How one designer led an AI revolution at Pendo: The paternity leave epiphany | Brian Greenbaum

Brian Greenbaum is a Senior Staff Product Designer at Pendo who led a company-wide AI transformation after a personal epiphany while on paternity leave. After experiencing the power of AI coding tools firsthand, he created a structured approach to help his entire product organization adopt AI. In this episode, Brian shares his complete playbook for driving AI adoption across teams, measuring success, and navigating the organizational challenges that come with new technology adoption. *What you’ll learn:* 1. The exact Slack message Brian sent while on paternity leave that kickstarted his company’s AI transformation 2. How to structure both synchronous and asynchronous AI learning opportunities for maximum adoption 3. The two-pronged approach that dramatically increased AI tool usage across teams 4. Why becoming your company’s AI champion is one of the best career moves you can make right now 5. How to measure AI adoption success with sentiment surveys and clear metrics 6. The critical role of creating a “golden path” for AI tool usage with legal, security, and finance teams *Brought to you by:* Google Gemini—Your everyday AI assistant: https://ai.dev/ Lovable—Build apps by simply chatting with AI: https://lovable.dev/ *In this episode, we cover:* (00:00) Introduction to Brian Greenbaum (01:38) Brian’s paternity leave epiphany that sparked an AI initiative (05:00) Sending the message that launched a transformation (12:25) The two-pronged approach: synchronous and asynchronous learning (17:29) Encouraging experimentation and creative exploration (18:41) How AI enables designers to move beyond MVP thinking (22:00) Quick summary of the two-pronged approach (24:43) Measuring AI adoption (33:48) Creating a centralized AI knowledge center (35:58) Building an MCP server to demonstrate AI’s potential (44:08) Why technical understanding is crucial for non-technical roles (46:01) Final thoughts *Tools referenced:* • Cursor: https://cursor.com/ • Bolt.new: https://bolt.new/ • Claude: https://claude.ai/ • ChatGPT: https://chat.openai.com/ • Midjourney: https://www.midjourney.com/ • Gemini: https://gemini.google.com/ *Other references:* • Pendo: https://www.pendo.io/ • Confluence: https://www.atlassian.com/software/confluence • Slack: https://slack.com/ *Where to find Brian Greenbaum:* LinkedIn: https://www.linkedin.com/in/briangreenbaum/ *Where to find Claire Vo:* ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo _Production and marketing by https://penname.co/._ _For inquiries about sponsoring the podcast, email jordan@penname.co._

Brian GreenbaumguestClaire Vohost

Dec 22, 202547mWatch on YouTube ↗

WHAT IT’S REALLY ABOUT

A designer’s playbook for scaling AI adoption across product teams

While on paternity leave, Brian tried Cursor, rapidly built a prototype, and sent a decisive Slack message to leaders proposing an AI upskilling initiative across product (design + PM + others).
He then drove adoption with a two-pronged model: recurring synchronous learning sessions with live exercises, plus an asynchronous Slack channel for “radical many-to-many sharing.”
To make AI usage safe and scalable, the team measured sentiment and awareness, then built a centralized AI Knowledge Center that clarified approved tools, data rules, and procurement pathways.
Brian also demonstrates how individual experimentation can influence company roadmap—e.g., building a prototype MCP server to show how agents could query Pendo data and generate dashboards.

IDEAS WORTH REMEMBERING

5 ideas

A single concrete “I built this” moment can ignite organizational change.

Brian’s fast Cursor-built prototype created undeniable proof, making his leadership outreach compelling and actionable rather than hypothetical.

Position AI adoption as both productivity and market leadership.

He framed the initiative around internal leverage (do more, better decisions) and external credibility (Pendo as a thought leader for customers undergoing the same shift).

Adoption requires both calendar time and a sharing surface.

Bi-weekly sessions create protected time for hands-on practice, while a public Slack channel sustains momentum through continuous peer examples and experimentation.

Make sessions interactive to reveal how AI really behaves.

Having everyone run the same Bolt.new prompt exposed variability, failures, and debugging realities—building practical confidence instead of “AI theater.”},{

Use playful experimentation to break “MVP-only” thinking.

Encouraging wild iterations (themes, gamification, media) helps PMs/designers rebuild the muscle of imagining “magic” experiences now feasible with AI.

WORDS WORTH SAVING

5 quotes

“I think we really need to uplevel the skill of our entire product organization, not just designers, but also PMs.”

— Brian Greenbaum

“There’s no playbook for how to learn this stuff… the technology’s evolving so fast.”

— Brian Greenbaum

“If you don’t make the time for it, you’re never gonna learn it, and at some point you’re gonna get behind.”

— Brian Greenbaum

“We’ve lost our muscle for asking for the magic thing… now our bar can just be so much higher.”

— Claire Vo

“One of my most popular sessions… was called ‘WTF is MCP?’”

— Brian Greenbaum

Paternity-leave “epiphany” and leadership messagingCross-functional AI upskilling for product orgsSynchronous workshops with interactive build-alongsAsynchronous sharing channels and anti-hoarding cultureMoving beyond MVP thinking via AI-enabled creativityMeasuring adoption via sentiment + policy/tool awarenessAI Knowledge Center: approved tools, data rules, access processMCP server prototype to demonstrate agentic analytics valueTechnical literacy for non-technical roles (PM/design)

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