How I AI - How to get your whole team excited about AI (and actually using it) | Brian Greenbaum (product designer at Pendo)

Episode Date: December 22, 2025

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:The exact Slack message Brian sent while on paternity leave that kickstarted his company’s AI transformationHow to structure both synchronous and asynchronous AI learning opportunities for maximum adoptionThe two-pronged approach that dramatically increased AI tool usage across teamsWhy becoming your company’s AI champion is one of the best career moves you can make right nowHow to measure AI adoption success with sentiment surveys and clear metricsThe 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 assistantLovable—Build apps by simply chatting with AI—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 [e-mail].

I had 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 going to 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 want to figure out how our team can use AI.

I'm going to 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 Clarevow, product leader and AI obsessive, here on a mission to help you build better with these new tools. Today I have Brian Greenbaum at Pendo, and he's going to 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, Shrejhta here from Google DeepMind. The Gemina 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. Brian, thanks for joining us on Hawaii 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 HowI AI episodes, we've shown specific ways that you can use specific tools to build or do things with AI. and you're going to 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 jumpstart the energy around AI. And I think you approach this in a really interesting way. So I'd love you to walk us through what you did at Pendo. Yeah, absolutely. So to take you back, it's the end of last year. So last July I had my daughter Meyer.

My daughter Maya was born. You can kind of see the nursery in my background with this is sort of a shared office nursery. And I was on paternity leave at the end of last year. And I'm sort of like a tech geek. I've been following AI for a while. My day job is a designer at Pendo, but, you know, I've always sort of been into tech. And so I've been following AI very closely. I've also had some experience, like building side projects and things like that.

And I think it was back in November. Cursor came out, or maybe it was a little bit earlier than that. But Cursor, I had tried Cursor for the same, for the first time. And what I was able to create just blew me away. So I had like a side project idea, this hobby app in my mind about a music player where I can play albums by scanning a QR code on sort of like a piece of paper. I was very jealous of people who had record players. I don't have space for a record player in New York.

And they get to choose music by just sort of flipping through albums. And I like having unlimited access to music via Spotify, but I sort of missed that sort of like tactile experience. So it's like, well, what if I create these sort of like laminated cards and I have this way of just being able to play the albums that are on that? So I had this idea of like what if I can create sort of a mobile app where I can scan like a QR code or I could recognize the album cover and I can print these album covers out and just be limited in that way. And I had no idea how to do that like on my own.

Like I'm not an active developer. I can't sit down and write that application. And I pulled up cursor and like within a couple of hours, I had a working prototype and like that just blew me away. I was creating QR codes. I was creating PDS. I was like doing all this like really, really cool stuff. And, you know, like I said, my day job is a product. And I immediately understood that like, okay, this is really cool. As a sort of side project, it's really fun. But I could use this to build interactive prototypes. I consider myself pretty proficient with Figma, especially when it comes to prototyping.

But I understand the limitations of using Figma for prototyping. A lot of what I do at Pendo is sort of working on features that are analytics based. And so when you're creating mockups and prototypes that are data-driven, it's really hard to communicate what the, you know, how these things are actually going to work with real data. So having a prototype that is code-based that is working with even just fake data and interacting sort of in a more dynamic way is really useful. So I was like, wow, I think I would really use this at Pendo. So I had the, you know, even though I am on paternity leave, you know, I had this idea and I was like, I couldn't contain myself. You know, I wasn't going to come back to work until the beginning of January.

So in December, I wrote a whole bunch of folks at Pendo. I still had access to my Slack. And so I wrote, you know, I sent a message to my manager, my manager's manager, the CPC. 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, you know, we really need to up-level the skill of our entire product organization, not just designers, but also PMs. We need to become more familiar with this technology.

When you need to understand how we can use it. I had already understood that, like, there's no playbook for how to learn this stuff. There's no class you can take. There's no book you can read. And the technology is evolving so fast that the only way to really know how to apply it, is to become very familiar with how it works, to kind of stay current with all the latest technologies and the tools and just sort of like see a bunch of examples. And like selfishly, like I wanted to spend more of my time at work doing these things. But I also wanted to

help my, my colleagues and my company just be more successful because I saw a clear path to that. And just getting more people, more of my peers, more of my colleagues, like doing the same thing and sharing their experiences, I know it would help me learn. And I think it would just sort of like, you know, rise all the boats. And so this is sort of an example here. Not an example. This is actually the message I pulled it up that I sent while I was on paternity leave just to kind of give you an example of what something like this looks like. And I wrote this like pretty long message. I mean, for folks that are not watching this, you know, I just kind of said, TLDR in a similar fashion to, you know, there's an engineering focused sort of group that had been around for at least a year,

but nothing really focused on PMs and designers. I was like, I'd like to lead a group like that before a cross-functional, cross-functional product team with design designers, PMs, and et cetera, with two goals. Pendo's product team can leverage the cutting edge of AI tools to get more done in fewer hours and less resources, improve decision-making, and communicate and validate ideas more effectively. And then two, because Pando is also sort of servicing a lot of product organizations that are going through similar transformation to help position Pando as a thought leader in the space because I knew it was just going to be really important. And then I went to through like a longer version of sort of like my my experience of like building this app and um and why

i thought it was important and um you know i'm really fortunate to be part of an organization that supports sort of initiatives like this and so i you know that definitely got my my leaders like really fired up in fact the cpio was like hey can you come to like all hands next monday and talk about this this concept and i was like i'm on paternity leave i can't do it yet um but i will start as soon as i come back and so that that's sort of that's what happened so that was a catalyst for uh this idea and i got to say like i'm i'm the kind of person that uh you know sometimes i can be like type a and like really like think things through but i also know that sort of committing to something or just like forcing myself to like throw myself into a situation um without knowing like how it's going to work

out uh can also result in something really interesting um so i didn't know exactly how this was going to go All I knew was that I need to get more folks paying attention to this AI stuff. And I also need to create time in people's calendar where everyone can just like focus on it and play or maybe like hear a presentation on something new. So I have to call it a couple things here that I think are really important. One for anybody trying to, you know, give it a justification if you need it for investing extra time resources and energy into this AI transatlantic. in your organization. I love that you call up actually the two things that really matter. They're very similar things to how I called out the value of AI transformation at Launch

Darkly, which was one, our team's got to know how to use this stuff. Like we've just got to know how to use these tools, get more done, be more efficient, just use the best of the best. The second one though, I think is really interesting and there's still a lot of opportunity here. You know, you're on this podcast, which is, there's this opportunity for leading organizations to position themselves as thought leaders in how you get stuff done with AI in your vertical. And so for us, it was like, we have to be great AI engineers because we need to be great engineers. Generally, this is the next phase of how software engineering is going to get done.

We need to be thought leaders in the space. And very similarly for you on the product side, I think it's just really important that you can create platforms for your company to be experts in the space if you lean in early into these technologies. You know, the other thing I want to call out is, you know, I try to tell people at this all the time. This is like promo making work. And what I mean is like, this is the kind of initiative that doesn't come around that often as an opportunity. And if you're the first to raise your hand, like if you were the first designer that says, you know what, I want to figure out how our team can use AI. I'm going to leave this organization. it's such a unique leadership opportunity to show cross-functional broad impact on teams.

And like, there's only give me one or two of you that get to be the leader of it. So I'm like really encouraging people to be like you. Raise your hand early to take on the initiative for the organization. One, because I think it's the right thing to do for the team. But two, it's really great from a personal career perspective. Absolutely. And like, yeah, I wasn't going to focus on that. Yeah.

But like what you're saying is absolutely 100%. true. So, like, this sort of initiative has opened so many doors. I'll get into it in a moment, but it's opened so many doors internally within the organization. Like, I'm speaking with you. There's no way I think I would be speaking on such a high profile podcast if I didn't start working on this and sort of build up sort of the body of work that I have over the last nine months. I get to work on some really cool AI projects. I have folks throughout the organization that are not even in product and design, folks I didn't even know. reaching out to me and sort of like looking to me as a thought leader. And that wasn't my intent,

but it's absolutely true. It's like there are opportunities across all organizations right now, regardless of your level. I mean, I'm a senior staff, but I'm an ICI'm just a product designer. Like, but I'm having an influence way beyond my scope. And I think regardless of where you are, like if you have the initiative and the energy, and it does take a little bit of time, like there is some nights and weekends that like I kind of put into it. But I also love this stuff. like I was kind of doing it anyway. Yeah. And so absolutely, it is a career builder.

Yeah. And then, you know, maybe my last reflection is, do you know how many people I know that have gone on parental leave and in between rocking their newborn have been shipping stuff with like cursory? Like every single parent I know, this just might be my peer cohort. Everyone I know has been texting me from parental leave being like, Claire, I've been vibe coding with my baby. And I am so into it. So if you have somebody on parental leave right now, it's very likely they're going to come back AI-pilled for sure, because that is what I have seen consistently with some of my friends. Okay, so let's actually get into this message, kick things off. But then you actually have to functionally make this happen.

And you sort of had like a two-pronged approach to two things that were really effective in getting this going in your organization. So what were those two things? Yeah, yeah. So the two things, so I'm just kind of bringing up here in case. is helpful. So this was sort of the first announcement I made within the organization I had come back in January. This is sort of like our private chatel of the entire product organization. So within Pendo the product team are PMs, designers, writers, and a few other folks. And so I was like, hey, I'm starting this initiative. And in my mind, I was thinking that there's sort of a two-prong approach.

There's an asynchronous and asynchronous. One thing that I was very familiar with, like just in my own but also talking to other people is that you'll typically hear something like, yeah, that AI stuff, like, I know it's important, but I just don't have the time. Like, I don't have the time to, like, watch all the videos and, you know, vibe code and lovable or whatever it is, right? And the crazy thing is that, like, if you don't make the time for it, you're never going to learn it. And at some point, you're going to get behind, right? And so it was really important for not just there to be a place within Slack and encourage people to share on Slack, asynchronously to do it at their own pace, but also to create time in people's calendars so that they can come and focus on like whatever the topic is.

And also within that session, it's not just about a presentation. It's also like it's really important for that presentation or that session to be interactive. So let me give you an example of that. So this was a kickoff as well as an exercise about building apps. Just to sort of give you a insight into how I start this off. I was like, hey, AI is getting better. It's getting faster. and it's evolving how software is planned, designed, and built.

And this was really meant to speak to not just us as builders, but also sort of the product that Pendo was building. And right around that time, Andrew Ng had a really, I thought, thoughtful blog post about how he was thinking about how PMs need to position themselves sort of in the AI, in this AI future. And then AI is typically sort of in the space of sort of engineering and technical stuff. And, you know, he was positioning AI as perhaps being, or at least engineers being better positioned

to sort of like take advantage of all of the stuff because they are technical. But he was saying it was really important for PMs and I would also put designers in that camp as well to become proficient. And so these were the sort of five things that he was, he really wanted to focus on technical proficiency, just iterating on the development,

like using AI in a sort of iterative capacity, being very proficient with data, skill and managing ambiguity, and his ongoing learning. So like that was really sort of the emphasis that I wanted to drive. And so again, the structure of sort of like, or at least the goals, sorry, the goals of the product AI was around to up level and modernize the skill set of our product people to improve our comprehension and literacy. And then because our customers are also builders to empathize and assist with them as well.

And I wasn't sure if this technique again was going to work, but this was how I was thinking about approaching it, just being more hands on, getting our hands dirty, radical many to many sharing, being intentional, creating the space. and then identifying the patterns that worked, and then sort of turn those into reusable patterns. So in this opening session, like I was saying, like it's really important to have an interactive session. And I'm not going to go through the slides of like how I talked about code building tools and the different, you know, the various types and some things that I had built.

But there was a section that was at least, I think, 10, 15 minutes where I was like, all right, everyone, you know, go to bolt.com. That was the app that we chose to use at the time and create an account if you haven't created an account. And then everyone go to Bolt and copy and page, this. So this was just a prompt that I had created. It wasn't hyper-optimized. It was about creating a to-do list. The most basic, like, little mini SaaS app that you could possibly build. And I had everyone

type this in. And then there was, like, a little enhanced prompt thing that I wanted everyone to use just to sort of see how, like, this, this app could sort of take a very basic thing and turn it into a more sophisticated thing. And then let it rip. And there go. And I would say I wasn't expecting this when I did this the first time. But the thing that really stood out, because it was sort of like, obvious to me that this is, this is what would happen. But some of the feedback I got was like, wow, like we all typed in the same thing. We all clicked on the enhanced prompt button, and we all got different results. So like this was just sort of an example of like, these were all the to-do list applications that the app created after running that query.

And I think in the third of the cases, like, Bolt just came back and said, nope, like, like, like, error or whatever. And then like, so we immediately got into the whole thing, oh, okay, don't worry. Like if you get in there, just down to fix it, blah, blah, blah. Everyone sort of like got through it after two or three rounds. So that is like, it was great to experience that as a team and not only just to like do it and see how it worked, but also to see the diversity of like how like these applications are built and how genealize being used. And then the other thing I had people do in the last like 10, 15 minutes is experiment on their own. And I told people just to do crazy stuff.

Like we're not doing this for any, like we're not really building at the do list. And the AI will do its best to do as you say. So you can give it like the most wacky, you know, instructions, right? Like, you know, make it, you know, add a retro 8-bit pixel art theme, you know, introduce a dark mode title, make it look like MySpace from 2007. And so that was sort of like an interesting thing too. So like people sort of like went nuts. They shared some things.

Like I think there's a few examples here of like people saying, oh, you know, I tried. Yeah, here. This is what UI will look like in 2002, 200. here's my Tumblr style, you know, to do list. And like, this was intentional to sort of like make it fun. These are designers, but there's also PMs. And like we all know sort of like there's a line between sort of like professional stuff and personal stuff. But like what I really wanted people to experience is that this can be fun and just like to broaden their minds about how they can apply this technology.

One thing I want to call out as a meta benefit to this slide that you showed. And maybe we could go back to it of like now go. wild or optimize it is I think it's designers and product managers in companies and you can tell me if you have a different experience. But we have just gotten beaten by the scope creep stick so frequently that we have actually lost our muscle for like asking for the magic thing. We always start with the MVP. We always start with like what is the bare minimum thing I can ship to meet the user requirements that I know engineering can do. And like we've lost this ability to imagine like, what if it did this and what if it did that? And it could be interactive or there could be voice.

And what I like about AI is one, it makes those magic things a lot easier to build, you're more efficient to build. But two, like it's going to let designers and product managers return to the craft of building the awesome product as opposed to like the viable. product, which is so, like, if you reflect on it, it's so sad that we have put on a pedestal, like minimum viability as just like such a low bar. And now our bar can just be so much higher for what we build, but you have to like reignite this muscle of like how to even think about what those things could be. So I love the idea that you, you know, put these, these iterations in categories like visual iterations.

interactive iterations, entertaining our gamification iterations. And then like media again is something that's really interesting that you can do with AI. I know as a designer, like how many times have you been like, oh, an illustration would be amazing here, but no one wants to spend the time to like draw a custom icon or a photo would be here. But like we don't have any stock photo budget for this project. So I'm just going to like erase that and put white space. And so I just think like that piece is so underrated for AI is like getting. out of, getting us out of MVP mode. Yeah. And I got actually a really cool example of that as well. So like, you know, that was the sessions, right? But then there's also the channel. And so, you know,

people are constantly sharing things, links to articles, experiments that they've tried. I mean, that was the whole intent of it, right? It's just to sort of have a space where people can share things. And I think there's an example in here where, oh, yes, here it is. So Mark, you know, he's a, he's a product designer. And I think this was right on the time that Mid Journey launched the ability to do animations or video. And he was like, wouldn't it be cool? to have, you know, sort of in this intro screen, these little animated characters that sit there and just, like, wave at you, right? And it's so cute.

Exactly, right? And it wasn't that hard. I mean, like, I think, you know, he iterated on a couple of prompts. Like, this is not in the product. It's not in the product yet. But, I mean, he was able to create an asset that's not that hard to drop in if you have the right in spot for it. And like, like you said before, it was, oh, man, like, really cool to have a good

illustration or an animation, but I got to go talk to a professional or I got to go spend nights and weekends working on. It's like not worth the effort. And now we can bring a little more life into our applications. And that life, of course, turns into like what I just did. We're just like, oh, my God, I love it, which is just like customer connection to your brand, to your product, a little bit of sense of like this team actually really cares about the craft and is going to continue to invest in this product experience, all that, all the great stuff.

And then I just want to call out for folks that maybe miss this and part of the transition. So the two kind of major pieces you put in were. these sessions, these product and AI sessions, and you showed us the kickoff deck of what that looked like, both the why and then like, let's actually get into it. Let's do it together. And then the second peak, that's the sync piece. And you do those weekly, right? We do them biweekly. I mean, we could probably do them weekly, but we've done them biweekly. Yeah, I put in a, we'd have put in a similar thing. We call them like AI power hours on Friday. And it was like every week. We would do that.

And then the second thing is the async channel, which like, if you do not have it, you should definitely have it where folks are just sharing. I like this bullet point that you had in your slide that was like radical peer-to-peer share. I forget what it said, but it was such a good phrase. Yeah, radical many-to-many sharing. And so one of the things that I think organizations often suffer from during this AI transformation is information hoarding and like secret AI. And I think it happens for two reasons. Secret AI can happen because people aren't sure what they can use, and we're going to talk about that in a minute. And so they like kind of pretend they're not using AI or they use their like Gmail account because they don't want to get in trouble, but they're going to use it anyway.

And so there's like secrecy because people don't know the golden path of using AI. And then there's like information and skills hoarding right now, which is like the dark side of being an AI agent or an AI change agent, which is people are like, well, I'm the only one that. knows how to do this. So I'm going to stand out if I'm like extra good on these things or just get my work done faster or whatever. And so this like build in public many to many sharing is so important for a healthy culture around AI transformation. I cannot emphasize this, this one enough. Absolutely. This episode is brought to you by Lovable. If you've ever had an idea for an app but didn't know where to start, Lovable is for you. Loveable lets you build working apps and websites by simply chatting with AI. Then you can customize it, add automations, and deploy it

to a live domain. It's perfect for marketers spinning up tools, product managers prototyping new ideas, or founders launching their next business. Unlike no code tools, lovable isn't about static pages. It builds full apps with real functionality. And it's fast. What used to take weeks, months, or even years, you can now do over the weekend. So if you've been sitting on an idea, now's the time to bring it to life. Get started for free at lovable.dev. That's lovable.dev. You implemented this back in January, back from a leave where can you believe that the year is like almost over.

We're like there. It's unbelievable. I know. And, you know, how did you actually measure? Did any of this matter? Right. Like, did we do this and was it fun? or did people actually adopt this?

And how did you get there? Yeah, yeah. So I think there's like there's several ways I can answer that question. The first is like, you know, I didn't intend to have to implement a company-wide transformation, right? I need to start somewhere or at least I wanted to really focus on my craft and the people that are around me. So that was product design, a little bit of engineering, right? And so product AI is intentionally focused on the area around creating product. using AI to design, product management, engineering, that sort of thing.

It wasn't intended to sort of branch out to, you know, how does revenue sell better, or how does finance do whatever finance does better, right? The channel, so like it really, it was really important for the channel to be public. We have like 200 plus people on the channel now. That is way more than the product organization. So the thing is, like, even if you're sort of focusing on a functional area, there's aspects of that functional area that bleeds outside of the organization. So just to kind of give you a perspective on like the sessions that we ran, right?

So we started back in January, we were doing it every two weeks. And you can kind of see sort of like some of the different topics. It wasn't just all about vibe coding. It's about prompting. It's about, you know, how do you take customer feedback and sort of make sense of it? There are sessions here on just like diving into just Gemini. I mean, like, we have access to a whole bunch of Google features from Google that are AI related and they're spread out throughout their entire ecosystem. So it's like, hey, what are all the

things that we can do to sort of take advantage of that? And that was one where I intentionally made it not just about product and design because like, you know, the finance people and the revenue people could definitely take advantage of things like deep research within Gemini or the AI function within, within sheets. So sometimes like it makes sense to sort of like really promote these things outside. But again, it was like, you know, you kind of want to make sure that you stay within their group. And then separately, there was an initiative, an OKR in the first quarter of this year. Our quarters begin in February. So I had started this. Yeah. It's like it's so weird. That's a little enterprise, enterprise sales fiscal year right there. Yeah, it's really confusing

because we're like, we're in fiscal year 2026. I'm like, I thought it was still 2025. And it's October? What's happening? Yeah, totally. So yeah, we're like, well, like one month off. So our quarters begin in in February. So I had started this. And I think because to your, to your point earlier about like how this, this is also a good career move, it adds a lot of visibility, I think, to you if you try to take the initiative. Like I had just started this a couple weeks earlier, but I was invited to be part of a cross-functional group that was responsible for a company-wide OKR to improve AI leverage within the organization. And so I can show you some of the things that we did, but like, I think the most important thing that we did was just measuring, right?

Just measuring sort of like what is the, and we called it a sentiment survey because like we didn't really know what people's or like my colleagues' feelings were about AI, right? Like because, you know, you might feel like AI is taking your job or AI is creating slop or you might feel that like AI is such like a cool, fun, like incredibly transformational technology that, you know, is going to solve cancer, right? Like, I don't know what the sentiment is. We weren't really, you know, you're not, you were never really hiring for this skill or this attitude, right? And so you have a group of folks and, you know, you're thinking about instituting a transformation on how they work and the technology they use. And so it was really important, I think, for us to get a temperature read on, like, how people felt about AI. But we also wanted to know other dimensions as well. Are they aware of the, like, for instance, are they familiar with our usage policy, right?

like there's a lot of shadow IT happening just like you said like people are using their Gmail their personal chatGB accounts that do professional work and they're not sure is like is that cheating is that how loud or even like what kind of data am I allowed to put into chat gbtique and I put like customer transcripts in there like I don't I don't know what the answer is and some people are just doing it because they know it's going to be helpful and some people are not doing it because they're worried that you know that's not that's not cool and the other thing too is like they don't know what tools are available because yeah I mean like you have Salesforce, you have Gmail, but you don't, like, at the point, at that time, we didn't have

company-wide licenses for chat GPT, right? So, like, no one knows what is actually available to them. And so what I'm showing here is, like, at the beginning of the quarter, so, like, the idea was we would do some things within the quarter, but in the beginning of the quarter, we'd take this baseline, and we asked these five questions. And we also got some, some quality feedback as well. So it kind of gave us a little, an idea sort of like, why things were trending in a certain way. And then one thing that we had, we noticed, and you're kind of looking at sort of like the trend of what happened from the beginning of the quarter to the end of the quarter.

There was an increase along all of these measurements. And the biggest ones were around this usage policy and which tools do I have available to me. I think the biggest gap was here because we didn't spend any time with it. So there was a lot of work done in that quarter just by making people aware of what they can do and how they can request software. So here's just a screenshot of an internal confluence document. call the AI Knowledge Center. And in this document, um, there's all the information that an employee needs to know about which AI tools they have available to them. So like if you were to scroll

down, you'd get this like alphabetized table of all the products that have been approved to be used within our organization for security reasons, um, for, for legal reasons. I mean, the thing is that like, AI is a vector for doing some really bad stuff. And even though you want to move fast, and you want to use all of these really cool tools, you don't want to put your company and your customers' data at risk. And so it's really important that, you know, you work closely with your security,

your IT department, your finance department, your legal department. And like, again, I'm very fortunate to be in an organization where like those folks, which sometimes can feel like friction and a barrier, like they, I think they recognize that, like, this was also really important and sort of like prioritized,

you know, still doing all the solid work, but like adding my prioritize sort of like the enabling us to sort of like not just use these tools, but experiment with different ones. Like I found myself for like a month. Like every week I was submitting these like zip requests for a new software that I wanted to try out. And it would only take maybe like a week for me to sort of get the okay. And you can kind of see like it was really important not just to see which applications I have access to and how that application could be used.

But what kind of data can I share within an application? as well as if I wanted to get access to it, like what are ways that I can get to that? And so when I, you know, I go back to this slide, you know, that was one of the tactical things we're able to get done in a single quarter that really made a huge difference sort of in this, in this metric of awareness about policy and tools. I want to just call this out for the leaders on the team that are,

or the leaders in the audience that are listening. This is the first thing I tell them to do is I say define the golden path, to using AI. And it takes three pieces. It takes finance and procurement. It takes legal and it takes security. And what I tell them is it's really not going to benefit the acceleration of your team to say, you will go heads down and figure out how you can get chat GPT and cursor and you'll get your three little tools and we'll let you know what they are. You actually need what you called out, which is a very fast path to experimenting with reasonable tools to identify which one, are going to work for your team. And that rapid experimentation is really, really important. You can't go do

a big, like, multi-month evaluation of one code editing tool because, as you said, they're changing so rapidly. And so I love this documented place of like, here's the tool, here's the status, here's the data you can put in and the data you can't put in. Here's how you get a license. Here's how you get help. It's just very, very, very useful. And if you get this done, then it all starts to snowball from there because people have a place and a path to go down. So I, this is probably like not the most exciting screen share we've seen. Like it's a table and a confluence talk. But like I just want to pause, screenshot this. If you do not have this in your org, like you need it need to say because this is going to be the thing that changes how you work. I love this. Yeah, 100%. And like once you

kind of get that ball rolling. Like, you know, there, there's a separate channel, too. Like, I think it's called, like, the AI Knowledge Center. It's meant to be sort of like the product of AI channel, but more like broad base. And every once in a while, someone be like, hey, can I use granola for this? And someone outside of IT, you know, someone who's just familiar with this, with this process, which is like, hey, go check out the thing. Yeah, you can use it, but you have to get approval, yada, yada, yada. And so like, once you sort of get the ball rolling, you have really good documentation, you just sort of reemphasize this is where you go. This is the process. And on the flip side, I mean, I'm not in legal security IT, that sort of thing. But like, when

those groups, that group, those groups are responsive to an organization that wants to experiment and try this stuff, then that the flywheel just keeps going. And, you know, like I said, in the beginning of the year, there was a lot of, like, confusion about what I can do and whatever. And now, I wouldn't say it's all gone, but, like, it is nowhere near the top list, the top of our list of things that like we are concerned about when it comes to AI transformation. Well, I love this. You know, just to recap, you've shown us how you become a change agent, you know, sort of intercept your organization into taking this seriously as an initiative, how you use

synchronous meetings and asynchronous Slack channels to drive this as a consistent practice over time. And then you use OKRs to actually measure, does any of this matter? And you're showing that, like, if you put these simple things in place, you can actually inflect those measures, which, you know, just in the looking at the sentiment, I like that last question that you had on the sentiment survey, which is like, I think this is going to have a positive impact on our employees. And that went up. And that is a huge win for, for a company, because a lot of people are feeling fear about their careers, uncertainty, doubt. And so the fact that you can

show, you can do these very simple things and inflect that sentiment very positively in your employee population is also fabulous. So, Brian, And this was great. Thank you for showing us. Again, like, I could not write a better playbook for getting AI adoption in a team. This is what I've done. It works. Let's do this. Let's repeat this and stamp it out in our own teams. So let's get to some lightning room questions. And then I will get you back to all your fun AI projects. The first question I have is, okay, you showed us like you're incepting people and you're, you know, managing your stakeholders and all that kind of stuff. What is your favorite thing you've built with AI over the last year for work? I built a lot of really cool things. The one that I'm most proud of, but it's kind of geeky, is that I built my own MCP server for Pinto. So back in the spring, when MCP was becoming really hot, folks have been talking about MCP and like how it could be applied to Pendo. And what I clearly saw was after using tools like deep research, essentially like an agent that can basically run a bunch of web. queries over and over and over again to sort of build up sort of a research document.

I had spent, you know, I've been in tech for a while. I'm a designer now, but I've also spent time as a PM and I've done a lot of growth work. And one of the things that is common within growth is you're constantly monitoring like dashboards of conversion rates and retention and blah, blah, blah. And every once in a while a number will like dip or will dive, right? And then you're you're off and you're spending like the entire way you're trying to understand, like, what is it? Like, do we have, like, an issue? Do we have a bug? Like, is there something going on, you know, in one of our regions?

You know, like, if you're doing a year of your comparison, like, maybe a holiday fell, you know, last year and not this year. And so like that's why these, and usually it's like some common sense thing, but like if someone above you sort of sees this and they're just like, wait a minute, like fire drill, like we got to go figure it all out. And that like just eats up your whole week doing like a lot of like iterative research, right, looking at the data from different angles. And I'm like this could be like a deep research like query, but having access to like our data, right, or usage data could be like a killer. And like NCP is a technology that can leverage that. If I can give the AI tool, to run these queries and then like use its intelligence to like look at the data and be like, oh, what about looking at it by region? Let's look at it a year every year. Let's look at about a lot. And so that was sort of like the idea that I had of connecting like, okay, this is how MCP could be useful for our customers, right? Because we are also a product analytics provider. And so I had this conversation with my colleagues and they're just like, I don't know if, you know, because we have like a bespoke querying language. It's not SQL. So it takes, you know,

AI doesn't know how to write those queries, but I thought I had a way of doing it that they could sort of overcome that. And so over a couple of nights, I basically just leveraged the MCP documentation giving it to cursor. I have no idea how my, I built an MTV server.

I have no idea actually how it works. I understand like, right? It's like, I'm laughing. I'm laughing. Everybody closed areas. I legitimately approached MCP servers as true sorcery. Sorsery.

Before I built one, I was so, I don't, there's, there's some branding issue that, that the MCP platform and framework has because it seems like sorcery. So I was with you until I actually built one and like, you know, wrote the code. And then I was like, oh, okay. Yeah. Get it a little bit. There's a lot of elements that make it like really hard to grow, like model context protocol. Like what the hell do those words? Yeah.

Like it doesn't actually speak to what. Like even the naming. It's just, okay. So MCP framework caretakers, you might as well call it magic context protocol for all we know. Yeah, yeah. One of my most popular sessions, like, so, you know, it's not just media in the sessions, the different product. They had other people will do them.

But like one of my most popular one was called WTF is MCP. And I just spent like a whole hour telling people what MCP was. And afterwards they're like, oh, I got it now. It's kind of like web search, but like more tools. And like, yeah. Kind of. But anyway, so I built this thing. And like, I have like, so, you know, my wife also so works in technology, but she's in marketing.

And I'm sitting like next to her. And you know how it is. Like you have a baby. And like, you know, your nights are a little bit slower. And so you have some slack time just kind of like hang out. And she's watching TV. And I'm sitting there on the laptop, like working on this MCP server. And I got it to do a thing.

Right. I got it to like, you know, I wrote a query, a prompt within Claude. And it talked to my MCP server and I ran a thing and it returned data back. I was just like, you have no idea how credible this is. And she's like, I don't know what an MCU is. Like, what is an MCP? I'm like, it's not NCP. Goddain.

So I recorded, so I recorded a demo of me using it. And this isn't the exact one, but this is something very similar, which was, so I have my own MCP server that I hooked up. And I was just using the public APIs, right? So like, I have test accounts for Pendo. I didn't have any special access. I don't have a dev platform. I was just able to, like, do this on top of.

the APIs. Actually, any customer can do this. And so I had this MTP server that can do things, like just grab really basic stuff, like how many pages, which pages are the top pages, how often they accessed, you know, what are things, you know, what does this visitor do and that visitor do? So I was like, can you create a beautiful dashboard that shows me which pages, features, and guides were the most used over the last 30 days? And I think the key thing was that I'm combining accessing the data and having it create a dashboard. So I won't kind of go to through all the things I did, made a bunch of tool calls, that's not really important. But the important thing was, at the end, I had it put the data into this artifact. I'm sitting here in

Claude. And it's not, I mean, I wouldn't ship this, but just visualizing the connection between taking Pendo data, which now, you know, only exists within Pando or you can also export it and there's other ways of getting access to it. But making it accessible on the level where someone could just type in a thing like, tell me who, what the top pages are, and then show me a dashboard really like change people's minds and with over the next like a couple months like i'm now chatting with the cto the cto is creating another versions mcp and you know he's so he's create like we're iterating creating starting to like productional productionize some of these elements i mean what i've done here like they just kind of moved on it wasn't the code that i wrote or vibe

coded was not important what was what was important was like i was able to demonstrate the value of this somewhat, you know, hard, opaque technology to folks that like didn't, made, didn't see it in the same way. And that has now actually, that has like significantly impacted our roadmap. So like we're working on a lot of agents within Pendo that are leveraging sort of the MCP, you know, behind the scenes. And there's other things that we're planning to do with MCP. And we might have gotten there anyway. But that, that definitely sort of accelerated our timeline for that. So I'm, well, congratulations. for cracking through that.

And I think what you said is exactly right, which is like the code that you wrote is not important. Like people get so wrapped around the axle on the quality of like quote unquote vibe coded stuff, not the issue. The issue is until you can internally display value, it is really hard to get anything done in a product organization. And sometimes you can internally display value by saying a customer wants this, like very easy. Sales comes. I've got like a top quarter making deal. Customer wants that.

Okay. Like we love it. But something that's a little bit more nebulous, something that has a little bit more of an intangible value. Like I think we could use this new technology or this new framework MCPs to give our customers a better experience of our product. Like it just doesn't click until you can touch it. And so the more you can use these tools to let your peers sort of like touch your ideas, I think the more as you said, you can like impact the roadmap, which is what I hear all the time from designers, engineers, product managers, like, I'm tired of the roadmap being given to me. How do I, like, impact it? And this tool, these tools are definitely a way of doing that. Yeah. And I would say just one tip around this,

which I think is really important to emphasize, is that, you know, you might sit sort of like, you know, you might be designer or PM. I think it's really important for everyone to understand how this technology works. Like, I think you've got to get a little more technical. You got to understand how LMs are working. You have to understand what, like, what an agent is. You don't have have to be able to code these things. You don't have to be an ML engineer. But if you are a creative person or someone who's sort of in the solution space and is trying to think about like what, what are the different ways that I can apply AI to this, this problem, you won't arrive at anything really interesting unless you understand the underlying technology. It's like an architect.

Like architects, yeah, they design like pretty buildings, but they also understand how plumbing works and the electronics work, right? Like, they're not like the electricians and the plumbers, right? But, like, in order to build a functional building that stands up and is functional, right? Like, you got to have power sockets. You got to have room for the pipes. Like, all that stuff is important. I think the same thing applies to PMs and designers.

And I think if you're an engineer, I think it's also useful to understand, like, the business side, the customer side, the, you know, like to really empathize with the issue, the problems that your customers have so that it, you know, know, like what we're all looking for is basically how do you sort of connect the dots between the technologies that we have available to us to solve customer problems. I couldn't hype you up more because I have been screaming from the roottops. This is the era of the hard skill. Like, you need the hard skills to take advantage of this stuff.

I didn't call it out earlier, but I saw one of your sessions was like intro to HTML and CSS. Like, that is actually going to be the unlock for your designers because if you can read CSS, a whole world has opened up to you with these vibe coding tools. And so, yes, you need to know how the stuff actually works. Okay. So, Brian, last question, this has been so great, but got to have your strategy here. When AI is not listening, when that NCP is not being vibe coded correctly by cursor, what is your go-to tactic?

How do you get it unblocked? Do you yell? You know, I don't want to say that I don't yell, but I do yell sometimes. The other thing that I do too, what I think is also really helpful is I say, okay, you're not quite getting it. Like, think about a different way of approaching this, right? Like, I'm trying to nudge it to, like, it might be it's sort of like locked into a certain sort of groove, and I'm trying to make it think a little more broadly. I mean, I don't know if that actually helps, but I found that, like, sometimes that's useful.

So, like, if I'm not yelling, it's just like, okay. you try this a million times, think about five other different ways that you can solve this problem and go for it. Yeah, I think that's probably more effective than my, no, that I do when it's not working. Well, Ryan, this has been awesome. Where can we find you and how can we be helpful? Yeah, so you can find me on LinkedIn. I try to post when I can. And yeah, I mean, if you're a product builder or, you know, you're interested in working for a company that, That is sort of embracing AI. You should check out Pendo. Awesome.

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