CX Signals
What does it actually take to build an AI workflow that holds the bar on quality? Not the theory — the real thing, with all the context window limitations, mid-project pivots, and "why are you failing me, Claude?" moments. Clea Mahoney is a Learning Experience Design Manager at Rewst, a workflow automation platform for managed service providers, and the CE challenge there is one of the most complex I’ve come across. Every single customer is building something different, which means there's no standard, no one-size-fits-all. She has to figure that out fresh every time. What makes this conversation so good is that Clea isn't talking about AI in theory. She walks us through the actual workflow she's built inside Claude to audit, update, and maintain her course library — from the Notion drafts to the instructional design rubric she trained Claude on, to the multi-chat structure she uses to keep context windows from getting overwhelmed. It’s specific, it’s practical, and it’s the most honest account you'll hear of what it actually takes to build an AI workflow that holds the bar on quality. In this episode, we get into: * The course audit lifecycle she built — and how it's still evolving * Why breaking work into focused, separate chats is the key to quality output * How human expertise remains non-negotiable in the review process * What it feels like to manage a "team" of AI agents instead of humans Oh, and baby Willow made a cameo. That's just how we do things here. Find Clea on LinkedIn to keep the conversation going: https://www.linkedin.com/in/cleamahoney/ [https://www.linkedin.com/in/cleamahoney/] Connect with Samantha on LinkedIn: https://www.linkedin.com/in/samantha-murray613/ [https://www.linkedin.com/in/samantha-murray613/] Chapters: 00:00 Introduction 03:44 Clea's Journey in Customer Education 06:34 Understanding Roost and Its Challenges 08:50 Adapting to Team Changes and AI Integration 11:04 Transitioning to Claude AI for Workflow Design 13:40 Developing Effective Curriculum with AI 18:47 Iterating on Course Design and Content Creation 21:59 Incorporating Feedback for Quality Content 24:38 Adapting Terminology for User Understanding 26:49 Breaking Down Complex Processes 30:41 Automating Course Updates and Maintenance 35:48 The Role of Human Expertise in AI 37:53 Managing AI Agents as Team Members 41:37 Continuous Optimization in Learning Design
10 episodios
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