Most teams reach a natural plateau with AI agents. A single agent handling a focused task works well in isolation, but the workflows that would unlock real organizational value are rarely that simple. They involve multiple steps, handoffs between systems, and a need for consistent, trustworthy performance before anyone is willing to let them run without supervision.

In this hands-on workshop, bring your laptop and follow along step-by-step as we give you the practical skills to move past that plateau. You will learn how to design subagent architectures that break complex processes into coordinated, focused tasks, and how to orchestrate those subagents into reliable end-to-end workflows. The session also covers how to use evaluations to test whether your agents are actually performing the way you expect, how to set up agent accounts that give autonomous agents a governed identity in your Atlassian environment, and how to build automations that run without requiring human intervention at every step.

This session is designed for practitioners with foundational Rovo agent-building experience who are ready to move from experimentation into real-world deployment. If you are responsible for scaling AI workflows across a team or organization, this workshop will give you the architecture and the confidence to do it.

Key Takeaways

• Learn how to design and orchestrate subagent systems that divide sophisticated workflows into coordinated, reliable components that work together without manual handholding.
• Build a working evaluation approach that lets you test agent reliability, surface failure modes early, and establish the evidence base your team needs to trust autonomous agents in production.
• Understand how agent accounts and autonomous execution models give your agents a clear, governed identity so they can run end-to-end workflows independently while remaining auditable and controlled.