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Customer interviews are one of the most powerful ways to build better products — but they’re also time-consuming. In this video, Avinoam “Avi” Zelenko, Principal Product Manager at Atlassian, shares how he transformed the way he runs customer interviews using AI automation and Rovo agents. What used to take hours of coordination, note-taking, and manual summaries now happens automatically. By stitching together the Teamwork Collection and Slack, Avi built a workflow that captures conversations, summarizes insights, and shares them across teams in real time.

Bitbucket Pipelines already supports triggering on repository pushes and pull request pushes. But if you wanted to react to other events like a deployment finishing, a build failing, or a PR getting merged, you had to wire that up yourself with webhooks or external glue code. New trigger types let you define those conditions directly in your YAML. You can fire custom pipelines on events like pipeline-completed, deployment-completed, pullrequest-created, pullrequest-fulfilled, and more.

AI transformation doesn’t succeed without people at the center. At Atlassian, HR is leading the way. Our People team believes that the best AI culture isn’t mandated from the top. It’s built by meeting employees where they are, partnering with leaders across the business, and making AI part of how work gets done from day one. See how Atlassian’s HR team is building a culture of experimentation where everyone builds, and what that looks like in practice.

Bitbucket Pipelines lets you invoke child pipelines from a parent step, but until now there was no way to pass information between them. Variable sharing changes that. You can define variables in a parent step and pass them directly to child pipelines as custom pipeline variables. With dynamic step conditions, those child pipelines can make decisions at runtime based on the values they receive, like skipping a deployment when a security scan detects critical vulnerabilities.