Atlassian, Friday, October 23rd, 2026
Connect Agentic Pipelines to the Redesigned Atlassian MCP
Atlassian connects Bitbucket Agentic Pipelines to its redesigned MCP server for Claude and Codex agents using short-lived scoped tokens.
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Vol 343 · Issue 3
Atlassian — Archive · Vol 343 Issue 3
9 articles that week
Atlassian, Thursday, October 22nd, 2026
Showing What You Mean in the Age of AI
Atlassian launches Loom for Mac, Record for agent and MCP tools so teams can hand work to AI agents by showing it.
more → Atlassian, Thursday, October 22nd, 2026
AI Is Exposing the Missing Layer in Strategic Planning
Atlassian argues AI speeds up teams but not organizations without a governed work-context layer linking strategy to execution.
more → Atlassian, Wednesday, October 21st, 2026
Optimize Your Test Suite With Two New Agents
Atlassian adds Test Optimizer and Test Cleanup agents plus an improved Flaky Test Fixer to Bitbucket.
more → Atlassian, Wednesday, October 21st, 2026
Merge Queue APIs Now Available in Bitbucket Cloud
Atlassian releases public Merge Queue APIs for Bitbucket Cloud Standard and Premium workspaces.
more → Atlassian, Tuesday, October 20th, 2026
Say Yes to AI Context Without Losing Control: A New Way to Set Up and Govern Connectors in Atlassian Administration
Atlassian adds new tools in Atlassian Administration for IT to set up and govern Rovo connectors to third-party data.
more → Atlassian, Tuesday, October 20th, 2026
How We Used Agentic Pipelines to Turn Test Coverage Into a Daily Habit
Atlassian describes a scheduled Bitbucket agent that finds thinly tested files, writes tests and opens pull requests.
more → Atlassian, Tuesday, October 20th, 2026
AI Is Making Developers Faster. It's Also Exposing What's Broken in Software Delivery
Atlassian's 2026 State of Developer Experience report finds 87% of developers ship faster with AI, but 72% see the same or more friction.
more → Atlassian, Monday, October 19th, 2026
Context Engineering: Managing Context Quality for More Efficient, Effective AI
Atlassian argues context quality, not model quality, explains most AI pilot failures and is something enterprises can control.
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