Rollout Stages
Define the engineering intake contract
Align support and engineering on required repro fields, issue template fields, severity values, labels, owner rules, and customer follow-up expectations.
Connect read-only context tools
Enable read access to ticketing, CRM, product usage, logs, incident status, and issue tracker search. Keep write actions disabled at first.
Run shadow repro gathering
Have Duckie summarize historical and live bug reports, score repro completeness, and suggest missing follow-up questions without posting to customers.
Create draft engineering issues
Let Duckie draft Linear or Jira issue content for human review. Compare against issues engineers would have written.
Enable reviewed issue creation
Allow Duckie to create issues only after support or engineering approval. Store links between the support ticket, issue, Slack thread, and Duckie run.
Enable engineering Slack collaboration
Post summaries to an internal engineering triage channel. Route engineer questions through the question routing workflow instead of ad hoc support pings.
Enable customer follow-up with review
Draft customer questions and resolution messages in the original support ticket, but require human approval before sending.
Enable live two-way sync for safe paths
Automatically sync customer answers and resolved issue updates for approved product areas, severities, and support queues.
Testing Plan
Use historical tickets and known bugs:- Replay complete and incomplete bug reports
- Include duplicates, known incidents, cannot-reproduce reports, and high-priority customers
- Compare Duckie issue drafts against human-created issues
- Verify that issue fields use only allowed values
- Test engineering questions routed to support owner, customer, and internal lookup paths
- Confirm customer replies sync back to the correct issue and Slack thread
- Confirm issue completion routes to the original support ticket
- Run batch tests after issue template, routing, or follow-up prompt changes
Success Metrics
Track:- Percent of customer bug reports converted to engineering-ready issues
- Repro completeness before issue creation
- Duplicate issue detection rate
- Engineering rejection or reroute rate
- Time from customer report to engineering issue
- Time waiting on customer details
- Engineering questions answered
- Resolved issues followed up with customers
- Sync failures across ticket, issue, and Slack records
- Support and engineering satisfaction with summaries
Launch Guardrails
Start conservatively:- Require human approval before sending customer-facing messages
- Require human approval before creating high-severity engineering issues
- Use allowlists for issue teams, projects, labels, priorities, and statuses
- Keep not-planned and cannot-reproduce responses behind review
- Store all cross-system IDs before enabling two-way sync
- Post daily reports during rollout
- Review issue template edits and engineer corrections weekly
The first live win is usually not full automation. It is reliable context gathering, better issue drafts, and a record map that lets support and engineering stop losing the thread.
Related Docs
Deployment Modes
Move from Testing to Live when each part of the loop is ready.
Batch Testing
Evaluate changes across historical bug reports.
Guardrails
Gate sensitive customer and engineering actions.
Alerts
Notify the team when sync failures or blocked loops appear.