A (1:53)

You give a little background on yourself.

C (1:55)

And your role at Gen Layer?

E (1:56)

Yeah, so my background is in computer science. I've been in crypto and AI for about a decade now. Like actually crypto, I started, you know, like in 2013. Before then I had actually managed an algorithmic traded fund. And then I've been essentially since the rise of ChatGPT. Right. So November 2022, I was like fascinated by the idea of having these agents, you know, being able to write code and start to interact with each other and so on. And then both things essentially turn into how do we essentially build a trustless decision making system? Because right now we're so used to having just these AIs and these algorithms just make decisions on our behalf. You don't know what appears on YouTube. You don't know what appears on Instagram. The feed is absolutely up to the AIs. Whether you get hired or not, whether you get an insurance payment or not. Everything is just managed by the algorithm. It's just going to get worse. So like we're trying to basically make it. How can we make it so that it's, you know, a more trustless system, that you just don't just rely on what the AIs are doing.

C (2:55)

Right, yeah, yeah, love it. Well, yeah, let's, let's dive in then. And I want to start with really defining this, this accountability gap. And so you've talked about the need for systemic trust in the agentic economy for a marketing leader at a, you know, Fortune 500 company. What, what is the lack of this trust look like in practice? You know, going be HR examples and what does this look like for accountability that could impact marketing, sales and customer service operations?

E (3:29)

Right. So we're all racing towards using AI, right. We all kind of still, I think, baffled by how strong these things are. And we're trying to really understand how to use this technology. I think that that's the mandate right now for many, many brands. Right. But the real question is that, well, what does it mean? How do you implement it? How do you really make it a reality? And the problem with this that few people are talking about is, well, who's in control? Who's making the decisions? You're used to having tools that just do your bidding, but this is a bit of a different system. You basically are not in control anymore. You're saying, okay, I want this agent to be representing my brand in front of the public, but I don't even know how it's thinking, what it's doing, what promises it is making. Right? Did it hallucinate something? Did it deny something, let's say deny a refund that really should have been refunded. Can I get sued because of that? Am I responsible because of that? So all of that, we're in a system that's really kind of struggling from a legal perspective. The whole legal system is really struggling with the number right. Of people in the world. Right. There's like 5 billion people that don't have access to justice. Right. The problem is when these agents come online, they're just going to be suing each other just for fun. They're going to be able to be just patent trolling. They're going to be able to be just thinking, what are the edges of the contracts, anything that you put on top of them, how can they benefit Sometimes breaking the law, sometimes not breaking the law, but for sure, stressing the system. A system that right now is already under stress. Right. So I think to me, like, that's the, that's the systemic trust. Right. It's like trust is kind of breaking apart. It's been breaking apart for quite a while. It will just become even more, it will become worse in the moment where you have, you know, whatever, 10 billion agents out there, 100 billion agents out there that are transacting with each other at light speed for like, you know, bigger or smaller amounts. I think at the beginning will be smaller amounts. Eventually will be huge amounts. Right. It will be very difficult to understand, okay. What is actually happening with my business. I've got these, you know, thousand agents dealing with other people outside and there it's, it's going to be quite tricky. So, yeah, that's, that's what we're looking at. Right. Like how do you reduce this risk? How do you improve, you know, the turn? How do you, you know, avoid like brand damage that they can be just by hallucinating stuff?

D (5:51)

Yeah, yeah.

C (5:52)

Well, and I think for the, for the humans that are, you know, overseeing these things. I mean, you, you mentioned this briefly, but I want to, I want to dive into this a little bit more, which is, you know, we're all used to using software and using tools as, as you had mentioned as well. But this, this shift, in addition to, to the legal and, and other implications that you mentioned, it's also a mindset shift for the humans involved in this. Of, instead of just, okay, I open this application and I do this thing. What, whatever it is, it's. I now I, you know, autonomous, semi autonomous agents doing this thing. How does, how does a leader start to teach their team to think in terms of, of that instead of again, I, I do an action and there's a, there's a defined and limited action versus now it's could be unbounded or at least relatively unbounded.

E (6:50)

I would go kind of like, what's the, what's the difference between, you know, a leader and just let's say the person that are being led. Right. Yeah. I think that humans are going to have a job like long term. Right. Which is liability, responsibility. Right. Like you are using an agent. Yes. And you spin up this agent that's going to be doing something for you. It's not like a tool. Tools just execute. Right. And that says you can oversee the tool because you're actually running the tool. It's doing something that you asked it to do. Now these agents are going to be able to be doing the their decision making on their own and they're going to be doing some things wrong. So if you're the person that puts the system in place, that agent in place and you don't put the borders so that it doesn't create complexities and problems, well, you're going to be the one responsible. And I think that this is going to be long term. What do I see 10 years down the line? Humans don't really have any more baseline job but they will have their liability, their responsibility that things go well. Just, you know, that's what the leaders are normally doing, right? Like taking on the responsibility and trying to, you know, manage a lot of people. I think what's going to happen is that everybody will become leaders, everybody will become their main job will be, you know, I'm responsible for this thing to happen and I've got this team of agents that are doing this thing and then the question really for me would be okay, how do you create the railway, right? How do you create the borders, the constraints so that things work well? How are they accountable, right? How can you track what they're doing? How do you make sure that they don't do something off, right? And I think that that's what most people should be right now thinking about as well. It's like, okay, we're moving really quickly towards this adoption. I'm the number one in doing that. But at the same time what type of limitations am I putting into the system to make sure that it doesn't break apart?

C (8:40)

Yeah, yeah, well and I think that that's a good segue to. I want to talk a bit about your solution to at least some of this is with genlayer and something that you call global synthetic jurisdiction. So I'd love for you to unpack what that means and kind of break it down in practical terms.

E (9:02)

So you can think about Gen Layer as a digital judge, right? It's only that it's not just one entity, one AI, but rather many different AIs that anybody can be part of together reaching a consensus on how to resolve a contract or how to resolve a dispute, right? So for those that are like into crypto, right, like Bitcoin is basically trustless money, right? Like you don't need the bank in order to transact, you don't need a third party in order to move money around, right? There's this other one called Ethereum, right, which is this global computer, this world computer that can essentially be running applications in a trustless manner. And what Zen layer is, is basically like trustless decision making. How do you enable decision making? Like you would be going to a judge, right? Like you and I have a dispute, we go to a judge, we're expecting the judge to be fair, right? And essentially we're trusting him, her to be able to be fair between us. Right? What Bitcoin and Ethereum do is that they remove that trust for technology. What Genlier does is also the same, right? We're removing the trust in making decisions and instead putting technology in the mix. What that means is that then you can essentially have disputes and contracts that can be resolved at AI speed because it's a bunch of different AI, a thousand different AI models that are basically reaching an agreement in a majority vote on whether some dispute or some agreement should be resolved one way or the other. What that basically means is that now you have this railway, you have this constraint, you have a system that allows you to create a contract that will be self enforced and that will be decided by this consensus, this group of AIs that will be looking into, okay, this is the evidence, this is the contract, this is the asset. What should we do? And well, if you think about it, most of the contracts in the real world are not really black and white. Most of them are not something that you can codify as a smart contract. Normally it's like, okay, you have this creator campaign and you have, you know, like, did this creator do what we asked him to do? Right? Like, was the content high quality? Right. Did he actually get the audience? How many impressions did he get? Some of those things are something that is objective, but some of those are subjective. Right. And so what Generator does is essentially enables for these like fuzzy contracts. Not just, you know, very deterministic, very, you know, black and white contracts, but fuzzy contracts that you can deploy into it and then they get executed across the world.

B (11:31)

As we talk about navigating the complexities of the enterprise marketing landscape, there's one topic that often gets pushed to the back burner until it's too late. Data privacy. As a marketing leader, you know your personal data and your team's data is out there. Data brokers are constantly collecting, siloing and selling your information, leading to increased spam, heightened security risks, and frankly, a lot of noise. We just don't need the. That's why I want to talk about Incogni. Incogni is a personal data removal service that acts as your proxy. They reach out to hundreds of data brokers on your behalf to request the deletion of your personal information. Instead of you spending hundreds of hours navigating confusing opt out forms, Incogni automates the entire process. They don't just do it once, they continuously monitor these sites to make sure your data stays off the market. Personally, I recommend the unlimited plan which includes custom removals. If you find your sensitive information on a specific site such as a news portal or health app, you simply send Incogni the link and their privacy experts will handle the manual takedown for you. It's essentially white glove security for your digital footprint. For my fellow enterprise professionals looking to reclaim your digital privacy and reduce your risk profile, this is a no brainer Protect your identity so you can focus on leading your brand. Take control of your data today go to incogni.comagile that's I N C O G ni.comagile and use code agile to get 60% off an annual plan. That's incogni.comagile.

D (13:02)

You know that moment when marketing wants a landing page? Design mocks it up and engineering says, yeah, we'll get to it. Thousands of businesses from early stage startups to Fortune 500s are choosing to build their websites in Framer, where changes take.

B (13:16)

Minutes instead of days.

D (13:17)

Framer is a website builder that works like your team's favorite design tool. With real time collaboration, a robust CMS with everything you need for great SEO and advanced analytics that include integrated A B testing, your designers and marketers are empowered to build and maximize your dot com. From day one, changes to your Framer site go live to the web in seconds with one click without help from engineering. Framer is also an enterprise solution, giving brands like Perplexity, Miro and Mixpanel the confidence they need to build their websites in Framer. Learn how you can get more out of your.com from a framer specialist, or get started building for free today@framer.com, sL agile for 30% off a Framer Pro annual plan. That's framer.com agile for 30% off framer.com agile rules and restrictions may apply.

A (14:08)

So I think you touched on some of this already.

C (14:10)

But you know, when a lot of people think about blockchain, they think about things that you mentioned like Bitcoin, Ethereum or NFTs. You know, all sorts of things like that. So why blockchain for this as opposed to some regulatory body, government entity, tech company, something like that? And what are some of the unique aspects of this that blockchain can solve?

E (14:36)

I think one thing we've seen for the last decade or so is that trust is breaking apart. There's a lot of countries that are just. The governments are filling apart companies that are using their power in order to harm their users. Like from making you addicted to their platforms. Right. To just presenting you with things that you shouldn't even see. Basically the power has been concentrating in the hands of very few. It happened the same with money. Very few had the power over money. And that basically meant that you had to be paying multiple percentage in order to make a single transaction or that you had to be waiting for days to make a transaction by decentralizing, by making it so that it's not just one entity that has the power to be the gatekeeper, that has basically opacity. I mean, we've seen with Bernie Madoff all the lack of transparency has just created issues across the system. What we're doing is basically trying to make it so that the future of decision making the. You want an AI to be making the decisions or do you want basically nobody to make the decisions for it to be a traceable, a fair and open and accessible system that everybody can essentially rely on. Right. And they don't need to be just trusting a single model with a specific bias, specific point of view and owner. Actually, we think that decentralization enables new types of use cases. That's been proven by Bitcoin and Ethereum. I think it will be like equally proven through generally, as you know, we are already being decided upon by many different AIs we don't know anything about. Right. We just want to move a little bit out from that if we can.

B (16:17)

Yeah, yeah.

D (16:18)

So let's, let's talk a little bit.

C (16:20)

About the customer experience and the customer dynamic here. So, you know, when a human agent, you know, an employee at a company makes a mistake, there's a clear path for escalation, apology, you know, whether that person continues to work at that organization or not. You know, all kinds of things like that. Obviously things get different when we, when we start talking about autonomous agents. And so, you know, what does this, what does a process of, you know, let's call it like CX recovery look like in a world that's run by autonomous or semi autonomous agents? You know, how can brands still manage risk and protect themselves against AI failure?

E (17:05)

Let's say for me, it's quite interesting. The question. Because customer experience at the end of the day is because the customer is really the one you're interfacing with. And I wonder what it will mean. And I'm not A CX expert at all. I wonder what it will mean when the customer is really not the customer, but rather an agent that's operating on behalf of the customer.

C (17:25)

Customer. Right.

E (17:26)

My perception is that they're going to be looking at, you know, any type of angle and any type of margin. Right. They will be trying to, okay, what is the best objective product? Not just, hey, you know, like, oh, these marketing works well, they will be able to see through that. So I think that marketing will fundamentally change the moment that you have these agents working on our behalf. Right. Like, and like, I think this year is the year we're going to see that. As we start to see, you know, like shopping from OpenAI, I think many people watching this or listening to this are going to be thinking, yes, I actually this year for Christmas, for example, I was asking the AI to give me recommendation of what can I give? Even trying to look at the products and give me. Yeah, I think that that's going to be fundamentally changing at the end of the day from the legal perspective. It's just going to be like, well, you will want there to be escalation levels. You will want there to be first a system that's automated, that's giving you an input. You want that then to be some human that's giving you that input that responds. Right. And you will want to have the safeguards so that it doesn't, you know, escalate potentially into the legal world. Right, right. What Genlier does is essentially also like offers that type of framework. But really I think that, that what you need to have is a system that can understand that. Okay. I'm actually dealing with an agent. I will be like, my agent will be able to deal with it and like negotiate and like try to find common ground. Right. And so things are going to be changing very quickly on this front. I'm not an expert on cx, so like.

C (18:56)

Yeah, yeah, yeah, no, of course. But. And then I think to, but to, to escalate it up to the legal level. There, there's a, there's risk here, there's brand risk. Right. I mean there's, there's the brand perception part, which, you know, we could talk about, but I'd rather focus on the risk mitigation. I mean if things go so wrong, in other words, with a customer experience that it becomes a legal issue, how should brands be starting to think about measuring and managing risk in terms of this?

E (19:30)

I think that at the end of the day measuring will be the way. Yes. In order to measure first you need to take that data and analyze it. So making things explainable, understanding. Okay, I've got this customer service agent. One option is to just not track anything of what it's doing. The other option is to make it so that it has very enforceable rules that it needs to be acting upon. So you want it to be as deterministic as possible. These agents are non deterministic in general. They're just, you can let them do anything they want. Right now what you want is to reduce the degrees of freedom so that they create less issues. So reduce the degrees of freedom, make it so that there's clear escalation processes. Again, put them just as many constraints as you can and constraints enable for completely new types of opportunities. Right. I think ultimately the customer's agent will try to find a way to game your agent. It's going to be trying to find a way because you're a good brand and your naive agent is just going to be there for agents to be attacking to see. Okay, what's the best way I can search the whole Internet to find for ways to basically profit from this offer? Yes. And it will be able, like the whole, the whole thing will change.

C (20:47)

Yeah, yeah, agreed. So looking out, you know, future, future states, you've said, I won't wait for lawyers. You know, looking out over the next couple of years, what's the, what's the biggest mistake that brands are currently making as they rush to adopt AI agents? Without considering some of these things that we've talked about.

E (21:11)

I think the next two, three years is when we're going to see this. We're going to see that companies are going to be deploying agents at scale, at a scale that it will be even hard to control because your competitor is deploying all these new agentic systems. Why are you not doing it? And it's just so easy and you can buy code so you can just move really quickly. What I think will happen that people are not really seeing yet is that the legal system is going to be really in stress. These agents, they will be able to sue each other just for fun, do anything they want and they don't sleep. You don't know who is behind them. They're just crazy smart. So I think just the infrastructure is not ready. The infrastructure is not ready. You don't know if the agent that's buying your product is actually from North Korea. How are you going to do? Okay, now you need kyc. Are you used to having KYC on your, on your chatgpt? What happens if one doesn't like, do we have this infrastructure? We don't have that right now. Right. So I think that you will see the emergence of all these adversarial agents. You will see how the legal system starts to struggle and how probably in a couple of years, right, it will be obvious that you really need to have a layer, like a legal system for this future of AI. Right? This AI commerce layer needs to exist because if not, well, the, the human legal system just kind of scaled to that level. I don't think that it's going to be replacing it. I think it's going to be like, okay, I want to offer to you this product. Right. I will put an escrow, and then the escrow will be smart enough to understand whether actually I fulfilled my promise. And then your agent will be able to say, yes, I want to enter into this contract. And then you just have, you know, maybe it's a thousand dollars contract. You don't need to go through, you know, hundreds of thousands of dollars of litigation a year or so to get something resolved, if not worse, just for a thousand dollars. That's where we are right now. Right. The customers are feeling like they're not in power, right? They are like the brands are in power. They just, you know, they cannot really do much for many of the things that are happening. I think that that's going to be like shifting a little bit into, into making it trustless. That's what, that's what we're working on.

B (23:19)

Yeah. Yeah.

C (23:20)

Well, thanks so much for joining. Got a couple last questions for you before we wrap up. So first, if we were having this interview one year from now, what is one thing that we would definitely be talking about?

E (23:32)

I think we will see how agentic commerce is really kicking off. I think you will see how people are just asking their agents to make money. It's just so easy to say, right, make money for me. And then the agent will have to find a way to make money. So you can think of what would you do if you were that agent?

C (23:50)

Yeah, definitely. Well, and last question for you. What do you do to stay agile in your role and how do you find a way to do it consistently?

E (23:57)

I'm always trying to be innovative and understand where we're heading. And on top of this, I don't really have a sunk cost fallacy. Very adaptive. Always need to be tip of the spear, understanding that things are moving really quickly and ready to just change focus if you need to.

C (24:16)

Yeah. Love it. Well, again, I'd like to thank Albert Castellana co Founder and CEO at Gen.

A (24:21)

Layer for joining the show.

C (24:23)

You can learn more about Albert and.

A (24:24)

Genlare by following the links in the show notes. This episode is brought to you by Tech Systems. They're leaders in full stack, tech services, talent solutions and helping companies put it all in action. You can learn more@teksystems.com and thanks again for listening to the Agile Brand podcast. If you like the episode, hit subscribe and drop a rating. Subscribe so others can find the show too. And if you're interested in consulting, advisory work or if you need a speaker for your next event, feel free to reach out. Just visit GregKillstrom.com that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co. Op. From ideation to Create creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile. The Agile Brand.