All right. Look, we're just delighted to have Pegasystems joining us. Ken Stillwell, to my left, is the CFO and COO. What we'll do is we're gonna talk a little bit about Ken's background first. Pega really. They didn't get rewarded appropriately, but man, you guys had a great quarter, right?
Yeah.
Yeah. Very frustrating. We'll talk a little bit about the what's going on in the business, then we'll open up to Q&A. Where do you live?
We are located outside of Boston.
Yeah, yeah. You live in Boston.
I live outside of Boston.
Yeah, yeah. Yeah.
I live, you know, a three wood from the office.
You have kids? What do you got?
Three boys.
Three boys. What's their ages?
22, 20, 16. two in college, it's.
Where are the two in college?
my oldest son goes to Babson.
Yeah.
And, uh-
I think we have a right there. Nick on my team went to Babson.
Oh, nice.
Yeah.
He is actually on the cover of Inside Lacrosse today, if you're curious. He happened to get lucky and get on there.
Come on. Look it up, Nick.
Yeah. My middle son's at TCU.
Last name Stillwell on the cover-
Yes
of Inside Lacrosse today.
Well, it's, you, He, you'll see is 29. It'll be hard to miss him.
Okay.
My middle son's at TCU.
Mm-hmm
... in Fort Worth.
Yeah.
My youngest is a sophomore in high school.
Yeah
Fun times in the Stillwell house.
My high school daughter got into TCU, so that's on the possibilities list.
Yeah.
Really fun, right? It's a great school.
Well, he loves it.
Yeah.
It's a really great experience. Lot of smiling students.
Yeah. All right. Cool. How long have you been at Pega?
It will be 10 years.
Is it really?
... in a few months.
Wow.
June something or other.
Yeah.
It's 10.
What were you doing before that?
... 10 years. 10 years in. I was
2015. Yeah. What were you doing?
I was a CFO at Dynatrace. I was part of the Thoma Bravo team that took Compuware private years ago and then split it up between Dynatrace and Compuware, and I was the CFO at Dynatrace.
I didn't realize that's where Dynatrace came from.
Yeah. Well, Compuware bought Dynatrace.
Oh, okay.
Made it Compuware APM. When they carved it out, they split the business up 'cause they had a cash cow slow grower.
A rocket.
... a cash neutral-
Yeah
... faster grower. I had a dual role there. I was the CFO of Dynatrace, and I was on the board for the debt syndicate for both... 'cause the entities were still connected, so.
Yeah. Were you at Thoma Bravo before? No.
No, I was at.
Okay
... I was with Vista before that.
You were at Vista before that?
Mm-hmm. Yeah.
What years were you at Vista?
2011 and 2012-ish.
Wow. What did they have under management back then?
Huh.
Not a lot, right?
Less than $10 billion, I think.
Yeah
... when I first started there.
Yeah, yeah.
It was crazy.
Yeah. okay. How's business?
It's interesting. You know, the actual, the business aspect of business is actually quite solid and stable.
Yeah.
the noise around all the business is quite irrational.
Yeah.
You know, our clients are forging ahead with trying to become modern, and that means a lot of things. That could mean moving to the cloud, that could mean getting off of old systems, that could mean trying to figure out how AI fits into their strategy, different client experience. I mean, there's a lot of pieces to that. I think in today's world, I think that if a company is not trying to fix the technical debt that they have in their organization, they're definitely in the overwhelming minority, right? I mean, everybody's trying to address-
Well-
... address different parts of that.
... we had actually, in this room, we had the CEO of Citizens and the CIO, there and there, and we were talking about, you know, Citizens has a Reimagine the Bank initiative. That's a
Yeah
... it's a big initiative, right? It crosses a ton of use cases. A year ago, we were still sort of in experimentation mode, and we are not in experimentation mode at all anymore.
Yeah.
One of the things the CIO talked about, he said, "You know, lucky for us, we had these six pillars that we had spent the last five or six years addressing.
Yeah.
A lot of it's around data.
Yeah.
You know?
Yeah.
It was getting to the cloud and getting your data estate in good order.
Yeah
... and then four other things, and that puts you in a reasonably good position to try to implement AI in all these different use cases. If you haven't done it's really hard, right?
Yeah. You know, I met with Michael earlier today, he and his.
Oh, our Michael?
Yeah.
Okay. Great.
You're Michael. You're CIO.
Okay. Great. Yeah. Perfect. Yeah.
Yeah. Michael Ruttledge.
Yeah, yeah. Yeah
... Citizens CIO. He and his team were at Pega in November, and we actually went through the Reimagine the Bank...
Oh, you did? Oh, great.
how our role is in that. You know, there's a lot of really challenging. You know, when you have these. You know, one of the biggest challenges that organizations like Citizens has is you end up building solutions for the channel. Not building solutions for the customer. You know, one of the examples that is common in the banking industry is, you know, the level of risk and fraud management of somebody that goes through a digital channel versus walks into a branch is not the same.
Mm
cause the systems that they're using are different. Just trying to synchronize that so that if someone actually, you know, if someone goes through a digital channel or calls into a call center, there's a certain set of controls that happen because of they're using the underlying technology. If you go into a branch, that might be 20-year-old technology that they're using in a branch, and this is a very common challenge.
How you authenticate people.
How do you basically create a seamless experience, manage risk across all of those?
Oh.
In the branch, you're historically, culturally, you're more dependent on the branch person making a decision, versus in the digital channel, you kind of assume that you can't validate through a driver's license or seeing the person. I mean, it could be a bot. In the branch, as an example, the culture was-
You walk in, you show your driver's license, you figure you should be good.
Right.
Right.
The reality is that's just not true.
Yeah.
Right? I mean, it's very easy.
You should see the collection of fake IDs in my daughter's bedroom, so yeah. It really, really, yeah.
And the-
They look great, yeah.
... and the bad guys...
Yeah
... figure this out, and they understand where the crack is.
Oh
... the secure, and they go after that.
Mm.
I think that's a really big challenge for financial institutions, and that same challenge exists even when there's not a brick-and-mortar and digital difference because people come in through resellers.
Yeah
... through partners, through the actual brand. It's a really interesting challenge that when you talk about it's, like, pretty obvious, but it's also one of those ones that is built because many of these apps were built point by point.
Mm-hmm.
There really wasn't a thought about how to keep that experience seamless across.
Yeah
... the customer journeys.
Let's go back to the. Your comment was really interesting. You said that, the business is solid, stable, but the noise. I didn't actually get everything that you said, but the.
Yeah
Let's talk about the noise. What do you mean by the noise?
Well, I, you know.
Not just the noise that's impacting the valuation of stocks, right? You're talking about the-
Yeah. I, well, I think that some of it's... They're related.
They probably are related.
They are related.
Yeah.
I would say the noise around decisions that. Let me take a step back.
Okay.
There is noise with our customers around decisions that they are trying to make around how to modernize faster.
Mm.
Should we move to the cloud? If so, where? How should we manage that? What risk tools should we use? What's the right way to think about our customer? How do we embed AI in the appropriate areas in the technology stack? Those are all things that are, you know, are. I would say the pace of change is higher now, which causes some of that. There's the noise in the investment community.
Yeah
...which is directly correlated to some of the valuation. What's really interesting is when you talk to a client, when you talk to CIOs of large organizations, and then you hear some of the things which are, interestingly enough, are... You know, now there's, you know, everybody on X or any social media channel is an expert in every industry because they could just put a blog post out there. It's a really interesting dynamic to see the disconnect between the reality of what executives are doing and what people are talking about. Then as an investor, if you're an investor...
By the way, many investors now, Pat, I don't know what your view is of this, but my perspective is 10, 20 years ago, when I would talk to investors, the investors understood the industry that they covered in a way that they don't now. There's a lot more generalist kind of investors, people that may not understand how a company buys software. How do they deploy it? What's sticky versus not?
We're much more as an industry, more quantitative and modeling discipline, but there's a lot. When you get into these situations of, like, "Well, can you explain to me which software is gonna be disrupted and what isn't?" You kind of have to fundamentally understand the vertical, understand the business case, and that is not as common now as what I feel like it was, you know, a decade or so ago. That then causes more noise and confusion because you see a press release, you read something, you know, you hear something that comes out from another company and you immediately think, "Oh my gosh, what's gonna happen?
Mm.
Because there isn't a deep domain expertise on the operating model of those companies, it freaks people out, right? They think that, "Well, wait, if I can write code, then maybe I should just rewrite everything." When you actually then think about, like in a bank, like Citizens, you know, I would wager a guess, and the reason why I use this percentage-.
as a bank in general.
A bank in general.
Maybe we won't focus on.
We'll generalize.
Yeah, yeah.
I would imagine that any large financial institution like yourselves, that 80% or so of the technology that you use couldn't be dramatically changed because of regulatory oversight.
Mm.
Right? Unless you think that all the laws are gonna somehow change around fair lending and credit cards and...
You really think it's that high? You think it's 80%?
Well, the reason why I get that % is I actually heard it from one of your competitor CIOs.
Oh, interesting.
... who actually said, "80% of my technology I could never touch." His words were, "In my lifetime or my children's lifetime.
Come on, really?
I don't know if that number's right, but I can tell you that talking to a lot of that person's peers, it's a very high percentage. I think most investors think it's inverted. I think they think that it's 80% is fair game to change, and there's very small numbers of that, of technology that. This is where the question about AI comes in.
Mm-hmm.
Because AI is a very powerful tool, we've gotta figure out how to harness it, how to get as much value out of it as we can. Even with that 80%, let's just assume that number's right, the 80% of applications that aren't gonna move, there's tremendous value leveraging AI around that, right? You're augmenting that workflow, that process where you can get human beings further out of that. Because right now a lot of those, a lot of those workflows rely, or excuse me, rely heavily on human beings, whether that be the customer doing lots of work that they shouldn't have to, or a person at the bank making judgment calls on, or a Know Your Customer use case where they've gotta go out and do manual searches and the.
Those are all things that can be automated.
Yeah.
Right? That's really where the power is.
Just an anecdote. You know, for all of these fireside chats, I have my little keynote outline, right? Then I have, you know, the most recent note. I was like, "I'm just gonna have Copilot do one of these for me." Such a disaster. Oh my God. The one that I didn't look at closely enough, like it's like, "This executive spent 20 years at Amazon Web Services and..." No, he didn't. Right? The amount of time it takes to check the keynote, you know, outline-
It's interesting.
... that Microsoft Copilot is gonna write, I can just bang it out. Now, flip side to that is I didn't want to come to this conference, it's like the fourth time I've said this. Have you used Cowork yet? Have you used Claude Cowork?
Mm-hmm.
You have? Okay.
Yes.
I hadn't used it, right? I was like, "This is terrible," right? Like, how. Part of the reason I hadn't used it is because of course we are a regulated, organization and we all have completely locked down laptops.
Oh.
There's no way.
Yeah
... that you are gonna get to run, you know, Claude Cowork on this, for good reason, right?
No.
I, you know, I had to get to a Mac and I... What it did with my calendar was insane, right? Like one of the very first How do you use it? What do you use it for?
I've been actually trying to build simple apps.
Yeah
... and understand like with not being a coder-
Yeah
... like what level of expertise, and just trying to understand like where some of the-
With Claude Code?
With Claude Code.
What did you build?
I've tried to build things like a travel management app or something. Like, just, you know, trying to say, you know, go try to find the Delta Air Lines schedules.
Yeah
... and create, and merge. Just trying to build something simple like that. To be honest with you it's actually pretty cool...
Yeah
... to see what it can do, and it can be done without someone that necessarily understands how to code. Now, this is where the trick comes in though.
This is where the trick comes in.
When you're actually going to write more complex applications. I don't even mean, I'm not talking about ERP systems. I just mean something simpler than go grab all the travel schedules from the public websites and put it into one view.
Yeah.
Something where you now have a real big dependency on the product management aspect of a human being because the AI models cannot be your product manager.
Yeah.
You have to have a human being on the front, and you have to have a human being on the back. These systems write code so fast that a human being cannot process even reviewing it.
Yeah
... So now you're left to a model to check the work of another model that a human can't tell what actually was actually written.
Yeah
... until you see it in the wild, and then you hope it works.
Yeah.
This is where it gets dangerous.
Yeah.
You really have to think about ways to. Because you can't. You're not gonna ask a model, "Please go figure out what business we should be in, put a business plan together, and then go write all the." You're gonna have.
Yeah
... someone that wants to drive the strategy. I think there's a lot of work in the middle that can be done, but you gotta figure out how, you know, how do you leverage it in a way that makes sense.
I know. One CEO told me that He says, "Look, historically, I had a bunch of, you know, young developers and they had one gray-haired guy who reviewed, you know, their code. Now I need everyone to be a product manager.
That's... That, that, that is-
He goes, "I basically, now I need everyone on my team to be a product manager. They all have to think like a product manager.
Someone is writing the code. It's.
Yeah
... it's a machine that's writing the code, but you need the human being to actually watch and give instructions to what needs to be built.
Yeah.
I think that's, you know, that's really where the, you know. There's value there and there's gonna be tremendous value there. It's just kinda like, you know, figuring out how this will play out and where the, you know, where that opportunity set is.
Okay. Let's take this back to Pega.
Yeah.
How's the noise impacting you on both sides?
I would say with the clients, we really just need to keep the clients focused on where we can help them the most, which is transforming their legacy applications.
Yeah.
Help modernizing their apps. Making sure that we're also supporting them in the selection of which apps they pick. you know, primarily we're focused on the workflow-centric apps because that's relevant for us. using Blueprint. tools on the front end, you could use Claude, you could also use AWS Transform to basically digest the COBOL code as an example. That information can be ingested into Blueprint. Blueprint, the reason why Blueprint is different than any other kind of AI tool is that Blueprint understands the context of workflow. That's our business. All of our intellectual property is in Blueprint, where you could not get that if you just went to a standard model.
Now, we can use models on the front end to feed information in, and we do, and we use the LLMs as the guts of actually how the decision model actually manifests itself on the platform. Kind of our view is use this, use tools to digest what these applications are, put them into Blueprint, which helps to model out the future app. Then you have human beings, product managers of sorts, helping to decide like what does that new experience need to look like?
Okay. Start over.
Yeah.
That was super interesting.
Yeah.
step one is?
AWS-
Use-
... transform Claude Code, pull the-
Use Claude Code. Yeah
... code, pull the COBOL. Basically interpret the COBOL code. I'm just using COBOL.
Yeah, yeah.
as an example. Interpret the code. What is the system doing?
Right.
What are the steps? What are the transactions? What are the processes? What are the data, the user Like, what's happening with this custom-built app? That information, second step, gets loaded into Blueprint, just basically with a simple attachment of a document, a file, a video. Whatever the easiest vehicle is to get that in there. Blueprint takes that, understands the context of cases and stages and steps and processes.
Yeah
... and says, "Based on what I understand here, this is actually what the system does." A lot of times what you'll see is it'll take this custom-built system and it'll create a workflow that has, like, 100 steps in it, right? That's what someone customized. What it's then able to do is compartmentalize the pieces into what might be not one workflow.
Four.
... it might be 25 workflows that have dependencies or not relationships to a. That's.
Yeah
kind of where, that's what the reality of what we're seeing. What that then does is a human product manager is actually looking at those options and understands the business, understands the use cases, and helps to kind of, in Blueprint, reorganize those workflows that then what gets productized is a series of workflows that agents can actually be called on the front end, and they will be purpose-built to understand which workflow to call. The agent will drive that automated work across the workflow based on the rules and the process and the compliance on the workflow. What you're doing is you're getting speed to build, best practice kind of application modernization. You're leveraging all the agents to get human beings out of there, and the agents are guided to go through that process. That's like.
that's maybe, you know, not necessarily reality for every transformation, but that's the way we would hope that it would play out.
Oh
in terms of the best scenario for our clients.
This step one where you're using, AWS Transform.
As an example. Yep.
... to understand what the code is doing.
Yes
... is huge.
Huge.
It's a huge difference, right? This is why IBM went down 13% in a day, right? The same thing.
I don't.
Not that you necessarily agree with.
Yeah. I don't know how much people overreact to think that.
Yeah
... that, like, somehow transformation's gonna happen faster. That's probably the reaction in that particular case.
Yeah.
I think the interpretation of the code is a really. Now whether. Sometimes we do it, and admittedly, it's probably better to interpret the code than just looking at screens. We can get someone on a phone to video with voiceovers of someone, you know, showing how an application works, and we can get a pretty good depiction of what that application does. Understanding the actual code is that. Another thing we love is get process manuals that explain.
Mm-hmm
... like, how the business is run. That's sometimes even more powerful than the code because that's the way it should happen. The code is how it does happen. That doesn't mean it's the right way. You have to kinda triangulate a lot of these points. By the way, before AI, before any of this existed, this was done with, like, you know, 10 smart people, a whiteboard over months. Which is why transformation after 15-20 years, we're still only 10%-20% of the way through this.
Okay. speed round for me. Just two-
Yep
... quick ones. I mean, the Pega Cloud numbers are fantastic.
Accelerating big. Yeah.
Yeah.
Pega Cloud's gonna be in the 30s.
That's, so that's number one. Okay. Pega should be in the 30s. There you go. Number two is this, the Supreme Court unanimously affirming the decision of the Court of Appeals. That's good, right?
Yeah.
Would that be in-?
Well-
It's just checking.
Yeah. It's, I mean, we were pretty confident that was gonna happen.
Oh, you were? Yeah.
It was good to just get that, you know, to get that.
Now they have to start all over. Is that how it works?
also under a very specific set of rules.
Oh, they do? Okay.
... and guidelines because of the mistakes that were made by the first judge.
All right. Okay.
Which is what led to that shock verdict number.
Yeah. Okay, perfect. We have two minutes. Any questions from our audience? Sure. Go ahead. Go ahead, Austin.
Oh, yeah. What has gone better with the cloud transition or, like, when you think about how the acceleration there, like, just break down kind of what factors are driving that acceleration and whether you expect that to continue?
Just to repeat the question quickly. What's been successful with our transition to the cloud, and what's worked well? In the first few years, we ended up with about 50% of our growth was Pega Cloud and 50% was Client Cloud, which is where the. In the last, call it 18 months or so, that number has dramatically grown to something above 80% or somewhere around that number. What I think it was a combination of a few things, Austin. One was our sales teams really had to learn how to go from selling perpetual license to subscription to cloud. With any transition, there's human beings involved. That takes a little time.
It didn't take that long, but it did take a few selling cycles, a few years to really get that into our DNA. Second thing is, when we have one environment of Pega Cloud for a client, it makes the obvious every new thing is gonna be Pega Cloud. so we had to kind of break into where enough of our clients had experienced Pega Cloud and saw the resiliency and the savings and the security and the ease and the upgrade of the... That just kinda led to more people saying... The last one was maybe more of a brute force thing, but we went to our clients and said, "We're going with Pega Cloud. That is our primary." Clients said...
You know, we wanted to make sure our clients were ready when we did that. Overwhelmingly clients said, "That's great," because that's, you know. Coupled with that third one is, governments have moved in a much bigger way to the cloud. You know, this is kinda goes back to, like, when we first started in the cloud, I remember countries like Germany, they would say, "No cloud. We're only gonna be on premise," right?
Really?
You know, like, oh, yeah, absolutely. Then that flipped, governments were kind of the last part of that. Now the governments want to be all cloud. They want to get out of data centers. I know you guys, I think.
I think we are
... open out of all of your data centers.
I think we are.
... I think. That's.
I think we are
that's awesome.
Yeah. All right, Ken, thank you so much. It's a pleasure having you here. I actually learned a lot. Yeah, you're a smart dude.
It's.
You got a lot going on in the head. There's a lot going on.