What happens when you stop thinking about “training” and start designing a revenue architecture? In this episode, we down with Sean Reay - a seasoned revenue enablement leader with experience at companies like Outreach and Canva, and now leading enablement for an AI-first CX company, Intercom. We unpack how AI, enablement, customer education, and customer success are converging into one continuous fabric of learning that spans your entire go-to-market motion. This episode dives into ideas like an “operating system for execution that reduces friction,” why many traditional LMS-centric approaches need to evolve (or die), and how AI agents can finally deliver “learning in the flow of work” instead of more information overload. We explore practical patterns - from conversational intelligence tools to AI roleplay and contextual knowledge delivery in Slack - that help revenue and CS teams ramp faster, execute with clarity, and deliver truly personalized experiences at scale. If you’re in Customer Education, Enablement, or Customer Success and trying to make sense of AI, this conversation is a rich, tactical blueprint. Key Takeaways: From training to clarity: Why high-performing teams need an operating system for execution, not just more content. AI in the workflow: How tools like Outreach, Gong, Intercom’s Fin, and AI-powered knowledge systems can surface the right guidance at the exact moment of need. Personalization at scale: Using AI as a layer across your stack to tailor messaging, content, and guidance for different roles, segments, and customer journeys. Agentic learning: The emerging pattern where AI agents watch, listen, and respond across tools (Slack, email, CRM, product) to drive just-in-time learning. Customer education + enablement ≠ silos: How internal enablement content and external customer education should be co-created and re-used, not duplicated in isolation. “Pull” vs. “push” learning: Moving away from mandated content dumps toward on-demand, contextually triggered support in tools like Slack and in-product. AI-assisted coaching: Using call intelligence and AI roleplay to coach sales, CS, and trainers on talk time, questioning, and customer-centric behaviors. Rethinking the LMS: Why static courses and rigid LMS structures struggle in modern SaaS, and what a more dynamic, AI-driven content fabric might look like. Revenue architecture lens: Viewing the entire customer journey—from acquisition through expansion—as a continuous learning and behavior-change system. Accountability and impact sprints: Using impact sprints and clear business outcomes to connect enablement & education work to measurable revenue and retention.