Mics, on?
Yes, they are.
Hey, welcome to our next session. Really happy to have Don Schuerman on. I think you were here last year as well, right, Don?
I think I was.
Yeah.
Maybe a year last year or a year ago, yeah.
Yeah, yeah, yeah. For those of you that were not here last year, maybe Don, introduce yourself a little bit and your role at, at Pega, and we can take it from there.
Yeah, so, I'm Pega's Chief Technology Officer. I've been in that role for about 10 years. I've been at Pega for over 25, come through both our engineering organization, and was a, I think what we're now calling a forward-deployed engineer at Pega for a long, long time, so sort of half in go-to-market and half in engineering, and a lot of what my role as Chief Technology Officer these days is really more like Chief Translation Officer. I spend a lot of my time and my team's time with clients, sort of helping them understand both where we're going with the technology, but in the broader landscape with everything around AI and agentic, I think there's a lot of confusion and need to kind of translate that into real value for clients, so.
You mentioned you've been at Pega for a while. As part of that, you've been part of a lot of, like, technology changes, tech shifts.
Absolutely, yeah.
Schuerman, kind of internet, cloud, etc. How do you compare this kind of Gen AI era with what you've seen before?
I think it reflects a lot of what we've seen in previous technological disruptions. I think there is, one, a lot of excitement. I think we are going to see pretty substantial change in how people use technology, and especially how enterprises think about technology. But at the same time, I also think there's a lot of confusion and a lot of noise in the marketplace. You know, I was just at AWS re:Invent last week and walking around on the expo floor. You know, hundreds of companies, all agentic something or other, but it becomes very hard to tell, like, exactly what value each one of them is doing, right?
I think enterprises, at least the clients that I talk to, are trying to figure out what does this all mean in terms of their businesses, their ability to be profitable, and their ability to better connect with their customers.
And then, does it kind of, in a way, change the competitive field? And it's kind of one. You have, like, your current set of competitors, and we can talk about it in a minute. But then the notion that I get from investors a lot is, like, "Oh, there's going to be all these new companies, and they're going to be changing everything." And it starts at the model builders, and maybe they can do everything to these fancy new startups that are coming in. How do you think about that?
Yeah, I don't, I don't really look at the model builders as competition. I think what the model builders are doing with large language models is really powerful. And I think, you know, we've been, we'll talk a little bit about how we've been aggressively integrating that into what Pega does. But I also think that there are things that large language models aren't particularly good at. They aren't particularly good at deterministic workflows. They aren't particularly good at predictable execution. They aren't particularly good at efficiently and rapidly doing the same thing over and over again a lot of times. Which inside of an enterprise is something you actually want to be able to do pretty significantly at scale.
You know, I think from a competition perspective, the thing that's been exciting for Pega is we've seen by integrating large language models into our platform, we've been able to significantly reduce the barrier to entry, significantly accelerate some of the initial sales and go-to-market conversations we have, and that's allowing us to think a little bit more broadly about our addressable market, and as we expand our addressable market, there are new competitors that are sort of popping in those edges.
I mean, one of the things, like, you guys were relatively early on the Gen AI market with the Blueprint offering.
Yeah.
Can you talk a little bit about the initial thinking, like, and it was nice to see you were early, like, you know, but, like, you know, that's.
Yeah, I mean, the initial thinking around Blueprint was really around this aha moment that we could use what was then Gen AI and has now actually become a lot of agentic AI under the covers, to solve what had always been one of the points of friction in our go-to-market and our delivery motion, which is we have this really powerful platform. It can orchestrate and automate business processes and decisions at scale, but it required some degree of expertise and familiarity to map a client-specific business need into the platform. So our sales conversations could be drawn out. We would have this sort of conceptual discussion about what the platform can do, and we'd do these discoveries and walkthroughs to understand the client business.
And what Blueprint allows us to do is take what the power of the large language model can do, take a couple descriptions of the client business, and now in Blueprint, we can use agents to take in documents and images and videos. And in a couple of minutes, I can turn around and not have a conceptual conversation with the client about what Pega's technology can do, but I can actually show the client's to-be tech to-be state running in Pega in a fully actionable and touchable prototype. And that just greatly compresses that initial point of the sales conversation. And that's been what a lot of 2025 has been for Pega: how do we use Blueprint both with us and with our partners to accelerate that sales conversation?
I mean, and if you think about the original one, or like what you thought about, like what you could do with Blueprint, and that kind of got your head in the market, actually now like the whole world talks about agentic. Does that mean Blueprint needs to evolve, or like how, you know, how?
Blueprint will continue to evolve, right? We, you know, the exciting thing, you know, for us is our engineering team releases new updates to Blueprint every week. So just two weeks ago, we added to Blueprint the ability to both discover, generate, and design business rules. So if I get to a position in a loan process where I need to make the decision of whether or not I'm giving somebody a loan, and I want to look at their credit score and their loan-to-value ratio and their debt-to-income ratio and how much they're borrowing and make a decision, we'll actually design out and structure that business rule into a decision table that a business person can review and edit and, right? That was something Blueprint didn't do two weeks ago. Now it does.
The other big thing that we've seen is injecting agentic capabilities into Blueprint. And the big opportunity that that's opening up is work around app modernization and legacy transformation. So being able to take documents about a legacy system, videos of a legacy system. I was at Amazon re:Invent last week, right? And AWS has launched a set of tooling they call AWS Transform, which basically uses AI to look at COBOL code from a mainframe or .NET code and document what that code is doing so that a business can understand what is in that application.
Yeah.
Right? What we then do is take that output of AWS Transform through our partnership with AWS, and we were actually the only ISV launch partner for AWS when they launched Transform, plug it into Blueprint, and now they go from COBOL code through Transform to understand what it does to Blueprint and a running prototype of a cloud-based application that doesn't just re-implement what was in the mainframe, but actually reimagines it for a modern world where, as you think more and more about these workflows, they're not going to be the same workflows anymore because we're going to have agents doing more of the steps. We're going to have agents coming into the workflow to initiate them. We're really helping our clients make that transformation in partnership with organizations like AWS.
Yeah, yeah, and I wanted to stay on agentic for a little bit longer, so like, you know, it does look like everyone has agents now.
Everybody. It's all, it's all agents.
Yeah.
Even if they were, like, even if they were things that were agents, weren't called agents like 12 months ago, they're now called agents.
They're now called agents. Yeah, exactly. So, so how do you think about that? You know, there's a deep, there's a lot of deterministic stuff which doesn't need an agent, and there's, like, agents, but then nobody knows what they actually do yet. Like, how do you feel about this kind of new evolving?
So, I believe, and I think Pega believes, that ultimately this has to come down to business value, right? And so to me, the metric is never how many agents did a business deploy. I don't necessarily care how many agents a business deployed. What I care about is how is the business using technology to make its processes more efficient, to make them easier for employees, to deliver better customer experiences, and when I look at the scope of a business, what a client does, there are things in that business that I inherently want to be deterministic. If I'm a bank and I'm issuing loans, there are sets of steps that not only do I want to follow, but in some cases I have to follow because I have regulatory obligations to follow them.
Or, I have best practices that I have established that are my differentiated steps of my business, and I actually want to execute those deterministic things at scale. And I do not believe that large language models or agentic actually changes that. In fact, what I've seen with Blueprint is it actually gives us the ability to deploy those deterministic processes and get agreement across business and IT on what those deterministic processes are faster than ever before. So that's great. That said, there will be portions of that process where I actually want to be able to inject something that's non-deterministic.
So if you take our loan example and you pivot from, say, a consumer loan to a commercial loan, where at some point during the process, I would historically have sent an analyst off to go look at the company profile, look at the leadership profile, look at their current debt, debt ratios, understand, like, the risk of this company as a place to do business with, that might be a great place where I can actually dispatch an agent to go do a bunch of research on my behalf. It can go run Google searches. It can go look at 10-Ks. It can go get profiles of leadership. It can go look at previous loan histories and come back and give me a risk view of this organization I'm about to enter into business with.
Yeah.
But I want to run that research as a discreet and managed step of a longer process. And just the same way, if I had an analyst doing that work, I would want to quality check it. I would want to sometimes go in and validate whether they did it right. I would want the ability for a human to approve and override the final decision. If need be. So I think you're going to have these non-deterministic places where we plug in, but they're going to need to be audited as part of a larger and deterministic process.
And how do you think about the, if I talk to other players here, even at the conference.
Yeah.
The thing that comes up a lot is, like, "I want to be that agent platform.
Yeah.
How do you see your, like, with Blueprint, is that, the ambition for you as well, or are you sitting more?
I think overall our thinking on this is going to evolve because I think eventually saying, "I want to be the agent platform," is going to be, like, saying, "I want to be the software platform.
Yeah.
And there is no one software platform inside an enterprise, right? What, what I'm building for is a world where I am assuming there are going to be lots of agents.
Yeah.
Right? Some of the agents will have been built in Pega. So we just launched in our Infinity 25 release sort of two big categories of agents. One, I would call orchestration agents. So we've just made it so any workflow you build in Pega, its metadata is instantly available to an agent so that an agent can basically initiate and then follow that workflow. So I basically get agents for free every time I work, build a workflow in Pega, and I don't need to write any prompts to make that happen. The workflow actually becomes the prompt and the guidance for the agent. So I've got that type of agent.
I've also included in Infinity 25 the ability to call our workflows via MCP or via A2A because I assume there are going to be other agents in the enterprise that probably also need to execute the same workflows, and then the same thing is true when I look from the bottom up. At an individual step of the workflow, I'm going to want to be able to call an agent. We launched a new agent capability in Infinity 25 that's a document agent that can basically take a bunch of documents and do standard document processing stuff, extract data, validate signatures, provide synthesis and summary of what's in the document. So I can call that Pega agent at a workflow step. I could just as easily, and I think I'm going to have to.
Call agents that sit outside of Pega at individual workflow steps, again, using, I'm assuming, MCP or A2A. You know, I think a lot of this stuff is moving fast, and I'm sure there's going to be other standards and other protocols that emerge, and we're going to have to support those as well.
Yeah. So then it's really more a diverse world. I mean, the question is also, like, who. I mean, it's very authoritative to say, like, "Oh, I want to be the agent platform because there's going to be some very big players.
Yes.
Like, trying to do that, so.
I mean, my experience with the enterprise, right, if you walk and talk to most enterprises, they have pockets of technology that exist in different areas. And the big question for them is, "Can I get interoperability?" And more importantly, "Can I weave all those different technology pieces together?" Some of which are old, right, and they're not going to replace everything instantly. Some of which are new and coming in, but ultimately, "Can I weave those together into business processes that actually deliver outcomes that are meaningful to the business and meaningful to the customer I'm trying to serve?
You sound like.
We want to help provide that weaving and that threading together.
It sounded, you sounded a lot more grounded than the AI presentations, right? I see across, so that's kind of, yeah, it's nice to see.
That's good to be grounded.
You mentioned a little bit earlier application modernization.
Yeah.
you know, and you mentioned AWS kind of Transform kind of came up with something there. How do you see that opportunity? Because, like, there's so much COBOL code that's still out there. Like, we're still, Barclays, we're still using t he alphabet. And for years and years and years, we tried, you know. App modernization was always something.
Yeah.
You could never automate it because it's just too painful.
Yeah.
How realistic is it now that the world is really changing?
I think large language models and agents have changed two things about the app modernization conversation. First is they've created a lot more urgency, right? All of this excitement about agents and using LLMs, like, enterprises aren't going to fully realize it if their data, their business logic, their knowledge, their content is locked up in a mainframe application that two 70-year-old programmers are the only people who understand, right? So that's like, there's an urgency to start moving some of this stuff off if they actually want to play in this brave new exciting world. But the second thing it's done is it turns out that agents are really, really good at accelerating a lot of that hard work that used to be manual of moving the application forward. So AWS Transform is an example of one of those agents.
It's an agent that can look at COBOL code or .NET code, and whereas two or three years ago, you would have had to send an engineer into that code to document and tell me what it does, AWS Transform will document it for you. Great. Now I've accelerated that process. Where Blueprint comes in and where I think there's a real power opportunity, and I think this is why, you know, we were lucky enough to be one of the launch partners for AWS. It's why if you were walking around at re:Invent and went into the AWS Transform booth, they were actually demoing Blueprint in that booth, is because I don't just want to lift and shift this legacy application, right? This mainframe application, yes, I want to get the code off the mainframe so I can maintain it and free my data.
But the workflows that I built into that mainframe application were the workflows that my business was running 20 years ago, 25, 30 years ago.
Longer.
Longer, right?
If it's COBOL.
They're certainly not the workflows that I want to be running today. They certainly don't anticipate the fact that my customers might be coming into those workflows through all these new front-end digital channels. They certainly don't anticipate that more and more of that work at individual steps is going to be done by agents and powered by AI. So there's a real need to not just sort of re-platform these apps, but actually reimagine them and rethink them. And that's what Blueprint is great at because it can actually take the input that we get from AWS Transform. It can take videos of the application. It can take documents. It can take screenshots. But it can also take in best practices that us and our GSI partners, the Capgeminis and the Accentures of the world.
Yeah.
Have built around, "Well, what does a best-case lending application or claims application look like today?" And synthesize that and actually create pretty quickly a, "Here's what that application could look like and should look like in the future." And I think that, that ability to not just move, but reimagine, all of a sudden this becomes not just an IT conversation, but this becomes a business transformation conversation. And that's really exciting both for the client because it unlocks more value. It's also really exciting for our partners because it unlocks more consulting opportunities for them.
Yeah, yeah. And then, I mean, there's a more fundamental question that comes out of that one, and that's, here we talk about, like, app modernization, and everyone thinks about COBOL from the 1980s, but it also shows that applications can be modernized more quicker and that they don't need to be 40 years old. Could be, like, you know, like a five-year-old one.
So.
Like, what does it mean to, like, the stickiness of applications then?
So I think, I mean, I think especially for some of the stuff that has been built on technology where I don't have the flexibility to change it. Right? That opportunity to move it onto a platform where I do get that flexibility to change, and I do get that pre-built integration with agents, and I get that pre-built ability that Pega has to run across any digital front end you want becomes really enticing and possible. At re:Invent last week, one of the things that AWS launched was this concept of what they call composable offerings on the marketplace. So AWS, for those of you who aren't familiar, is trying to drive more and more business through their cloud marketplace. One of the ways they're doing that is composable offerings.
So rather than just be a single vendor selling on the marketplace, it would allow multiple vendors and maybe a GSI to come together and put together a joint offering, sort of composable, that a client can buy on the marketplace. And we were a launch partner with this for AWS, and we put two offerings on the marketplace. One was with Accenture around mainframe modernization and tied to AWS Transform. The other was with Capgemini, also tied to AWS Transform and Blueprint, but focused on Lotus Notes.
Okay.
So, focused on, like, there's this, you know. But believe it or not, there is, like, a universe of Lotus Notes applications. We've been working with Capgemini at a very large credit union client here in the US who's got a couple of hundred Lotus Notes applications that are still running mission-critical elements of their business that they're moving off of, and they're using Capgemini's tools and Blueprint to go do that.
Yeah, yeah. And then, more generally on Blueprint, it does feel like it's helping kind of Pega system to re-engage more. I mean, it's a new shiny toy.
Yeah.
But it's a really good tool to re-engage because it does add value to the client, and it's a unique offering in the market. Like, what do you see in terms of client conversations?
Yeah. So I think there's two things, right? I think a lot of what we saw this year was around changing the go-to-market conversation, and you know, admittedly, like, one of the things that dings against Pega was we were a pretty technical, complicated conversation to have, right? We would come in and we would talk to you about Center-out architectures and layer cakes and all this kind of.
Yeah.
Very crazy important. Like, trust me, I'm an architect. I get the value of this, but it's a lot for a client to digest at a first meeting. We don't do that anymore. I come in and I show the client a Blueprint, and I say, "Let's talk about your business," right? And I have a meaningful conversation about their business and how Pega could add value to it. And that totally transforms the selling experience. We've seen impacts of that. You know, we talked about, I think in our earnings call about, you know, we had a deal that showed up in Q3 that, like, we literally, from the first conversation with this client to close, happened all in the quarter. That never would have been possible without Blueprint for us. So that's meaningful.
But the other thing, and I think this is going to be a big focus of Pega in 2026, is now pushing that into continuously accelerating the delivery cycle. I think Blueprint has already compressed the design phase of the delivery cycle from weeks to a couple of days. But I was on stage with some clients from Toyota Motor Corp, in Dallas on Tuesday, and they were talking about how impactful Blueprint has been in their delivery cycles because they're from the IT side. And now when they sit down with the business to talk about a new project, they don't do this theoretical discussion of requirements documents and mocking up designs and all of this.
They go into Blueprint, they get the business to agree with what the business wants, they show them the prototype that comes automatically out the back of Blueprint, the business signs off on that prototype, and everybody knows exactly what's going to be delivered at the end of the life cycle. Right? And as they were saying, that's a totally different conversation than they've historically been used to having with the business. And it allows them to deliver faster, but it also allows them to deliver more accurately what the business really wants and needs.
Yeah. Did you, I mean, are you getting called into more conversations? Because, like, that's the one thing I've noticed, like, you guys were, you know, a very technical, capable.
Yes.
But very product-led organization.
Yes.
Blueprint kind of seems to be changing that.
It is, and I think it's changing the way sort of we think about go-to-market. It's, you know, definitely, we've been on a journey, and I think we need to be continually on a journey of sort of changing how our sellers behave. It's also, for example, allowed us to put Pega tools directly in the hands of sellers that are our partners. So this past June, we launched this idea of what we call a branded Blueprint. So if I'm with Capgemini or I'm with Cognizant or I'm with EY, we now, if you log in from Cognizant to Blueprint, it doesn't say Blueprint. It says Cognizant Reinvention Engine. So, and so Cognizant employees can now go to their clients and use Blueprint as a way to sell Cognizant's capabilities.
Not only is it branding, we've actually opened up the underlying RAG infrastructure, the vector database structure of Blueprint, so that Cognizant can inject their own best practices, documents they might have about how to optimize the supply chain process. So now they're not having a conversation with their clients that's like, "Hey, let us show you a PowerPoint." They're going into their clients and saying, "Hey, let's talk about how we transform your supply chain, and let me show you what we could do for you." Right? So I think it's opening up and changing the very nature of the sales conversation, which is both accelerating business for us, but also starting to open up some new channels, which is exciting.
The other question I had on that one is like, you obviously have, like, the Pega Cloud and then the client cloud.
Yes.
and I'm not asking, you know, like, numbers, but how do you have to think about, like, Blueprint's ability kind of on client cloud and, and would, in theory, Blueprint then also be a driver to get more clients to go to Pega Cloud because it's kind of more native there?
So the great thing is Blueprint itself is SaaS. So Blueprint is. You go to, by the way, we keep talking about it. If you guys want to experience this yourself, you just go to pega.com/blueprint, and I'd highly recommend just spending five minutes with it. It'll help you get a sense of what Pega does, how we're using AI, and I think just a broader sense of what's possible with some of this.
Yeah.
This AI stuff, but once you're done with your Blueprint and you export the Blueprint, you can load it into any Pega environment anywhere, so you can do that on Pega Cloud, right, and certainly we are seeing more and more momentum of clients wanting to be on Pega Cloud for lots of reasons, but you can also do that with client cloud, right, and so you know, we have some clients, large financial organizations, governments, who still for certain applications want to run it in their own private environment. We're going to continue to support that, and Blueprint works really well with that stuff too.
Yeah, yeah, yeah. And then, the other thing is like, so that Pega Cloud or, like, client cloud to Pega Cloud, not really impacted by Blueprint. The other thing I want to shift gear then a little bit is, you guys also have been selling solutions.
Yes.
So they're, you know, especially on the customer services side.
Yep.
There has been a lot there. How, how's AI impacting that part of the business? Because there seems to be a lot, especially customer service, there seems to be a lot going on there with AI kind of impacting, how the future looks there.
So I think there are two ways in which I'm seeing the impact. One is Blueprint directly into there, right? So for us, customer service, and this has been how we've long thought about it, is really just a collection of workflows that you need to run on behalf of the customer. If I'm a bank and I run a customer service operation, most of the customer service requests I get involve me ultimately running a workflow. "Hey, I need you to investigate a charge I disagree with on my credit card. Hey, I need you to transfer some money. Hey, I need you to update the address. Hey, I need you to send me a new copy of my statement," right? Like, those are all workflows. That then need to get run.
So we've always looked at customer service as a collection of workflows that we can run. And Blueprint can actually author customer service workflows. In fact, most of our customer service deployments now start with building a Blueprint of your workflows you want to deploy. The thing that I think is shifting from the servicing side, and frankly, I think it's an acceleration of a trend that has been underway in the service space for a long time, which is this idea of continuous deflection out of the contact center, right? So all of our clients are pushing more and more to move their service interaction points into self-service channels so that they can respond faster to customer requests. Frankly, they also would much rather have those customer requests self-served than have to hit somebody who's sitting in a contact center who's a paid employee.
There's a cost reduction need there. Blueprint is allowing us to more rapidly put workflows that are ready for self-service into place. But we've also used the agentic capability to now be able to wrap all those workflows with a self-service agent, right? So I can now have a self-service agent that's sitting on my website that's chatting to my customer in any language that the customer wants. But when the customer says, "Hey, I've got a problem with a charge on my bill," that agent will instantly go, "Great. I know how to manage a credit card dispute.
Let me step you through the process and capture all the information that you want." So it's opening up the potential for more and more of our clients to push more and more of the stuff, even some of the hard stuff that's kind of complicated workflowy stuff, into self-service channels, which is a real kind of business driver for them.
Yeah, yeah. What, and how good is the, like, sorry, that's not a Pega question, but like, it's more generic.
Yeah.
Question for the industry. Like, how good is that, that kind of call resolution, call deflection kind of rate that you're achieving at the moment, and how has that evolved?
I actually think it's a little bit of a Pega question because, to me, it's about what percentage of the workflows and service requests that you do can you make available on a self-service channel.
Yeah.
Historically, one of the limiting factors of that has been a lot of times these workflows would get built into a specific channel. I'd build the workflow for my contact center users. Great. That doesn't help me now. If I want to put it in self-service, I have to completely rebuild that workflow. I go build a workflow inside a mobile app. That's great. Now I've got a workflow in a mobile app, but now I've got an agent that I want to self-service that workflow, and I have to rebuild it another time, right?
What we've always done with Pega and our architecture, and ultimately I knew I would get to an architecture thing, but we have this concept of being center-out, which means I should be able to build the workflow once, I should be able to build the business logic once, and then I should be able to run it wherever the client needs me to run it. So if I need to initiate that workflow from a self-service channel, great. If I need to initiate it inside of a contact center for a customer service agent to use, great. If I now want to connect that workflow up to a smart AI agent that's running on the website, whether it's one of our agents or, you know, another agent, like an AWS Connect agent, right, which is one that we plug into, great.
The power is the customer only needs to build that workflow once, and they can put it wherever they need, and that allows them to take far more of their customer service workload and shift it into these self-service channels.
Yeah. Okay. Makes a lot of sense. Oh, last question. We only have 30 seconds left.
Yeah.
Maybe it's just an outside view, but like, it does feel like Pega's, like, the level of momentum and enthusiasm within the organization has increased with Blueprint quite a bit the last year. Is that just you doing better marketing or like, how does it feel inside?
I think it's just because we're having a lot of fun. Like, we're as a company, we're moving faster. Our engineers are building more stuff and getting stuff, like, we're making Blueprint changes every week. We're seeing clients use this stuff every day. We're impacting more value for our client as, you know, and as a company that's still very engineering in our culture, and I think also ultimately only measures our success when our clients are successful, being able to accelerate that feedback loop and the response we get from the client feels great for everybody. So I think it's just, you're picking up a lot of the energy that I feel every time I walk into the office.
Yeah. Okay. Great. That's a great summary, and Dom. Good to have you here. Thank you, huh?
Absolutely.
Really helpful. Thank you.