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January 31.2026
2 Minutes Read

Discover How Atlassian's Rovo Think Deeper Revolutionizes AI for Agile Teams

Rovo Think Deeper digital workspace visualization

Enhancing Workflows with Rovo: The New Standard for AI Integration

In today's fast-paced work environment, the quality and speed of problem-solving can make all the difference. Atlassian has introduced an innovative tool called Think Deeper, integrated within its Rovo AI platform. Designed for scenarios where quick responses fall short and extensive reports are unnecessary, Think Deeper strikes a balance that allows teams to enhance their operational efficiency without getting bogged down in information overload.

Rovo's Think Deeper functionality redefines how teams engage with AI. Instead of providing a simple answer or a lengthy document, it employs a systematic approach: breaking down queries into manageable parts, analyzing intermediate results, and ensuring that all relevant aspects of a request are addressed. This enhances understanding and decision-making, particularly in complex projects.

Empowering Teams with the Teamwork Graph

One of the standout features of Rovo is its Teamwork Graph, which contextualizes information across various Atlassian products like Jira and Confluence. By understanding the interconnections between teams, projects, and data, Rovo eliminates confusion and knowledge silos, empowering users to make informed decisions.

For instance, if an HR department needs to consolidate feedback and policies regarding hybrid work, they can input various data points into Rovo. The AI processes this information, generating a clear, up-to-date hybrid work policy that reflects current employee sentiments. This capability demonstrates Rovo's value in real-world applications, as teams see tangible results from its reasoning.

AI-Driven Decision-Making for Agile Teams

With the agile methodologies that many organizations adopt, the need for rapid yet accurate decision-making is paramount. Think Deeper was built to handle multifaceted tasks, avoiding superficial responses and instead anchoring recommendations within specific organizational contexts. This functionality ensures that every decision is based on thorough analysis, hence improving overall productivity.

In an engineering context, for example, Rovo's AI can review recent project updates against documentation, ensuring that all materials are current and relevant. This reduces the frequent mismatches between documentation and actual project status, allowing engineers to focus more on development rather than administrative tasks.

The Future of Work with Atlassian's Rovo

As teams increasingly trust AI solutions for complex problem-solving, it's crucial that the technology evolves to meet their needs. Rovo's innovative approach, particularly through features like Think Deeper, enhances human-AI collaboration. This powerful synergy positions Atlassian at the forefront of AI integration in businesses, supporting teams in navigating the complexities of modern workflows more effectively.

In summary, Rovo's Think Deeper functionality is a game-changer for organizations seeking to improve efficiency while maintaining high-quality outcomes. Those who embrace this transition will find themselves well-equipped to tackle the challenges of tomorrow.

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02.20.2026

How Datasite Achieved Agile Collaboration by Cutting Meetings with Loom

Update Redefining Workplace CollaborationIn the modern workplace, the challenge of maintaining productivity amidst a flurry of meetings is a familiar battle, and Datasite has discovered an innovative solution. By integrating video communications with project management tools, Datasite has managed to cut more than 4,000 meetings in just five months, achieving significant time savings and enhancing workplace culture.At Datasite, the implementation of tools such as Loom, Jira, and Confluence has created a new paradigm for communication. Traditionally, the company's reliance on meetings blurred the lines between productivity and time-consuming discussions, leading to overlapping schedules and diminished focus. However, with the introduction of asynchronous video updates, employees were empowered to share project updates and collaborate without the constraints of scheduled meetings.Embracing Time EmpathyOne of the remarkable shifts at Datasite is the cultural transformation towards 'time empathy', as described by JR Harrell, EVP of Product Operations and Enablement. This cultural ethos encourages teams to prioritize asynchronous communication, allowing them to communicate effectively while preserving time for deep work. This shift not only alleviates the clutter of meetings but also promotes a healthier work-life balance.The benefits are tangible; with over $500,000 reclaimed in lost meeting time, employees can now engage in more meaningful and impactful work, fostering both innovation and efficiency.The Power of IntegrationThe seamless integration of Loom with Jira further enhances project clarity and collaboration. Teams can now provide context through video explanations directly within Jira tasks, allowing colleagues to grasp complex concepts without unnecessary delays. Asynchronous tools like Loom have also shown to expedite bug resolutions and project updates by adding rich, visual information that enhances understanding in a fraction of the time a traditional meeting would take.As organizations continue to adapt to hybrid work environments, leveraging tools that reduce meeting fatigue and enhance clarity will be essential. The successful transition at Datasite serves as a compelling case for others grappling with similar issues in maintaining productivity across dispersed teams.

02.19.2026

Unlocking Efficiency: New Event Triggers in Bitbucket CI/CD Workflows

Update Revolutionizing CI/CD with New Event Triggers In a digital landscape where speed and precision are paramount, Atlassian's Bitbucket has recently unveiled new event-based triggers for its CI/CD pipeline that aim to streamline development processes and enhance efficiency. These updates, introduced on February 17, 2026, are poised to transform the way development teams manage and respond to pull requests and deployment activities. What are Event-Based Triggers? The new trigger types allow teams to execute custom pipelines based on key events, such as the successful completion of a prior pipeline or a significant update to a pull request. This paves the way for complex workflows, promoting better automation and reducing the manual oversight traditionally required in deployment cycles. Significant New Trigger Types The introduction of six new trigger types is a game changer for developers. These triggers include: pipeline-completed: Activates upon the completion of any pipeline, be it successful or failed. deployment-completed: Triggers when a deployment concludes. pullrequest-created: Initiates a custom pipeline when a new pull request is established. pullrequest-updated: Fires when any changes are made to an existing pull request. pullrequest-rejected: Executes upon the rejection of a pull request. pullrequest-fulfilled: Runs actions once a pull request is successfully merged. The Benefits of Enhanced Automation These new triggers allow for a much tighter coupling between CI/CD processes. By ensuring that further actions depend on the outcomes of previous ones, teams can build comprehensive workflows that maintain high-quality standards. For example, developers can automate the testing and alerting processes based on specific pull request events, which caters directly to quality assurance and boosts productivity. Real-World Implications For organizations embracing Agile methodologies, these streamlined processes align perfectly with the Agile Playbook's principles, enhancing responsiveness to changes and customer needs. By decreasing the number of manual checks and configurations required, development teams can deliver features faster and more reliably. Conclusion: Automation as the Future of Development As the tech community continues to embrace automation, the introduction of these event triggers in Bitbucket serves as a testament to the ongoing evolution of CI/CD workflows. By capitalizing on these triggers, development teams can not only enhance their efficiency but also stay competitive in an ever-evolving industry.

02.15.2026

Transforming AI Theater Into Results: The Path to AI Fluency

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