The Role of AI in Mainframe Modernization and 21st Century Software’s Place in the Z Ecosystem

On this episode of Futurum Live! From the Show Floor, Futurum Research Senior Analyst Steven Dickens talks with 21st Century Software’s CEO, Nicholas Pachnos, during the SHARE Conference in Atlanta. Their conversation covered 21st Century’s efforts to connect with younger generations entering the IT workforce, where they fit into the mainframe, and how AI is affecting their modernization agenda.

It’s a great conversation you don’t want to miss.

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Steven Dickens: Hello and welcome to the Futurum Tech webcast, brought you in collaboration with 21st Century Software. I’m joined today by Nick Pachnos. Hey Nick.

Nicholas Pachnos: It’s my pleasure.

Steven Dickens: Welcome to the show.

Nicholas Pachnos: Well, thank you very much for having me.

Steven Dickens: So I’ve really been looking forward to this. I know you’re relatively new in your role, but let’s first start there. Tell us a little bit about what you do for 21st Century Software.

Nicholas Pachnos: So I’m the CEO of 21st Century Software. And as you know, we are a company that designs software mostly for IBM, business critical software. And so my role as CEO is basically being responsible for most of the company. We’ve got a very talented staff of developers on the sales side. We’ve got locations all over the world. But it’s really ensuring that ultimately I feel my goal and my role is to ensure that we develop quality software, that enterprises that run business critical applications can rely upon. That is what I ultimately feel my goal is, is to ensure that software is bulletproof and will not fail, and not fail our customers.

Steven Dickens: So I think, let’s expand on 21st Century Software a little. Even in the mainframe space, I don’t think you’re that well-known a name. Give me a little sort of what would you say that classic sort of elevator pitch is? Where do you sort of fit in the overall mainframe ecosystem?

Nicholas Pachnos: So what we do, and again, for for IBM is we develop software in the area of performance and capacity management, business resiliency, device and storage management. When you think of those three areas, they’re very key areas within the mainframe space, essential areas in the mainframe space. And we’ve got development teams in Australia, in Germany, in the U.S, teams that really know how to build software really well and ensure again, that software for the customers that rely upon it. And on behalf of IBM, the customers that use our software are some of the biggest companies in the world. And so it’s not a matter of just creating software that works, it’s got to work at scale. It’s got to work for those organizations that are running billions and billions of transactions every hour.

Steven Dickens: So we were talking off camera while we were setting up, talking about modernization. Personally don’t like the phrase, especially when it’s applied to the mainframe. We were talking about it. I think the whole premise of that sort of assumes that the mainframe’s not modern by design. And in a lot of cases we’re talking about a platform that is the most modern, both from some of the chip architecture through to the sort of overall system design. One of the topics that are getting a lot of sort of industry buzz and hype right now is AI. I know you’ve got some strong opinions there. Where do you see AI in the mainframe space?

Nicholas Pachnos: Is that not the most overused term?

Steven Dickens: I’ve got to use the cool terms. I’ve got to use all the cool terms.

Nicholas Pachnos: It’s either AI or cloud, one or the other. What’s interesting about AI is first off, everybody talks about it. We know that. But at the premise, if you’re not solving a specific business problem, to me, any AI discussion has to start, what is the business problem you’re solving?

Steven Dickens: What are we fixing for?

Nicholas Pachnos: Yeah. Why would you need intelligence in something that someone could do on their own? Why build something that might be slightly faster than what someone can do without AI? So that’s why I do get frustrated because we throw this term around, before we really understand number one, what’s the business problem, and could AI potentially solve the business problem? For example, if all you’re doing is just spitting out information that potentially again, a customer could have gotten on their own, and it’s not business critical, do you call that AI? Or is AI something a little bit more strategic? Perhaps you can identify an outage well before it’s going to occur. Now that’s the part of AI that would interest me, if you can stop a potential problem from occurring. That’s something that obviously with the current software you might may not be able to do.

Steven Dickens: See a pattern.

Nicholas Pachnos: See a pattern.

Steven Dickens: See something emerging, maybe that’s been given the volume of the data too big-

Nicholas Pachnos: Exactly.

Steven Dickens: For an individual or a human to spot.

Nicholas Pachnos: Exactly.

Steven Dickens: Be able to apply some learning and thinking to that and be able to predict, hey, we’re on this trend line, this is going to happen if we don’t take remediative action.

Nicholas Pachnos: So what you’ve described is one of the reasons why AI has such a big potential future in the mainframe. Because think about this, we’ve got decades and decades of customer data. We have real life data over the decades, and because of that, give me a good data scientist, they don’t have to know anything about the mainframe.

Steven Dickens: It’s a large data set.

Nicholas Pachnos: A large data set with multiple, multiple parameters and feeds and all that stuff. I am convinced that if we basically decide or understand what the business problem we’re trying to solve is first and foremost, if we do that, then our ability to basically see are there patterns that are developed. Like if there’s an outage, can we basically look back and see what that outage pattern may have been five days prior to that?

Steven Dickens: See how it emerged.

Nicholas Pachnos: Yeah. Is there a commonality?

Steven Dickens: I like to use the phrase, the slow moving car crash.

Nicholas Pachnos: Exactly.

Steven Dickens: If we know that we can stop, hey, there’s the car crash, let’s maybe move that dial and look back two, three miles back down the road of what led to that car crash.

Nicholas Pachnos: Exactly.

Steven Dickens: And I think that’s our clients.

Nicholas Pachnos: And even more important, using the car analogy again, we almost all have collision avoidance systems in our car. What is that really doing? It’s letting you know that if you continue on a current course and speed, and the car in front of you basically does that, you’re going to eventually crash into that car. So it’s really nothing. I think we over-complicate AI. But the first and foremost is to me is if you don’t know what customer problem you’re solving, you’re wasting your time talking about AI. That’s the first piece that you really have to solve.

Steven Dickens: And do you see AI come into the portfolio of software that you develop more over time?

Nicholas Pachnos: Absolutely. Absolutely. When you think of this in terms of the capacity and performance solution, if we can get ahead. Performance solutions were always really good at predicting when you may run out of capacity. And in the past, a lot of the metrics that fed into that were fairly simplistic, especially when it was just the mainframe. There was a time when if you just knew when the CPU was going to run out of gas for growth, that was reasonably good capacity management.

Steven Dickens: So Nick, where do you see AI in the portfolio? We’ve just been talking about kind of its applicability. I think there’s a huge potential here, but where do you see it specifically in the 21st Century portfolio?

Nicholas Pachnos: Well, there’s a couple of areas. One area in terms of storage management. Storage management is really complex, because you have a different hierarchy of where you should place data. And in the past, a lot of that was done with someone’s tribal knowledge as to what was the best case. Because obviously what you want is you want your business critical data to be the closest to the CPU because it’s got to be instantaneous response. And then you’ve got at the end end you’ve got tape, which maybe you might want to access one or twice a month. So that’s going to be a little bit of a different thing. So the hierarchy of storage is really interesting because if you can basically look at the history of storage usage, and then basically see if what kind of patterns you have, it’s going to help you ensure most cost effectively how I basically manage the hierarchy of storage, not just in terms of saving cost, but you want that business critical data to be closest to the processor.

And when you think of it, it’s not always like every day the hierarchy is the same. Because if you do say end of month processing, some of that data that was on tape becomes really critical if you need to finish that level of processing. What if you had AI that basically said, end of month, now I need to basically have this one be much higher priority, instead of doing that manually or having someone set up a process to do that. So I think that we’re really looking at AI in terms of managing storage better, in terms of performance and capacity management.

Again, in the past, it was really, really easy because most of capacity management was about when is my CPU processor going to basically run out of gas? When am I going to just not have enough space to basically run my processing? That was true when it was largely on the mainframe, when the applications were largely in a mainframe.

Now applications basically span multiple platforms, multiple devices. We all are on our smartphone banging away at business reservations, airline reservations, hotel reservations, banking, insurance, at the back end, almost every time it goes back to the mainframe, the mainframe data. So that level of forecasting becomes much more sophisticated, much more difficult. And to be able to basically bring those pieces of the puzzle together and do an accurate forecast, not just at the machine level, but really at the business level. Because at the end of the day, why do any capacity management? The way IBM ships their processes now, it comes shipped with everything. You just turn things on instantaneously. You’re not solving anything if you’re sticking just to that processor. You have to take a business-centric approach to capacity management and performance management. And I think that AI can help basically connecting the dots of everything that goes through to make that application whole.

Steven Dickens: Tend to agree, tend to agree. So pivoting here a little, Nick. You’re relatively new, not long in your tenure at 21st Century, but you’re not new to the mainframe space. You’ve got some experience. Tell me a little bit about where you see 21st Century sort of taking that sort of position in the ecosystem.

Nicholas Pachnos: So we, again, very fortunate to be working with a lot of business critical software from IBM. We are looking to expand upon that. One area that we’re looking at is we’re very interested, we talked about storage devices. I think the cloud, another overused term, but I do think that the cloud has a place in the mainframe. Now you could be the classic cloud, where you’re using an AWS or Azure, where you’re basically doing off-prem cloud. I see nothing wrong with that, in terms of when it comes to devices and using off-platform or off-prem cloud. I think that’s appropriate for the mainframe.

If you’re a large bank and you’re concerned about security, you want to keep everything on-prem, using the cloud could be a much more cost-effective means of storing data. So we are certainly looking at that as an area that we’re really looking to expand upon. Some of the other areas, business resiliency. We are working with IBM right now on business resiliency. That’s a very important thing. With the new regulations that are coming from the EU, Dora for example. That’s a key area and that’s not going to stop. Let’s face it, government’s not going to get less regulatory. It’s going to get more regulatory.

Steven Dickens: It’s only going to ramp up, right?

Nicholas Pachnos: It is. It is. And so having and proving that you need business resiliency… One of the areas that we’re doing is not only we’re basically providing more information on what resiliency is and which you can do to basically get there. I’m finding that because there are now more eyes on the output of what resiliency products do, it is not enough I believe… We’re all wedded a lot of us to the golden greed screen, 32 70 output. I don’t think I want to show that to a business auditor, who basically also now cares about the mainframe. What we’re doing is it’s very important for us to basically the output that we produce that shows how resilient your business is– it’s got to be very, very easy to navigate through for different parties. Because everybody has a little bit of a different interest in what resiliency and what they want to see. There’s a technical side, there’s the business side, is the application resilient? Are the specific databases made up of that application resilient? So that’s another area that we’re looking to modernize the entire experience of business resiliency. We think that’s really important for us.

Steven Dickens: So one of the areas, Nick, that’s been an increasing focus over the last sort of at least decade or so, is the trajectory of VSE. Longstanding operating system, hardcore set of customers that are on that and probably will be on that for decades to come. I know IBM’s just transitioned that over to 21st Century Software.

Nicholas Pachnos: Yes, they have.

Steven Dickens: Tell me a little bit about that, what the reaction’s been, we’re a few months past that now coming into your stewardship. What’s that been like?

Nicholas Pachnos: So the first job that we have is building more awareness.

Steven Dickens: That’s why you’re talking to us today, right?

Nicholas Pachnos: That’s why I’m talking to you today. The VSE market tends to be, as you say, a very static market. And because it’s static, most often the companies involved or have VSE operating systems, they’re not out there looking, Hey, what’s happening with VSE? What’s happening with VSE? But at the same time, they’re relying upon the stability of VSE. Their business is important to them as the largest businesses in the world that may be using ZOS. So the first thing first and foremost is we’re building the awareness that we are now the owners of the VSE operating system. And because of that, we take that very seriously and first and foremost, as IBM basically comes out with newer machines and newer capabilities, that where it’s possible, we not only can be supporting that with the new VSE operating system, but we’re enhancing it where it makes sense. It’s not just enough for us to basically keep this VSE operating system running.

We’re looking at different ways of… Can we increase the performance of VSE? VSAM happens to be the predominant database on VSE. Are there ways that we can increase the access for VSE data? So we’re looking at, I guess my point is that there’s not one area within the VSE ecosystem that we’re going to ignore. We’re going to take a really holistic approach and look at every way that we can improve the operating system, because we want to give people the incentive to move to the newest release of VSE and stay on VSE. We would love it if they would stay on VSE and have them trust in us that there is a future and they don’t have to worry about it. Because I’m sure they get approached by vendors every day saying, “Why are you still on VSE? Why do you need to be on VSE?” We want to eliminate that feeling if they have any risk in the future of that. That’s our job first and foremost is making sure the platform remains available, remains high performing, and really looking at other areas where we could make it run even better.

Steven Dickens: I think that message is going to resonate with that community. I think being able to provide that long-term future, that viable roadmap, new feature function, not just day one support, but exploitation and the underlying hardware. I think that’s what that community’s been crying out for. IBM’s done a good job of keeping the lights on, but I think the strategic investment that I’ve heard about from your team’s going to really help that community.

Nicholas Pachnos: It is. And I had just got back from, it’s predominantly managed out of our office in Stuttgart, Germany. I just got back from there a couple of weeks ago. And we have built such a strong team of not just developers, but support. And extending that worldwide into the greater company ecosystem to make certain that people still need 24/7 support for VSE. We cannot basically have a customer that relies upon the VSE operating system to have any outage, or if they have any kind of a problem, to have to wait if it’s a crit situation. So it’s key for us to provide that level of availability.

Steven Dickens: I’m going to give a shout-out to my old friend, Gonzalo. You’ve got one of the best guys in the industry managing that team for you, so you’re lucky.

Nicholas Pachnos: Absolutely. I am very lucky and he makes my job much easier.

Steven Dickens: He owes me a beer for that comment.

Nicholas Pachnos: He does owe you a beer for that.

Steven Dickens: But no, Gonzalo’s a friend of mine. You’ve got a great guy managing that platform.

Nicholas Pachnos: Yes. And just by being over there and seeing how well that team was built, it just really gives me such confidence that we can do the job.

Steven Dickens: So as we bring this home, you’ve been active on some of the social platforms, talking about skills, talking about where you see the platform going in that regard. Just briefly give me some comments. What’s your perspective there?

Nicholas Pachnos: So interestingly enough, I think we all have a challenge in getting the recent college graduates interested in the mainframe. Because what are college graduates looking for? They want to be in gaming maybe. They hear cloud, they hear AI, they hear all these modern things. And I think that in the mainframe community, we need to do a better job of reaching out to the college grads. There is one university, University of Northern Illinois that runs a mainframe program. We’re actively working with them and we actually had four of their interns visit our office a couple of months ago, and we’re actually looking at potentially hiring a few of them when they graduate. We’re going to continue that relationship with them. And we are doing the same thing. We have a big development lab in Perth. We’re doing the same thing. We just recently brought on four graduates in Perth. So beginning career, going to be working on the mainframe.

But there’s another area that we’re concentrating on, and we rolled this out first in Australia. I believe there’s a lot of second in career people who are mature enough to understand, all you have to basically do is explain to someone who still uses the mainframe. And that level of maturity they get, oh my god, well, they’re not going to go, that company’s not going to go away. That platform can’t go away. And so we’re actually looking at second in career people and we’re getting a ton of interest in Australia. We did a whole kind of webinar series over there and we’ve got a lot of interest there. So we’re experimenting with that. And I believe we can do the same thing in the U.S and in other areas. And really get those second career people who are looking at getting into IT. We’ve built a really good fundamentals mainframe training program that we have in Australia. We’d like to be able to roll that out when we hire here in the States too.

Steven Dickens: I think that’s fantastic. Well, Nick, this has been a fantastic conversation. Really enjoyed some of the perspective. Good to get you on camera. Good to shine a light on the good work the 21st Century Software’s doing in this space.

Nicholas Pachnos: Thank you.

Steven Dickens: I think the VSE market’s going to really enjoy your stewardship of that platform from what I’ve picked up from your team and some of the key individuals you’ve got looking after that. So thank you very much for your time.

Nicholas Pachnos: Well, thank you. I appreciate it. Thank you.

Steven Dickens: You’ve been listening to The Futurum Tech webcast, brought you in collaboration with 21st Century Software. Please click and subscribe and check back for more content. We’ll speak to you next time. Thanks very much.

Author Information

Regarded as a luminary at the intersection of technology and business transformation, Steven Dickens is the Vice President and Practice Leader for Hybrid Cloud, Infrastructure, and Operations at The Futurum Group. With a distinguished track record as a Forbes contributor and a ranking among the Top 10 Analysts by ARInsights, Steven's unique vantage point enables him to chart the nexus between emergent technologies and disruptive innovation, offering unparalleled insights for global enterprises.

Steven's expertise spans a broad spectrum of technologies that drive modern enterprises. Notable among these are open source, hybrid cloud, mission-critical infrastructure, cryptocurrencies, blockchain, and FinTech innovation. His work is foundational in aligning the strategic imperatives of C-suite executives with the practical needs of end users and technology practitioners, serving as a catalyst for optimizing the return on technology investments.

Over the years, Steven has been an integral part of industry behemoths including Broadcom, Hewlett Packard Enterprise (HPE), and IBM. His exceptional ability to pioneer multi-hundred-million-dollar products and to lead global sales teams with revenues in the same echelon has consistently demonstrated his capability for high-impact leadership.

Steven serves as a thought leader in various technology consortiums. He was a founding board member and former Chairperson of the Open Mainframe Project, under the aegis of the Linux Foundation. His role as a Board Advisor continues to shape the advocacy for open source implementations of mainframe technologies.


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