Kieran Gilmurray x Matt Healy: The Reality of Agentic AI

AI is moving fast, but enterprise leaders are starting to ask a sharper question: are we getting value for the money we’re spending? Matt Healy from Pega joins us to unpack what “agentic transformation” looks like when it has to survive real-world constraints like compliance, security, and customer-facing reliability, not just a slick prototype.

TL;DR:

• extending AI-driven development into the platform with coding agents such as GitHub Copilot, Codex, and Cloud Code
• deploying agents that run predictably against rules, regulations, and compliance needs
• shifting from token-based consumption to outcome-based agentic pricing for predictable ROI
• why vendor pricing changes can flip an AI use case from profit to loss
• using AI to analyse legacy systems, translate code into natural language, and guide modernisation
• combining AWS legacy analysis with Blueprint to support mainframe exit and reimagined journeys
• building enterprise-ready apps that are explainable, secure, scalable, and consistently developed

We talk about AI-driven development and the growing role of coding agents in everyday work, including tools such as GitHub Copilot, Codex, and Cloud Code. Speed is great, but Matt explains why it can also create apps that aren’t explainable, hide vulnerabilities, and struggle to scale. The goal is to keep the acceleration while making the output enterprise-ready: transparent, deployable at massive scale, compliant, secure, and built consistently.

Cost control is the other make-or-break topic. Token-based pricing sounds simple until reasoning agents start consuming unpredictably and vendors change their models. Matt lays out an outcome-based approach to agentic pricing that focuses on work done and value delivered, aiming for predictable costs and predictable ROI so promising AI use cases don’t suddenly turn unprofitable.

We also dig into Pega Blueprint’s progress on legacy modernisation, including how AWS-powered analysis of legacy languages like COBOL can produce natural language understanding that feeds transformation work. If you care about mainframe exit, cloud modernisation, and reimagining customer journeys rather than lift-and-shift, you’ll find plenty to take away. 

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Transcript

Who Matt Healy Is

SPEAKER_00 0:02

So I'm Matt Healy. I lead product marketing and strategy here at Pega, which means I get to think about how we're applying AI across development and across operations to help enterprises really drive agentic transformation. Tons of amazing announcements this week, the biggest in probably a decade, which precedes my time.

AI-Driven Development And Coding Agents

SPEAKER_00 0:20

But you know, we're continuing our development in Pega Blueprint to help enterprises drive transformation at pace they've never seen before. We're now extending that AI-driven development approach into our platform, really infusing the leading coding agents, Cloud Code, Codex, GitHub Copilot, into the day-to-day development work of developers. And then we are also allowing enterprises to deploy agents which run predictably. So making sure that it hits 100% on their rules, their regulations, their compliance in mission-critical customer-facing scenarios, and also do so with predictable costs and predictable

Outcome-Based Agentic Pricing Explained

SPEAKER_00 0:56

ROI. So we had a big announcement about our agentic pricing approach, which is all predicated on the work you do, the value you're extracting, the amount of automation you're driving, the outcome, rather than the amount of tokens you're spending through that process. So enterprises are investing so much in AI right now, they're putting big bets into it, and they're really in a race to deploy AI at scale. But very few executives to this point have really started to ask the question, which they're now asking, are we getting value from our investment? So they're building these systems which are really baking in the use of tokens. So agents which reason, you know, and churn and really drive massive consumption of tokens. And these vendors who have been sort of feeding them with low-cost tokens are now ramping up their pricing and changing their pricing models from all you can eat towards a consumption-based approach. So enterprises where they may now be building use cases that deliver a positive ROI, they're at the mercy of an unpredictable and an increasing price market that will then turn their use cases into being in the red.

Blueprint Plus AWS For Mainframe Exit

SPEAKER_00 2:01

Yeah, so Blueprint has dramatically changed over the past year. So last year you saw Karim introduce the idea of having AI agents which can analyze legacy systems, and that has really taken off over the past 12 months. So we've partnered super heavily, especially with AWS, but many of our partners to really accelerate real enterprise transformation. So in the keynotes today, we heard from AWS talking about how a deep partnership and integration between their transform capability, which analyzes COBOL code and a couple of other languages and produces a natural language understanding of what's in your legacy system. That's now integrated with Blueprint to allow enterprises to take that understanding and begin to reimagine based off of it, carrying forward all of the nuances that they need to from their heritage apps. We also heard from UNAM, one of our earliest clients, to leverage this AWS and Pega-based approach on how they're using it to accelerate their mainframe exit and not just lift and shift what's in the mainframe to the cloud, but reimagine how they're working in that process. So Pega Blueprint allows you not just to take a lift and shift approach to transformation, which has been sort of the status quo for many, many years, but also, you know, reimagine your customer journeys, reimagine the ways that you're working, reimagine your operations in the process, which allows you, okay, yes, to get the benefits of modernization in terms of TCO, in terms of getting to the cloud, but also extract dramatically more business value throughout the process. So really create a more compelling funding mechanism, more compelling economics to transformation. If you weren't fortunate enough to be here this week, we missed you. Hope to see you next year.

Building Enterprise-Ready AI Applications

SPEAKER_00 3:40

But uh, you know, one of the main things that I'm excited about is how we're using AI to accelerate development of enterprise-ready applications. So we know all developers across the board are using AI in their day-to-day work, which is great. They're moving faster, but in the process, they're building applications right now which aren't explainable, which introduce potential vulnerabilities that you can't see, which aren't instantly scalable to millions of customers, thousands of employees. So we've put a heavy focus on using that same approach, taking that same acceleration and applying it to enterprise ready applications, which are instantly transparent, uh, instantly deployable at massive scale, compliant, secure, and consistently developed.

Where To Go Hands-On

SPEAKER_00 4:21

If you want to find out about all of these exciting products, uh go to Pega.com. There's tons of great information, but the best way is actually to get hands-on. And you can start that right now at Pega.com slash Blueprint.