Tech Talks Daily
00:03:27 · Valerie Henderson
[00:03:27] S1: Yeah. Well, in short, everything. So I know that that can be really overwhelming for any customer to hear, and that's part of why Caylent exists is to break that down and help customers understand what needs to change first. Obviously, for decades, work has run on a cycle of handoffs and sinks, and now things are happening concurrently and seamlessly. And humans get to have the most effective conversation, which means they can make decisions and quickly correcting what agents did. So we think about how we're helping customers do build and then actually just get into the point where they're mostly just making decisions really quickly as the human in the loop. We talk also a lot about the the steam engine to the electric engine. And when the electric engine came out, they just dropped it in to where the steam engine was. They changed nothing about the factory floor, the different pieces, parts of that workflow, and they didn't get productivity for thirty plus years. So that's a huge part of what needs to happen. You have to redesign processes. So agents, human workers, and the legacy systems can coexist with a more clear view on the human in the loop and the change management. It's the operating system piece. And we did a survey, and it shows 60% almost of enterprise leaders are ready to let agents run autonomously in production, but only with defined guardrails. And we partner with AWS. We only build on AWS. It's the one cloud we build on. And that's part of why I think Bedrock has been such a powerful solution just with those built in guardrails and really getting people more security, more operational structure from the beginning.
00:05:18 · Neil C. Hughes
[00:05:18] S0: If we also take a look at that, I've been to a few tech conferences recently, and one that struck me was last year, it was an industrial AI event, and they were talking about individual agents and working for individuals. This year, that event, they were talking about teams of agents. In twelve months, it's gone from individual agents to absolutely teams of them there. So we're... Before a company deploys autonomous agents, from what you're seeing out there, what are the big decisions leaderships need to to make and what it can access? And most importantly, who is accountable? That is a big question that many struggle to answer now as well if one of those agents has an unexpected delivery item there. What's the best way around that, and where should they start to avoid mistakes later on?
00:06:01 · Valerie Henderson
[00:06:01] S1: I think I have... We've always told our customers to think about a problem that a couple of steps being automated would add a huge amount of value and start there. Let's start very simple, and then I think if you start simple, you can build on that. The teams of agents and how they're working together, I think it's very exciting. But to your point, the access they have is a huge part of them actually being able to be productive. And we find that in terms of accountability, there's a reason why there's a human in the loop. The humans are the ones that are telling these agents what to do and where to go and why to do it. And at the end of the day, we have to be held accountable. And I believe that you should assume nothing. You have to be very intentional about what you are doing and building and testing before you're moving anything into production. That hasn't changed. That's been the same for a very, very long time, and it doesn't change now. And the security piece, I think that this is such a very full time for companies in cyber and how they're thinking about evolving their platforms. I... That's one area I'm just very fascinated to see how that evolves because it's just gonna continue to need a heightened level of inspection and visibility. And I always like to talk about the known unknowns. And right now, there are a lot of them. And it can be overwhelming to customers, which is why I would say start small. We often start in HR or go to market motions where there isn't necessarily gonna be some major issue on these agents and the work that they're doing. And if they make some mistakes, which they will, that's okay before we're moving things into more business critical applications and departments.
00:07:49 · Neil C. Hughes
[00:07:49] S0: And, of course, there will be lots of leaders listening to our conversation today who are increasingly focused on ROI, measurable value and delivery, etcetera. Plenty of AI pilots. They look great in a demo. But what should a CEO listing... What should they be asking before believing that the agent is delivering that real repeatable business results or in in... Or just delivering value? What what should they be looking for?
00:08:13 · Valerie Henderson
[00:08:13] S1: I think the things that they have to be looking for always are how how are they organized up the stack so you can think about the infrastructure, the data, and the applications. And I often find that because of the pressure customers are getting from their boards, their customers, their employees to leverage this technology, you can want to just deliver something. And I think at the end of the day, if you are not thoughtful about what you have and what you can actually deliver securely, you're never gonna get that momentum. And I actually feel it can be more dangerous if you rush these things out. And even if they look great in a demo, if you're not actually able to turn it on and show ROI over time. And my belief is it does not have to be a crazy amount of ROI in the beginning. We have some customers that might... Maybe you're saving 10,000, 20,000, 50,000, but the way these things compound over time can be so meaningful. And that's the other piece as well, just being thoughtful of, okay. Where are your expectations? And I think starting at the bar low and rising it over time is the way to make sure that you're actually able to codify this within a business. Because, otherwise, it will always feel like something extra. I mean, at Caylent, we had to reinvent the way we deliver. It was always human based and based on time and materials, and we had to totally change what that looked like because AI changed the way our coders worked, our developers worked, how all of our actual IP could help power and speed things up across the rest of our projects. So I think, again, it's looking at the whole stack and then your operating system as a company. And if you don't have clarity on how this is gonna fit in there, a demo is just literally a demo.
00:10:07 · Neil C. Hughes
[00:10:07] S0: 100% with you. And Yeah. If we look on our news feeds and maybe even go on Netflix, the the hugging face and so many big headlines there has made a lot of people a little bit, security aware, or certainly more so than they were. So on the topic of deploying AI agents securely, I was reading that you've embedded AI deep into your AI first approach, but tell me a little bit more about that and how you've been able to scale your services organization in this AI era, but most importantly, doing it securely.