CELab: The Customer Education Lab

In this episode of the Customer Education Lab, Adam Avramescu sits down with Kelly Mullaney, Head of AI Guild at Juniper Square, to unpack how AI is actually changing Customer Education. Kelly traces his journey from tax tech writer at Microsoft, to leading Customer Education at Envestnet, to building AI Guild—an internal enablement function focused on helping teams 10x their productivity with AI. Along the way, he shares concrete builds: an AI‑driven help center that watches code commits and auto‑drafts release notes and docs, a 37‑agent competitive intelligence system feeding Slack, and experiments in “vibe‑coded” e‑learning that challenge what LMSs and SCORM should look like in an AI‑first world.

Adam and Kelly go deep on the questions every Customer Education and Customer Success leader is wrestling with: Will AI kill our jobs, or amplify our impact? When does it make sense to build with AI versus buy another SaaS tool? How can small, scrappy teams of one keep up when engineering output increases 10x? You’ll hear a practical breakdown of the Anthropic stack (Claude Chat, Code Desktop, Cowork, Design, Managed Agents), a simple “80% AI / 20% human‑in‑the‑loop” mental model, and a candid look at the future of help centers, LMSs, and documentation. If you’re trying to move past the hype and see what AI‑enabled customer education really looks like, this episode is for you.

We talk about:

AI as the new “electricity”: why simply bolting AI onto old workflows fails—and what it means to rewire your education stack.

Kelly’s path: tech writer → running Customer Education at a $5B company → leading AI Guild at Juniper Square.

Human‑in‑the‑loop: using AI to get to 80% done and relying on experts for the final 20% quality bar.

AI‑driven help centers: monitoring Git repos for meaningful commits, pulling Jira context, applying style guides, and auto‑drafting release notes and help docs.

Fixed docs vs. AI assistants: why Kelly layers AI chat on top of a traditional help center instead of replacing it outright.

Discovering content gaps: using AI search and chat logs to identify missing documentation and new questions customers are asking.

Build vs. buy math: when building 80% of a SaaS tool in a weekend (with Claude + Supabase + agents) beats paying $30–60K per year.

Agentic competitive intel: 37 Claude agents monitor competitors, post daily briefs to Slack, and learn from a feedback loop.

Rethinking LMS and SCORM: legacy tools’ reporting limitations vs. what AI‑enabled tracking and analysis can unlock.

Demystifying Anthropic’s stack: how Claude Chat, Code, Cowork, Design, MCPs/connectors, and Managed Agents fit together.

Tool choice vs. governance: innovating even when your company only “allows” one AI vendor like Copilot.

Why CE leaders are primed for AI: curiosity, user empathy, and great questions matter more than coding backgrounds.

Getting started advice: don’t just “insert AI into the SDLC”—reimagine your education model for a 10x‑faster product team.

In this episode of the Customer Education Lab we sit down with longtime friend and customer education leader Lila Krutel at Skilljar by Gainsight to unpack how MCP (Model Context Protocol) and modern AI tools like Claude are reshaping the role of Customer Education in B2B SaaS. Together they explore how MCP acts like “arms” for your AI assistant—connecting it to systems like your LMS and Customer Success Platform so you can finally query, explore, and analyze your own data without waiting in the CS Ops queue.  

Lila shares concrete, in-the-trenches stories from Gainsight, including how she used Gainsight’s CS MCP plus Claude to identify customers with unused training passes, analyze the business impact of admin certification, and start connecting education programs to ARR and retention - all without writing SQL or begging for a special report. If you’ve ever felt blocked by data access, stuck waiting on BI dashboards, or unsure how to “prove” the value of education, this conversation will show you the art of the possible and give you practical ways to start experimenting—safely, skeptically, and out loud—with AI in your own CE or CS org.

In this episode of the Customer Education Lab, we sit down with Jess Katz, Senior Customer Education Manager at Forter, to unpack how she built an AI‑powered customer education function as a team of one. Jess walks us through her journey from joining Forter with a blank slate and an aggressive launch timeline, to orchestrating a “swarm” of more than 20 specialized AI agents that now support everything from research and course design to writing, video scripts, and brand voice.

You’ll hear how Jess leveraged an internal AI hackathon to create her first product‑ and brand‑trained agent, then scaled that approach into a full “agentic learning” stack using tools like Claude, Gemini, Glean, and video platforms such as Clueso—plus a next‑gen AI‑native LMS. She explains her step‑by‑step method for designing agents, reverse‑engineering “what good looks like,” and acting as the strategic director of a hybrid team of humans and AI. If you care about Customer Education, Customer Success, or doing more with less through AI, this episode is a practical, down‑to‑earth blueprint for where our field is heading.

Click here for our Agentic Learning Survey for Customer Education!

Episode Highlights:

From zero to launch: How Jess joined Forter with no existing customer education function and set an aggressive timeline to ship a full Help Center and Academy.

Team of one → team of many (agents): Why she now operates with 20+ specialized AI agents across research, writing, analysis, and design.

Agentic learning in practice: A concrete definition of agentic learning as a network of domain‑trained AI agents supporting both creators and learners.

Hackathon origin story: How an internal AI hackathon (open to non‑engineers) became the catalyst for Forter’s first product‑ and brand‑trained agent.

Replacing weeks of meetings: Case study where an agent analyzed a product screen recording and drafted a full article outline, saving weeks of PM/PMM + CE collaboration.

Multi‑agent workflows: Using Glean to mine 100+ pages of onboarding data, one agent to analyze patterns, and another to convert that into on‑brand course modules.

Strategic director mindset: Moving from “content producer” to director of a hybrid human + AI team, focusing on goals, quality, and business impact.

and much, much more ...

In this episode of the Customer Education Lab, we sit down with Jess Katz, Senior Customer Education Manager at Forter, to unpack how she built an AI‑powered customer education function as a team of one. Jess walks us through her journey from joining Forter with a blank slate and an aggressive launch timeline, to orchestrating a “swarm” of more than 20 specialized AI agents that now support everything from research and course design to writing, video scripts, and brand voice.

You’ll hear how Jess leveraged an internal AI hackathon to create her first product‑ and brand‑trained agent, then scaled that approach into a full “agentic learning” stack using tools like Claude, Gemini, Glean, and video platforms such as Clueso—plus a next‑gen AI‑native LMS. She explains her step‑by‑step method for designing agents, reverse‑engineering “what good looks like,” and acting as the strategic director of a hybrid team of humans and AI. If you care about Customer Education, Customer Success, or doing more with less through AI, this episode is a practical, down‑to‑earth blueprint for where our field is heading.

Here's the link to Jess's LinkedIn Article, "How I Built a Scalable Customer Education Engine as a Team of One Using AI Agents".

We're also very interested to learn from you! Click here for our Agentic Learning Survey for Customer Education!

Episode Highlights:

From zero to launch: How Jess joined Forter with no existing customer education function and set an aggressive timeline to ship a full Help Center and Academy.

Team of one → team of many (agents): Why she now operates with 20+ specialized AI agents across research, writing, analysis, and design.

Agentic learning in practice: A concrete definition of agentic learning as a network of domain‑trained AI agents supporting both creators and learners.

Hackathon origin story: How an internal AI hackathon (open to non‑engineers) became the catalyst for Forter’s first product‑ and brand‑trained agent.

Replacing weeks of meetings: Case study where an agent analyzed a product screen recording and drafted a full article outline, saving weeks of PM/PMM + CE collaboration.

Multi‑agent workflows: Using Glean to mine 100+ pages of onboarding data, one agent to analyze patterns, and another to convert that into on‑brand course modules.

Strategic director mindset: Moving from “content producer” to director of a hybrid human + AI team, focusing on goals, quality, and business impact.

and much, much more ...

In this episode, we are joined by Ashley DeKerlegand, Director of Customer Education and CX Enablement at Quickbase, to unpack how she transformed Quickbase University from “optional training” into a core driver of expansion and reduced churn. Ashley shares her journey from manufacturing and product training into SaaS, how she built and now leads a 12-person global team, and why Quickbase’s customer education program is tightly woven into the company’s onboarding and Failure-to-Launch strategy.

Ashley and Dave go deep on action mapping as a performance-first design framework, how Ashley evaluated 13+ learning platforms before choosing Brainstorm, and why private, co-branded customer portals have become a game-changer for governance, security, and adoption. You’ll hear how she partners with Sales, CS, and Product, uses customer interviews and Gong calls to shape strategy, and is now reorienting learning paths around AI-powered app building and customer-specific use cases.

Episode Highlights:

How Ashley repositioned Customer Education from “nice-to-have” to core expansion strategy at Quickbase  

Using Failure to Launch (no app built in 60–90 days) as a key churn signal and CE design input  

Moving from order-taking (“we need a course”) to strategic problem-solving using action mapping  

The four blocker categories in action mapping: environment, knowledge, skill, and motivation  

Why traditional frameworks like ADDIE/SAM often break down in fast-moving SaaS environments  

The power of private, branded customer portals for governance, security, and co-created content  

Turning CSMs, TAMs, and Sales into educators and content contributors (without overwhelming them)  

and much, much more ...