Teams | Collaboration | Customer Service | Project Management

Individual Capacity Planning in Jira: How to Manage Team Bandwidth

Individual capacity planning in Jira is a native view that connects team member bandwidth directly to live work items, epics, and initiatives—eliminating the need for disconnected planning spreadsheets. In this video, we cover how to set up individual capacity planning, import existing spreadsheets with Atlassian Rovo, track non-project time like PTO and KTLO, prevent overallocation across spaces, and rebalance resources using AI natural language commands.

Formula Fields in Jira: How to Run Real-Time Calculations

Formula fields are a Jira custom field type that runs real-time calculations directly on work items using values from other fields. In this video, learn how to create formula fields in Jira, calculate dynamic metrics like budget variance and ROI, use Atlassian Rovo to generate formulas with natural language, and set up conditional formatting to highlight at-risk work. IN THIS VIDEO: CHAPTERS: RELATED RESOURCES.

We're bringing governed agent loops to the AI-Native SDLC

Here’s a stat that’s been rattling around in my head. In our 2026 AI SDLC study, 94% of engineering leaders told us they’re using AI, but only 6% have the systems to actually scale it across their whole software lifecycle. Almost everyone is playing with agents, yet almost no one can let agents run at scale without things breaking.

How Teamwork Graph Helps AI Agents | Teamwork Graph | Atlassian

This is video is part of the Teamwork Graph benchmarking series being launched by TWG PM/PMM. It is in support of the soon to be released Teamwork Graph benchmark report blog. About Atlassian: Behind every great human achievement, there is a team. From medicine and space travel to disaster response and pizza deliveries, we help teams all over the planet advance humanity through the power of software. Our mission is to help unleash the potential of every team.

The Agentic Pivot: Why the work around code matters more than ever

AI is accelerating implementation. The engineering teams who benefit most will connect context, orchestration, and accountability across the work around code. AI can now help engineers turn ideas into working code in minutes, but software delivery has always been more than just producing code.

Atlassian's usage-based pricing: AI value with predictability and control

AI is changing what entire organizations can accomplish. As it moves beyond individual productivity to orchestrating entire workflows, the value of software outgrows what seat count alone can capture. Atlassian customers are already realizing tangible business value from AI and automations, from reporting processes that run up to 40x faster with agents to saving 400 hours per month with automations.

Using @Jira in Microsoft Team: create, update and assign work from chat | Atlassian

Yes, Jira works inside Microsoft Teams. The Jira Cloud for Microsoft Teams app brings project management into your conversations, and it just got smarter. Over a million users already rely on the Jira for Microsoft Teams integration for notifications, work item previews, and quick actions. Now Jira understands natural language, so you can create, update, and assign work without ever leaving your Teams chat.

AI polish makes it harder to spot problems. But there's a quick fix.

AI makes it quick and easy to turn rough notes into a clean, easy-to-read document. Job well done, right? Think again. Atlassian’s Teamwork Lab suspected that this professional veneer—what we call “AI polish”—makes it harder to spot foundational flaws and give feedback, so we tested it. We wanted to know: Does AI polish make it harder to identify problems in early drafts? How can we solve for this blind spot?

Building your AI work factory

There’s a concept in software engineering called a software factory – a structured, repeatable pipeline that takes raw inputs (requirements, code, tests) and reliably produces high-quality outputs (working software). The magic isn’t just automation. It’s the combination of standard tools, curated configuration, and encoded expertise that makes every run predictable, consistent, and improvable over time.