Atlassian

At Atlassian, we know you’re only as strong as the Team around you. Today at Team ‘26 Europe, we are celebrating this year’s Impact Maker Award winners. These organizations have been selected because they are transforming how their teams scale, thrive, and do their best work in the age of AI. This year’s winners represent global enterprises, public sector pioneers, and high-growth disrupters who are turning modern ways of working into measurable business advantage.

Atlassian is putting elite AI engineers directly inside its customers’ teams to accelerate AI transformation initiatives. The role is called the Forward Deployed Engineer, and we’re scaling it fast. We have 46 engineers today and are moving quickly towards 100 by the third quarter, deployed across the US, EMEA, and India. In fact, they’ve already worked with more than 100 enterprise customers and put 80+ AI agents into production.

Atlassian’s Chief Product Officer on how roles are expanding, not converging Research and insights on how teams can deliver results with AI. What does the “AI builder” era look like for product managers inside a large company? At the Lenny and Friends Summit, Atlassian’s Tamar Yehoshua shares examples from Confluence, a new product, and Jira to show how PMs can help teams move faster.

An agent is only as good as the context you give it. Feed it the right pages, recordings, relationships, decisions, and chat history, keep that context accurate and current, and it ships real work. Cut it off or feed it stale data, and it hands you confident nonsense. The Teamwork Collection, Jira, Confluence, Loom, and Rovo, is built on a shared context layer called the Teamwork Graph.

For too long, teams have been trapped in the service status quo: a reactive loop of break-and-fix, siloed tools, lost context, and ticket limbo. The cost is real. Forrester Consulting found that 97% of enterprise leaders struggle to meet service expectations, with lost productivity as the top business cost. Meanwhile, adoption is moving fast. While only 21% of organizations use agentic AI today, 80% plan to within the next 12 months.

Over the last two decades, millions of teams have run their work on Atlassian, writing code, shipping products, and supporting customers across billions of workflows. Our platform is also where they make the hard calls, prioritizing which features to build, deciding which customer problems to chase, and choosing where to invest their resources.

G’day from Amsterdam. What a week. The energy at Team ’26 Europe is hard to beat – thousands of people who build, run, and fix things, all here together, testing, sharing, and learning. Events like this remind us that the best work is never done alone. Teams improve ideas. They catch what one person might miss, and move faster together. AI should work the same way. But at many enterprises today, it just…doesn’t.

When we delivered Atlassian MCP a little under a year ago, the idea was simple: let the AI tools your teams already use – Claude, ChatGPT, Cursor – reach the work that lives in Atlassian. The response was immediate. Now, we’re seeing more than 15M calls a day as it’s become the first thing teams reach for when they want to connect AI to their work. But teams have made it clear they want more. More products, more context, and more of the whole job done. So we rebuilt it to deliver exactly that.

Frontier models can now reason through problems that stumped businesses just a year ago. Yet inside every enterprise, the most critical knowledge remains dynamic and distributed, from the architecture decisions agreed upon last sprint to the exact owner of a service being updated. For over 20 years, hundreds of thousands of organizations have planned, built, and shipped on Atlassian. And in the time since our initial partnership in 2023, more than 2.5 million businesses are using OpenAI products.

Teams across the industry are sprinting to reinvent their software development processes with agentic AI. Yet, navigating the fast-changing landscape of tools and opinions can be daunting for even the most AI-forward organizations. This guide shares Atlassian’s approach and best practices, informed by our own internal AI SDLC transformation and collaborative learnings from top engineering organizations.