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VOOZH | about |
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VOOZH | about |
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Atlassian, the creators of Jira, released a generative AI product called Rovo that features pre-configured AI agents and the ability to create your own AI agents using natural language.
Rovo also has extensions for IDEs and GitHub for Copilot, allowing developers to access standards, edge cases, code or other information stored in enterprise systems like Slack, the Git repository solution BitBucket, and Atlassian’s knowledge management tool, Confluence, without leaving the developer workspace.
The AI solution has more than 20 pre-configured AI agents, and will introduce two of particular interest to developers: Auto Dev and Auto Review. Currently, the agents are in the lighthouse phase but Atlassian developers have documented a 75% time saving for simpler tasks, according to Atlassian’s Matt Schvimmer, a senior vice president who oversees product for the Agile and DevOps division of Atlassian.
It also incorporates enterprise-wide search and a chatbot similar to ChatGPT, both of which leverage semantic indexing and natural language. Semantic indexing helps provide context around the information so that users don’t have to find “magical keywords” to pull up the data.
Rovo is generally available now after a six-month private beta. However, the developer AI agents will launch within a year, pending the results from the lighthouse trial.
The Auto Dev AI agent can take an issue, generate a technical plan, and then generate code to resolve the issue. Developers can tweak the results at any step of the process.
“They can either make changes manually or ask the agent to regenerate things, and it gets you all the way to a PR,” Schvimmer said.
Auto Review reviews code and cleans it up for the developer prior to a code review. It currently supports BitBucket and GitHub and will eventually support GitLab, Schvimmer said.“This is a, basically, a virtual senior reviewer that can go in and give you suggestions on what needs to change before something can get approved,” he said. “More commonly, you’re going to use it to help speed up the time it takes you to review a PR.”
Developers and users can also create their own bots with or without code. Atlassian employees have created more than 500 custom agents internally.
Schvimmer, who began as a Cobalt programmer, created a “fluff eliminator” AI agent using natural language. It detects whether content from Confluence takes more than 10 minutes to read, and if it does, the AI agent will distill the page down into a summary and email the author to let them know the page is too verbose.
“It’s easy to do, and the other nice thing is that you can add [a workflow engine] underneath JIRA, so whenever some action is taken, an agent is triggered,” he said.
Another useful agent for development teams is the Issue Organizer, Schvimmer said.
An Atlassian AI agent works within BitBucket to review code. Screenshot via Atlassian’s blog.
“If you’re in a development team, oftentimes you’ll have a ton of different issues that are written,” Schvimmer said. “A bunch of these requirements are written that really should be aggregated to one epic — one big block of work. So the Issue Organizer finds all those pieces, suggests epics that should be managed together and allows you to group them into an epic and then schedule them into sprints, simplifying the time, putting light work together.”
Rovo is a standalone product that’s available to all users within an enterprise, not just Jira or Confluence users, at no additional cost to user organizations. Based on the beta, Atlassian estimates it’s saving 1-2 hours per week for users, according to a video introduction by Jamil Valliani, head of product for Atlassian Intelligence. He believes there’s more potential for savings.
It’s also designed to work with other popular software. For instance, a browser extension allows Rovo to function within Google Drive and Figma files on Google Drive accounts. It also integrates with SharePoint.
“Internally, we’ve been able to document a 75% time savings in terms of some of the simpler tasks.”
— Matt Schvimmer, senior VP, Agile and DevOps, Atlassian.
Overall, Atlassian plans to integrate the AI via connectors with nearly 80 popular SaaS apps over the next six months, allowing the AI to pull from those tools as well. It will have data center connectors starting next year with Confluence, Valliani added.
More than 80% of their data customers said it helped them find results in a timely manner, according to Schvimmer.
In addition to answering questions, Rovo can also provide context for the information. For instance, documents and other information used by people you collaborate with are prioritized higher in the search results. It also creates people and team knowledge cards so that developers and other users can learn about the teams and people on them, including what projects they’re working on and other contextual information.
Rovo Chat is enabled throughout the Atlassian suite. The chat understands the context you’re in, so if you’re on a particular Confluence page, it will focus on answering questions related to that context, Schvimmer said. It can also take actions such as creating a Jira issue or a Confluence page on command, he added.
Editor’s Note: Updated to correct Jamil Valliani’s first name.
