Operations | Monitoring | ITSM | DevOps | Cloud

Ever had a broken test stop your flow? In this Bitbucket Blitz video, we look at how to setup self-healing pipelines using Bitbucket and Bitbucket Agentic Pipelines. Instead of just failing and waiting for a human, the pipeline triggers an agent when a build or test breaks on a feature branch. The agent reads the logs, finds the root cause in the source code, creates a fix branch, and opens a pull request ready for review.

Tired of spreadsheet trackers, lost Slack requests, and SaaS sprawl? Learn how to turn your existing Atlassian stack—Jira, Confluence, and Jira Service Management—into a unified HR hub for recruiting, zero-touch onboarding, and compliance. Most companies run on Atlassian, but HR workflows often remain scattered across spreadsheets, endless email threads, and disconnected SaaS tools. The answer isn't another point solution or a costly rip-and-replace—it's connecting the systems you already have.

Dave Killeen will tell you, on record, that his relationship with AI has crossed into unhealthy territory. He also says he has never felt more alive, that he is 50 and feels 30, and that he sometimes waits for his two small children to go to bed so he can start a coding session. In between, he gives Axel Sooriah the most practical answer on this show yet to the question every product team is facing: your exec says "we need AI," and you have no idea what they actually want.

Jira Planner is an AI planning agent in Jira that turns high-level product requirements into ready-to-build plans (requirements, technical specs, and Jira work items) grounded in your actual codebase, architecture, and Confluence context. In this video, you'll see how Jira Planner brings due diligence to the pre-build phase, so engineers and AI coding agents start from a plan that reflects the real code instead of a vague prompt. It's useful for product managers, engineering leads, and developers who want to cut the rework that comes from AI guessing at requirements.