Template / 3 min read

Automatic app improvement loop template

One finding, one change, one verification metric—human review before anything ships.

Growth loop preview

Agent workflow in 60 seconds

OpenClaw and the Growth Engineer: signals in, reviewed issues and PR plans out.

Covers all signals that drive growth decisions.
Implementation-ready work—not notes.

A Growth Engineer template for turning all product data into one reviewed app improvement task with evidence and a verification KPI.

Who this is for

Start here if the problem below sounds familiar. You do not need every connector on day one—just enough signal for the Growth Engineer to propose work you can review.

  • Apps with analytics, revenue, crash, review, and code signals
  • Founders wanting a recurring AI improvement loop
  • Teams needing agent issues without auto-deploy

How it works

The loop is the same across guides: connect evidence, let the agent read it, then ship a reviewed task with a verification metric.

  1. Gather latest analytics, revenue, crash, review, store, and code summaries.
  2. Rank opportunities by impact, confidence, effort, and risk.
  3. Pick one improvement with evidence, surfaces, owner, and KPI.
  4. Review, ship normally, and verify after release.

What you get back

The output should be concrete enough to review without opening five dashboards.

  • Covers all signals that drive growth decisions.
  • Implementation-ready work—not notes.
  • Discovery is automatic; shipping stays human-reviewed.

Common questions

Quick answers before you connect product data to an agent.

How automatic should the app improvement loop be?

Automate collection, ranking, and drafts. Keep judgment, merges, pricing, and releases human-reviewed.

What should the Growth Engineer output?

Finding, evidence, journey, surfaces, proposed change, risk, confidence, and verification KPI.

How often should this run?

Weekly default; daily for high traffic, monthly for small apps.