The Exchanges

Q who are Building these things practically. I want to get a little bit of insight from you in terms of how this is happening. Obviously you work at Okta. Okta is helping companies set up agents. So how exactly is this process taking place of you working with companies to be able to handle some of these tricky things we talked about in the beginning and actually set up agents?

A Yeah. So we, we do four things, uh, currently that really help, um, our customers and the developers that are, that are building this agent experience, right? So the first one is pretty simple, which is we verify both the agent, uh, and the user. So making sure that You are who you say you are. You're Alex, and that the agent that you, that you have essentially, uh, consented this agent to go do stuff, um, on your behalf. The second thing that we do is we provide capabilities for, um, our customers essentially, um, uh, secure APIs. So this capability called Token Vault, because in this world, You know, agents are going to be talking to lots of systems, and it's really cumbersome to go system by system or API by API and figure out how to handle their security. So we do this in a scalable way and make it super easy for a developer to use our product to essentially make sure that all of the API and agent communication is secure. Then the third one is agents will always need humans in the loop, or at least At the moment, right? And like just this example I had shared about, um, the travel example, right? I want to go to Japan in, in November and give a bunch of criteria to the agent to go find me the best itinerary. But before the agent purchase attorney, I probably want to review it, right? So there are always tasks that you will want to review. And so we call this having human in…

AI assessment note: “we do four things, uh, currently that really help, um, our customers”

Q So, I mean, talk a little bit about how, what is an AI governance, uh, process or, or document and then how does that, How does not having one sort of hold a company back?

A Yeah. So I think, I think different companies approach this differently. There is no one way to solve this. Obviously there are a few frameworks, uh, uh, companies that are deploying, but essentially you want to have, it's, it's not even AI governance, it's really data governance. So you want to make sure that all of your systems that are housing, you know, like sensitive data or, or critical data, That there is a system to make sure that only people who should have access to it have access to it. Now there are different levels of sensitivity, right? Like if somebody just accessed some meeting notes, uh, for a team that may not be as consequential, but imagine, uh, if I was in a meeting and I was talking about a customer and the customer information was accessed by somebody that could be. Problematic. My other example was, you know, my salary information was disclosed. That could be problematic. Or if a team is working on a confidential M&A, right, they're trying to buy a company, and that project name or the company name got kind of exposed internally. That would be problematic. And so, I think a lot of companies, you know, a good practice has been classifying the different types of sensitive information you have in the company. And then really making sure that all access to that information is really locked down, and you have this centralized way of managing permissions, so t…

AI assessment note: “it's not even AI governance, it's really data governance”

Q And what about outside of the coding realm? Is there a potential for this in use cases outside of coding?

A Yeah, so there, there are other categories. I know in healthcare, healthcare has a lot of, Uh, well, it's highly regular, but it has a lot of manual processes and entry, manual entry. So, so I've seen, I can mention, uh, customer names. We have customers who are using agents to essentially process medical information for their, for their patients and customers. So, uh, a lot of benefits there. And you can imagine other scenarios. I think, uh, retail, uh, and pretty soon retail and e-commerce is another area where you will see Uh, these agents play a, a pretty big role. Um, I, I can see travel being another category. You know, I, I wanna travel, uh, to Japan in November. I can easily, uh, instruct an agent to say, you know, go find me the right airfare, build me an itinerary, and if the agent knows kind of my preference of what, what kind of, um, me, you know, if I have any meal preferences, any hotel preferences. So, Those things are really valuable because I'm really busy, I don't have the time to figure this out, and an agent can go do all this work, um, for me, and I think it's extremely helpful, uh, to me as a consumer. Now, of course, hopefully it's done with all the security controls, and, you know, it's not signing me up and buying airfare that I haven't approved, but, but, so there are many scenarios where I think agents will make our lives easier, and, and today you're…

AI assessment note: “Yeah, so there, there are other categories. I know in healthcare”

Q sometimes thought partner and companion are the same thing, depending on how much you trust your AI companion to handle your thoughts. Uh, why do you believe in the, the agent use case? Because, uh, it, it has become, we've talked about this on the show. It has become a bit of a buzzword, uh, in the business world right now. Um, so, so why is it worth the hype?

A I think there are three characteristics about agents that are super interesting. One, they're asynchronous. It can, it can go do, you don't have to be in front of, uh, your laptop or, or phone and, you know, the input is not limited to like your mouse and how fast you can type. So it's asynchronous. Second is I think now, especially now with agents, they can do long running tasks. Now, most of the experience we have today, when we ask questions, we're doing research, I think you'll see agents responding fairly quickly, but You will, but there are tasks that require quite a bit of research that may take a long while, and so I think agents are perfect for these long-running tasks. So whether it's minutes, hours, I think there'll be some tasks that will run for days or weeks.

AI assessment note: “there are three characteristics about agents that are super interesting. One, they're asynchronous.”