John Radko on AI Agents and the Future of Information Management

Hey everyone. Welcome back to another Tech Drunk TV segment. I'm really happy to introduce you to my guest.

I think this is his first time on Tech Drunk TV with us. His name is John Raco. John is the SVP Senior Vice President for Enterprise Engineering and our good friends at OpenText.

Hey John, welcome to Textron tv. It's great to have you on. Thanks, Alan.

It's great to be here. So John, you know, we're gonna talk a little bit about OpenText in a minute, but for now, suffice to say OpenText is a really one of the giants in the tech industry. I don't know if a lot of people realize the full breadth to be SVP for all of enterprise engineering.

There is, it's quite a job, quite frankly, right? Congratulations to you. But can you share with our audience maybe a little bit of how you came to be SVP for Enterprise Engineering, kinda what your path has been?

Yeah, Absolutely. Thanks for asking. Um, one of the funny things is I am an extremely rare animal in the tech industry.

Um, I am still essentially with the organization I joined out of, out of college. Um, when, uh, when I graduated, I joined, um, uh, general Electric in what was then GE Information Services. I know it well.

It used to be a merit data before that. Yeah. And, and then it was, uh, spun into private equity, um, about 12, mm-hmm.

14 years after I joined. And then I came to OpenText as many people come to OpenText, I dare say the majority, through an acquisition. Um, so my, my career has been pretty varied.

I started it, I spent a brief time in it, moved over to software engineering. Um, I did build management project leadership. I was an engineering manager.

Um, and then I got an outward facing job where I spent a lot of time with the sales team explaining our technology. Uh, that led to an inside job in leading an enterprise architecture team. And that's the role I had when, um, when I was, when OpenText acquired GXS.

That's a, that's a particularly good job during an acquisition or a major change because you have the advantage of explaining a lot. So talking to people at a high level, the our executive leadership team and the, and the CEO, and then you also get, um, you also get to know all of them. So when the opportunity to lead, uh, lead enterprise engineering came up, I was able to transition first into business network and then into, uh, enterprise engineering.

Excellent. What a great story. John.

You know, we, we'll talk off camera. I actually have a lot of experience with the GE information system of MARATA folks. Uh, the group that founded that good friend of mine, Brad Feld, was the CTO when, when that deal went down.

But we'll save that for an off camera discussion. I mentioned OpenText having, you know, a wide breadth of, of products and solutions. Most of our audience, I'm sure is familiar with the name OpenText, and they probably have a very tunneled vision of Yes, OpenText of the people where I get this solution from or that solution from, I don't know how many of them really see the bigger picture.

John, if I had, you know, to put it on your shoulders, you've been there long enough, how would you describe OpenText to these folks? So, so OpenText is really about managing information across a, a series of problem donates. Um, our, our, the thing we're best known, or that we've been known for the longest is document or content management.

Um, but we also manage information that companies exchange back and forth with each other through our business network. Um, we help with marketing and customer communications through our experience group. Um, in the, in the last five to seven years, we've made a major thrust into cybersecurity, both on the consumer space with WebEx and Carbonite, and also in the enterprise space with, with key brands like Fortify and ArcSight.

Also, in those last, um, last few years, we've entered the developer space in a big way, especially through testing tools in our A DM division. And finally, I would say of the, of the big ones, our IT operations management. And what's interesting is when you look at all those spaces, what they have in common is generally we are managing information that belongs to the enterprise, but making it available in a secure way to the, the teams and staff that work in those enterprises, whether it's content management or service tickets or, or, or, you know, automated tests.

It's all about managing information and increasingly in the cloud. Excellent. And, and I should also mention, look, you came on board o to OpenText via an acquisition.

OpenText is a company that has grown both holistically or, or organically, let's say, you know, as well as via acquisition, right? They've made a number of acquisitions, uh, some big, some not as big, but really just, you know, a tuck in here, break into this market there, and you look back over, as you mentioned the last couple years, and you could see a, a real big expansion in the go go-to market here. Yeah, I mean, the, the company is I think easily four times as large as when we initially joined it.

Um, and that was only back in 2014. That's crazy. Yeah.

I mean, think about it's nuts. Some of that is organic and some of that is acquisitions, and I think it's the blend of the two. It makes it such an interesting place to work.

Agreed. com, correct? Absolutely.

Yep. So we'll, we'll close that one out. Let's move over to what we wanted to talk about today, and it's what everyone seems to be talking about today, right?

Agen, ai, AI agents, some people are calling them digital workers. I think that freaks people out a little bit because those digital workers might be replacing human workers. You know, we think of them as competition rather than as tools.

Um, and you know, we, as I said, everyone's talking about these, there's so much hype, so much fud, so much fake news, you know, really where, what, what is. But that being said, beneath all that, there's reality that this is, this stuff is real. It's getting more real every day.

It's getting more capable every day, and it's doing more every day. So how, where do, how do we see through the fog, through the, the hype in terms of what's real, what's possible, what's doable, what's open text, seeing and doing? So what's interesting is we a a few, you know, maybe even just two years ago, right?

We had the LLMs burst on the screen, on the screen, and, and that was chat, the chat interfaces and being able to talk to 'em. And those are still playing a big role with everybody. And everyone saw that and was wowed and blown away.

And we thought, this is gonna change everything, but it actually wasn't. I think AG agentic is gonna be the driving change. And, and the reason is that it is going to enable us to realize the latent potential in all the work we've been doing for the past decade or two.

What I mean by that is it's true automation of knowledge work. If you think about the, the change automation drove in the physical space with factories, with robotics and, and, and CMC machines, we haven't been able to hit that in the knowledge workspace. And that is because we generally need, and I'm, I'm gonna use a word here that's overloaded in the AI space, but, but you need some context and, and some goals, right?

So I, I can go to an information system, an ERP system or a manufacturing system, and I can get all kinds of wonderful information, but the system has no intent and it has no ability to understand what that information means. There have been some, some niche areas, you know, with, uh, typically other areas of ai like machine learning and whatnot, but it's been really hard to say, you know, give a, give a tool something and say, Hey, go analyze my product set and, and gimme a profitability analysis on each arm. Obviously technology is incredibly important to answering that question, but generally there's an army of people hitting keys and stuff, and you go back and forth.

There was never a, um, a system or a piece of software that could understand your goal and try to carry it out. And this digital knowledge worker or agentic ai, there, there's two really important things. One is you can be way less precise about what you're asking for, and that's where the LLMs come in and their ability to understand human language and try and turn that into something more specific.

The second thing is it's ability to interface to systems that are already there using APIs we've already built. And that's what I mean by the latent potential. So we have all these systems we've rolled out across our enterprises and that dominate our world, but it's not necessarily easy to hook them together and ask them questions.

Um, ag agentic AI is sort of that last mile, if that makes sense. There is, that's a great way of looking at it, John. It's a great way of explaining it.

I don't wanna put you on the spot, but John, how much of it is real today? I think, I think a lot of it is real today, but the wave is just building. And, and let me explain, let me explain why OpenText is so interested in this.

Um, we, like I said, we give our customers tools for information management across all the, all those domains I talked about. And the, the only limitations customers have on what they can do with the tools we give them are their capacity, typically human capacity and their imagination, right? Agen AI is not gonna help us with imagination, right?

Nobody's found a, nobody's found a computer, um, tool for imagination, but it's going to help us a lot with capacity. And what, what I mean by that is think in your own life or in your own business how much information is available to you versus what you can process. At the same time.

Think of like the best assistant or or direct report you've ever had who could go find answers to you when you asked interesting questions. Ag agentic AI is gonna attempt to automate some of what that assistant did relative to those data. Now it's not going to be as good as the best people out there, right?

The best analysts, the best consultants are still going to outperform. But if you think about the areas where it's just not cost effective to put people in analyzing data and put people in there working across systems, agentic AI is gonna give us disability and we're starting to see it. I'll, I'll give you a case from, uh, another division of open text.

Um, I work with, um, another, uh, vice president Tall Levy Joseph, and she runs our developer tools division. And her customers are using our AI agents to generate test cases. In many cases, customers don't have automated testing across their whole portfolio because the, the ROI on devoting QA staff to build out tests on existing code is not there.

But by using AI agents, they can now fill that in. So that's happening today. That's an existing, yeah.

Um, in our, in our content management space with our Aviator product, we've been giving customers the ability to talk to their documents, um, via chat interface. So essentially you load a document up, it gets ingested, and, and you can, um, you can ask questions of it very similar to what you'd see in an LLM if you uploaded a file, except that all the, all the protections and security are still applied, which is very important to our customers. What we're launching next in the next two quarters is basically a agentic version of that to the point where you could workflow it.

So I want you to think about a customer, um, opens the, uses a self-service ticket to open an incident, and we know the customer, we know the product, we know about the configuration, the workflow can actually ask the documentation of the product about the error, the error, and generate a summary. And when the agent first opens that up to address the client, they already have a whole bunch of context on the customer and the problem. So, agents, agentic, AI have already worked on it.

And, and the power here that that is amazing is I was at the Google Cloud next event recently. Each company is implementing agents in their own software. So ServiceNow is doing it, Salesforce is doing it, OpenText is doing it.

So all these agents will be able to collaborate together, so you're not losing the benefit of all the partners you're working with. But this can all happen in an automated fashion before you look at it for the first time. So it's, it's, that is happening today.

You can see examples of that today. And I think the biggest limit right now is on the imagination front. 'cause the technology's there.

This, uh, the protocol, uh, MCP, um, you know, I'm looking at what people are doing with it. Um, MCP enables those APIs to be accessed with agents, and then the agent to agent protocol, which is younger, um, is gaining traction, and that's gonna let agents interact with each other. So I, I think it's coming on really fast.

I love it. I love it. You know, unfortunately, John, we only have 15 minutes.

This is a subject, well, I I do a lot more interviews than probably you do. I do five, six of these a day. So by the end of the day, I do a lot of talking on agents and, uh, agent ai, but unfortunately, we, we need to pull the plug on this one.

How can people stay abreast of what OpenText is doing in this, in this new frontier? com is your best resource, and we have blogs up there and announcements. Um, we're, we're putting up demos on a regular basis of what we're doing, and in OpenText it's all about our Aviator AI strategy and the digital knowledge workers, which is what we, we refer to our AI agents as well.

Sure. I should also, a quick plug. We're actually doing a series of interviews with OpenText, I think Mitch Ashley, uh, CTO here at Text Trunk Future Analyst for DevOps, uh, is doing a series of interviews around ai, agent AI and so forth.

I specifically on the developer tools For, and that's a really exciting area because of the productivity and the improvements of quality. You can see working with our A DMT. Absolutely.

Uh, you know, for whatever reason we, and maybe it's because I live in the IT bubble that I live in, we tend to really focus on what AI's role is in terms of the developer experience, in terms of testing, in terms of writing code and security. I think AI is gonna disrupt so many different verticals across the board, but we're very focused in, in this IT area right now. Well, and can I share one more thing with you then?

Sure, you can. The whole basis of the package software industry is that it's too expensive to write software that's customized for your business. But what if that changed?

What if suddenly you could, and that is what we're seeing is we're seeing it. Uh, we're Still, that's the promise Applications, but these agents basically make the application look more like a library. We, um, and you have people stringing together capabilities from different vendors and homegrown, and you can do it so much more quickly.

I think it's going to revolutionize our industry, and I don't use that word lightly. I, I've, I mean the, No, I, I don't disagree. Oh, look, I, I think it's not good.

Just the industry. This is, this is a, a civilization changing kind of thing, right? And it's gonna disrupt and change.

Just real quick, that series I mentioned is called Control Alt Deploy. So you can catch it on text drunk for people watching at home. You could catch it on, uh, text drunk TV or on our OTT app or what have you.

Anyway, hey, John, it's been great having you on. Please don't be a stranger. Come back on.

Keep us posted, keep up the great work. These are exciting, you know, for people like you and I who have been around a bit, these are exciting times. I mean, there's such, so much good stuff happening.

Thanks, Alan. I really enjoyed it. John Ratko, senior VP for enterprise engineering at OpenText.

Here, ONT Text drunk tv. We're gonna take a break. We'll be back in just a bit.