The Agentic AI Gap: When Tech is Used Before its Architecture is Ready - Anthony Alcaraz, Agentic AI Architect (EP 25)
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What changes when AI moves from reactive systems to agentic AI?
Hello, this is Eva, and you're listening to the Inbetween Tech and Trust podcast. And in this week's episode, I get quite exciting because we talk about one of the most pressing topics in the tech and AI's era, and these are AI agents. And if I had to give it a title, then it's like the 101 of Agenc Systems for organizations. And for that, I Have Anthony Alcatraz, author of the O'Reilly book on agentic graph rack, a senior figure of AWS pushing agentic AI adoption at enterprise scale. And he's also a business angel working with early-stage startups that are actually building, scaling, and incorporating layers of the AI economy. And so with his background and His daily operations, Anthony sits at an quite unusual in-between and intersection because he digs deep enough in the technical architecture to write a book and to co-author it, but he's also close enough to the business reality to know where organizations, corporations, and teams currently are struggling.
And so in our conversation, We get like so knee deep into what actually changes when it becomes more of a systems perspective and when it also starts making decisions and taking actions on your behalf when agents take over and do the research and feed it back into an organizational output. And so the tension that we looked into is that agentic systems If they are already, you know, incorporated into the organizational structures in a way that users cannot see them. The biggest question that we need to discuss is how we build trust into something that is invisible and that is yet to be defined and to be educated. Welcome Anthony to the In Between Tech and Trust Podcast.
Thank you for the invite.
I wanna start with you at the intersection of technology and trust. And particularly when you think about it and um from a context of agentic AI but also from your collaboration with startups. What's the first thing that comes to your mind? In terms of
For the technology and trust, that is to say, especially for Agentic. Um I think currently so there is a clear change. Okay. Before we had systems that were mostly reactive, I would say. So you you would ask a question, you would get an answer. Now we change considerably with Agentic AI. We can't define Agentic AI, but system basically that observes, reason, and act. So when will you have such system? I would say the trust, you need much more trust than before. Because basically you you are delegating what we used to do as a I mean people human to a system that is automated, that will make that that will reason for us and that will take decision. So if you think about implementing that in regulated uh industries like I don't know, healthcare or even legal in the legal system or
or insurance analysis, you you need to have a clear trust in what the system is deciding. And also to put, I would say, the human expertise that is still needed at the right place. So it changed considerably, I would say, the data governance around it and even the governance around it. I think there is a problem currently because we don't have, I would say, currently there is no clear framework or governance that has emerged to manage at large scale such system. I mean currently we can generate, we can like build the build the system, scale it. This is what we are doing at Anthropic Open Air, et cetera. But I would say the governance infrastructure of it is not quite there. We struggle, for example, to secure the security risk, et cetera.
So.
Particularly when it comes to building a gentic systems. You work with startups, but you also help them scale into like environments that then also enable them to grow and to transition into this enterprise context. Yeah. What fundamentally changes when AI shifts from a single use case and maybe also in an early stage company into a system setup that then also need to be robust, need to be trusted and need to be able to also be, you know, as flexible as the market evolves, but as stable as the company or organization requires. Yes. Yeah.
Yes, yes, yes. So so it's complicated, okay.
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Chapters
8 chapters
1
What changes when AI moves from reactive systems to agentic AI?
0:14–5:33
2
Why do agents need access to enterprise data and what infrastructure is missing?
5:33–10:29
3
What are the three core challenges (data, governance, people) for deploying agentic AI?
10:29–16:05
4
How does graph architecture solve the “missing why” problem in enterprise data?
16:05–21:10
5
What is the empowerment gap and why haven’t businesses bridged it yet?
21:10–26:55
6
How do tool‑poisoning and new attack surfaces affect agentic AI security?
26:55–31:10
7
Why can human‑in‑the‑loop adoption actually block true transformation?
31:10–35:33
8
What does the future of enterprise work look like when agents handle routine tasks?
35:33–38:15
Speakers
1 identifiedMore from The In-Between Tech and Trust Podcast
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AI Governance Structures To Ensure Trust - Solo Episode (EP 33)