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

1. 0:00 – 1:38

   Introduction to Brian Greenbaum

   1. BGBrian Greenbaum0:00

      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 gonna go. All I knew was that I needed to get more folks paying attention to this AI stuff.

   2. CVClaire Vo0:32

      If you are the first to [chuckles] 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. [upbeat music] Welcome back to How I AI. I'm Claire Vo, 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 gonna show us not only how he uses AI in his own product work, but his step-by-step plan for getting your product and design teams adopting AI as well. Let's get to it.

   3. SPSpeaker1:11

      This podcast is supported by Google. Hey, everyone, Shresta 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 Flash Lite is ideal for low-latency, high-volume tasks. Start building in Google

2. 1:38 – 5:00

   Brian’s paternity leave epiphany that sparked an AI initiative

   1. SPSpeaker1:38

      AI Studio at ai.dev.

   2. CVClaire Vo1:40

      Brian, thanks for joining us on How I AI. Happy to have you.

   3. BGBrian Greenbaum1:44

      Yeah, so excited to be here.

   4. CVClaire Vo1:46

      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 s- 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 a how I get everybody else to [chuckles] use AI episode. 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 approached this in a really interesting way, so I'd love you to walk us through what you did at Pendo.

   5. BGBrian Greenbaum2:40

      Yeah, absolutely. So to take you back, um, it's the end of last year. So last July, I had, uh, my daughter, Maya, m- uh, my daughter Maya was born. Um, you can kind of see the nursery in my background with... This is sort of a shared office, [chuckles] uh, nursery. Um, and I was on paternity leave at the end of last year, and I'm, um, sort of like a tech geek. I've been following AI for a while. Like, 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. Um, 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, in my mind, about a music player where I can, um, play albums by scanning a QR code on, on sort of like a, 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.

   6. CVClaire Vo3:35

      [chuckles]

   7. BGBrian Greenbaum3:35

      And they get to choose music by just sort of flipping through, through albums. And, uh, I like having, you know, unlimited access to, to music via Spotify, but I sort of miss that sort of, like, tactile, um, experience. So I was 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? Um, 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 it could recognize the album cover, and I can print these album covers out and just be limited in, in that way. And, uh, I, 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 hours, I had a working prototype, and, like, that just blew me away. I was creating QR codes.

   8. CVClaire Vo4:15

      [chuckles]

   9. BGBrian Greenbaum4:15

      I was, uh, creating PDFs. I was, like, doing all this, like, really, really, really cool stuff. And, um, you know, like I said, my, my day job is, is a product designer, 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. Um, I'm, I'm... I consider myself pretty proficient with Figma, especially when it comes to prototyping, but I understand the limitations of using Figma for prototyping. Um, a lot of what I do at Pendo is sort of working on features that are analytics-based, and so when you're creating mock-ups and prototypes that are data-driven, it's really hard to communicate what the- you know, how these things are actually gonna 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,

3. 5:00 – 12:25

   Sending the message that launched a transformation

   1. BGBrian Greenbaum5:00

      uh, really useful. So I was like: Wow, I think I- we could really use this at Pendo. Um, so I had the... You know, even though I am on paternity [chuckles] leave-

   2. CVClaire Vo5:07

      [chuckles]

   3. BGBrian Greenbaum5:07

      ... you know, I had this idea, and I was like, I couldn't contain myself. You know, I hadn't- I wasn't gonna come back to work until the beginning of January. So in December, um, I wrote a whole bunch of folks at Pendo. I still had access to my Slack, and so I wrote, you know, uh, I, I sent a message to my manager, my manager's manager, the CPO, um, and then a few other folks that I knew were really, really interested in AI, and I was like: "Listen, I had this, like, really profound experience, and I think, you know, uh, 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, we 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. Um, there's no book you can read. Uh, and the technology's 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, um, help my, my colleagues and my company just be more successful, 'cause I, I saw a clear path to that. And just getting more pe- more of my peers, more of my colleagues, like, doing the same thing and sharing their experiences, uh, I knew would help me learn, and I think it would just sort of like, you know, uh, 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, uh, that I sent while I was on paternity leave, just to kind of give you an example, um, of what something like this looks like. Um, and I wrote this, like, pretty long message. I mean, for folks that are, um, not watching this, you know, I just, uh, kind of said, "TL;DR:" In a similar fashion to, uh, you know, there's an engineering... There was an engineering-focused, uh, sort of group, uh, that had, 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, um, a group like that, uh, but for, uh, a cross-functional, cross-functional product team with design- designers, PMs, and et cetera, with two goals. Um, 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 Pendo is also sort of servicing a lot of product organizations that are going through similar transformation, um, to help position Pendo as a thought leader in the space, 'cause I knew it was just gonna be really important. And then I went 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, uh, supports sort of initiatives like this, and so I, I, you know, that, that definitely got, uh, my, my leaders, like, really fired up. In fact, the CPO was like: "Hey, can you come to, like, all hands next Monday and talk about this, this concept?" [chuckles] And I was like: "I'm on paternity leave. I can't do that yet." [laughing]

   4. CVClaire Vo7:47

      [laughing]

   5. BGBrian Greenbaum7:47

      Um, uh, "But I will start as soon as I come back," and so that, that's sort of, that's sort of what happened. So that was the catalyst for, uh, this idea, and I gotta 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 gonna work out, uh, can also result in something really interesting. Um, so 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, and I also needed to create time in people's calendar where everyone could just, like, focus on it and play or maybe, um, uh, like, uh, hear a presentation on, on something new.

   6. CVClaire Vo8:34

      So I have to call out a couple things here that I think are really important. One, for anybody trying to, you know, give a, a, a justification, if you, if you need it, for investing extra time, resources, and energy into this AI transformation in your organization, I love that you call out actually the two things that really matter. They're very similar things to, um, how I called out the value of AI transformation at LaunchDarkly, which was, one, our team's gotta 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 t- you know, be great engineers. Generally, this is the next phase of how software engineering is gonna get done. We need to be thought leaders in this 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 this space if you lean in early into these technologies. You know, the other thing I wanna call out is, you know, I try to tell people this all the time, this is like promo-making work. [clears throat] 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 [chuckles] raise your hand, like, if you're the first designer 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, and, like, there's only gonna be 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, 'cause I think it's the right thing to do for the team, but, two, it's really great from a personal career perspective.

   7. BGBrian Greenbaum10:41

      Absolutely. And like, yeah, I wasn't, I wasn't gonna, uh, focus on that. Um-

   8. CVClaire Vo10:45

      Yeah

   9. BGBrian Greenbaum10:46

      ... but I will, but, like, what you're saying is absolutely 100% true. So, um, like, uh, i- this, this sort of, uh, initiative has opened so many doors, and we'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 the sort of the, the, the body of work that I have over the last nine months. Um, I get to work on some really cool AI projects. Um, I have folks throughout the organization that are not even in product and, and, and, and design, folks I didn't even know, reaching out to me and sort of like looking to me as a, a thought leader. And that wasn't my intent, but it's absolutely true. It's like there, there are opportunities across, um, all organizations right now, regardless of your level. I mean, I'm a senior staff-

   10. CVClaire Vo11:34

       Yeah

   11. BGBrian Greenbaum11:34

       ... um, but I'm an IC. I'm, I'm just a product designer.

   12. CVClaire Vo11:36

       Yeah.

   13. BGBrian Greenbaum11:36

       Like, but I'm having an influence way beyond my, my scope, and I think, uh, 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-

   14. CVClaire Vo11:47

       Yeah

   15. BGBrian Greenbaum11:47

       ... but I also love this stuff. Like, I was kind of [chuckles] doing it anyway.

   16. CVClaire Vo11:50

       Yeah.

   17. BGBrian Greenbaum11:50

       Um, and so absolutely, it is a, it is a career builder, builder.

   18. CVClaire Vo11:53

       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, [chuckles] like Cursor. Like, every single parent I know, this just might be my, 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, uh, if you have somebody on parental leave right now, it's very likely they're gonna come back, um, AI-pilled for sure, because that is what I have seen consistently

4. 12:25 – 17:29

   The two-pronged approach: synchronous and asynchronous learning

   1. CVClaire Vo12:25

      with, 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?

   2. BGBrian Greenbaum12:41

      Yep. Yeah. Um, so the two things, um, so I'm just kind of bringing up here, um, in case it's helpful. So this was sort of the first announcement I made within the organization. I had come back in January. Um, we- this is sort of like our private channel of the entire product organization. So within Pendo, product- the product team are PMs, designers, writers, um, and a few other folks. And so I was like: Hey, I'm starting this initiative. And, um, in my mind, I th- I, I was thinking that there's sort of a two-prong approach. There's an asynchronous and a synchronous. One thing that I, um, uh, was very familiar with, like, just in my own life, 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, uh, vibe code in 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 gonna learn it, and at some point you're gonna 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, um, and focus on, like, w- 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, uh, an example of that. So this was, this was a, this was a kickoff as well as an ex- exercise about building apps. Um, just to sort of give you a, uh, uh, insight into how I start, uh, started 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, the product that Pendo is building. And, uh, right around that time, Andrew Ng had a, a really, I thought, thoughtful blog post about how he was thinking about how, uh, PMs need to position themselves sort of in the AI, in, 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, as perhaps being, uh... or at least engineers being better positioned to sort of, like, take advantage of all of this stuff because they are technical. Um, but he's saying it's really important for PMs, and I would also put designers in that camp as well, uh, to become proficient. And so these were the sort of five things that he was- he really wanted to focus on: technical proficiency, um, just c- uh, iterating on the, the development, like using AI in a sort of iterative capacity, uh, being very proficient with data, skill in managing ambiguity, and then his ongoing learning. So, like, that was really sort of the emphasis that he wanted to drive. Um, and so again, the structure of sort of like, or at least the goal, sorry, the goals of the, the product AI was around to, uh, uplevel and modernize the skill set of our, 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, um, 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 gonna go through the slides of, like, how I talked about code building tools and the different, you know, the, the various types and some things that I had built. Um, but there was a section that was at least, I think, ten, fifteen minutes, where I was like: All right, everyone, you know, go to Bolt.new, 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 paste this." So this was just a prompt that I had created. Uh, 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, uh, this, this app could sort of take a very basic thing and, and turn it into a more sophisticated thing, and then let it rip, uh, hit 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 was, this is what would happen, but the... Some of the feedback I got was like, "Wow, like, we all typed in the same thing. We all clicked on the Enhance 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, that query. And I think in, in a third of the cases, like, Bolt just came back and said, "Nope," [chuckles] like, like, like, "Error," or whatever. And then, like, so we immediately got into sort of the whole, like: "Oh, okay, don't worry. Like, if you get an error, just know how to fix it," blah, blah, blah, and everyone sort of, like, got through it after two or three rounds. So that, 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, um, are built and how gen AI is being used. And then the other thing I had

5. 17:29 – 18:41

   Encouraging experimentation and creative exploration

   1. BGBrian Greenbaum17:29

      people do in the last, like, ten, fifteen 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 a to-do list, and the AI will do its best to, um, do as you say. So you can give it, like, the most wacky, [chuckles] 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 toggle, make it look like MySpace from 2007. And so that was sort of, like, an interesting t- 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, here, this is what UI will look like in twenty, uh, 2000, uh, uh, 200. Here's my Tumblr style, you know, to-do list." Um, 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 the, the, there's a line between sort of, like-... professional stuff and personal stuff. Um, but, like, what I really wanted people to experience is that, uh, this can be fun and just can, like, to broaden their minds about how they can apply this technology.

   2. CVClaire Vo18:32

      One thing I wanna call out as a meta benefit to this slide that you showed, and maybe we can go back to it, of, like, now go wild or, or optimize it,

6. 18:41 – 22:00

   How AI enables designers to move beyond MVP thinking

   1. CVClaire Vo18:41

      is I think as 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 and more efficient to build. But two, like, it's gonna let designers and product [chuckles] 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, uh, these iterations and categories, like visual iterations, interactive iterations, entertaining or 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 gonna, 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.

   2. BGBrian Greenbaum20:39

      Yeah, and I got a, 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, um, you know, there's people are constantly sharing things, links to articles, experiments that they've tried. I mean, that was the whole intent of it, right? Is just to sort of have a space where people can share things. And I think there's an example in here where... Ah, yeah, here it is. So Mark, you know, he's a, he's a, a product designer, and I think this was right around the time that Midjourney, um, 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-

   3. CVClaire Vo21:13

      It's so cute!

   4. BGBrian Greenbaum21:14

      Exactly, right? [laughing] And that it wasn't that hard. I mean, like, I think he-

   5. CVClaire Vo21:19

      Yeah

   6. BGBrian Greenbaum21:19

      ... you know, he iterated on a couple of prompts. Like this, this is not in the product, it's not in the product yet, but, I mean, he was able to create an asset that... Not that hard to drop in if you have the right spot for it. Um, and like, like you said, before it was, "Oh, man, like, really cool to have, like, an an- illustration or an animation, but I gotta go talk to a professional, or I gotta go spend, like, nights and weekends working on it. It's, like, not worth the effort." And now we can bring a little more life into our applications-

   7. CVClaire Vo21:43

      Yeah

   8. BGBrian Greenbaum21:43

      ... with things like this.

   9. CVClaire Vo21:43

      And, and that life, of course, turns into, like, what I just did, which is like, "Oh, my God, I love it," which is just, like, customer connection to your brand, to your product. Um, a little bit of sense of, like, this team actually really cares about the craft and is gonna continue to invest in this product experience, all that, all the great stuff. And then

7. 22:00 – 24:43

   Quick summary of the two-pronged approach

   1. CVClaire Vo22:00

      I, I just wanna call out for folks that maybe missed this in 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. Um, and you do those weekly, right? Or just about-

   2. BGBrian Greenbaum22:22

      We do them bi-weekly.

   3. CVClaire Vo22:23

      Okay.

   4. BGBrian Greenbaum22:23

      I mean, we could probably do them weekly, but we've, we've done them bi-weekly.

   5. CVClaire Vo22:27

      Yeah. I, um, I, I, I, I put in a... We had to put in a similar thing, um, we call them, like, AI power hours on Friday, and it was, like, every week we, 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. And 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 gonna talk about that in a minute, and so they, like, kind of pretend they're not using AI, or they use their, like, Gmail accou- Gmail ChatGPT account 'cause they don't wanna get in trouble, but they're gonna 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 [chuckles] 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 gonna stand out if I'm, like, extra good, uh, 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.

   6. BGBrian Greenbaum23:54

      Absolutely.

   7. CVClaire Vo23:55

      [upbeat music] 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. Lovable 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.

8. 24:43 – 33:48

   Measuring AI adoption

   1. CVClaire Vo24:44

      You implemented this back in January, back from, from, ah, leave. We're-- Ah, can you believe it? The year is, like, almost over. We're like, we're, like, there. It's unbelievable.

   2. BGBrian Greenbaum24:53

      I know. I know.

   3. CVClaire Vo24:54

      Um, and, and, you know, how did you actually measure? Did any of this matter, right? Like, did we do this, and was it fun, and, or, or did people actually adopt this, and how did you, how did you get there?

   4. BGBrian Greenbaum25:08

      Yeah. Yeah. So, um, I think there's like, there's several ways I can answer that question. The first is like, you know, I, I didn't intend to have to implement a company-wide transformation, right?

   5. CVClaire Vo25:18

      Mm-hmm.

   6. BGBrian Greenbaum25:19

      Like I want-- I need to start, uh, somewhere, or at least I wanted to really focus it 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 products, um, using AI to, um, to design, product management, engineering, that sort of thing. It wasn't intended to sort of, like, branch out to, you know, how does revenue sell better? Or how does finance do whatever finance [chuckles] does better, right? Um, the channel, so, like, it really-- it was r-r-really important for the channel to be public. We have, like, two hundred plus people on the channel now. That is way more than the product organization. So the, the thing is, like, even if you're sort of focusing on a functional area, um, there's aspects of that functional a-area that bleeds outside of the organization. Um, so just to kind of give you a perspective on, like, the sessions that we ran, right? So we started this back in January. We've been doing it every two weeks, and you can kind of see sort of like some of the, 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? Um, there are sessions here on just, like, diving into just Gemini. I mean, like, we, we have access to a, a whole bunch of Google, uh, features from Google that are AI related, and they're spread out throughout their entire ecosystem. So it's like, "Hey, what's, 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, 'cause, like, you know, the, the finance people and the revenue people could definitely take advantage of things like deep research within Gemini or the AI function within, within, uh, 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 your group. And then separately, there was an initiative, uh, an OKR in the first quarter of, of this year. Our quarters begin in February, so-

   7. CVClaire Vo27:09

      Of course they do

   8. BGBrian Greenbaum27:09

      ... I had started this-- Yeah. [chuckles] It's like it's, it's so weird that we're in, like-

   9. CVClaire Vo27:12

      That's middle enterprise, enterprise sales, uh, fiscal year right there. [laughing]

   10. BGBrian Greenbaum27:16

       [chuckles] Yeah, it, it's really confusing because, like, we're in fiscal year twenty twenty-six, [chuckles] you know, like, I thought it was till twenty twenty-five.

   11. CVClaire Vo27:23

       Q2, and it's October. What's happening? [laughing]

   12. BGBrian Greenbaum27:26

       Yeah, totally. Um, so yeah, we're like a little, like, one month off, so our quarters begin in, in, uh, in February. So I had started this, and I think because, uh, you know, to your se-- to your point earlier about, like, how this, this, uh, is also a good career move, it adds a lot of visibility, I think, to you, if you sort of 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, um, um, AI, AI leverage within the organization. And so, um, I can show you some of the things that we did, but, like, I think the most important thing, uh, 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', uh, 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 gonna solve cancer, right? Like, I don't know what the, the sentiment is. We weren't really- you know, you're not h- you, 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's 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 ChatGPT accounts to do professional work, and they're not sure. It's like, "Is that cheating? Is that allowed?" [chuckles] Um, or even, like, what kind of data am I allowed to put into ChatGPT? Can 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 'cause they know it's gonna be helpful, and some people are not doing it because they're worried that, you know, that's not, that's not cool. Um, 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... W-we didn't- at the point- at that time, we didn't have company-wide licenses for ChatGPT, right? So, like, no one knows what, what is actually available to them. Um, and so what I'm showing here is, like, 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 take this baseline, and we ask these five questions. And we also got some, uh, some qual feedback as well, so it kind of gave us a little, um, an idea of sort of like wh- why things were trending in a certain way. Um, and then one thing that we, we, we noticed, and you're kind of looking at sort of like the trend of what happened be- uh, from the beginning of the quarter to the end of the quarter. Uh, there was an increase along all of these measurements, and the biggest ones were around this, uh, 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, um, just by making people aware of what they can do and how they can request software. So here's, uh, just a screenshot of an internal s- uh, uh-... a Confluence document we call the AI Knowledge Center, and in this document, um, is 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, the thing is that, like, AI is a, is a vector [chuckles] for doing some really bad stuff, and even though you want to move fast, and you wanna use all of these really cool tools, you don't wanna 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 in, to be in an organization where, like, those folks, which sometimes can feel like friction [chuckles] and a barrier, like, they, um... I think they recognize that, like, this was also really important and sort of like prioritized, um, you know, still doing all the, the solid work, but, like, adding, uh, like, prioritize sort of like the, uh, 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, to try out. Um, and it would only take maybe like a week for me to co- sort of get the, 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, 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, I can get to that? And so when I, you know, I go back to this slide, you know, that was, that was one of the, the, the tactical things we were able to get done in a single quarter that really made a huge difference sort of in this, um, in this metric of awareness about policy and tools.

   13. CVClaire Vo32:13

       I wanna just call this out for the leaders on the team that are, or the leaders, uh, 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 gonna benefit the acceleration of your team to say, 'You will go heads down and figure out how you can get ChatGPT and Cursor, and you'll get your three little, 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 ones are gonna 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, 'cause 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, um, is just very, very, very useful. And, and if you can get this done, then it all starts to snowball from there because people have a place and a path to go down. So I, I- this is probably, like [chuckles] not the most exciting screen share we've seen. Like, it's a, it's a table and a Confluence doc, but, like, I just want everybody to pause, screenshot this. If you do not have this in your org, like, you need it, you need it today 'cause this is gonna be th- the thing that changes how you work. I love this.

   14. BGBrian Greenbaum33:47

       Yeah, 100%.

9. 33:48 – 35:58

   Creating a centralized AI knowledge center

   1. BGBrian Greenbaum33:48

      Um, and, like, uh, once you kinda get that ball rolling, like, y- y- 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 AI channel, but more like broad-based. And every once in a while, someone will 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, will just be like, "Hey, yeah, go check out the thing. You know, 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 re-emphasize, "This is where you go. This is the process." And on the o- on the flip side, I mean, I'm not in legal, security, IT, that sort of thing, but, like, when the, those groups, um, that, that group- those groups are responsive to an organization that wants to experiment and try this stuff, then that, the, the flywheel just, just keeps going. And, um, 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.

   2. CVClaire Vo34:52

      Well, I love this. You know, just to recap, you've shown us how you become a change agent, you know, sort of incept 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, um, I like that last question that you had on the sentiment survey, which is like, "I think this is gonna 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, uh, Brian, 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. I... You- it works. Let's do this, let's repeat this, and stamp it out in our, our

10. 35:58 – 44:08

    Building an MCP server to demonstrate AI’s potential

    1. CVClaire Vo35:58

       own teams. So let's get to some lightning round questions, and then we'll 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, for work?

    2. BGBrian Greenbaum36:16

       I've built a lot of really cool things. Um, the one that I'm most proud of, but it's, it's kinda geeky, is that I built my own MCP server for Pendo. [chuckles] Um-... So, uh, back, uh, maybe back in the spring whenever when MCP was becoming really hot, uh, folks have been talking about MCP and, like, how it could be applied to, to Pendo. And, um, what I clearly saw was after using tools like Deep Research, as essentially like an agent that can, you know, basically run a bunch of web queries over and over and over again to sort of build up sort of a, a research document, I had spent- You know, I've, I've, I've been in, in tech for a while. I'd, m- I, 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, you're constantly mon- monitoring, like, dashboards of conversion rates and retention, and blah, blah, blah. And every once in a while, a number will, like, dip or it will dive, right? And then you're, you're off, and you're spending, like, the entire week 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 f- you know, in one of our regions?" Uh, you know, like, if you're doing year-over-year comparison, like, maybe a holiday fell, you know, last year and not this year, and so, like, [chuckles] that's why these... And usually, it's, 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 gotta 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, like, a Deep Research-like query, but having access to, like, our data, right, uh, or usage data could be, uh, like, a killer. And, like, MCP is a technology that could leverage that." If I can give the AI tools to run these queries and then, like, use its intelligence to, like, look at the data and be like: "Well, what about looking at it by region? Let's look at it year over year. Let's look at it blah, blah." Um, and so that was sort of, like, the idea that I had of connecting, like, okay, how... This is how MCP could be useful, um, for our customers, right? Because we also a- a- we're a product analytics, um, provider. And so I had this conversation with my colleagues, and they're just like, "I don't know if..." You know, 'cause we have, like, a, a bespoke querying language. It's not SQL, so it, it takes, you know... The, the AI doesn't know how to write those queries, but, like, I, I thought I had a way of doing it that, that could sort of overcome that. And so over a couple of nights, um, I basically just leveraged the MCP documentation, giving it to Cursor. I have no idea how my- I built an MCP server. I have no idea actually how it works, but I understand, like- [laughing] Right? It's like that, that's a lot-

    3. CVClaire Vo38:47

       Hold on. I'm laughing, I'm laughing. Everybody close your ears.

    4. BGBrian Greenbaum38:50

       [chuckles]

    5. CVClaire Vo38:50

       I legitimately approached MCP servers as true sorcery, sorcery! Before I built one, I was so... I don't- uh, 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, [chuckles] okay. I get it-

    6. BGBrian Greenbaum39:15

       Yeah

    7. CVClaire Vo39:15

       ... I get it a little bit."

    8. BGBrian Greenbaum39:17

       It's-- There's, like, a lot of elements that make it, like, really hard to gras- like, model context protocol. Like, what the hell do those words mean?

    9. CVClaire Vo39:23

       Yeah, I know.

    10. BGBrian Greenbaum39:23

        Like, it doesn't actually speak to what-

    11. CVClaire Vo39:25

        Like, even the naming, [chuckles] it's just... Okay, so MCP-

    12. BGBrian Greenbaum39:28

        It's just terrible

    13. CVClaire Vo39:28

        ... framework, uh, caretakers, you might as well call it magic context pro- protocol for, for all we know. [chuckles]

    14. BGBrian Greenbaum39:36

        Yeah, yeah. One, one of my most, uh, popular sessions, like, so, uh, you know, it's not just me doing the sessions during product day. Other people will do them. But, like, one of my most popular one, 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 get it now! It's kind of like web search, but, like, more tools," and I'm like, "Yeah." [chuckles]

    15. CVClaire Vo39:56

        Kind of. [chuckles]

    16. BGBrian Greenbaum39:56

        Um, but anyway, so I, I, I built this thing, and like [chuckles] I have, like... So, you know, my wife also still 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, y- y- you know, your, your nights are a little bit slower, and so you have some Slack time, just kinda, like, hang out, and she's watching TV-

    17. CVClaire Vo40:13

        Yeah

    18. BGBrian Greenbaum40:13

        ... and I'm sitting there on the laptop, like, working on this MCP server, and I got it to do a thing, right? [chuckles] I got it to, like... You know, I wrote a query, uh, a prompt within Claude, and it talked to my MCP server, and it ran a thing, and it returned data back. And I was just like: "You have no idea how, how incredible this is." And she's like: "I don't know what an MCU is. Like, what is an MCU?" [chuckles] And I'm like: "It's not MCU, it's MCP, goddamnit!" Um, so I recorded, so I recorded a demo of me using it, and, um, this isn't the exact one, but this is something very similar, which was, um, I- so I have a- the- my own MCP p- server that I hooked up, and I was just, I was just using the public APIs, right? So, like, I have test accounts for Pendo. I didn't have any special access, and on the dev platform, I was just able to, like, do this on top of the APIs. Actually, any customer can do this. Um, and so I had this MCP server that can do things like just grab really basic stuff, like how many pages, uh, which pages are the top pages, how often are they accessed, you know, where are things... You know, what, what does this, this visitor do, and that visitor do? Um, 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 thirty days?" And I think the key thing was that I'm combining accessing the data and, uh, having it create a dashboard. Uh, so I won't kind of go through all the things that I did. I made a bunch of to- tool calls. That's not really important, but the important thing was, at the end, I had it put the data into this, uh, artifact. I'm, so I'm sitting here in Claude, and it's not... I mean, I wouldn't ship this, but just visualizing the connection between [clears throat] taking Pendo data, which now, you know, only exists within Pendo, 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, changed people's minds. And with- over the next, like, couple months, like, I'm now chatting with the CTO. The CTO is creating [chuckles] another version of this MCP. Um, and, you know, he's, so he's create- like, we're, we're iterating, creating, uh, starting to, like, productional, productionize, um, some of these, these elements. I mean, what I've done here, like, they just kind, they kind of moved on. The, the... 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-... um, to folks that, like, didn't, maybe 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, um, that are leveraging sort of MCP, but, you know, behind the scenes. And, um, there's other things that we're planning to do with MCP, and we might have gotten there anyway. Um, but that, uh, that, uh, definitely sort of accelerated our timeline for that. So I-

    19. CVClaire Vo42:53

        Well, well, congratulations-

    20. BGBrian Greenbaum42:55

        Yeah

    21. CVClaire Vo42:55

        ... uh, for, 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. [chuckles] 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 a..." "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 per 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, these tools are definitely a way, way of doing that.

11. 44:08 – 46:01

    Why technical understanding is crucial for non-technical roles

    1. BGBrian Greenbaum44:08

       Yeah, and I would say one- just one tip around this, which I think is really important to emphasize, is that, you know, y- you might sit sort of like, you know, you might be designer or PM. Um, I think it's really important for everyone to understand how this technology works. Like, I think you gotta get a little more technical. You gotta understand how LLMs are working.

    2. CVClaire Vo44:25

       Hundred percent.

    3. BGBrian Greenbaum44:25

       You have to understand what, like, what an agent is. You don't have to be able to code these things. You don't have to be an ML engineer, but, um, if you are a, a creative person or someone who's sort of in the solution space and, uh, is trying to think about, like, what... 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, they design, like, pretty buildings, but they r- also understand how plumbing works and electri-

    4. CVClaire Vo44:55

       Yeah

    5. BGBrian Greenbaum44:55

       ... and the electronics work, right? Like, they're, they're not like the electricians and the plumbers, right? But, like, in order to build a functional building that stands up and, and is functional, right, like, you gotta have power sockets, you gotta 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, the issue, the, the problems that your customers have, so that it... You 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?

    6. CVClaire Vo45:31

       Uh, I couldn't hype you up more, because I have been screaming from the rooftops, this is the era of the hard skill. Like, you need the hard skills to take advantage of this stuff. I, 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 gonna be the unlock for your designers, 'cause 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, actually works.

12. 46:01 – 47:53

    Final thoughts

    1. CVClaire Vo46:01

       Okay, so Brian, last question. This has been so great, but gotta have your, your strategy here. When AI is not listening, when that MCP is not being vibe coded correctly by Cursor, what is your go-to tactic? How do you get it unblocked?

    2. BGBrian Greenbaum46:19

       [chuckles]

    3. CVClaire Vo46:19

       Do you yell?

    4. BGBrian Greenbaum46:21

       Uh, you know, I, I, I don't wanna say that I don't yell, but I do yell sometimes.

    5. CVClaire Vo46:25

       [laughing]

    6. BGBrian Greenbaum46:25

       The, the other thing that I do, too, what I think is also really helpful, is I say, "Okay, you're not, you're not quite getting it. Like, think, think about a different way of approaching this," right?

    7. CVClaire Vo46:34

       Mm-hmm.

    8. BGBrian Greenbaum46:34

       Like, I just... I'm trying to nudge it to like, it might be, it's sort of like locked into a certain sort of, uh, uh, groove, and I'm trying to, to make it think a little more broadly. I mean, I don't know if that actually helps, but I've, I've found-

    9. CVClaire Vo46:46

       Mm-hmm

    10. BGBrian Greenbaum46:46

        ... that, like, sometimes that's useful. So, like, if I'm not yelling, it's just like, "Okay, you tried this a million times. Think about five other different ways that you can solve this problem, and, and, and go for it."

    11. CVClaire Vo46:56

        Yeah, I think that's probably more effective than my, "No!" [laughing] That I do when it's not working.

    12. BGBrian Greenbaum47:02

        Yeah.

    13. CVClaire Vo47:02

        Well, Brian, this has been awesome. Where can we find you, and how can we be helpful?

    14. BGBrian Greenbaum47:07

        Yeah, so you can find me on, on LinkedIn. Um, I try to post when I can. And, um, yeah, I mean, if you're sort of, you're a product builder or, um, you know, you're interested in working for a, a, a company that is sort of embracing AI, you should check out Pendo.

    15. CVClaire Vo47:22

        Awesome. Thanks so much. [upbeat music] Thanks so much for watching. If you enjoyed the show, please like and subscribe here on YouTube, or even better, leave us a comment with your thoughts. You can also find this podcast on Apple Podcasts, Spotify, or your favorite podcast app. Please consider leaving us a rating and review, which will help others find the show. You can see all our episodes and learn more about the show at howiaipod.com. See you next time!

Episode duration: 47:53