Wait, How Did You Get AI to Do That?”: AI Workflows for Customer Education

Customer education pros keep having the same conversation:

“Wait—how did you get AI to do that?”

The most useful answers rarely come from generic prompt lists. They come from practitioners who have experimented, corrected weak outputs, documented what “good” means, and turned their expertise into repeatable workflows.

Join Christie DeCarolis and Clea Mahoney for a practical show-and-tell exploring how customer education teams are using AI in their day-to-day work.

We’ll walk through a typical week in the life of a customer education practitioner—from Monday’s backlog and planning meetings through course design, SME interviews, content development, quality checks, and Friday follow-up. Along the way, Christie and Clea will show where AI workflows actually appear in the work, including the small, useful moments that rarely make it into webinar headlines.

You’ll see examples of using AI to uncover content gaps, extract useful material from expert interviews, improve instructional writing, design better courses, evaluate lessons, automate handoffs, and prepare content for publication. Christie and Clea will share what they built, what didn’t work the first time, and where human judgment still matters most.

You’ll also get an inside look at ideas from the community-built Customer Education AI Playbook, featuring real prompts, workflows, and lessons from practitioners using AI right now.

This isn’t another session about asking AI to “make a course.” It’s about seeing how AI fits into the reality of your workweek—and teaching it what quality looks like in your context so you can build better, not merely faster.

You’ll learn how to:

• Recognize where AI workflows can naturally support a typical customer education workweek
• Move beyond one-off prompts and create reusable workflows
• Turn your instructional standards and recurring decisions into clear AI instructions
• Use focused AI skills and intentional handoffs instead of one do-everything mega-prompt
• Give AI the learner, product, and business context it needs to produce useful work
• Improve the quality—not only the speed—of course design and development
• Decide what AI can draft, what a human must own, and where both should be involved
• Come ready to steal what works, skip some trial and error, and leave with practical ideas you can try when you’re back at work on Monday.