What separates AI products that users trust from those that frustrate them? In this revealing interview, Atlassian’s Chief Design Officer pulls back the curtain on the principles, strategies, and hard-won lessons shaping enterprise AI product development.
Charlie Sutton occupies a unique position at one of the world’s leading collaboration software companies. As Chief Design Officer, he’s responsible for ensuring that AI capabilities enhance rather than undermine the user experience across Atlassian’s platform—from Jira to Confluence to the new Rovo agent.
In this conversation from Atlassian Team in Anaheim, Sutton reveals insights that most companies are still figuring out through expensive trial and error. You’ll discover why the transition from deterministic to non-deterministic software creates unprecedented design challenges, and how Atlassian addresses them through structured approaches that balance innovation with control.
What you’ll learn in this interview
This isn’t a surface-level discussion about AI trends. Sutton shares specific strategies Atlassian uses to tackle real challenges that every company deploying AI will face:
The hidden cost of AI that’s catching companies off guard: Discover why some organizations are reconsidering AI-assisted development after discovering the true token costs, and learn Atlassian’s approach to managing these expenses through strategic use of structured data and design tokens.
Why user agency matters more than control: Sutton explains the crucial distinction between direct control and the sense of agency—and why getting this wrong undermines user trust in AI-powered features.
The advantage work tools have over consumer apps: Find out why enterprise software can deliver better AI experiences than Netflix or YouTube, and how the teamwork graph enables context-rich recommendations that feel expected rather than random.
Eight principles that guide AI product decisions: Learn about Atlassian’s framework for evaluating the overwhelming number of potential AI features, including the dynamic content principle that reveals opportunities across the entire platform.
How to move beyond AI experimentation: Most companies are stuck in the “please use it” phase of AI adoption. Sutton describes the next phase focused on outcomes rather than outputs, and shares practical examples of high-value use cases that accelerate adoption.
The full spectrum of AI-assisted design: From traditional Figma work to generative prototyping to designers submitting pull requests directly—see how Atlassian’s design team uses different approaches for different challenges.
Balancing the familiar with the novel: Sutton offers a framework for thinking about how much transparency users need, why it depends on the task, and how quickly novel AI capabilities will become assumed infrastructure.
Why this conversation matters now
The AI era is compressing what used to take decades into just a few years. Companies that develop principled approaches to AI product design now will have significant advantages over those treating every new capability as an isolated feature decision.
Sutton brings both strategic vision and tactical specifics to this discussion. Whether you’re a product leader evaluating AI features, a designer grappling with non-deterministic experiences, or an executive trying to understand what AI maturity actually looks like, this interview offers frameworks you can apply immediately.
Watch the full conversation to discover how one of the world’s most successful collaboration software companies is navigating the transition to AI-powered products—and what you can learn from their approach.