Tech Talks Daily
00:00:00 · Neil C. Hughes
[00:00:00] S0: The leading issue of agentic AI in businesses right now is ensuring agents act with compliance guidelines, and Denodo applies guardrails across your entire data estate. By aligning your company's data infrastructure under one system, these guardrails perform consistently across your platform. So start scaling your business and start with Denodo. Simply visit denodo.com to learn more. What would change for your business if your IT department could resolve endpoint problems before employees even had a chance to report them? Well, for many teams, the working day still involves moving between dashboards, investigating alerts, passing support tickets to colleagues, all with different levels of expertise. But the question is whether AI can help complete all that work reliably with controls and evidence that the problem has been resolved. Well, today, I welcome Jed Ayres and... The CEO of ControlUp and Feldman, the chief product officer, to join me here on Tech Talks Daily. Jed will discuss the business cases for autonomous IT and what it could mean for employees and support teams. While Gadi, he will help explain the technology, including specialist agents, connections to existing systems, and the company procedures that these agents need to understand. I will also discuss a very real example to bring all that to life, talk about human approval and ways to assess value across support time, employee disruption, and device performance. But enough scene setting for me. Please join me in welcoming not one, but two guests here on Tech Talks Daily. So a big thank you for joining me on the show today. We've got not one, but two guests. Jed, a repeat visit for you, but can you just remind everyone listening with a little about who you are and what you do?
00:02:08 · Jed Ayres, Neil C. Hughes, Gadi Feldman
[00:02:08] S1: Sure, Neil. Great to, be on again with you. Thanks so much. I'm Jed Ayres. I'm the CEO of ControlUp. I've been here for about three and a half years, but I spent the better part of the last thirty years in enterprise technology, and most of it, focused on the end user compute sector and kind of focused on how people experience technology through work. Awesome. Great to be on again. [00:02:29] S0: It's a pleasure to have you join me. Of course, you're talking to me from San Francisco today, but I'm now gonna beam everyone listening over to New Jersey where Gadi's joining us as well. Can you tell everyone listening a little about you too, my friend? [00:02:41] S2: I'm Gadi. I'm the CTO of ControlUp in the company for quite a while, and a lot of experience in the history in the IT space from the beginning. Like, been through different companies like HP, Citrix, Google. And the last couple of years, I'm responsible for managing the engineering and product of ControlUp. [00:03:01] S0: Awesome. Well, thank you both for taking the time to sit down with me today, and there's a lot I wanna talk about. There's a lot of hype and buzzwords out there at the moment around AI and autonomous IT. So, Jed, just to set the scene today, when we talk about the move towards autonomous IT, what what does that actually mean for the typical enterprise listening, whatever anybody is listening in the world today, and how far can IT operations realistically run without someone constantly watching and and intervening?
00:03:32 · Jed Ayres
[00:03:32] S1: Yeah. Well, I mean, I think in the enterprise today, this is the holy grail, right, of of kind of taking an operational problem all the way through its life cycle. And a lot of what has happened in the past has been more around observing it or detecting it and lots of great dashboards. And and I think now where we're we're headed is the ability to take that dataset intersect it with AI and, you know, see what's causing it, take an authorized action, and then most importantly also verify that the problem has gone away. And, of course that last step matters enormously. Yeah. Because running a script doesn't necessarily mean that it it fixed, anything. Right? So, yeah, I think this is this is an exciting part of why Gadi and I get out of bed with a spring in our step these days, is that, yeah, we're we're seeing, I would say in the next, you know, four or five quarters, you're gonna see, you know, very big movement and what, you know, for the last three, four decades has been kind of a a cycle where, you know, the same problems are solved over and over again with a lot of lot of tooling, a lot of tickets and a lot of human intervention. And I think a bunch of that is is set to be wiped away. And, that I think is what's getting a lot of people excited that, you know, we can we can completely rewrite how we manage devices and and really improve the life of both the employee and IT.
00:05:05 · Neil C. Hughes, Gadi Feldman
[00:05:05] S0: That will be music to the ears of a lot of people listening. And, Gadi, to bring you in here, endpoint teams have already had enormous amounts of monitoring of data, so many different dashboards. Alert fatigue is very real. So is the real problem now less about visibility and more about turning all that information into decisions and actions before employees even experience a problem? [00:05:28] S2: Yeah. Exactly. This is what we we aim to do eventually because, like, currently, like, think about that. Actually, what Jed said that this IT the IT ecosystem have never been changed for the last twenty five years. Right? It was the same thing, same same tools usually, same same, like, structure in the teams. What we're trying to do is actually finally disrupt it. And we want to, like, to... Finally, we're... Actually, in the the beginning of Control, we try to do it always with kind of, like, different, like, manual work or, like, some of our automations as well. But finally, we have, like, the the engine, the AI agents that actually would able to to do it, to actually run the IT autonomously or almost all autonomously, to get all the data, to create these old connectors to different, like, third party solutions, get all that across our agents, across the other other products, and actually take decisions and take actions to adjust the environment before users start filling the issues. So, yeah, this is exactly the case.
00:06:25 · Jed Ayres, Neil C. Hughes
[00:06:25] S1: And Neil, I would just add one thing to that that I think is important for us. Our origin story came from the VDI world, as you know, where we were trying to solve one of the largest and hardest problems in end user compute around virtual desktop and the observability there. A lot of those users are frontline users. Right? They're in a health care setting or a retail setting or a manufacturing setting and they actually don't have the opportunity to even open a trouble ticket. Right? And so that's where we also see kind of profound impact here. Right? Because those, those environments many times the experience just degrades and they kind of put up with it and it affects a lot of things downstream. And so that's where we also get quite excited that this technology can do an even better job of kind of proactively seeing those environments where the the end user just can't open a ticket and play ping pong all day trying to solve it. [00:07:22] S0: Yeah. And I do suspect we have many business leaders and indeed techies listening. They've they've seen IT teams spend huge amounts of time firefighting reoccurring issues across endpoints, AVD and EUC environments, of course. And maybe they're thinking, you know what? I've seen this movie before. We've been promised this utopia before. So to bring this to life, what we're talking about here, are there any examples that you're seeing where AI and automation is already identifying, diagnosing, and remediating some of these problems we're talking about without waiting for yet another support ticket?
00:07:57 · Gadi Feldman
[00:07:57] S2: So I can give you some examples. For example, we have, like, we have this concept of, like, skilled agents. Skilled agents actually kind of the replica of, like, SMEs in the IT team, like skilled agent for Intune, skilled agent for network, skilled agent for security, so on so on... Storage and so on and so on. These skilled agent actually can work together to to understand or manage or fix an issue. And then, for example, we can put the Skid agent in front of the tickets or, like, let's just monitor on your environment. But let's take, like, the skid... The the tickets for for example. You can just listen for each tickets, go to the ticket, understand the ticket. If need be going to, like, ask the storage guy, the storage AI agent, analyze something or ask the vSphere skill agent, analyze something else, then combine this... All this analysis together and provide with, like, solution or just, like, a kind of kind of, like, analysis of the ticket. And then it can... Or, like, act as a comment to the ticket or just solve the issue by itself. So it's something that before then, it's going to be, like, maybe work of, like, a week or a couple of days between, like, moving these, like, tickets between different teams. Now it's just matter of of minutes. So this is just, like, a really quick example of, like, how it got to be changed.