an AI agent?
How is a playbook different from a workflow?
Last checked: 2026-08-28