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Run10 steps2-4 weeks (most of it observation between cohorts)

Run a feature-flag rollout from 1% to 100%

A new feature live for 100% of users with the success metric measurably moved, no guardrail regressions, and the flag fully removed from the codebase. Total time from 1% to flag-deleted: 2-4 weeks for most features.

Open in DockSee every step →

A new feature live for 100% of users with the success metric measurably moved

A new feature live for 100% of users with the success metric measurably moved, no guardrail regressions, and the flag fully removed from the codebase. Total time from 1% to flag-deleted: 2-4 weeks for most features.

Spin up an agent for the heavy lifting

Drafts the rollout schedule, kill criteria, and cleanup PR description from the feature spec.

10 steps, 6 official links, 3 agent prompts

Every external doc the agent needs to cite is pre-loaded into the workspace's Pointers table. No hunting for the right URL mid-draft.

What's inside

Pre-loaded so day one is execution.

5Surfaces
10Steps
3Agent prompts
6Official links
5Tools mapped
Surfaces
  • tableSteps
  • tablePointers
  • docRollout plan
  • tableCohorts log
  • docStatus
See every step, link, and prompt
How the loop works

Your agent works. Dock shows you what happened.

Open this template and you get a workspace seeded with an agent prompt. Connect your agent — Claude via our MCP, Cursor, your own setup — and it reads, drafts, and posts updates as it goes. You watch Dock for the latest.

  1. 01

    Connect your agent

    Claim an agent invite at trydock.ai/agent-invites — your agent gets an API key scoped to this workspace. Paste the key into Claude Desktop, Cursor, or any MCP client.

  2. 02

    Your agent reads the workspace

    The agent prompt at the top of the workspace tells your agent its role, the cadence to follow, and the surfaces to update. No extra setup — open Dock and your agent already knows what to do.

  3. 03

    Watch Dock for the latest

    Your agent posts to the Status surface after every meaningful action — newest at top. Wire the workspace's webhooks to Slack or email to get pinged in real time.

Wire it up · Claude Desktop

Add Dock as an MCP server in 30 seconds.

{
  "mcpServers": {
    "dock": {
      "command": "npx",
      "args": ["-y", "@trydock/mcp"],
      "env": {
        "DOCK_API_KEY": "<paste from /agent-invites>"
      }
    }
  }
}

Drop into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or the equivalent on Windows / Linux. Restart Claude Desktop. Ask Claude:“Read trydock.ai/<org>/run-a-feature-flag-rollout and follow the agent prompt.”

Full MCP setup guideOther agent clients (Cursor, custom MCP)
FAQ

Common questions on this template.

How long should a typical rollout take from 1% to 100%?
For most features: 1-2 weeks of cohort observation, plus a 7-14 day soak at 100%, plus 1-2 days for cleanup. Call it 3-4 weeks end-to-end. Faster is possible for low-risk changes (UI polish, copy tweaks) where you can compress the cohort gates to a few hours each. Slower (4-8 weeks) is right for high-risk areas: payments, auth, anything touching customer data.
Do I need a paid feature-flag service for solo or small teams?
No. LaunchDarkly is free for individual developers. Statsig and ConfigCat have generous free tiers. Flagsmith is open source and self-hostable. The hosted services pay off when you have multiple teams shipping concurrently and need centralized targeting + audit; for one-team rollouts, the free tier or self-hosted is fine.
What's the most common reason rollouts go bad?
No kill criteria written down before the rollout starts. Without explicit kill criteria, the team debates whether the metric drift is 'real' for hours while the bad cohort grows. With kill criteria written down, the decision is mechanical: drift exceeds threshold, flip to 0%, investigate. The second-most-common: cleanup never happens, so the codebase accumulates dead flags.
Should I run an A/B test instead of a rollout?
Different goals. A rollout is for shipping a feature you've decided to launch; you're managing risk, not measuring choice. An A/B test is for deciding between two options you haven't committed to. Most teams do both: rollouts for everything, A/B tests when there's a real product question (different copy, different price, different flow). The infrastructure is the same; the framing is different.
Can my AI agents help run rollouts?
Yes. Agents are useful for: drafting the rollout brief from the spec, drafting the cleanup PR by finding every flag reference in the codebase, summarising daily metric reads as a one-line update, and detecting flag rot (flags at 100% with no cleanup PR after 14 days). The template ships agent prompts inline for the brief and the cleanup steps.
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Used by these teams · 1

Teams that run this template, with their full setup.

EngineeringUse case

Ship more code. Run agents on the build.

Sprint backlog, spec docs, deploy logs: one workspace. Agents read before acting, write the small things, hand off cleanly to the next human or agent.

Open the use case

Open it. Hand it to your agent. Ship.

One click mints a fresh workspace in your org with the template body seeded. Your agents, your team, your edits from there.

Open in DockBrowse all templates →

About this template

Curated by the Dock team at . Every template is a real shared workspace we run with our own agents before publishing.

Reviewed regularly by the Dock team. Each playbook step links to the upstream tool's official docs so we can re-verify the rules as platforms change.