2 min lesson
The recommended first automation
Make the call in this situation: "An exec asks you to report 'lines of AI-generated code' as the pilot's headline metric. What's wrong with it and what do you offer instead?" Explain what supports it.
Step 1 of 2
The recommended first automationlow risk, high stickiness
When a pilot team asks 'what's the first automation we should set up?', there's a data-backed answer: 'Summarize Changes Daily.' It posts a Slack engineering digest of notable repo changes each morning. Cursor's data science found it the stickiest automation at 89% retention. It's the ideal opener because it's low blast radiusHow much breaks if a change goes wrong; the scope of potential damage. Press Enter for the full definition. (it reads and reports, it doesn't touch code), it's visible to the whole team and it builds the daily habit that makes everything above it on the ladder feel normal.
To use cloud agents, a repo is onboarded at cursor.com/onboard: select/add repos, install to GitHub, optionally add env vars and secrets, and Cursor auto-sets-up the dev environment. Setting up an environment from scratch takes roughly 5-30 minutes (often quoted ~20), so don't let a slow first run spook the champion.
Two mitigations to name up front: launch many agents at once rather than serially, and save the built environment as a team snapshot so new agents start from the snapshot instead of rebuilding (this is critical for slow-to-build repos). After that, engineers move freely between local and cloud from the client.
You measure against a four-lens scorecard and you set the baseline before you start. A pilot with no day-zero baseline proves nothing, because every result answers 'compared to what?'
- Lens
- Adoption & capability
- What it captures
- Are people using it and at what rung?
- Example signals
- WAU/DAU, ladder rung reached, % on governed workflows
- Lens
- Flow
- What it captures
- Is delivery actually moving faster?
- Example signals
- Cycle time, PR-to-merge, deploy frequency
- Lens
- Quality & safety
- What it captures
- Are we shipping safer, not just faster?
- Example signals
- Escaped-defect rate, BugbotCursor's automated PR reviewer that posts inline findings and can push fix commits from isolated VMs. Press Enter for the full definition. catches, policy coverage
- Lens
- Experience & trust
- What it captures
- Do engineers and security trust it?
- Example signals
- Developer sentiment, security sign-off, retention of usage
| Lens | What it captures | Example signals |
|---|---|---|
| Adoption & capability | Are people using it and at what rung? | WAU/DAU, ladder rung reached, % on governed workflows |
| Flow | Is delivery actually moving faster? | Cycle time, PR-to-merge, deploy frequency |
| Quality & safety | Are we shipping safer, not just faster? | Escaped-defect rate, BugbotCursor's automated PR reviewer that posts inline findings and can push fix commits from isolated VMs. Press Enter for the full definition. catches, policy coverage |
| Experience & trust | Do engineers and security trust it? | Developer sentiment, security sign-off, retention of usage |
Four lenses, baselined day zero. 'Lines of AI code' is NOT a lens; it's the wrong headline.
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Optional practice
Practice: The recommended first automation
QA pilot team in the Expand phase asks 'what's the first automation we should turn on, and how long will cloud onboarding take?' Give them a concrete, low-risk answer.