How to get better AI outcomes with Jira, Confluence and Loom

Watch AI workflows for engineering, marketing, and HR teams. Join us to see how Atlassian's intelligence layer, Teamwork Graph, creates connectivity across your enterprise in Jira, Confluence, Loom, and other 3rd party apps, giving AI the context it needs to deliver better outputs for fewer tokens.

If your team has embraced AI but is still falling short of the high-impact outcomes you expected, the missing piece is often organizational context.

In this live webinar, you’ll see how to give AI what it needs to respond in a way that’s more accurate, costs fewer tokens, and supports practical workflows across Teamwork Collection: Jira, Confluence, Loom, and Rovo.

Watch demos for marketing, engineering, and HR, including how to:

  • Create with context: Build a plan using existing knowledge, past learnings, and customer insights.
  • Automate delivery: Turn requirements into execution-ready work items and automate review checks on status changes.
  • Onboard faster: Answer new-hire questions automatically with policy-grounded agents

Can’t make it live? Register anyway, and we’ll send you the recording.

Speakers

Ali Amin

Director of Product Management, Atlassian

Ali Amin leads AI product strategies across the Teamwork Collection. He is focused on leveraging Atlassian’s Teamwork Graph (TWG) to ground AI agents in a rich enterprise context. Ali previously scaled enterprise AI and agent platforms at Salesforce (Agentforce) and Intuit.

Sanja Samirana Panda

Head of Product, Teamwork Graph, Atlassian

Sanja is Head of Product for Teamwork Graph at Atlassian, where he leads efforts to grow adoption and usage of the graph across Atlassian experiences and external AI surfaces. He brings over 18 years of experience spanning engineering, product leadership, and strategy. Previously, Sanja led AI initiatives for Alexa Smart Home at Amazon, building intelligent and agentic experiences for millions of customers.