From PegaWorld: Pega CTO Don Schuerman on AI ambitions versus reality

Summary

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Podcast Summary: The Agile Brand with Greg Kihlström®

Episode: From PegaWorld: Pega CTO Don Schuerman on AI ambitions versus reality
Date: June 15, 2026
Guests: Don Schuerman, CTO and Head of Marketing at Pega
Location: Pegaworld 2026, MGM Grand, Las Vegas

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Episode Overview

This episode, recorded live at Pegaworld 2026, dives deep into the gap between AI ambition and real-world enterprise implementation. Host Greg Kihlström interviews Don Schuerman, CTO and Head of Marketing at Pega, exploring why so many large organizations stall after initial enthusiasm for AI, what brings real value from agentic AI, and the mindset and organizational changes needed to realize AI's potential—especially in marketing and CX.
The conversation also covers findings from new research, best practices from regulated industries, agent-powered operating models, and how to make the economics of AI predictable and sustainable.

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Key Discussion Points & Insights

1. Rethinking Processes is the Real Unlock for AI Success

• Research Insights: Pega and Savanta’s recent research found that “96% of organizations that succeeded with agentic AI had first rethought their existing processes,” while those that failed most often blamed “a lack of understanding of what the technology could do.” (04:07)
• Don’s Practical Take:
  • Traditional, siloed marketing processes are inadequate for agentic AI.
  • Success comes from “redesigning how that works...moving from big departmental operations with teams owning channels...to smaller, agile teams with the autonomy and accountability to operate...with the ability to pull in AI agents for content, data, and brand work.” (04:52)
  • The focus should shift from chasing incremental model improvements to fundamentally transforming workflows and roles.

2. AI Enables Customer-Centric, Omnichannel Marketing

• The Problem: Org charts and silos tend to show up in customer experience—teams don’t talk, channels don’t connect. (06:53)
• AI as an Enabler:
  • “Agents and AI allow us to approach marketing in the way that we've always talked about wanting to do it, putting the customer at the center, not thinking in terms of channels.” (06:53, Don)
  • Empowers marketers to oversee the end-to-end customer journey.

3. Human Roles Are Evolving, Not Disappearing

• Case Study:
  • Don tells the story of a copywriter who initially feared AI would threaten her job. Instead, she embraced AI as a tool to scale her expertise organization-wide:

    “She now builds the underlying skills and prompts so everybody in the company can write brand-compliant, high quality copy.” (07:52, Don)

  • Her “impact has gone from...the couple of documents and website pages she sees every month to almost every piece of copy that the company might generate.”

4. Balancing Creativity and Precision: The Sculptor and the Watchmaker

• Don’s Metaphor:
  • Great marketing—and safe, scalable use of AI—needs both the “sculptor” (creative, generative) and the “watchmaker” (precise, reliable processes).

    “There are still steps I need to complete and gates I need to go through ... even if we have agents plugged in.” (10:25, Don)

  • Example: Wells Fargo uses agentic AI in design to generate options, but relies on well-understood machine learning models at runtime for compliance and explainability, making 6 billion fast, explainable decisions per year. (10:51)

5. AI Economics: Moving Beyond the Token Meter

• Pega’s Announcement:
  • Pega will not charge clients by LLM token usage, but based on business outcomes (“work done”—e.g., customer service requests fulfilled, exceptions resolved, loans funded).

    “We're not going to run a token meter on you, we're going to charge you based on the work you get done...We can give the agents very narrow context and instructions at runtime so they don't burn up these giant, giant token costs.” (12:40, Don)

  • This model addresses the unpredictability of LLM costs and supports sustainable AI scaling.

6. Fighting Hype with Pre-Agreed Success Metrics and Change Management

• Many organizations fail implementing AI due to FOMO and lack of clear goals:

  “Boards and CEOs saying, ‘What do we want? AI! When do we want it? Now! What do we want it to do? We don't know.’” (16:34, Don)

  • The research shows that “successful implementers had, surprise, surprise, pre-agreed success metric.”
  • True AI transformation requires deliberate change management, training, and cultural adaptation—just as with earlier tech shifts in the enterprise. (17:22)

    “LinkedIn is not the real world. The real world is complicated enterprises with messy processes and legacy systems and really passionate, skilled people that now need to learn and evolve their ways of working to take advantage of that.” (17:22, Don)

7. Legacy Systems: Reimagine, Don’t Just Lift-and-Shift

• Tools like AWS Transform and Pega Blueprint can identify and reimagine core processes "buried in COBOL", not just migrate them to the cloud. That’s where value emerges. (18:33)
• Deploying reimagined processes quickly is key to actualizing AI-driven value. (19:28)

8. Federation over Centralization: The Future of Orchestration

• The industry is moving away from “single orchestration hub” models towards federated architectures where agents (with domain expertise) become reusable “brand code” services. (20:58)

  “If I've got an agent that really understands my brand ... now I want to use MCP to make that agent available wherever ... my salespeople ... my HR processes ... welcome letters ... it becomes less about there being a single orchestration hub.” (20:58, Don)

• This model enables brand consistency, flexibility, and reuse across marketing, sales, HR, and more.

9. Culture & Staying Agile in Fast-Moving Times

• Don’s advice for remaining agile:

  “You've got to be constantly playing ... AI is a hands-on tech and it's not the job of a CTO, it's everybody's job.” (23:50) “Nobody's an expert in this right now … The architectural patterns have not been written yet … they’re kind of jello and squishy right now." (23:50, Don)

  • Balance deep experimentation with stepping away to recharge creativity: “That human connection, that creativity, that taste is a spark ... AI isn’t going to bring that. And so we have to keep that alive. And that means turning the AI off every once in a while.” (24:26)

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Notable Quotes & Memorable Moments

• On Process Over Technology:

  “That kind of completely shift of what does the process look like and how do we work? ... that's the real unlock for AI value. Not getting the latest version of the model.”
  — Don Schuerman (05:50)

• On Human Expertise at Scale:

  “What she actually now has the ability to do is scale good copy across the entire organization...that's empowering if you treat it that way.”
  — Don Schuerman (08:45)

• On Cost Control and AI Economics:

  “We're not going to run a token meter on you, we're going to charge you based on the work you get done...we can give the agents very narrow context and instructions at runtime so they don't burn up these giant, giant token costs.”
  — Don Schuerman (12:40)

• On the Hype Cycle:

  “New technology shows up. We get shiny object syndrome ... what we're realizing is ... sometimes I want a screwdriver, sometimes I need a power saw.”
  — Don Schuerman (13:37)

• On Real-World Change Management:

  “LinkedIn is not the real world. The real world is complicated enterprises with messy processes and legacy systems and really passionate, skilled people...”
  — Don Schuerman (17:22)

• On Federation and Reusing AI Assets:

  “I think one of the things marketers need to start doing is think about brand as code. Like it's literally, it's code. It's managed in markdown, it's stored in a GitHub...that agent may plug into my marketing processes, sales processes, HR processes...I can reuse the knowledge that lives in an agent in a bunch of different places.”
  — Don Schuerman (21:25)

• On Staying Agile:

  “Nobody’s an expert in this right now ... the architectural patterns have not been written yet ... you just need to get your hands on and do it.”
  "AI isn’t going to bring that [human connection]. So we have to keep that alive. That means turning the AI off every once in a while.”
  — Don Schuerman (23:50, 24:26)

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Important Timestamps

• 01:11 — Introduction and episode framing
• 03:26 — Don’s background and rare dual CTO+Marketing role
• 04:07-06:25 — Research findings, importance of process redesign, concrete organizational tactics
• 07:52-08:45 — Human-AI collaboration: Copywriter case study
• 09:44-10:25 — The “Sculptor and Watchmaker” metaphor; balancing creativity and control
• 10:51 — Wells Fargo AI: explainability and performance at massive scale
• 12:40 — Pega’s new work-based AI pricing model
• 16:34-17:22 — Hype cycle, pitfalls, and need for clear success metrics
• 18:33 — Reimagining (not just migrating) legacy processes with AWS and Blueprint
• 20:58 — MCP and the move from hub-based to federated, reusable AI services
• 23:09 — Don’s highlights from Pegaworld: Brainstorming transformation with clients
• 23:50-24:26 — How Don (and others) stay agile, keep creative energy alive

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Conclusion

This episode offers a candid, experience-rooted perspective on AI transformation in large organizations: Beyond technology adoption, transformative value comes from organizational change, process reinvention, realistic cost models, and a new paradigm for orchestrating AI assets. Don Schuerman emphasizes that human creativity, adaptability, and thoughtful change management are more important than ever—even as AI capabilities scale. The clear message: Real AI impact is a journey of cultural and process reinvention, not just technical implementation.

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Transcript

[Greg Kilstrom]

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[Greg Kilstrom]

Hi, I'm Greg Kilstrom, host of the Agile Brand, and here's a question for you. Nearly every marketing leader has been told to do more with AI and many of them are now sitting on a pile of pilots, a growing bill for token usage and too often not much to show their cfo. So why is it that adoption of AI is so high while the number of organizations actually getting predictable returns from it is so low? Today we're at Pegaworld 2026 at the MGM grand in Las Vegas and we're going to discuss why so many enterprise AI initiatives stall between ambition and production and what separates the organizations that succeed from the ones that quietly cancel their projects. How marketing and CX teams can move from disconnected experiments to a governed agent powered operating model that turns a brief into a live one to one engagement and how to make the economics of AI predictable so the people approving these investments can actually forecast both outcomes and cost welcome to season eight of the Agile Brand Podcast. This season we're going all in on Expert Mode, MarTech AI and Customer Experience, talking with the people and platforms behind the brands you know and love. Again, I'm your host Greg Kilstrom and I help Fortune 1000 companies make sense of martech AI and marketing ops. Hit subscribe or follow to make sure you always get the latest episodes and leave us a rating so others can find us as well. Pega provides the leading AI powered Platform for enterprise transformation. The world's most influential organizations trust pega's technology to reimagine how work gets done by automating workflows, personalizing customer experiences and modernizing legacy systems. Since 1983, Pega's scalable flexible architecture has fueled continuous innovation, helping clients accelerate their path to the autonomous enterprise. Learn [e-mail] to help me discuss this topic, I'd like to welcome Don Sherman, CTO and head of Marketing at pega. Don, welcome back to the show.

[Don Sherman]

It is great to be here, Greg.

[Podcast Host/Interviewer]

Yeah, looking forward to talking about this. And yeah, it's been great being at pegaworld as well. Before we dive in though, why don't you give a little background on yourself and your role at pega?

[Don Sherman]

Yeah, so I'm kind of in an interesting position. Right. My career at PEGA started in delivery and engineering. I was in support delivery engineering and then eventually ended up finding myself in the go to market side doing a lot of pre sales what you know, the cool kids today call a Ford deployed engineer. Right, right. And eventually from that role moved into kind of becoming the CTO for PEGA in terms of our field facing technology leader and ultimately running product marketing. And that eventually kind of unbeknownst to me, sort of picking up different pieces of marketing and to the point that like I found myself in this weird role of being both the CTO but also the person running the marketing team. So.

[Podcast Host/Interviewer]

Well, yeah, and that's not a, that's not a common set of roles. Yeah, nice, nice. Well, yeah, let's dive in here and we're going to talk about a few things but one of the things that was talked about here at pegaworld was some research that PEGA did recently with Savanta that found 96% of organizations that succeeded with agentic AI had first rethought their existing processes. And the biggest barrier the unsuccessful ones cited was simply a lack of understanding of what the technology could do. So for that leader that's been handed like many have a mandate to do AI. Right. But not really a roadmap. What does rethinking the process first actually look like?

[Don Sherman]

Well, you know, let me just share and frankly from my own sort of perspective, right. I think you know somebody who in my day job runs a marketing team, there is so much in marketing that has the existed in kind of traditional approaches, manual production, request dispatch kind of modes of operation and a lot of those processes fall over and don't work anymore. They don't scale when you really want to use AI agents. So we've been spending a lot of time just with my team sort of redesigning how that works. How do we move from maybe kind of big departmental operations with teams owning channels and teams owning creative, to smaller agile teams that have all the right skills sort of embedded in them, have the autonomy and the accountability to operate maybe on a campaign, but complete control of the execution to then also be able to pull in AI agents to do things like brand development, brand compatibility, content generation, agents that can plug in and pull in the right necessary data science and data elements, you know, that we use of our own customer decision hub to make that happen. So that kind of completely shift of sort of what does the process look like and how do we work? I think that more so than you know, what does Opus 4.8 bring us over? Opus 4.7? I think that's the real unlock for AI value. Not getting the latest version of the model.

[Podcast Host/Interviewer]

Yeah, well, and in a way that just like more organizations are and should be moving towards in an omnichannel world, nobody should have to understand the organization's org chart.

[Don Sherman]

Right.

[Podcast Host/Interviewer]

To interact with the org, like to what you're saying, it's almost the inside of the org is starting to look like that too. As far as you have teams doing multi channel work instead of channel teams that don't talk with each other.

[Don Sherman]

That don't talk with each other. And you lead to, as you kind of perfectly described it, your org chart is showing, it's showing up in your marketing and in your customer experience. And in some ways, agents and AI allow us to approach marketing in the way that we've always talked about wanting to do it, putting the customer at the center, not thinking in terms of channels. But that was always really hard to do when you have agents that can actually start taking on some of those skills. I actually can empower a marketer to think about an entire customer journey from end to end in a way that I perhaps couldn't before.

[Podcast Host/Interviewer]

Yeah, yeah, well, and I mean that for the, for the marketer, I think that kind of elevates the level of thinking as well. I mean, even if you're super strategic in email marketing, once the customer gets outside of the email marketing silo, you know, their, their strategy kind of ends. Right. So doesn't that kind of elevate what humans are able to do?

[Don Sherman]

It does. I'll tell you a great story. One of the women who works on our team is a copywriter. Right. And so you talk about a role that feels Threatened by AI. Right. And even when, you know, two years ago, when GPT first showed up, she talked about how she was resistant, she was kind of pushing against it. But the realization that she had was, this doesn't take her job, it changes it. And her job as a copywriter historically been generate, write good copy. Well, I can actually do much more of that because I can use this tool to bake ideas off of. But what she actually now has the ability to do is scale good copy across the entire organization, build the underlining skills and prompts and markdown files that actually let us make everybody in the company capable of writing brand compliant, high quality copy. Right now. Now her impact has gone from, you know, the couple of documents and website pages she sees every month to almost every piece of copy that the company might generate. Yeah, all right. And that's like, that's empowering if you treat it that way.

[Podcast Host/Interviewer]

Yeah, yeah, of course, you know, with increased, you know, automation and agentic, there's also, you know, there, there is potential risk when, you know, if an agent is just to go too far down a path or something like that. And yet, you know, you had Wells Fargo on the stage today. Pego certainly works with a lot of customers in highly regulated, you know, industries and stuff like that. So what's the best approach? You know, there's a lot of pressure to do more and automate more and go further, kind of end to end. What's the, you know, how do you do that while still, you know, maintain it or minimizing risk?

[Don Sherman]

So the metaphor we use today that I really like is the idea of the sculptor and the watchmaker. Yeah, right. So if you think about it, watchmaker precision, right. Consistent execution, ticking off the seconds, gears perfectly aligned, sculptor, creative free flowing, discovering the forms, et cetera. And I think good marketing needs both. Right. And there's great ways in which generative AI can help a sculptor generate new ideas, conceive of a brief. But there's also stuff that you need that watchmaker in. Like, you know, even if I have agents helping me with my marketing process, it's still a process.

[Podcast Host/Interviewer]

Yeah.

[Don Sherman]

There are still steps that I need to complete and gates that I need to go through. So we're using pega's workflow capabilities to make sure that even if we have agents plugged in to do things like intake my marketing brief and recommend creative treatments and help us generate copy and pull in the right data sets, that's all being orchestrated against a process where we've defined very clearly, these are the Steps we have to go through.

[Podcast Host/Interviewer]

Yeah.

[Don Sherman]

You know what's powerful about what Wells Fargo is doing is they're using agentic AI at design time to figure out what potential offers and actions are. But at runtime, the AI that they're using is far more watchmaker like. It's what we used to call AI three years ago, machine learning, statistical models, et cetera. And those have a benefit of being one really, really fast. So they can run decisions in 200 milliseconds, which is, you know, and they do that 6 billion times a year, like massive scale. It is always explainable. Like those models, because they're based on structured data, they can tell you why they made a decision. We can say this is why we offered this person this loan or didn't offer them this credit card. And those models have the ability to be continuously evolved in self learning at a pace. That AI to retrain an LLM is really expensive even to fine tune it. So. So we've got the watchmaker models when they make sense, the agentic models and the large language models at design time when they make more sense. And it's the two of them coming together that I think is where the power lies.

[Podcast Host/Interviewer]

Yeah, and I think that's really powerful because to your point, there's not just one kind of AI and there's not generative AI. Amazing in many ways, but very inefficient in so many other ways. And I think that gets to the cost component. I know there's been a lot of talk about, you know, token maxing and all that stuff. And just, you know, I know there was a big announcement about how PEGA is structuring things, which I think speaks a lot to how much faith you have in your, in how this works. So can you talk a little bit about that?

[Don Sherman]

Yeah, well, what you're referring to is we announced this week that we are not for clients who want to use PEGA to manage their workflows and decisioning and then even plug agents into that. We're not going to run a token meter on you, we're going to charge you based on the work you get done. How many customer service requests do you process? How many exceptions do you resolve? How many loans do you fund? So that work based approach, we are confident that the way we've built the architecture, we can give the agents very narrow context and instructions at runtime so they don't burn up these giant, giant token costs, which is something that I think everybody is starting to realizing and I think it's part of frankly, I think it's just part of the maturity of any technology as it goes through its sort of hype cycle and learning curve. Right. A new technology shows up. We get shiny object syndrome. Right, right, right. We get in the mode of like, well, if, when you've got a hammer, everything looks like a nail and we start beating agents and LLMs against everything. And what we're realizing is, oh yeah, sometimes I want a screwdriver, sometimes I need a power saw. Like, it's. And by the way, it's not that agentic and LLMs aren't massively transformational and massively valuable tools in the tool chest.

[Podcast Host/Interviewer]

Yeah, yeah.

[Don Sherman]

Like, like we are going to find ourselves and we maybe are at a place. I mean, I find in my life I probably couldn't work without it. Right? Like if, like it's massively, massively valuable. Right. But it doesn't obliviate the need for me to still have Microsoft Word on my laptop. It doesn't obliviate the need for me to still want to be able to. Sometimes I just want to make a spreadsheet. Now I can use AI to help me make that spreadsheet. I can use AI to help me evolve that spreadsheet design time. But at runtime, I just want to run formulas in a spreadsheet.

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[Podcast Host/Interviewer]

Maybe to tie the hype, the hype cycle thing back to the research. Even the research found that the successful implementers had, surprise, surprise, pre agreed success metric. Again, not a shocking thing. When you run an experiment, you need a hypothesis and all that stuff. And yet we get so caught up in the hype and isn't this cool and stuff?

[Don Sherman]

Well, and I think, you know, one of our presenters from, from MetLife this week threw up a cartoon that I think many of us have seen before, right? Of just sort of the boards and CEOs saying, what do we want? AI? When do we want it Now? What do we want it to do? We don't know. Right. And, and so there is, and I think we did have these, these moments in the industry and it happens, right? Because this stuff is, is exciting and it is transformational and it's very easy to feel FOMO and concern. And like, I find people are almost kind of more stressed than ever. Cause if you spend too much time on LinkedIn, you would think that, like, everybody in the world has started up a $2 billion business with themselves like an intern paid in coffee and 30 agents. Right?

[Podcast Host/Interviewer]

Right.

[Don Sherman]

Where in reality, that's not what's happening. Right. LinkedIn is not the real world. The real world is complicated enterprises with messy processes and legacy systems and really passionate, skilled people that now need to learn and evolve their ways of working to take advantage of that. And as cool and exciting as the models are, what the data in the survey points out is the people who are successful are the ones who lean in and do the kind of grindy work of change management, of helping everybody understand what the benefit and value is of getting people agreed on what the outcomes need to be on. Really thinking about how do I need to change my processes and my culture to make this stuff work? Like, and to some extent, you know, it's a little bit of like, yeah, this is Change Management 101. And AI doesn't make that go away. In fact, AI needs it more than ever.

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[Podcast Host/Interviewer]

I mean, and in a sense, you know, some of the tools available now to, you know, help with mainframe and legacy tech migrations and stuff, it accelerates that part of it but to your point, it doesn't. The processes, the people, all that stuff still has to change. So.

[Don Sherman]

Yeah, well, and that's one of the things that we've been doing a lot with Blueprint. We were very deeply partnered with aws, and we had AWS and also our joint client, Unum Insurance on stage. And what they were talking about was just that. Right. That it's one thing to lift and shift a bunch of COBOL code to the cloud, but the value comes when you can find the processes that are buried in your COBOL code, reimagine them for the AI world. That's what Amazon can help find the process with their tool called AWS Transform. Our capability in Blueprint actually helps you now reimagine those processes for the AI world. And then what we've been showing this week in Infinity Studio now helps you then once you've reimagined those processes, rapidly deploy them, so you start getting real value from them.

[Podcast Host/Interviewer]

Yeah, well, and I think that reimagined part is. I'm sure everyone has a thought about that at some point, but I think they get caught up in the, you know, I call it like AI offense versus defense. Right. So it's like the defense is, let's just put the COBOL stuff in the cloud and everything status quo. But to actually reimagine, I mean, that takes human thought and creativity and strategy, right?

[Don Sherman]

Yes, exactly. That's exactly right. Which is why I think that even as AI continues to evolve and get smarter, the human role, to bring that judgment, to bring that strategy, to bring that creativity, it becomes even more important than it was before.

[Podcast Host/Interviewer]

Yeah, yeah, definitely. So one other thing here that I think is important to talk. There's a lot of. Any organization has a lot of platforms and systems working, whether in silos or ideally more closely together. One of the other interesting things that I heard at pegaworld here is just the promise of MCP marketing teams. For instance, they're already using Adobe or this other system, so on and so forth. The ability for, you know, because everybody wants to be the hub and there's, you know, a million spokes or vice versa. So, you know, how does MCP kind of unlock that ability to have actual orchestration?

[Don Sherman]

Yeah. And I think one of the things that I think is interesting is sometimes as technology evolves, words lose meaning. And one of the words that I worry is losing meaning in this AI world is orchestration. Right. Because everybody's now orchestrating agents and orchestrating this. And it's great as somebody who's been in the orchestration business for 20 years. I'm glad. And everybody is welcome to the party. It's great. I also think if you look though, at most organizations, there's not going to be a single orchestration hub. Like, like this world doesn't work in hubs anymore. This world is increasingly becoming federated. So what MCP offers is the ability for us to create almost catalogs of services, domain expertise. Right. So if I've got, if I've got an agent that really understands my brand and I've really successfully. You know, I think one of the things that marketers need to start doing is they need to start thinking about brand as code. Like it's literally, it's code. It's managed in markdown, it's stored in a GitHub. Like, it's code. So maybe you've got an agent that really has got your brand code. It knows it, it understands it. Now I want to use MCP to make that agent available wherever. And that agent may plug into my marketing processes, that agent may plug into my sales processes. So like my salespeople, when they do an outreach, they plug into the brand code agent to get that. That agent may plug into my HR processes so that when we send in, you know, a welcome to the company letter to a new hire, it also gets written in the brand. Right. So. So I think it becomes less about there being a single orchestration hub. You may have your HR process defined over here, you may have your sales process defined over here, you have your marketing process defined over here. But if I've got MCP on my agents, I can reuse the, the knowledge that lives in an agent in a bunch of different places.

[Podcast Host/Interviewer]

Yeah, yeah, Love it. Well, Don, thanks again for joining. Always great to talk with you. Got a couple, couple last things here as we wrap up. So we're here at pegaworld Day two, you know, towards the end, but not quite over yet. What's been a highlight so far?

[Don Sherman]

To me, the highlight is always the conversations that I have sitting with clients after, after the keynote presentations when they ask me sort of, hey, how can I use this? And we actually get to brainstorm and think about some areas where we can carry things forward. So I was talking with a couple of different clients today about how they're going to take things like Blueprint back to their teams and literally start using it next week to reimagine some of the processes they have in their business. That, to me, is what makes all this worthwhile.

[Podcast Host/Interviewer]

Yeah, yeah.

[Greg Kilstrom]

I Love it.

[Podcast Host/Interviewer]

And last question for you. What do you do to stay agile in your role and how do you find a way to do it consistently?

[Don Sherman]

Well, like one is you gotta be constantly playing, right? So just, you know, AI is a hands on tech and it's not the job of a cto, it's everybody's job to do it. So you've gotta stay constantly playing. You've gotta realize the other thing I think is important for us to everybody to get in their brains. I think we sometimes worry with tech that we don't know. We're not the experts. Nobody's an expert in this right now, right? Yeah, it's all new. The rules are changing, as CTOs would say. The architectural patterns have not been written yet. They're kind of jello and squishy right now. So you just need to get your hands on and do it. The other thing I also think is really important is also give yourself moments to stand up and take a break. Like it can become, it can become really tempting and really exciting to like just be in Claude all the time, constantly asking things, constantly playing with it. Go for a walk, go for a jog, you know, sit down, turn your phone off, have a conversation with a colleague or a friend, watch a piece of art or a movie that really, you know, interests you because that, especially as marketers, that human connection, that creativity, that taste is a spark that we need to continue to bring. And AI isn't going to bring that. And so we have to keep that alive. And that means turning the AI off every once in a while.

[Greg Kilstrom]

Yeah.

[Podcast Host/Interviewer]

Love it. Love it. Well, again I'd like to thank Don Sherman, CTO and Head of Marketing at pega, for joining the show. You can learn more about Don and

[Greg Kilstrom]

Pega by following the links in the show notes. PEGA provides the leading AI powered by platform for enterprise transformation. The world's most influential organizations trust pega's technology to reimagine how work gets done by automating workflows, personalizing customer experiences and modernizing legacy systems. Since 1983, Pega's scalable flexible architecture has fueled continuous innovation, helping clients accelerate their path to the autonomous enterprise. Learn [e-mail] and thanks again for listening to the Agile Brand podcast. If you like the episode, hit subscribe and drop a rating so others can find the show too. And if you're interested in consulting, advisory work, or if you need a speaker for your next event, feel free to reach out. Just visit GregKillstrom.com that's G R E G K I H L S T

[Podcast Host/Interviewer]

R O

[Greg Kilstrom]

the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile.

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