Checklist

Before you let an AI agent run an outcome

A short human prep checklist for delegating real-world goals safely. Give the agent the outcome, boundaries, approvals, measurement access, examples, and stop conditions before asking it to move a number.

1. Name the outcome

  • Write the one number you want improved: traffic, signups, revenue, activation, reply rate, support load, or something else measurable.
  • Include where that number lives: GA4, PostHog, Stripe, HubSpot, GitHub, a database, or a report.
  • Give the current baseline if you have it. If not, tell the agent where to collect it first.

2. Set the hard boundaries

  • List what the agent must never do: spam, fake traffic, paid spend, credential changes, destructive edits, off-brand claims, or legal/compliance-sensitive actions.
  • Define quality standards in plain language so the agent knows what counts as useful, not just what is technically allowed.
  • Write the brand, tone, and audience constraints that should survive every run.

3. Decide approval rules

  • Say what the agent can do alone: research, draft, edit local files, run scripts, analyze metrics, or prepare assets.
  • Say what needs human approval: publishing, deploying, sending emails, posting on social, opening public PRs, spending money, or changing accounts.
  • Tell the agent what evidence to show you at the approval boundary: diff, preview, exact post copy, target URL, or recipient list.

4. Provide measurement access

  • Point to the scripts, dashboards, APIs, exports, or saved reports the agent should use to read results.
  • Keep credentials out of prompts and repos; provide access through approved local files, environment variables, or existing connectors.
  • Name the secondary metrics that help explain the result, such as source, page, campaign, conversion, or referral domain.

5. Give examples of good and bad actions

  • Good examples teach taste: useful resource page, specific community answer, targeted pitch, helpful docs fix, relevant integration page.
  • Bad examples prevent damage: generic link drops, thin SEO pages, fake engagement, irrelevant outreach, vague social posts, or misleading claims.
  • If there are past attempts, show which ones worked, which failed, and why.

6. Define stop conditions

  • Tell the agent when to stop and ask: missing access, unclear ownership, risky external action, weak evidence, or a change outside the agreed goal.
  • Set budget, time, and blast-radius limits so one run stays small enough to review.
  • Require a short record of what changed, where it shipped, and what result should be checked later.

The prep sheet

Outcome:
Metric source:
Baseline:
Never do:
Needs approval:
Measurement access:
Good examples:
Bad examples:
Stop and ask when:

Want the loop run for you?

An Outcome Deal runs this checklist on your organic clicks from Google Search. Nimrobo proposes a target, an AI agent works on your site through the deal window, and nothing goes live until you approve it. You pay up front, and we refund the share of the promised lift we miss.

See the Google Search Outcome Deal →