How to get your whole team excited about AI (and actually using it) | Brian Greenbaum (product designer at Pendo)
Episode
47 min
Read time
2 min
Topics
Productivity, Remote Work, Leadership
AI-Generated Summary
Key Takeaways
- ✓Inception strategy: Message leadership during paternity leave after building a working prototype with Cursor in hours, demonstrating concrete value and proposing cross-functional AI initiative with two goals: team productivity and thought leadership positioning.
- ✓Two-pronged adoption approach: Run biweekly hands-on sessions where entire team builds same app simultaneously (like to-do lists in Bolt) to experience AI variability, plus maintain public Slack channel for radical many-to-many sharing to prevent information hoarding.
- ✓Golden path framework: Create documented AI knowledge center listing approved tools alphabetically with security status, allowed data types, and license request process. Work with legal, IT, and security to enable rapid tool experimentation within one week approval cycles.
- ✓Measurement through sentiment surveys: Track five metrics quarterly including AI sentiment, policy awareness, and tool familiarity. Biggest gains came from clarifying usage policies and available tools, with positive employee impact sentiment increasing significantly after establishing clear guidelines.
What It Covers
Brian Greenbaum shares his framework for driving AI adoption across Pendo's product organization through biweekly sessions, async Slack channels, and OKR-based measurement, transforming team sentiment and establishing clear usage policies.
Key Questions Answered
- •Inception strategy: Message leadership during paternity leave after building a working prototype with Cursor in hours, demonstrating concrete value and proposing cross-functional AI initiative with two goals: team productivity and thought leadership positioning.
- •Two-pronged adoption approach: Run biweekly hands-on sessions where entire team builds same app simultaneously (like to-do lists in Bolt) to experience AI variability, plus maintain public Slack channel for radical many-to-many sharing to prevent information hoarding.
- •Golden path framework: Create documented AI knowledge center listing approved tools alphabetically with security status, allowed data types, and license request process. Work with legal, IT, and security to enable rapid tool experimentation within one week approval cycles.
- •Measurement through sentiment surveys: Track five metrics quarterly including AI sentiment, policy awareness, and tool familiarity. Biggest gains came from clarifying usage policies and available tools, with positive employee impact sentiment increasing significantly after establishing clear guidelines.
Notable Moment
Greenbaum built a custom MCP server for Pendo in evenings without understanding the underlying code, then demonstrated it to leadership by querying analytics data and generating dashboards through natural language, directly accelerating the product roadmap for agent features.
Episode Transcript
I tried Cursor for the first time, and what I was able to create just blew me away. I sent a message to my manager, my manager's manager, the CPO, and then a few other folks that I knew were really interested in AI. And I was like, listen. I had this really profound experience, and I think we really need to uplevel the skill of our entire product organization, not just designers, but also PMs. We need to become more familiar with this technology. We need to understand how we can use it. This is actually the message that I sent while I was on paternity leave that definitely got my leaders really fired up. I didn't know exactly how this was gonna go. All I knew was that I needed to get more folks paying attention to this AI stuff. If you were the first to raise your hand that says, you know what? I wanna figure out how our team can use AI. I'm gonna lead this organization. It's such a unique leadership opportunity to show cross functional broad impact on teams. Welcome back to How I AI. I'm Claire Veaux, product leader and AI obsessive, here on a mission to help you build better with these new tools. Today, I have Brian Greenbaum at Pando, and he's gonna show us not only how he uses AI in his own product work, but a step by step plan for getting your product and design teams adopting AI as well. Let's get to it. This podcast is supported by Google. Hey, everyone. Srishta here from Google DeepMind. The Gemini 2.5 family of models is now generally available. 2.5 pro, our most advanced model, is great for reasoning over complex tasks. 2.5 Flash finds the sweet spot between performance and price, and 2.5 Flashlight is ideal for low latency, high volume tasks. Start building in Google AI Studio at ai.dev. Ryan, thanks for joining us on How I AI. Happy to have you. Yeah. So excited to be here. Well, what I am excited about in our conversation is in a lot of our How I AI episodes, we've shown specific ways that you can use specific tools to build or do things with AI. And you're gonna help us take a step back and say, you know, let's say you have all these tools and you want to start using them. How do you get a full team or a full organization, a full company actually adopting AI? And so this is, how I get everybody else to use AI episodes. So I would love to start with what I call the inception phase, which we all have gone through or are all in the process of trying to get our team to go through, which is when you get people excited and sort of jump start the energy around AI. And I think you approach this in a really interesting way. So I'd love you to walk …
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Books, tools, and gear mentioned in this episode
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Tools
- CursorRecommended
“Message leadership during paternity leave after building a working prototype with Cursor in hours, demonstrating concrete value”
- BoltRecommended
“Run biweekly hands-on sessions where entire team builds same app simultaneously (like to-do lists in Bolt) to experience AI variability”
“Sponsors: Lovable (lovable.dev)”
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