Please welcome to the stage Pendo CEO and co-founder Todd Olson.
Morning everyone. Good morning. How's everyone doing? It's great to see each and every one of you. This is my favorite week of the year. It's an opportunity to engage with each and every one of you, learn from you, share, and I'm so excited to be here. Well, look, normally I start out my Pandemonium opening talking about what's happened in the last year, what's transpired. I usually have a dizzying array of statistics and charts and graphs, but to be honest, I thought that would be tone-deaf walking into this year because just fundamentally it feels like the world has changed. And when I say the world, I mean our world, the world of technology, the world of software. Just since literally December, like right around Christmas, it is almost unrecognizable.
Andrej Karpathy, really famous programmer, said that programming is unrecognizable now that AI agents actually work. I don't know about you, but I've been developing software for, may date me a little bit, about 36 years. Yes, probably older than some of you in the room. And I can even say that is like fundamentally different. And look, I don't know if it was like one specific event. Could have been Opus 4.5. It could have been maybe Open Claw that some of you may have on a Mac Mini in your house.
But you can see this is a chart that's plotting GitHub commits by Claude. And you can see here it's like roughly flat in just 2025. This is like less than a year ago. And you can see this massive jump starting in October. Then you see it again in November. And then of course now you see it just like skyrocketing over the last few months. That's crazy.
And so why is that crazy for all of us? And you know you're seeing these statistics like coding agents are 10x-ing our best engineers. And the reason this is crazy is that for most of our careers, certainly from the time that when we created Pendo, software engineering has been one of the largest constraints we've had in our businesses. We never have enough. It's really, really hard to find. Recruiting's tough. I mean, heck, how much investment do we have in STEM education and trying to get people to like get excited about computer science? Like, it's been a real challenge. A real challenge. It's been a challenge honestly for all of our business. And it's been a challenge for society.
And now that challenge is all of a sudden sort of I wouldn't say disappearing, but it's definitely changing. It's being disrupted. And already some of the leading companies are taking advantage of this and showing remarkable results. Stripe is shipping 1,300 pull requests a week. Shopify has synthetic robots that are shopping for you to sort of understand your shopping experience.
Ramp is using coding agents to build whole products without a human being involved. Well, maybe not totally not involved, but like almost completely autonomously.
Now, look, every day I wake up and I go on to social media and I see a new company doing amazing things. And of course, that creates a lot of stress. Why are we not doing these things? Are we missing out on something? Oh my gosh, I can't believe they're doing this and we're not doing this. And that what does that create? Honestly, it creates this fear. I mean, it is literally feeling like we're on one of these playground spinners just holding on for our life. We don't want to spin off. That sounds really, really scary. But this is how fast the world is changing. Literally this morning, I woke up and read two or three things from various companies. And I'm like, 'Oh, yet another thing we have to pay attention to.'
And we're seeing this across our organizations, this concept of vibe coding. People that have never built a piece of software in their lives. People in our, no offense to folks in the G&A organization, but folks that are in like finance and HR are building apps. They're shipping them. They're software engineers now. And we're seeing this like crazy crazy explosion in applications like we've never seen before. It used to be hard to build these things. I remember when it was hard. It is not hard to build anymore.
Now, this has created some fear and uncertainty in our financial markets. Wall Street doesn't quite know what to do with the fact that now anything can be built. They're like, why would anyone need a software company if all of us can be software builders? Of course, that's created some stress for a lot of us. I'll say a lot of us because we're all in this, you know, a lot of us are in this together where $300 billion dollars was wiped off the face of the earth in software value basically in a week.
Because they don't know how to process all this change. What's the terminal value? What's the future state of what software looks like in the world?
But I don't know about you, but my life and my company relies on software. We build it and things like I don't know our paychecks rely on software. I don't know there's probably a show of hands in the room people who actually build software that create paychecks. I think a lot of you actually are in the room. I don't know about you, but you want your paycheck vibe coded, your tax calculation vibe coded, your benefits. You want to make sure that you actually have benefits and they're actually paid on time correctly to the right providers so that when you show up for healthcare, like everything sort of works. I mean, actually, do you want your doctor's software vibe coded so that your medical records are like by someone who just like whipped it up, you know, in Lovable last night? No. We obviously don't want that. Like that's not the future. That's not real.
I am not a buyer of everything is going to go away and we're not going to have software companies anymore because this is like this is like hard important stuff. There's a reason why these companies exist. Actually, there's a reason why some of these companies existed for decades because these are hard problems to solve. We are solving hard problems. And the interesting thing, the interesting challenge I think today is now we're in this world though where it is really really easy to build things. The question is what do you put in the prompt?
What do you build? What's the level of detail that you're putting in it? Because you can just let AI guess what you want to build or you can give it a lot of really, really good instructions. You may care about the craft of what you're putting into that prompt. So, what you get out reflects not just what you're trying to solve, but reflects something about you, what you believe in, what you like to build, how it's supposed to work. We all like things working a certain way.
It's called taste. I'll talk more about that later. But that to me, taste, originality, that's what's really important. And what are all those things about? That's about being good at product. That is product's job. Our job, arguably, many of us in the room is probably more important today than ever before. In a world where you can build anything, the question is what are you going to build and how is it going to work? That is a product job. That is what we do. That is our craft. That is our profession. And it is our time to step up.
Like the constraints we used to have do not exist to the same degree in which they did before. That means the onus is on us to figure out what to put in that prompt. Now the challenge for all of us is this means our jobs everything's sort of like changing.
I don't know about you but my job has changed. And you know, we when we build companies, when we build teams, we used to have this term, I don't know if you know this term, but I used to use this term a lot called a T-shaped resource. No one likes being called a resource. I get that, not me included. But when we try to build skills, we try to say you have to be really deep at something and you have to be like generally broad. That's typically how we do things. And then teams have specific roles. I'm in charge of design. I'm in charge of, you know, product. I'm in charge of engineering. You generally have a team of T-shaped people like really deep at one thing and generally broad and then you have specialists.
And I just don't think that's the way we're going to be building teams in the future. You know, I heard this new concept of an E-shaped person. What does that mean? Oh, congratulations. Now you have to be good and deep at two things, not just one thing.
And I think we're going to have teams of E-shaped people that aren't going to have as well-defined roles. You're not going to be on the design person or the product person. You may have specialty. You may have like certain skills that other people don't have, but we're all going to have to be kind of broader than we used to be and deeper than we used to be in every role probably.
And I heard a great interview, I think it was on Lenny's podcast with Marc Andreessen and he just laid it out very directly for all of us. Like if you're just a designer, and by the way, being a designer is a hard thing. It's a profession. You go to school for it. Or just a coder or just a product manager, you could be swapped in or out. Like this is the future.
And you may be sitting there in the room like, 'Ah, it's not going to happen to me. I'm like really really experienced or I'm later in my career.' But it probably will because this stuff is happening very very fast. And if it's not going to happen to you, like I don't know, it's going to happen to our kids for sure.
This is absolutely the future. You're going to have to be good at more than one thing. And then AI is going to make you great at all these things because that's what it does. That takes this goodness and the skills and it kind of fills in the gaps and teaches you the skills and that is that's the world we're going to be in. Now, here's the good news. The good news is when we make these changes,
we're going to get a lot of stuff done because at the end of the day, even though we've been doing software and technology for a long time, there's still a lot of problems to solve. A lot of problems to solve. Society is not perfect.
And go go stand at an airport right now. It's obviously not perfect. And that may be bureaucracy, not software. I get that. But at the end of the day, there are a lot of problems.
There's still a shockingly large amount of paper. I get insurance renewals and it's like literally like two trees were chopped down to get like, you know, to solve that problem. Like I still don't know why, but someone has not solved that problem yet. There is a lot of paper and I am hoping through this revolution that we are able to create more automation to create things more efficient and honestly just like make things easier to work with and we're going to solve a lot of problems. That is my goal. So hopefully when we get through this we're going to solve these problems.
Now I want to talk a little bit about how Pendo is going to help you make this shift. And the first area that we started with was we saw that many of you basically everyone is talking about we got to release an agent. We have to ship AI. Certainly when it came out when ChatGPT came out we started seeing this rise in you know as a proxy CEOs referring to AI and earnings calls. All of your CEOs probably said we're going to ship AI. Everyone's being challenged to do it. Everyone wants to do it. There's budget to do it.
We're kind of being told we have to do it and that's what's happening. Now the challenge is many of you are doing this but you are not taking the time to build in the governance model the metrics the measurement to make sure that whatever you're releasing actually works, delivers on user needs, performs, doesn't hallucinate. And that was the vision between our first product we were launched last year in this agentic era which is agent analytics like we're going to help you measure these things because we know that the way you build anything well is you get something out there and you measure it and you understand how users are using it and adopting it. It is a mission-critical problem. We saw you all building these things and we knew that we had to deliver a solution to help you measure them.
Now thankfully from being in market for over six months we've learned a lot about this problem and we've added a lot. We're measuring around 350 agents. Interestingly many of the folks that are using it are using it on more than one agent. The average number of agents is somewhere around a half a dozen. We're seeing two and a half million prompts per week. The team's doing a lot of work helping you understand what are the top use cases for your agents.
What are the use cases that you don't even know people are using your agents for? We call those emergent use cases. There's things that you built it for, but there's things that just people type in and they say, 'We want to know about this.' And if you aren't planning or building for that, guess what? The results vary. And you don't want variable results.
We give you things like rage prompt. We were the first to sort of pioneer this idea. Well, we weren't the first to pioneer rage certainly, but we were the first people to help put a measure behind it. And look, how many times do you use all caps or exclamation points or dare I say a profane word when you're interacting with an AI agent? I have to admit, even though I know it's a machine, sometimes I get pissed. Can you just do the damn thing I want it to do? I know it doesn't really matter to the AI, but it still makes me feel better just typing in that prompt. But that's the vision around agent analytics and we've seen amazing results and I want to actually jump right in and talk with a user of it. So, please welcome to the stage Kevin. Kevin's with a company called RF Smart and Kevin is an early adopter of agent analytics. Welcome to Pandemonium, Kevin.
So look, RF Smart is building AI agents in a space where there's really little room for error. You're dealing in shipping, transportation. This isn't like a nice to have thing. This is like your package doesn't show up on time in the right place if you screw up. So before you get into how you're using Pendo, I'd love to hear a little bit more about what you're building, why it matters, just more about RF Smart in general.
Sure. So right now there are about 350,000 trucking companies in the United States. Ballpark 90% of those are operating with 10 trucks or less. Many of those are one guy, one truck. So securing capacity, the basically the lynchpin of American logistics, it doesn't happen with an API call. Happens with a phone call or an email between your logistics coordinator and your favorite broker or your carrier directly perhaps. So, one thing we're working on building right now is an agent that does the job of this logistics coordinator. And importantly, it also does the job that this logistics coordinator should be doing, but may not be. But with logistics, if the AI gets things wrong, like Todd said, it's not AI famously miscounting the number of Rs in the word strawberry. It's a truck that doesn't show up. It's a customer escalation call. Or maybe you've just made a customer that's never going to call you again. So in this high stakes world of logistics, it's really important that we operate on the assumption that observability has to be a day one priority for us.
Awesome. Awesome. Now you are launching a new agent and that agent... talk me through how you're thinking about measuring it and how are you using agent analytics to do it. So you're trying to automate this logistics coordinator sounds pretty challenging actually. How does agent analytics play a role in that?
So I'm going to operate on the assumption that no one came to this conference on their very first day in product in which case like me everyone in this room has trust issues. So let's get that out of the way first. So the purpose of agent analytics for us at RF Smart is it's about building trust. It's trust that our agents delivering value. But interestingly enough, it's also building trust that our agents align with our values as a company. And so a key area where we're exploring really heavily, I think that lends itself to this topic of conversation is an AI agent that helps you as an onboarding catalyst. And so this is after all how your customers gain access to the value that we that you create as product teams. And so traditionally enterprise software implementations in particular, those are done between a human consultant and a human systems admin. Now I won't unpack all the details of that here. But I think when you think about an agent like that, it has to consult you. It has to tell you what the best practices are. Sometimes it has to even convince you. And so would you trust an agent that's convincing you to implement your software in a certain way if it was made by a company that couldn't observe what that agent was doing? I know I certainly couldn't. So for us, it's about using agent analytics to observe these interactions between the humans and the agents in the internal alpha phase. I can't think of anybody in our organization who's going to want to break this thing more than our consultants. We're grateful for that. We can't wait to see it. We're also going to use it to observe customers during the beta phase because they're going to bang on it as well. And even for us, as early as the internal development phase, we've used this thing to observe conversations that our own product team are having with this agent trying to break it. And so for us, we need to actually get in as many reps on this as we possibly can because it's not just about learning about the agent and about how agents work. We're actually right now like the rest of you, we're actively learning how to learn about these agents.
That's fascinating. Now, now part of that learning is you're understanding what users want to accomplish. So like walk me through a little bit about what you're seeing and what you're learning and how you're starting to take action on it.
Sure. You can see here we've got lists of conversations. So for the first time ever, users are talking to our software about our software. Hopefully they're polite like Todd alluded to earlier. Sometimes they're not. But I think it's really interesting because famously users who aren't happy don't tell you. They just walk away and suffer in silence. That's not the case anymore with AI, but when someone walks away, that's feedback, too. And so, we're trying to capture all that feedback, the same as we were in the others.
That's awesome. Now, you can go right from these conversations to go even deeper. You can even watch people interact with it. Is that part of your process and how are you thinking about this and what have you learned so far?
Yeah, so my first takeaway here, Todd, is if you aren't both inspired and terrified by AI, the reality is you're just not spending enough time with it. And that's the truth. And so, my first takeaway is just spend more time with it. Now, you're going to get beat over the head with this, I'm sure, plenty of times throughout the rest of this conference. But it works. And so, the second thing I think is important is there's this MIT study that gets thrown around a lot lately. It's about 95% of AI pilots failing to deliver positive ROIs, largely speaking about Gen AI. So, I think some people read that study and they pumped the brakes. They said, 'Hold on, this is really hard.' And so when I look at that, I said, 'Hey, someone quantified the learning curve for us. Thank you so very much.' And so when I look at that, I want to press on my team and I want to say, okay, great. So now we need to know, or now we rather know how many times we need to get up to bat to be successful. But the rate of change with all this is so fast. The AI you worked with today is not the AI you worked with 6 months ago. Not by a long shot.
And so I think right now, it's the velocity of experiments that matter. It's keeping on top of these things in time is probably going to teach you more than the success of an individual experiment by itself.
That's awesome. That's awesome. Look, thank you so much. I appreciate your story. For more information, Kevin and his colleagues are going to have a session to talk deeper around their experience with agent analytics and just in general what they're doing with AI technologies. So, thank you Kevin. Appreciate it. Let's give Kevin a hand.
So what's next for agent analytics? So we're just going deeper. Again, we've been working on this problem for around nine months. And what we've learned is people want deeper insights into what's going on. Advanced issue detection. Things like if you're using tools in your agent, which tools are delivering results, what are the top tools being used? How do you iterate on it? What's actually failing?
We're now going to go a step further as well and start recommending solutions to the agent itself based on real data. So we see this happening, make this change, adjust the prompt, fix this, we believe this is broken. You'll see actually even a little more later in our demos around this, but we want to not just be the system of intelligence, we want to be the system of action to make sure you're delivering a better agentic experience. And then lastly, we're going to be starting to iterate on like full-on experimentation.
As models change, again, as tools change, there's going to be different characteristics around performance, cost, cost matters, and if you can deliver a great experience at a much lower cost that ultimately may be much more beneficial for your business. So, all of these things we're going to be delivering. We're really excited. The team is just fired up. And again, if I haven't plugged it yet, go out to the product experience zone. You probably had to walk by it or through it to come into this room and spend time with the actual builders. The builders of this software are sitting outside ready to talk to you to not just share what it does but also get your feedback on what you wanted to do.
Now, one of the great benefits of being here at Pendo is that we get to use all this stuff. And last year, we also shipped what we call agent mode. Agent mode was our agentic experience within Pendo.
And of course, we're using agent analytics on our own agent mode. And we're looking at almost 4,000 users across 300 design partners. And we're looking around how are people using it, what's working, what's not, what are the use cases, what do people want to do.
One of the things that we saw though early on that was a really positive signal is that it has led to more people inviting people into the application. We've heard from some of you that says, 'Hey, as an admin, I was a little bit nervous about bringing more people into the subscription because Pendo's a sophisticated enterprise software application and this has sort of reduced that bar, made it easier, made it more approachable to just get in and get insights out of the application.' But we wanted to take a step further and that's what the feedback says is while agent mode is great, we need to continue deeper integration into the rest of the platform to help navigate again a very large sophisticated product. And with that, we're excited to reintroduce agent mode as Leo, the Pendo agent. And what Leo looks like is a very different experience. It's not a mode. Leo's an agent following around the application, answering questions around every page, even charts within the pages so that you can understand what does this mean? How do I apply it? What actions can I take? That's really the power of it. And to show you Leo, we're going to bring on stage Emily Miller, one of our lead customer engineers to actually do a demo. Emily, welcome to Pandemonium.
So, we're gonna get Emily's screen up. Look like great jacket, Emily. So, looking good. Very on theme this morning. Look, this is Leo and you can see already Leo has replaced your existing homepage. So, when you come into Pendo, this is where we want you to start. In the first page, we're telling you signals. And again, when you think about signals, I think about again, how do we separate signal from noise? These are things we want you to look at. You don't have to guess. You don't have to explore. These are the things that probably should be mattering to you as a business. Like things like retention. If you have a product that people come to and do not return, that is a bad thing. That's a bad thing. Just if you didn't know that free tip from Todd early in the morning, it's bad if people don't want to come back. Retention's good. So, I hear I'm being surfaced retention front and center, but I want to know like what does this even mean and how do I fix this? So, let's ask Leo. We're going to click in. We're going to ask Leo. Leo comes up. It gets some level of insights and you can see Leo has a to-do list to start answering my question. Again, think of Leo like an assistant, a Pendo analyst, a Pendo expert and Leo is executing through this data. So, what is this? What is this task list or to-do? This is what we're calling a skill. So, Leo is now preconfigured with a set of skills. I'll show you more after this that knows how to do certain things. And one of those things that Leo know how to do is to interpret retention results. So, it's going to go through and collect data and start building a report here. And you see here, I'm already generating. Now, look.
What's amazing here is if I asked a human being on Slack to give me a report for retention, it would definitely not take less than a minute. And then we are demoing this. This is a live report. And these are questions we get from a lot of you which is like and then we scroll past it really fast but what are the features that are the key areas that I need to focus on to drive retention and the good news is we're telling you right there these four features are important for retention get people to use those. We're looking at things like time to first use you can even see that we are surfacing an action we want you to take which is creating an onboarding guide so the idea here is not just we're giving you data. We're going deeper, but we're actually also auto-generating a guide.
So, it took again it takes a few seconds to do this, but Emily's going to bring up the guide right here. And this is what it created. Now, look, I can adjust the theme. I can make it look better and prettier. And then, of course, if you did not know this, you can very easily edit this guide right within the product. So, if I click edit guide, open it up here, I have inline edit. This is very, very, very easy to use. I can then save this, get this the way I want, publish it, and drive it out to my users. So, all of that was driven by Leo. Think of it as a Pendo expert, a Pendo agent, helping you navigate. Now, let's go back to the homepage if we can.
And let's walk through the other skills that we have pre-baked in. So, you can see here on skills, we have things that we when talking with you and working with you, these are things we know you want to do.
Hey, I've got a call with this customer. Can you give me insights on what's going on? Now, the power thing about these skills that they're highlighting the breadth of our platform. You don't just want to know usage for that customer. You want to know, have they asked me for a few features that we haven't built? I should probably be prepared for that question. So, it's bringing qualitative data in. We have account reviews, which you know, you're sitting in a room, you want to know, hey, is this company going to churn? Is it going to stay? Is it going to expand? Use Pendo data. It's pre-built skills out of the box, recent activity, power user. So, these are things that we know that many of you like and more are coming. If you have feedback, you have, hey, it'd be great if you could create a skill for that. Let us know. Our team is outside. There's a Leo booth. We would love to hear from you and continue iterating and evolving this amazing new addition to our platform.
But before Emily goes, I want to show one more thing because we had a lot of questions on what's the future of guidance, what's the future of directing our users. So for that demo I want to highlight Acme Travel. This is our standard demo app. So if you've bought Pendo recently, we probably demoed this to you because it's an application that all of us can relate to travel and bookings. So here we have our resource center. So if you haven't used our resource center or actually I know many of you have because in my most recent customer forum plug for our customer forum, every quarter I do a customer forum live. I got some feedback already this week that people love it. So we'll continue to do that. But I got so many questions around the resource center. So I want to show you our re-imagined capabilities for the resource center. So we have a new module called AI assistant. I click on that and without any setup like we didn't do any work to do this. It has the ability to we're going to have some zoom issues up here. It looks like it will prompt what you can do. So here it says how do I create expense report? And I can say take me there. And you can see here immediately it's going to take me right to the application. We actually have a new guide type. You can actually highlight the button and it shows me click here. Now the power of this is that this didn't require setup. This is AI understanding my application because by the way we have all that information surfacing the key use cases and then directing it automatically to the area. So this is what we see as a future of guidance and the future of the resource center. Completely autonomous guides generated for you using the intelligence of your application. Well, that thank you, Emily. I appreciate it. And let's give Emily a hand.
Let's go back to my deck. So that's Leo and that's your Pendo agent and that's a more of course way within our software application to make it easier to navigate our data. But one of the questions we get a lot is what if I want to bring that amazing rich data set to my agent of choice? Maybe you want it in ChatGPT. Maybe you want it in Claude, maybe you want it in Cursor. And that is why we built MCP.
One of the great use cases of MCP is just bringing all this amazing context right directly into your agent. And since launching MCP, we've seen incredible growth, almost 2,000% growth since January. And that is like an actual statistic. So we so many of you are just using this to like and I think the power here of course is joining Pendo data with other tools other solutions to start unlocking new use cases. This is me. I literally have created board level presentations with Pendo data all from Claude. I type it in. I provide it my template. I provide other context. It can look at other priorities for me and out spits a board slide or set of slides. And it's so crazy. For so many years,
I've been thinking about ways to like auto-create board slides, but now with MCP and Claude, it just works. It just works. It's actually the solution we always wanted. And it's all powered by our data. And again, the power of our MCP server is not just usage data. We have data on the performance of guides in there. We have data, qualitative data. We have replay data right within our MCP. Everything's there that you need to deliver a really compelling story to your leadership team and it's really really easy to use and we're seeing great results. Companies that you know we've all heard of like Ticketmaster are using 15 hours a week just using MCP and Claude and a lot of this is just like basic automation around marrying user action. But that helps them understand usage and how it correlates to sporting events, music events, helps them plan. It's pretty amazing results.
I think the interesting thing is that MCP not just is a tool that's going to make your pre-built agents like the Cursors and the Claws and the OpenAIs successful. What we really want to talk about this morning is how it can make your agents better. So if you're building an agent and Pendo's inside your application, just think about how much smarter it can be if it has all this context from how your users are using your application. That to us is like the holy grail. It's a massive opportunity. So if you're building agents, I've now shared two things that are valuable. One, we can measure how good it is and two, we can make them smarter by enriching it with information what the user is doing and about your application.
One of the companies we're excited to share and announce a new partnership with this morning is Intercom or the makers of Finn. Finn is the customer service agent. It's a very fast growing agent that automates many cases first-line customer support for a lot of people.
Finn recently announced that they're going to be expanding their customer service agent to look at the entire customer life cycle. And in that initiative, that is where we're partnering with Finn. And what's exciting is you think about the combination of Finn, which has all your essentially ticket data, customer support data. It's triaging real issues from customers. But now I have behavioral data.
Imagine Pendo recognizing as someone stuck in a conversion funnel and then Finn intercedes and handles it for you. Or imagine that we know that someone just triggered something that should drive growth and Finn can follow up and see if we can take that order or expand that contract completely autonomously. Or of course imagine protecting revenue, understanding someone's a churn risk and then stepping in to like drive retention, drive usage and adoption that's the excitement of this is these honestly all this working together to deliver a better and more autonomous experience.
So as we talked about MCP is not just about building board slides or making you smarter although you should do that I'd encourage you to do that but it's about giving your users a better experience to choosing your agents that you're building. And with that, I'm really excited to bring on my friend Luis out. I've known Luis for years. She's now the chief product officer of Planview. Planview is both a Pendo customer and a partner. And we're very very excited to we're build together. We're both focused on product. And yeah, we how long we've known each other? A long time.
Let's give Luis a hand. So welcome to Luis. So like let's start off because like folks may or may not know about Planview, but talk about what you're doing and how are you playing and helping making all these folks more superhuman.
Yeah. Awesome. So yeah, so really briefly what we do is you take your company strategy breaking it down to initiative, prioritization, funding and bring this into one kind of planning layer, but make sure it's very very connected with delivery whether you do agile or waterfall or however you deliver. But the most important thing is measuring the outcomes and most of the time it's a product is the outcome. So this is kind of where the product management and all that becomes really really important in this end-to-end ecosystem.
Yeah. Outcomes matter. I mean these are all critically and you handle like significant scale projects. I mean these are not like Lovable prototypes like these are like these are real things.
Totally. And I'd love to hear like what are you seeing in terms of when you work with customers and how product is changing? What are you seeing and how are you really adjusting your strategy to help meet that need?
Yeah, I say this all the time. I think the product management are the cool kids now, right? So, I think we've taken over from kind of the project management kind of outlook. The thing that we see customers do sometimes is change project managers to product managers. And any product manager in the room knows that they're just cringing right now or they hear that. But product has never been more important honestly as you a lot of our customers talk about the product operating model and all that means is at the end of the day is how you define your products and you're measuring the outcome by products get who leads that cycle is the product managers and I look at product management as a business role end to end that helps go drive this AI revolution that we're having if we're not on the tip of the spear and driving that then we this is just like a mecca for product management right now how to redefine on everything, think differently, and product management needs to lead the way. So, we see this, we're seeing more and more CPOs and like Fortune 500 and banks and insurance companies are now having CPOs because product is becoming so important. So, that's a lot of what we see. And look, Pendo and Planview doing that together just makes so much sense.
Yeah. Yeah. I like to think that we helped make product cool kids.
100% you did. Yeah. Absolutely. Pink has something to do with it. But no we're seeing a similar thing in terms of chief product officers a traditional business is it's a new role it's emergent but it really reflects a company caring about the product experience it really matters. Absolutely now one of the exciting initiatives you have is Anvy.
Yes is your AI agent. I remember seeing it online. I reached out to you immediately like what's going on. It looks super cool. How can we help partner with you on it? I'd love to hear yeah let's maybe walk through Anvy and see a quick video and like let's talk us through how you built it and how you designed it and how you think about blending a sort of a hybrid experience between the two.
So if you Anvy is the middle of Planview. So it's A and V I starts with an A ends in an I. We spent a lot of money with marketing to figure out that name. So now you'll never forget that. So but yeah we kind of think about it in two buckets really. An automation bucket where to make product managers lives easier or any of our users easier and that's almost table stakes at this point but where it gets really interesting and what you were talking about Todd is this intelligent layer to be able to have AI running in the background automatically do scenarios for you automatically bringing things to the surface reporting in the future is just going to look so different I mean I'm not even sure it exists right so it's just so we're a lot very much focused around Anvy being very intelligent early warning system looking at the end-to-end data. And then you know it just changes how we're all going to do our jobs.
That's awesome. And what we're seeing here is a user interacting with Anvy and then a blended experience where it's like, hey, let's just go show you with a Pendo guide. That's right. That's essentially what it's doing, right?
So we're loading customized Pendo guides into Anvy and instead of kind of getting this flat list back, it also walks you through exactly what you have to go do in the product itself. So it's no more kind of this, you know, flat chat and I have to go figure it out. It just walks you through and it's what you guys have been good at forever. So marrying these two together, we're seeing a lot of traction in our customers making a lot of progress there. So we're really excited. There's a lot more we can do in the future, I think.
Oh, I totally agree. I totally agree. I think this is the very start this type of integration and I'm so excited that you guys are pioneering it. So congrats to you guys and your team. You guys are definitely on the forefront and excited what you're doing in the world of product.
Yes, absolutely. Yeah, we're really excited about I mean again it's just never been a better time and we're going to continue that cool kid mantra for sure.
That's awesome. Well, it's great to see you.
