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AI Driven SDLC Documentation

Guides, references, and best practices for the AI Driven SDLC platform.

Insights

Productivity Insights

Engineering delivery and collaboration metrics at the team and contributor level.


What Productivity Insights shows

The Productivity Insights view provides a data-driven picture of how your engineering teams are delivering software. It is designed for engineering managers who need to understand team health, identify bottlenecks, and track improvement over time.

Available metrics

Delivery throughput

The volume of work shipped to production over a selected time period. Includes:

  • Pull requests merged: Total PRs merged per week across the team.
  • Tickets completed: Jira or equivalent issues moved to done (requires Jira integration).
  • Deployment frequency: How often the team ships to production (requires CI/CD integration).

Code review participation

Signals around collaborative code review practices:

  • Review coverage: What percentage of merged PRs received at least one review.
  • Review turnaround: Median time from PR creation to first review.
  • Approval rate: The share of reviews that resulted in approval vs. change requests.

Contribution patterns

An aggregate view of contributor activity:

  • Active contributors: Number of engineers with merged activity in the period.
  • Contribution distribution: How evenly work is distributed across the team (useful for identifying over-reliance on specific contributors).

Filtering the view

Use the Team and Time range filters at the top of the page to focus the data:

  • Team filter: Restrict the view to a specific team or sub-team (populated from your org chart if uploaded).
  • Time range: Default is 8 weeks. Adjust to see shorter or longer trends.

Contributor drilldown

Click on any contributor in the team breakdown table to open their contributor detail view, which shows their individual metrics in the same categories (throughput, review participation, and contribution patterns) over the selected period.

Metrics are for team health, not individual performance reviews

These numbers describe team patterns and bottlenecks, not a leaderboard for individuals. Use them to fix workflow issues, not to rank people.

Data requirements

Metric Required integration
PR throughput, review data GitHub
Ticket completion Jira
Deployment frequency GitHub Actions (CI)
Team grouping HR Org Chart (CSV) or Jira team labels

Next steps