The most important work in an AI-native software team often happens in terminals, IDEs, source control, and local agent sessions. But when context does not travel with the work, developers waste time reconstructing intent, while reviewers struggle to understand what changed, why it changed, and whether it is ready to progress. Teams gain speed in one part of the lifecycle, only to lose it through rework, manual coordination, and slower reviews.
Atlassian closes the context loop.

In this session, we will show how Jira and Teamwork Graph connect planning intent, local development decisions, organisational standards, and verification evidence across the software development lifecycle. It starts with immediate value for developers in the local loop, then compounds into stronger coordination and higher-confidence review on the “right of code.”

You will learn how to:

• Bring work intent, prior decisions, and related delivery context from Jira and Teamwork Graph into the tools where developers and agents already work
• Capture meaningful progress and implementation decisions back in Jira, reducing manual status updates and artifact linking while maintaining governance
• Ground AI-assisted review in intent, implementation evidence, and organisational standards, then surface risk assessments in Jira so reviewers can focus their attention, fast-track low-risk changes, and ship with confidence