Atlassian
Maker of Jira, Confluence, Trello, Bitbucket, and the broader Atlassian collaboration suite.
Atlassian is productizing its own agent plumbing while pushing Rovo deeper into Microsoft's surfaces.
◆Recent moves
- 16d ago
How we made vulnerability fixes review-ready with Agentic Pipelines
A Bitbucket-blog write-up of how Atlassian used Agentic Pipelines internally to take routine vulnerability fixes from ticket to review-ready pull request. It is the same internal remediation story told three days earlier, told from the pipeline side; nothing ships to customers here, but it is further evidence of the agent-runtime thread running through this feed.
View source ↗ - 19d ago
Agentic automation in practice: putting standard engineering work on autopilot
The framing post for Atlassian's internal agentic-automation work, using security vulnerability remediation as the worked example. Commentary on practice rather than a release, and the companion piece to the Bitbucket Agentic Pipelines write-up.
View source ↗ - 19d ago
Put your conversations to work with the Teamwork Graph connector for Microsoft Teams
A Teamwork Graph connector pulls Microsoft Teams chat, threads, and meeting transcripts into Atlassian's context layer. Real new reach for the graph, but it extends the Rovo-into-Microsoft arc already sparked a week earlier rather than opening a new surface.
View source ↗ - 19d ago
How one leader rebuilt his feedback loop with an AI agent
A single-customer story about a leader using an AI agent to gather feedback. Marketing narrative with no product change behind it.
View source ↗ - 20d ago
Opening the Door to Agent Autonomy: The Architecture Behind Rovo’s Agent Harness
An architecture disclosure on Rovo's agent harness: a sandboxed execution environment that ties automated testing back into runtime optimization. It documents rather than announces, but it is the clearest public description yet of the runtime Atlassian's agent ambitions depend on.
View source ↗ - 20d ago
From prototype to production: lessons learned taking AI-built software to enterprise scale
Lessons-learned commentary on scaling an AI-built prototype into a production system. Engineering-culture content with no user-visible change.
View source ↗