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The most common sprint planning anti-patterns — no goal, capacity theatre, hidden dependencies, the backlog dump — and how to design them out before they cost you a sprint.
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Federal calendars are full of days your team isn’t working. Subtract holidays, PTO, and training first, then commit. A practical capacity framework.
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Velocity tells you how fast a team usually goes; capacity tells you how far it can go this sprint. Here’s why the difference trips up public-sector teams.
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Roster headcount lies in government. Here’s a bottom-up framework to turn part-time, detailed, and shared staff into a defensible sprint capacity number.
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Government teams that deliver predictably plan sprints and capacity together. A practical framework, a worked example, and how to make it repeatable in Jira.
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Jira Cloud now starts and completes sprints automatically. It’s a real improvement — but it requires parallel sprints site-wide, has no exportable audit trail, and stops at single-sprint scheduling. Here’s where Sprint Automation for Jira still earns its place.
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Earning one Atlassian trust signal is hard. Three of our Jira Cloud apps now hold both Runs on Atlassian and Cloud Fortified at the same time — here’s why that’s a big deal for your data and your delivery.
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The latest update to Sprint Automation for Jira Cloud makes the Application logs page more useful: your sort order is remembered, you can export any log table to CSV or JSON, and sprint lifecycle events now appear in the audit trail.
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In government agile, overcommitting costs more and recovery room is smaller. Here’s why capacity planning — not just sprint planning — deserves a front seat, with a practical five-habit framework and a worked example.
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Story-point estimates are forward-looking guesses. A statistical, retrospective approach forecasts your agile release date from your team’s real past throughput — and it’s a far more honest number to hand a stakeholder.