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Best practices · Jun 5, 2026 · 6 min read

What belongs in a governed AI playbook

Steps, context, review gates, review records, and versions are the minimum structure that turns a recurring AI task into team process.

On this page
  1. Start with the outcome
  2. Separate human and AI steps
  3. Carry context with the work
  4. Put review inside the workflow
  5. Save a review record and version
  6. The takeaway

01Start with the outcome

A governed playbook begins with a result the team can judge. Before prompts or tools, name what good looks like and who owns the decision.

02Separate human and AI steps

An AI tool can draft, compare, summarize, or propose. People still own judgment, approval, and exceptions.

03Carry context with the work

The playbook should list the documents, examples, rules, or source material the work needs so each person does not rebuild context from scratch.

04Put review inside the workflow

Review gates make the important moments visible. They do not remove judgment; they make judgment easier to apply consistently.

05Save a review record and version

A review record can preserve the decision. Approved improvements can become the next version over time.

The takeaway

Constraint is most useful when recurring AI-assisted work needs shared shape: a playbook, a review gate, a review record, and versions over time.

Ready when you are, start with one workflow.

Prefer to look first? View playbook examples, no email needed.

AI-assisted workflowsPlaybooksReview gatesVersions

Constraint is the shared playbook and version control layer that sits beside your AI, designed for teams using Claude, Codex, and other AI agents. The expert Bank is seeded with method distilled from 1,100+ operators, via Firneo.