Sherif Mansour mentions he is in his 16th year at Atlassian. He talks about the number of Atlassian employees with more than 10 years of tenure (nearly 400). He identifies some colleagues who have been there longer than 15 years. He recalls first meeting Martin in the early days of Confluence and working together.

Sherif thought about leaving Atlassian after about 12 or 13 years because many small things were frustrating him. He had a conversation with Scott Farquhar and told him he was considering leaving. Scott advised him, before leaving, to walk around and tell people what to change if something bothered him, acting as if he ran the place. Scott reminded him of one of Atlassian’s values: “Be the change you seek”. Sherif then practiced this value more deliberately at the macro level, which led to a mindset shift and gave him newfound energy. This was one reason for him to stay.

It is mentioned that psychological safety is achieved when trust grows with someone. Sherif describes his long-standing relationship with Martin being built on trust, allowing him to speak freely.

Sherif and Martin discuss how people are often hesitant to speak freely due to fears of politics or compliance issues. Martin believes that people who don’t care get furthest, as long as they feel they are doing the right thing and can be transparent. He sees this hesitancy among Atlassian colleagues as well.

A System of Work is described as a set of practices and a methodology for how technology and business teams work together. It’s likened to the Agile Manifesto with principles like aligning teams to goals, unleashing knowledge, and introducing virtual teammates. These principles are easy to say but hard to implement in scaled organizations. The System of Work helps customers with tools and practices to implement these principles. Rovo plays a big part in accelerating the System of Work by helping introduce or accelerate these principles. For instance, Rovo introduces AI agents and provides a framework for them. Rovo also helps unleash knowledge trapped in different document stores.

The Team Graph is Atlassian’s understanding of how teams work on projects and how they relate to different things in their system. This helps Atlassian provide better, more contextual results to customers.

A key insight from customer research is the difference between the Microsoft world (often “Default to Closed” for documents) and the Atlassian world (often “Default to Open” for knowledge bases like Confluence and Jira). If documents are closed by default, new employees have no access to knowledge, and AI provides less useful results. If a knowledge base is open by default, AI gets a lot more instant results, especially for answering questions. Atlassian software helps users become better AI consumers because it defaults to open.

Atlassian has introduced the “Teamwork Collection,” offering Jira, Confluence, and Loom for $15 per user, which is cheaper than Jira and Confluence alone used to be. The goal is to democratize the software and accelerate adoption. Atlassian has a history of providing good value software to help organizations transform.

The most powerful recommendation is a cultural shift and behavioral change to work with new AI teammates. Organizational leaders should give their teams space for “tinkering” to explore new ways of working, including adopting the System of Work or deploying AI. Customers should consider cloud migration as there are over 10 years of innovation in the cloud offering. To get started with AI, it’s suggested to map out a manual business process and find opportunities to automate or speed up individual steps with AI.

The current strategy is to transparently merge different hubs in the portfolio (e.g., Help Center Hub and Confluence Hub) into a single concept. Future hubs are intended to serve as team, department, or company-wide landing pages and be extensible for app vendors and customers. Atlassian focuses on providing the canvas and letting the ecosystem add extensions rather than building everything themselves (e.g., event planning or micro-blogging).

Atlassian aims for agents (like Rovo agents) to use the same ecosystem APIs as other things, though there might be some differences due to legal limitations and privacy issues. In scenarios where the market is moving fast and platform capabilities are limited, it might be different. The ideal would be to handle everything through the same extensibility platform, but reality depends on the situation.

Increasing human-to-agent collaboration is expected. Sherif believes most knowledge workers will move from “doing the thing” to “architecting the thing” they want to do. AI is seen as an excellent tool for training and can help with tasks within any job function. AI can also act as a teacher providing personalized guidance. Organizations still need to invest in their future workforce, as they will be the ones working with the agents.