Teams | Collaboration | Customer Service | Project Management

Tracking deliverables in Jira as a Product Manager | How I Atlassian

Tired of being your team's "status bot"? In this video, a Product Manager shares how she stopped chasing updates over DMs and started using Jira to keep her team aligned, so she can focus on what actually matters. Here's what you'll learn: How to centralize launch tasks in Jira as work items How to organize your backlog and pull priorities into sprints How to use work item comments so your team self-reports progress.

Capturing feedback in Jira as a Designer | How I Atlassian

Tired of digging through Figma comments, Slack threads, and random meeting notes just to find feedback? In this video, a Designer shares how he stopped sorting through scattered feedback and started using Jira to centralize it all, so he can get back to actually designing. Here's what you'll learn: How to create a work item with all your design details in one place How to share context and @mention reviewers with clear questions How to watch work items so feedback comes straight to you.

From tool to teammate: How one Atlassian team made AI a real coworker

In Q4 FY26, Atlassian’s People Insights (PI) team stopped treating AI as a productivity add-on and committed to something harder: fully agentifying its operations—giving AI persistent access to the team’s context, data, definitions, and workflows so it can act as a genuine collaborator rather than a smarter search engine.

For You Page for all your AI sessions in Jira | Atlassian

All your AI sessions in one place. The For You page in Jira gives you a real-time view of everything your agents are doing, what's running, what's finished, and what needs your attention. Review completed coding sessions, approve pull requests, and kick off new agent sessions directly from the page. Stay on top of your AI-powered workflow without hunting across tools. Watch to see how it works.

How Rovo helps finance close the books faster | Atlassian

Managing financial systems at scale is complex. Multiple SaaS applications, ERP integrations, transaction flows, and month-end close activities must work seamlessly to ensure data integrity and reporting accuracy. In this video, Alex Auerbach, on the Finance AI and Enablement team at Atlassian, shares how they built Finance360, a Rovo agent that delivers real-time monitoring, proactive alerts, and intelligent troubleshooting across critical financial systems.

What 5M+ daily MCP tool calls taught us about the future of AI at work

Less than six months ago, the Atlassian Rovo Model Context Protocol (MCP) server went GA, giving Claude, Cursor, and every major AI agent direct access to Atlassian for our customers. Today, over one million users trust it every month to do real work through agents. But that number isn’t the story. The story is what’s happening inside those interactions: how AI agents are actually being used at enterprise scale, and who’s getting the most value.

Secure AI adoption with data loss prevention (DLP)

AI makes your organization’s knowledge easier to find and use. That’s the whole point. But it also means sensitive data moves faster, surfaces in more places, and becomes harder to track. The pressure to act is real, but the playbook isn’t new. You still need to know where sensitive data lives, govern how it’s being used, and prevent it from unauthorized exposure. AI is now giving you a reason to revisit your data security posture and make sure it’s strong enough to keep up.

How Atlassian and Dropbox are driving effective AI transformation

Adopting AI technology without an effective strategy is costing the Fortune 500 an estimated $161 billion a year.* Enterprises are making big investments in this space but are struggling to realise the returns. We know the technology is designed to make businesses more efficient, but we’re still seeing the opposite because most businesses are treating AI as purely a technology transformation. That’s where they get stuck.