Most AI conversations focus on using a tool for a single task. This interactive lab focuses on something more lasting: designing an AI collaboration agent that can support your work beyond the session.
Participants will walk through a simple process to define the role and personality of their AI collaborator, provide the right context, and test it on a real workplace challenge. By the end of the session, attendees will leave with a configured AI collaboration agent they can continue using and refining in their day to day work.
No technical background or coding is required. If you can describe your role and a challenge you are trying to solve, you can begin designing an AI collaboration partner.
Key Takeaways
- Design a personalized AI collaboration agent aligned to individual roles, priorities, and working styles.
- Apply key design decisions such as personality, context, collaboration style, and guardrails to shape how an AI agent supports decision making.
- Test an AI collaboration agent on a real workplace challenge and leave with a reusable configuration rather than a single output.
- Understand the difference between AI as a task executor and AI as a thinking partner and why this distinction matters for Total Rewards work.
This lab complements the session “How a Comp Guy Learned to Stop Worrying and Love AI,” which introduces the broader framework for designing an AI collaboration partner. This session focuses on building and applying those ideas in a hands on setting.
Originally from Chicago, Ryan now calls the Twin Cities home, where he serves as Director of Total Rewards and People Operations at Edmentum. He holds an MA in I/O Psychology along with CCP and GRP certifications, and brings over 15 years of experience across manufacturing, technology, retail, and financial services. A TCCN member since 2006 and current President-Elect, Ryan is known for his behavioral economics approach to rewards design. He's also an unlikely AI builder, designing custom AI agents and automation tools for his HR team with zero development training, applying a "problem-first, tool-second" philosophy to Total Rewards work. He lives in Woodbury with his spouse, three kids, a high-energy black lab, and two kittens. In his free time, he enjoys cooking, sourdough, and exploring museums with his family.
