TL;DR:
Iterations gives teams a single place to see what was planned, what actually shipped, and how work flowed through a sprint. AI Iteration Summary then turns that data into a concise, shareable narrative with recommendations your team can use for better planning and retros.
Overview
The Iterations view combines your project management issues (Jira or Shortcut) with real Git activity to show how work moves through a sprint. You can use it to:
- Track progress on current iterations (Current View).
- Analyze past iterations for retrospectives (Completed View).
- Spot unplanned work, carryover, and unlinked branches.
AI Iteration Summary builds on this by generating a structured, plain-language summary of a completed iteration, highlighting:
- Key accomplishments and delivered work.
- Planning disruptions and unplanned work.
- PR review and flow patterns.
- AI-generated recommendations for the next sprint.
Video Walkthrough: Team Iterations & AI Iteration Summary
Before You Begin
Prerequisites
- Teams configured in LinearB Your team must exist in Settings → Users & Teams and be connected to the right Git repos.
- PM board connected Connect a Jira or Shortcut board to the team so Iterations can map Git activity to PM issues.
- Scrum board for AI Iteration Summary For AI Iteration Summary, the team’s board must be configured as a Scrum board so iteration boundaries and completion states are clear.
- Permissions You need permission to view team data in the Teams → Iterations view.
- AI Services enabled The AI Services toggle under Company Settings → General must be toggled on.
Where to Find Team Iterations
- Go to the Teams tab
- Select Iterations
Recommended setup & conventions
- Include the Jira/Shortcut issue key in the branch name, PR title, or commit message so LinearB can automatically link work.
- Keep sprint dates and board configuration accurate in your PM tool to ensure iteration boundaries are correct.
- Use consistent issue types and story points so planning and delivery metrics are meaningful.
Understanding the Iteration Views
Current vs. Completed View
Current Iteration View
- Shows in-flight work and real-time Git activity.
- Ideal for daily standups, mid-sprint reviews, and spotting bottlenecks early.
- Highlights active branches, PRs, and issue status as things move.
Completed Iteration View
- Shows a fixed snapshot of a completed sprint.
- Focuses on planning vs. delivery, unplanned work, and effort distribution.
- Includes key completed metrics and the AI Iteration Summary.
Key data shown in Iterations (applies to Current + Completed)
This section reflects how LinearB connects your Jira/Shortcut issues with Git activity so you can understand progress, scope changes, and delivery flow within the selected iteration.
- PM Issue Details – Issue name, story points, and status. In supported setups, you can update issue status directly from LinearB.
- Contributors – Developers who contributed to an issue through commits, opening PRs, merging, or releasing code.
- PR Size & Code Changes – Combined code changes across PRs associated with an issue, plus visibility into how many repos the linked branches touch.
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Branches
- Active – Branches in the coding or open PR stage.
- Merged – Branches merged into the base branch.
- Released – Merged branches marked as deployed.
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Issue Timeline – Daily Git activity summary:
- Work – Commits, PRs opened, and reviews.
Completions – Merges and releases.
Subtask Git activity is bundled under the parent story.
Key Completed View metrics (for retros + planning improvement)
Retro View focuses on how well the team delivered against what was planned and what disrupted predictability.
- Planning Accuracy (Scrum) – How much planned work was completed.
- Capacity Accuracy (Scrum) – How completed work (planned + unplanned) compares to the original plan.
- Throughput (Kanban) – Weekly throughput, used instead of planning accuracy. This the average number of issues (or story points) the selected team delivers per week.
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Delivery Performance
- Planned – Work added before or within 24 hours of sprint start.
- Completed – Planned work finished within the sprint.
- Unplanned – Work added after the sprint began and completed within the sprint.
- Uncompleted – Planned work not finished by sprint end.
- Investment Profile – Distribution of work by issue type to show where effort went.
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People Effort – Percentage of active contributors involved in completed work during the iteration.
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Formula:
(Active Contributors ÷ Total Developers) × 100 - A contributor is considered active if they were assigned to an issue moved to Done.
- Low participation may indicate bottlenecks or uneven workload distribution.
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Formula:
- Delivery Breakdown – The detailed list of issues in the iteration, grouped by status.
Note: The 24 hours grace period applied to planned work is also applied to issues removed. There for any issue removed before the first 24 hours after the start of a sprint will not appear in that sprint.
AI Iteration Summary
AI Iteration is currently only available for SCRUM sprints while Kanban support is in development
What AI Iteration Summary shows
The AI Iteration Summary is a structured narrative generated for completed iterations. It includes:
- Iteration name & dates – The sprint name and start/end dates for context.
- Overview – A short description of how the iteration went (planned vs. unplanned work, capacity vs. planning, key themes).
- Key Accomplishments – A list of notable delivered work, including story-pointed features, fixes, and infra changes.
- Planning Disruptions – Unplanned work, untracked/unlinked branches, and blockers that impacted predictability.
- PR Flow Analysis – Insights about review quality, large PRs, fast merges, or under-reviewed changes.
- AI-Generated Recommendations – Concrete suggestions, such as adjusting planned scope, addressing untracked work, or adding automation.
AI summaries are created only for iterations that are closed after the feature is enabled. Older iterations do not receive summaries retroactively.
Accessing the AI Iteration Summary view
- Go to Teams → Iterations.
- Select your team and choose a completed iteration.
- Ensure you are in Completed View.
- Click View AI Iteration Summary to open the AI summary panel.
The panel opens alongside your Iterations data so you can easily cross-reference narrative insights with the underlying issues and activity.
Sharing & feedback
- Share via deep link – Copy a link to the iteration summary and share it with teammates who have access to the team.
- Copy as Markdown – Copy the summary text to drop into docs, project pages, or completed notes.
- Provide feedback – Use the built-in like/dislike controls to help refine the AI summaries over time.
Best Practices
Using Iterations in your ceremonies
- Daily standups: Use Current View to see what’s in progress, who is blocked, and what’s at risk.
- Mid-sprint checks: Look at unplanned work and unlinked branches to catch scope creep early.
- Retrospectives: Use the Completed View plus AI Iteration Summary to discuss planning accuracy, carryover, and where process adjustments are needed.
Making AI summaries more useful
- Keep story points and issue types (Bug/Story/Task) consistent so insights reflect reality.
- Ensure branches and PRs are linked to PM issues to avoid “shadow work” and untracked effort.
- Review AI recommendations as a team and decide on 1–2 concrete changes to try next iteration.
Troubleshooting
No data in Iterations
- Confirm your team is connected to a Jira or Shortcut board.
- Check that issues on the board are assigned to the correct team.
- Verify that branches/PRs include the PM issue key so LinearB can link activity.
Unlinked branches piling up
- Review the Unlinked Branches section at the bottom of Iterations.
- Update branch or PR names to include the relevant issue key.
- Align on a simple naming convention as a team.
No AI Iteration Summary for a sprint
- Verify that AI Iteration Summary was enabled before the sprint ended.
- Confirm the board is configured as a Scrum board with clear sprint boundaries.
- Check that the iteration is closed and visible in the Completed View.
Notifications not arriving
- Ensure Slack or Microsoft Teams is connected to LinearB.
- Confirm the correct channel is configured for the team.
- Check that AI Iteration Summary Notifications are toggled on in the team’s Insights tab.