Tech Talks Daily
00:09:10 · Jed Ayres, Neil C. Hughes
[00:09:10] S1: I guess I would add one too, Neil. Like Yeah. When we look at, like, the dataset that we can collect for our customers, it's it's it's huge. Right? And, now with AI kinda working at machine speed looking across these environments, and doing it, you know, at a very fast speed, we can see patterns, distinct patterns that are causing problems. I I, I would say there's a good one on our website, for CHRISTUS Health where our Pulse insights... Your Pulse AI insights identified an audio driver problem that was affecting 900 different devices. Right? That, you know, in a hospital setting where they were having problems with the dictation. And so it sees that and so instead of, you know, people having to sort of call in individually and, you know, solve these device problems, you know, one at a time, we see it holistically. We know the remedy. We update all those drivers and, you know, hopefully also do it before it becomes a real issue across the organization. [00:10:14] S0: And I guess, Jed, that there's also an interesting workforce question here. If autonomous endpoint management, if that continues to succeed in removing much of that repetitive operational work, how does that role of the IT professional change? Where should organizations redirect that time and expertise that they get back? I know for many years, IT departments have been looking to be more of a value add department, get... Maybe get involved in project resources, etcetera, and adding value around the business. But how do you see this playing out?
00:10:45 · Jed Ayres
[00:10:45] S1: Yeah. Well, I think I just spent the weekend up in Napa with about 30 CIOs, and it's the same old refrain. Right? More more... Do more with less. Right? And and course, now that's even more extreme with AI and the budgets that are needed for AI, and then the security and governance that is needed for AI and the board level mandate that, hey, AI could, you know, help us get ahead of our competitors. Right? Or if we don't do it, it'll we'll slip behind them. Right? So I think there's more pressure than ever on IT right now. And so when you think about the budget that, you know, is applied to sort of the mundane, you know, that we're... We've been talking about. Right? This is an area where if you can solve for this, right, if you can have l one tech help desk, you know, solving what used to go to two or three, this allows the, you know, the the sort of intelligence level, and the sort of effort on strategic projects to to kinda redirect is what I would say. And that's very important, right, as, things are moving faster. And I kinda call it Groundhog Day, Neil. Right? Where it's like, we've been in this sort of like loop. We walk into an organization right now, and we can take 30 to 50% of the help desk tickets out immediately, just like they're gone. Right? And then you're taking the ones that are left and you're allowing the guy that might have just been triaging in the past where he was just getting kind of baseline information, and most of those were going to the more expensive two and three level, to get solved. Our AI is allowing them to kind of, you know, have the full intelligence of everything that has ever been solved in the universe of that environment, plus the rest of our millions of endpoints. Right? So that's where I think, the world changes dramatically. Right? It's like people get worried, oh, this is gonna... We're gonna lay off lots of people. I see it the other way around actually. We're gonna allow people to sort of stop digging trenches and do much more high value work.
00:12:58 · Neil C. Hughes, Jed Ayres
[00:12:58] S0: Yeah. And there is never a shortage of projects there. And I think the days of IT say, well, we can get that project in twelve to eighteen months. We'll get it into our pipeline. Those days are gone too. Right? Because so much changes now every 12 months. You gotta move so much faster. Right? [00:13:15] S1: Exactly. Yeah. The speed is the number one thing here. And, yeah, that's where... I think our origin story around the data, and Gadi's been here from the beginning of time, but the fact that we were trying to solve this really hard problem of observability and the VDI, it it meant we had to have a very wide dataset, about 10,000 metrics that we're collecting every three seconds. So very wide, very fast, and we... Now as we enter into this AI era, turns out that dataset has become a a real competitive advantage for us. [00:13:52] S0: Yeah. And, Gadi, to bring you back in here from a tech perspective, especially, there'll be many techies listening to you saying, yes, but autonomy can introduce, additional risks. So how do you decide which actions an AI system should be allowed to take independently, which require human approval, and, ultimately, how organizations can maintain accountability when machines start making operational decisions and maybe something that might might cause a surprise further on down the line. How do you handle that?
00:14:22 · Gadi Feldman
[00:14:22] S2: So you're right. You're totally right. So because of that, we're adding a lot of different layers of the guardrails, no risk agents. So for example, each one of them running in that kind of a containerized environment that we actually control what it can be reading outside and getting inside the container and so on. We have a human loop, so each agent will be able to work with specific setting of human and loop. So when it's to be approved by admin, why it's not... When it's not going to be approved by admin. We're going to, like, add different, like, connections and different, like, layers of connections, so what is, like, risk MCP, what is not risk MCP. So we're adding different, like, layers of, like, responsibility and there's some guardrails to to control these agents. But overall, I think it's also kind of a journey that we need to go together with the with the customers because some of them still, like, very afraid of it. They are kind of, like, coming to this position. Yeah. I'm not sure. Maybe whatever. I... Or I not want to touch it at all, something like that. It's a journey. They need to trust it more. In the beginning, it's going going to be many, like, analysis and maybe insights or, like, some recommendation. But going forward, I think, like, they're going to trust it more and, like, allow to do more actual work. But, yeah, we will provide whatever guardrails and whatever security layers we will need to make sure that actually not doing any harm to these environments.
00:15:41 · Neil C. Hughes
[00:15:41] S0: Yeah. So many great points there, and I guess another danger with automation is simply automating a bad process faster. So for anyone listening, before an organization moves towards autonomous IT, what what needs to be in place across their data, their workflows, policies, and all that organizational readiness for automation to genuinely improve operations rather than just create new problems and that old garbage in, garbage out problem that we've also seen many times?
00:16:08 · Gadi Feldman
[00:16:08] S2: I think it's mainly about connectors, by the way. So this is why we we spending a lot of effort, like, create a different connector to different system because eventually, we're not going to replace any kind of, like, IT system because, like, there are, like, hundreds or there are thousands of them. And, like, a customer, a usual environment using, like, kind of, like, 13... 20 to 30 different tools in these environments. So we're not going to replace internal. We're not going to replace, like, cluster or something like that. It's all about connectors. So whatever we will able to get the data from this, like, therapeutic solution to our engine, to our brain, and understanding and and and understanding how to to read it, this is the story of, like, how we will able to bring more autonomous solution to to this to this environment. Without connectors, it's kind of like, yeah, it's kind of the same thing. Right? You you you see what you see eventually. And to allow this kind of very smart engines to make analysis and make the actual work, you need these connectors. So this is the first step. The second step, again, that creates kind of, like, policies to what the agents need to be... Need to do, like kind of instructions, provide these... All the knowledge base you need to be familiar with. For example, it's not just a connection to crosstalk, but any... But you need to actually understand where are your VIPs, for example, or what is your policy, what are, like, your your procedures you need to follow in the in the organization. And it's also kind of, like, stage stage stage that you need to take to take. I can't think... Usually kind of, like, trying to create a parallelism between, like, agents and and IT IT workflows. So whenever that you're building your IT team, you're usually looking for someone responsible... To be responsible for your security environment. Right? So you're looking at some... Something in the wild, people with some experience with Cisco or or WIZ or whatever, kind of understanding with the the security. But they come with the knowledge, but you still need to teach them your procedures, your actual day to day process of your environment. And it's kind of the same with the agents.