At Cover Software here at RBC. I'm delighted to have with me Ken Stillwell, who's the CFO and COO of Pega. I think this is what, like, our 10th fireside chat we've done over the years. Yeah. Somewhere thereabouts. At least. Each time more fun than the last. Thank you so much for being here. Absolutely. Maybe I'll just start off with, like, you know, we were just chatting right before this. I've been getting a lot of, you know, new inbounds of people saying, like, look, what is Pega? I haven't looked at this in a while, or I haven't heard of this company before, but clearly stock's doing. Maybe let's just start, like, an overview of current Pega, right? Like, what's changed in the business? What's, you know, what's exciting? You know, and especially as we think about the role that you play in this new AI world and new AI paradigm we're in, maybe let's start with that. Sure. So, you know, just the, you know, the very high-level kind of statement to start, which is Pega does, you know, Pega's in the business of helping enterprise clients do, you know, automate work and using AI and decisioning capabilities to drive, you know, automated and best-in-class outcomes. Some of that is around, you know, work like things like onboarding a client or onboarding a patient into a health plan or a loan origination. Other use cases are things around customer service and ERP. There's also some, you know, very core decisioning capabilities around driving next- best- action or next- best- outcome or next- best- offer in digital channels. What's new around Pega in the last, you know, call it 24 months is really Pega Blueprint. I mean, that's really, you know, we've, there are some notable things that we've done in terms of the sales transformation that we did two or three years ago, you know, the subscription transition that we just kind of wrapped up and the business has been normalizing around moving to cloud that has helped us really drive significant increase in Free Cash Flow. I mean, we went from a business, you know, 10 years ago that had 3% of our business on Pega Cloud, and now that's over 50%. We went from a business that generated $20 million in free cash flow three years ago, and we're approaching $500 million of Free Cash Flow. There's been big transformation in the business. What's next for us, or maybe in the middle of what we're trying to drive that's next, is leveraging Pega Blueprint to really expand our addressable market and make Pega relevant, not just in the organizations that we targeted, but this expanded ecosystem. Maybe we'll talk about Pega Blueprint in a little bit, but that's kind of where we are now. Yeah. Actually, maybe let's just dive right into Blueprint. Okay. You know, I think there's still a little bit of maybe people's learning curve for people understanding exactly what Blueprint is. Sure. Maybe can you talk about, like, what are you seeing customers utilizing Blueprint for? Any, like, live examples you can give and, you know, how this manifests itself for your customers, whether it's, like, implementation time, ROI, LTV, whatever metric you want to use? Sure. When you're doing, you know, lots of the work that we do is tied to when clients embark on a digital transformation journey. Digital transformation typically meaning moving from, for example, a mainframe application that sits in a legacy environment and trying to mature that into a more modern environment. That could involve changing the workflow. It could involve just kind of refacing the application. It could involve merging, changing business processes, et cetera. One of the big challenges that a company has, one of our clients has, is the amount of time and cost that that typically would, you know, would entail. Getting teams together to design it out using whiteboards and Visio diagrams and mapping processes and lots of collaboration of all the different stakeholders. What that would result in is a slow move of digital transformation. You had to be very targeted with which applications you picked. You had to be really thoughtful about the resources. You could only do so many at one time, quite frankly. You could maybe do one at a time. Our business and other businesses like ours and the whole move to digital transformation had a slower pace to it, which is why we're 10- plus years into this and we're still probably only 15% or 20% of the way to being digitally transformed as an industry. What we thought of when we saw GenAI, we didn't, and this is really a testament to our Founder and his innovation skills, we didn't jump to, well, GenAI should be able to automate work and reduce human interaction and take people out of different functions of the organization. It can do that. We will certainly get those benefits as well. What he really focused on was what's the biggest hurdle to faster digital transformation? The biggest hurdle was this implementation design upfront time that really just takes a tremendous amount of effort. We focused on that problem. What Blueprint is, is it's a Design Agent. Just think about in that design process, we have an actual Generative Design Agent that goes through in a very structured way, what's your use case? What Workflow are you trying? What Industry are you in? What Problem are you trying to solve? It uses all of the best practices that Pega's had, all of the history of what we've had with thousands and hundreds of thousands of applications across our client base where we've done this work. It also uses domain-specific expertise that the client can provide. They can produce their own documentation, manuals, process manuals, screenshots, videos of user stories, videos of, sorry, videos of the use of the application and also user Stories to be able to get the Design Agent as smart as possible to build the app. Then what it does is it actually builds kind of Phase I or MLP of the actual application. You can share that application with all those Stakeholders and you can go into Production. If you wanted to, you could turn that Blueprint into Production. Most of our clients want to finish it a little more, but it's taken significant amounts of time out of the front end. An example, the real-life example is if you went before, if you went pre-Blueprint, that upfront design- to- ideation to the first kind of MLP might take three, six, nine, 12 months to get through that. We've now had clients do that in an afternoon, right? It's pretty significant in terms of the change. What we're trying to do is take that Blueprint product, all the knowledge we have, this massive industry problem of trying to get things modernized and trying to run as many Blueprint-empowered sessions as we possibly can. Interesting, the unfortunate outage that we had this morning with another software company impacted everybody, right? It was really interesting because at six in the morning, I was looking at our IMs and I'm seeing the number of Blueprints going on with clients saying like, you know, hey, like, what, you know, what, and, you know, unfortunate, you know, disruptions happen in the world, but just it was a real highlight of how much activity there is, you know, even, you know, in our, with our primarily our European Team actually doing Blueprints. It is really like, that was like a little anecdotal piece of like how much is going on. We are just, our sales teams are just so really riled up around the opportunity and that's our lead-in. We do not go to a client now and say, hey, I bet you need to transform an app. Let me come in and talk to you about what one you might pick and do a Situational Assessment and do an Operational Walkthrough and maybe after a few weeks we'll figure out what to do. What we're doing is we're going in saying, let's open up Blueprint right now, let's start. And that's a completely, that's a complete shift from what we've done over the decades before. Yeah. Maybe when we think about Blueprint, I guess maybe two pieces there. Number one, how should we be thinking about monetization, understanding it's more through consumption rather than like a distinct SKU? Yes. Then the usage of Blueprint between, you know, first-party Pega for customers, your service partners, because I know you've talked about the adoption there, and then just internally by customers themselves. Yeah. So Pega, probably about five to ten years ago, probably closer to ten years ago, we made a shift where we realized that it didn't make a lot of sense to go to a client and say, I'm going to automate your customer service process. And when I do that, you're going to require 50% less people to actually support your clients and have a user-based licensing model. So well before AI, we realized like that's really not a great, you know, if you go in and we save our clients hundreds of millions of dollars and the license that they pay us is reduced. Like there doesn't seem like that's a fair sharing of the value. We went, we shifted years ago to a case-based approach. A case is a unit of activity in Pega. It's the example of like an incident or a loan origination or an event or an employee workflow or whatever that might be. We now have licensed our clients around kind of events, let's call it activity usage, as you mentioned. That's a big shift for us. Interestingly enough, that has helped us a lot with AI because AI has come in and actually really accelerated the movement away from, you know, people that have user licenses really need to not have user licenses or they're going, you know, their value connection is really disrupted. That's been, that's our licensing model. For Blueprint, our sales teams are using Blueprint in all of these Blueprint-empowered sessions. We've given clients Blueprints. We have, you know, there's hundreds of thousands of Blueprints that have been done in the last 18 months, many of which have been done by our clients, not even with Pega involved. One of our clients, and I'll touch on partners in one second, but I was at the Gartner Conference in Barcelona last week and we had one of our clients, Simon Norton, who's a CIO of one of the Vodafone regions in Europe. He talked about how Vodafone is really using Pega Blueprint as their primary enabler around digital transformation, such that Vodafone actually tagged the line, no print, no sprint without a print, meaning they do not do an engineering sprint until they have done the application design in Blueprint. That's a like, so it was a really, it's a great customer example where our clients are actually able to do this. It's not something we need to technically do. What we're now moving toward, which is this next frontier, is this concept of autonomous partner selling. What does that mean? What that means is we're going to primarily system integrators and hyperscalers. We're going to the AWSs and GCP and the Accentures and Ernst & Young, Cognizant, Capgemini, all the companies that you would think of that are at the front end of digital transformation with large organizations. We are giving them branded Blueprints that they'll then use to go through that value, that value and valuation around digital transformation or legacy transformation starting with a Blueprint. That's something that we're just starting. We're very early days. We have some early momentum around that. Cognizant, for example, Cognizant's CEO actually did an interview with Alan Trefler, our CEO, and talked about how Cognizant is actually, he actually sent a note out to all of the employees saying, we are going to start all of our transformation discussions with Blueprint. We are hoping that we get a number of the partners that will see the value from that. That is kind of how Blueprint is evolving, our licensing metric, how we are using it internally and our partners. Yep. Awesome. A major topic that's been coming up really over the past couple months is really just around, you know, maybe enterprises dragging their feet on AI more because of concerns around security, privacy, governance, et cetera. What are you hearing in terms of concerns from your customer base in terms of fully, you know, going AI first, which is clearly the dream that we all want to happen? Yep. What's, either what's the tipping point to get them over the edge or what's in your control that you can do to kind of hold their hands and get them down that AI journey, just like you've done that with digital transformation? There's what we're seeing, and I just, you know, can tell you what I'm seeing, but I'm sure every company is maybe slightly different. Many large companies are having this concept of their GenAI gateway, right? Where what they're allowing is applications need to be controlled through a mechanism that they know what AI models are being used, what information is being shared, et cetera. I think that's a pretty pragmatic approach that clients are taking because they want to know where is their information, whether that be proprietary information or customer information, where's it going to go? Some of that is controlling the model to only point to certain libraries. Some of it is the whole kind of vector database approach of how they capture information and what they share. Some of it is even around only using certain models that only hold data in certain countries, for example. There are lots of controls around that gateway. What's interesting is Pega Blueprint really has the ability to kind of circumvent some of those insecurities. You might say, what's different? What's different is Pega Blueprint is in the design phase. In the design phase, you don't have production proprietary data around the consumers. You're using test data. The ideation piece of it, there is some intellectual property, so to speak, because a client may show screens of another app or they may show process documents, but they're not as concerned about it as the regulatory leakage of consumer information, emails, phone numbers, et cetera. We do have the ability to use Pega Blueprint with a little bit less push on some of those AI controls that might exist in, say, an agent that's working in a production environment, which is where, what we're seeing is clients are getting comfortable with this, just like it took probably ten years for companies to really get comfortable with the cloud, right? It probably won't take ten years, but it's going to take a little time for companies to just understand how to risk mitigate some of the, you know, the nightmare scenarios that CIOs and CEOs fear, which is information getting out, that information being used with a competitor or the agents, the unknown of like what are the agents doing with the information. That's one of the, I think the challenges the AI vendors will have to figure out is how do they create increased security and predictability and controllability on what the agents are doing. Yeah. I think that's a great segue into the next question, which is, you know, when we think about Pega and AI, there's obviously the Blueprint and we could probably spend the entire session talking about Blueprint. Then there's the other angle, which is you're just introducing more complexity with all these AI agents that, you know, might be coming from other software vendors or internally built. Things like MCP 8A are still super, super nascent. What role do you think Pega can play in bringing together both multiple agents and adding that agent orchestration layer, as well as getting AI agents that can connect with, you know, whether it's on-premise software, cloud software, or even COBOL systems sitting on the mainframe? One of the independent of the agents, I think it's important to start with, how is Pega fundamentally different than other companies? A fundamental difference that we believe we have is that we think first from the center and go out to the client experience or the customer experience and out to the database layer of where the information is residing. Most companies start at one of the others. They start with the actual center of the data and try to build some experience layer to handle data. Or they start with the experience of the client and then just put all the logic out in the channels. You end up with disparate channels and channel, you don't have the same experience. We think about in the center, you start with what is being done, what is the workflow, what is the body of work. That allows us then to plug into any UI or any front-end experience and any back-end database and any agent that might actually be used in that process. That is a very important differentiator for us. I'm going to give you a really quick customer example. We were with a large bank, large bank meaning one that everyone here would know. They were talking about the omnichannel disconnect that they had for consumers when they make some simple change like change an address or change an email. When they do it in the mobile app, when they make a change, the app actually sends a notification to the email. When a consumer goes to the branch, they can change the email and the address and no notification goes to the prior email because the prior email is actually deleted when they change the email address. What happened is bad actors figure it out. I can go in a branch and I can actually change it and no one will know that I actually changed the address or the email. Then I can try to do other things like send, you know, change the password, et cetera. It is a big, big fraud issue. Why is that? It is because they built each app in the actual channel. They built the logic in the channel. Everything is different. When you go to a branch, it is different than when you go on the desktop, when you go to the mobile app. That is an example where it just cannot work. You have to actually have every, you got to be able to pick up a transaction in any of those channels and finish it. The only way to do that is center- out. Yeah. Yeah. That makes a lot of sense. One thing that, you know, we've thought about with Blueprint is you've clearly had a lot of success expanding just within your existing customer base. Given now that, you know, Blueprint can lower barriers to entry, lower, you know, time to get up and running, how do we think about this as maybe being an accelerant to new logo activity, right? Having that, unlocking that as a growth driver for Pega? Yeah, it's a great question. If you go back to one of the things I said earlier, which is one of the biggest hurdles to digital transformation is the amount of upfront time that needs to be spent before AI, before Blueprint, to be able to kind of get a transformation project started. Just imagine if you go into a new logo who doesn't know you, right? Who has no expertise around that selling process is very long, which then leads a company like Pega to be very thoughtful about how many new logos you can target, how many salespeople you can actually hire. Because if it's a one or a two-year selling process, it's dangerous to get yourself, you know, too stacked up in the selling. Now if we can go into a brand- new logo or better yet, I can actually talk to you and say, go to the website yourself. Any of you right now can go to the pega.com website, assuming the websites are all up today, but go to pega.com. You can do a Blueprint yourself. The only thing it requires you to do is give an email address and where we'll send you some friendly emails probably as a result of that. You can go look at a Blueprint and you can do your own Blueprint and you can save it. When you log back in, it'll show you all the historical Blueprints. Imagine how much easier that is to engage with a client than trying to get a multi-day kind of discussion with someone that does not know you so that you can take them through a journey. That opens up new logos. It also helps our partners and how our partners can actually go after new logos in a much faster way. You know, Alan, our CEO, kind of jokingly says, but he is also, this is very accurate as well, where over time Pega made prospects and clients work really hard to prove that they were worthy of being able to buy Pega, right? Because there was a big investment on their side and a big investment on our side. I think what Blueprint does is really break down those barriers. That's the biggest value proposition it has is that it changes the confidence of our sales team, breaks down the selling process, and lets you get much faster to evaluating an actual real project. That makes sense. I want to maybe take this now to the model, right? If Blueprint continues to get, you know, greater traction, more success, et cetera, how should we be thinking about the impact of this on margins? Maybe I'll bring it a little bit closer, which is if we think about the product investment you have to make on the R&D side, the additional COGS from these LLMs, just how should we be thinking about the overall impact both in the near term and long term? Our gross margins, you know, is another big transformation that I didn't mention, but you know, our gross margins were in the 30% or 40%, you know, five or six years ago, and now they're above 80%. Can we do better? Yes, we certainly can do better. I don't think Blueprint or quite frankly even GenAI will make a noticeable impact in our gross margins. I think our gross margins will continue to track up as we get more scale. It will help tremendously in the selling process. Our cost of sale, which in the pre-Blueprint model required a salesperson, a sales engineer, a specialist, a vertical expert, maybe even a horizontal expert, like that all changes significantly to have more of the shift to have actual seller resources. I think lots of those same people at Pega will just become more tip- of- the- spear sellers than they would be the kind of the supporting ecosystem. That is a very big operating leverage. In terms of our customer support, our G&A functions, and even our engineering functions, there will be, you know, we'll probably see some of that 10%-20% efficiency just through automating things like customer support and certain workflows that internally we can get some of the same efficiencies that our clients will get as well. I think the thing that we're, you know, I think the thing that we're probably a touch skeptical on is, you know, that GenAI is really at the quality that standard that we believe in terms of writing core code of your product. I think it can be code assist. I think it can help. I think that if you go and ask people, you know, those of you that have friends or family members, ask them if they've actually done GenAI developed code and ask them about the quality of that code. It's not buggy. It's just not very efficient. I do think a human being like code assist, definitely there's value there. I don't think you can just go in and go into a prompt and say, you know, write me Java code that executes the following things. I think you, we're not there yet. We might get there. I think those are some of the model things. You know, at our investor day last year, you know, we talked about, you know, we had guided $440 million of free cash flow for this year and we had set a target in three years to make that number $700 million or greater. I think you're already seeing this year, we, you know, with some of the changes to the Section 174 R&D deductibility, we think that cash flow number, we think that'll be a positive of at least $20 million or so. Our cash flow is actually kind of approaching the $500 million number. I think we're well on pace, you know, over the next few years to be above $700 million. That actually assumes that our growth rate kind of stays in the range that it's been in. Naturally, if our growth rate accelerates and we're able to do that in an efficient way, which we believe we would, then, you know, there's certainly upside from there. Yeah. Maybe let's take it now. I mean, look, you've talked about Rule of 40 since before any other public company CFO, at least in software, had been talking about it and give you tons of credit for that. So you're. Glad you remember. I had never heard of the Rule of 40 until you mentioned it like a decade ago, to be fair. Maybe walk us through. You are basically knocking on Rule of 40 territory at this point. You have done it with improving margins, but also growth rates that are better than I think we expected. You kind of hinted at there is maybe potentially room for further acceleration from here. Can you talk about number one, what have you done internally to kind of get everyone at Pega aligned with this Rule of 40 mindset? Number two, as we look out over the next several years, if everything goes right, how do we think about your ability to go beyond the Rule of 40? Sure. For those that aren't aware, I spent a number of years in and around private equity. The Rule of 40 was kind of built into my DNA for a number of years. When I came to Pega, what I saw was a business that had a very sticky customer base that was selling perpetual licenses, that was not on cloud, that clearly could generate significant free cash flow margins. The business model itself was built to be a Rule of 40 or quite frankly a Rule of 50 company. I think that was the foundation of what we had at Pega was it was possible. The biggest thing that I did and our teams did at Pega that I think is that was not, by the way, it's not rocket science, but I do think is a level of discipline, was explaining why Rule of 40 made sense for a business, how it would happen, what are the behavior changes that we needed to drive, and then went to each of the functional groups and helped them understand it, dealt with questions, validated it, went into the detail of decisions they made and how they could actually change it. That was a hard three-year process, right? Where we went from Rule of 20 to Rule of 30 to Rule of 40. We believe we're kind of approaching Rule of 45 if you take our ACV growth and our free cash flow margin. We're kind of in that like low 40s. That was, and I think now what we have is we have an entire company, by the way, it's helpful that when you execute that, that the market rewards you with a valuation change because then you have credibility to your workforce, right? They actually see that and they go, I see the connection between doing this and the value that's created. Now what we have is we have Rule of 40 embedded in our culture. Like now it's not, now it's something that like when we do not talk about it, the behavior still gravitates there. Alan calls Rule of 40 in very simple terms. I think he's very accurate. He says Rule of 40 is just simply running a good business. It really is, it is that simple. I just think that unfortunately, unfortunately companies look for excuses and rationales of why they do not need to be held accountable to a balanced business. We have just tried to change our culture at Pega to just not allow that to be accepted. Like that is not who we are going to be. Now, the challenge with that is you have to be really careful that you are thoughtful about growth opportunities, right? Because Rule of 40 can also be thought of as like, well, we are not going to spend any money. We are going to try to generate as much cash and you can miss out on growth opportunities. I do not believe that is a risk, but we always have to keep ourselves honest about that. Sometimes you do need to invest to be able to get that next growth. That's where the trick of having good business acumen across our teams to be able to make the right calls. Yeah. Yeah. That's why we have to think about long-term Rule of 40, not just like what it is, and it's pretty good. Rule of 40 is not a point in time. It's a dimension of the business that you want to live in. Love it. Love it. All right. Maybe I want to turn to the competitive landscape, right? Obviously it's evolved tremendously over time, right? It used to be Oracle and IBM and then you've always had Appian there. You had the rise of like UiPath, Automation Anywhere. Maybe there's some potentially AI natives out there. Just maybe can you walk us through how you're thinking about the current competitive environment and how that's evolved, especially during your time as CFO? Sure. I mean, this is part of this question is probably one of the most boring answers I have, which is the competitive landscape over the last 10 years has not changed that much in terms of the players. I mean, we see the same cast of characters in terms of what we see either with a horizontal solution or with a vertical in certain regions in the public sector, like depends on the industry. Like, we do see a lot of similarity. There are very powerful transformation vendors. There are not that many. There are less than 10 really. We do see a lot of the same players. That has not changed. What has changed is the difference between what I might call a, you know, a deterministic workflow like transformation versus a best- efforts kind of transformation. What I mean by that is if the nature of the work needs to be structured, deterministic, either because of regulatory control or brand, GenAI does not help a lot there. It helps on the edges. It helps in the interaction. It can make all the interactions with that workflow digital. It can streamline human. Absolutely. It can help on the design side. It can help do testing. It can help analyze data. There is lots. It is not able to repeat the structure of the workflow in the way that you need to do from a regulatory standpoint. That is the determinist. On the best efforts side, there is a lot of workflow applications that were built that that is overkill because you do not care if you get 90% accurate. You do not care if you get 95% accurate. It is essentially like a Google search, right? If you're going to ask a question, you're going to say, write me an email that I'm going to send to my customer summarizing their experience when they took their Toyota in to get service. It doesn't have to be perfect, right? No, probably not. Like, so there's things that there's communication aspects of this that probably can live pretty well in the GenAI area. I think that that will be where certain aspects of software and workflow could be disrupted in that area. The last point is the trick I think is in the middle, which is doesn't need to be a deterministic workflow, but the answer has dire consequences like healthcare, things that where you don't want to actually ignore suicide triggers that a human being might be able to pick up, but the models may take more data to realize that. There's a middle ground. There's ones where I think 100% GenAI is going to solve those issues. There's deterministic ones that really the rigor and the structure of it is the value of the workflow. And then there's the ones in the middle that I think are probably going to be like human assist, right? Because you do need to make sure that it's catastrophic failure, right? To actually allow an AI agent to drive decisions. Love it. We ended just on time. I think this is the first time we've done this in a Fireside Chat. Great time management here. Thanks again. Thank you everyone for being here. Awesome.