On this period of AI-assisted software program improvement, builders have to know what to construct and find out how to govern it, whereas coding brokers want context to know find out how to execute appropriately.
To assist organizations navigate and succeed with AI-native improvement and supply, Atlassian at present is releasing a brand new set of capabilities in Jira that the corporate mentioned successfully create a context-rich orchestration layer for autonomous coding brokers
Atlassian added these capabilities to deal with the hole between how a lot code AI is producing and the dearth of productiveness beneficial properties by builders. Among the many points the business faces with implementing AI efficiently are an absence of context that causes brokers to float from necessities, prompts that haven’t any reminiscence so prior work must be redone, and an absence of governance over autonomous brokers.
“When the shopper doesn’t really feel like they should study a very new set of issues, however slightly with their data of the prevailing Jira, and that we put these new options within the place the place they will simply uncover and use them, the idea must be intuitive,” Ming Wu, Head of Engineering, DevAI, at Atlassian, defined to SD Occasions.
Among the many new capabilities in Jira are Jira for Slack, which allows groups to create context-rich specs from conversations, suggestions and concepts utilizing @Jira. Based on Atlassian’s announcement, “the agent updates work objects, syncs conversations as feedback, and assigns work to coding brokers whereas your staff collaborates in Slack.”
WIth this launch, the corporate is introducing Jira Planner for spec-driven improvement. Jira Planner gathers up code pulls, the staff’s Jira and Confluence historical past in addition to staff context to create necessities. Then, it will probably generate a spec in Confluence that builders or brokers can construct on. Additional, work objects will be assigned to fashions and brokers akin to Claude Code, Cursor or GitHub Copilot instantly from inside Jira, offering the context to get higher responses from coding brokers.
Moreover, video conferences will be turned by Atlassian’s Loom video messaging software program into directions and motion plans brokers can use to work on duties. It’s these contextual belongings that enable the agent to carry out properly, Wu mentioned. “Context engineering isn’t just providing you with the uncooked knowledge. It’s the environment friendly solution to retrieve the correct context on your agent,” she mentioned. “Extra context doesn’t essentially imply higher. With Jira Planner, you’ll be able to go begin from Jira and do the planning work along with your staff. And in the course of the planning part, one of many key issues is placing all of the contacts collectively from in every single place. We’re tryingto bare that course of tremendous handy and in addition efficient, ensuring the correct context surfaces in the course of the starting stage.”
To get complete visibility into agent habits, Atlassian’s Teamwork Graph collects session data accessbile from anyplace in Jira, the corporate introduced, together with new hooks within the Teamwork Graph CLI that may hyperlink native agent periods on to work in Jira, updating context constantly to keep away from agent drift.
Based on Atlassian, Jira for Slack, Jira Coding Agent, Jira agent automations, agentic templates, and agent periods in Jira can be found at present for paid Jira Cloud prospects at no extra price. Jira Planner is out there in early entry, and Codex in Jira is coming quickly. DX AI price administration is out there for Atlassian DX prospects.
