AI The Real Story About Adoption In Companies: With Tony Falco

Michael D. Levitt: I cashed out my entire 401k thinking someone stole my identity.

Narrator: A fake email cost me my dream home. After I sent my personal information to a scammer, my AI agent wired thousands

Michael D. Levitt: to an account I'd never seen.

Narrator: When billions of people feel unsafe, that's no longer a security problem, it's an economic one. At Jenn, we're building the trust layer for a more fearless planet with products and technologies from our global brands, Norton, Lifelock, Avast and Money Lion. See it in action@gendigital.com welcome to the

Narrator: Breakfast Leadership show, where we explore the realities of leadership, decision making and building organizations that perform under pressure. Your host, Michael D. Levitt, is the creator of the Breakfast Leadership Operating System, a, uh, framework designed to help organizations improve decision clarity, strengthen leadership alignment, and reduce the execution friction that slows teams down. Each episode features conversations with leaders and experts navigating the challenges of leading in today's complex world.

Tony Falco: Welcome back.

Michael D. Levitt: I've got Tony Falco on the line. Tony, how are you?

Tony Falco: I'm doing great, Michael. Thank you for having me.

Michael D. Levitt: Really looking forward to this chat. You've got amazing background, doing some great work, and even recently some amazing success. So why don't you share a little bit about yourself and then we'll jump into the conversation.

Tony Falco: Well, I mean, I guess, uh, I've seen it all when it comes to the Internet. I started back in 96 right out of school working for, uh, you know, for a company that was digitizing the Publisher's Clearinghouse or whatever you have, the government clearinghouse for documents, working with a bunch of librarians. Whenever I give my background, I love to give a shout out to librarians who had a huge hand in organizing the web early on and all the way through to managed hosting distributed systems. I was part of a NoSQL movement that really brought new kinds of databases to the market that fit the web's pattern of distribution. And uh, most recently I've been at Hydraulics, which is a company that's really taken the logic of, of specialization to its extreme, where we focus strictly on log data that companies generate. And while that may sound very boring, logs are exploding. Every time you, uh, take an action on the Web, you generate a ton, uh, of logs that record the facts of that transaction. And we sit at the crossroads of AI and explosion of, you know, digital workflows. So I'm at Hydraulics and it's been a fun, it's been a fun place to be the last, uh, several years.

Michael D. Levitt: Yeah, the growth you've Seen from just a few customers to, you know, just a ton and amazing growth and all of that. It's definitely one where I tell people, yeah, I mean, look, and kind of reverse engineer what, what they've done and it's simple, but it's not, you know, a lot of things have to, you know, fall into place, but you have the right team. It's amazing what you can accomplish. And you know, you've seen again everything, you know, from the, you know, pioneer days of the Internet to websites, to moving from dial up to dsl, the cable Internet, to uh, all of those things to, you know, now it's just you connect to nothing. You're just always connected. And if, you know, I'm sure my, my 20 something year old kids would be like, what do you mean you're not always connected? It's like, yeah, US Robotics, I was thrilled when I got that 33.6 modem, man.

Tony Falco: That was the.

Michael D. Levitt: Oh yeah, oh yeah. Until somebody picked up the phone and then, you know, then game over. Like, how am I going to download the latest Netscape if you keep picking up the phone? I'm dating myself there just a little bit, but that's. Oh, no, no, no.

Tony Falco: Remember how cool it was to have a status symbol, to have a second phone line?

Michael D. Levitt: Oh yeah, yeah. That was like. And of course that wasn't cheap back then, but it's like, you know what, I need to do this. Especially when you started doing work and if you had to, you know, if you had to work from home. What is this? Working from home? Oh my goodness. Yeah, this is amazing. It's like you must be the top 2%. Yeah, wasn't, but there we go. But with the AI play. And I know, and I love the, the logs research because that literally tells you everything that they've done and the workflow, the steps they've taken and all of that. Because what I see the organizations that are struggling, especially if they have the mandate from the board, implement AI. Well, thanks. Uh, that's great. Okay, what do you mean by that? What do you want to implement? And they don't know, they just, we just have, we just want you to do AI. Okay. You know, it's like everybody, you know, fire up copilot first thing in the morning. Okay, we're AI, we're good. Compliant. There we go. But I think again, with me and the work that I do, and especially with organizations that are trying to deploy AI, I tell them this, like, look, before you even think about doing any of that, do you have Deep down knowledge of how things flow in your company and to a company, I would say 99.9% don't truly know because there's different pieces. You've got three vice presidents with approval particular thing, but you don't know who has the higher ranking approval than the other one. They don't know, the employees don't know. And you're like, uh, how is this work? And so it's like, okay, we're going to have AI handle that. It's like, well, you're just going to expedite the speed of failure and things getting bogged down. Um, you're just going to make it faster. So in the work that you're doing and what you're seeing, I'm sure that's a common thing you're running up against is organizations are wanting to implement things, but they don't really have a true understanding of how things are actually working. Again, like going back to the logs, that's going to help you kind of guide all. Uh, right, this is how it's flowing. Do you want to take this opportunity to maybe change how this flows is it might work even better, especially if you're going to be looking at an AI play. So let me hear your thoughts on that.

Tony Falco: Well, so, you know, one of the things that, you know, I do listen to the podcast and one of the things that you had on recently was Randall Thames talking about, uh, you know, you know, how AI fit into both productivity and what he called actual insights, sort of reinterpreting AI as actual insights. And I think there's something there. First of all, people who view AI as a productivity tool, that's I think just really part of what's going on. The, the, the, what's really important, uh, in our view, in my view in particular, is that, you know, in the last couple years the tools have become available to interpret a bunch of data that was just so massive and so difficult to work with that, that it was completely black. You know, you had no idea it was dark. It was like the Marianas Trench, you know, no light had ever shown on that data. And so things like a CD and a content delivery network, that's the sort of thing that sits between you and Disney or Netflix. So that every time you stream, you know, every second of uh, a movie you stream is generating, you know, 30 log files. So, you know, think about that. Across millions of people watching millions m of movies, you can see this enormous amount of data. Hidden in all that data has been patterns of fraud, security risks, just normal Diurnal behaviors that are, uh, sort of strange. And with the advent of new cloud platforms, plus new data engineering tools, plus AI, we're finding things out that we never understood before. So as much as people think, oh, you know, just go use cowork or go use whatever tool you have to handle and do more, I think what people really should be thinking about is what data, what, what things have we not looked into more deeply? How can we look deeper at the patterns of our business? And luckily, what I'm seeing from some really interesting companies is that it's bubbling up that the operator, the person who's at the front line, you know, who has the, the domain knowledge and now has these tools, you know, somebody, if somebody says, hey, go be productive with, if, with this new tool, they're like, that's great. And then what they do is they get their hands on these massive new data, data sets that nobody's ever touched for 25 years, and they're finding just wild patterns and new kinds of ways of understanding how users behave, you know, finding things that happen. Everybody thinks that the users show up at websites on Black Friday and start, you know, doing searches and stuff, but really that, that, that pattern of, of, of searching hints at what people are going to buy weeks before. You know, there's this really interesting, unexpected, massive sort of global patterns that we're just now being able to take a look at. And I find it really exciting. And what's most exciting is it's kind of bypassing that vapor lock of authority. Um, and you know, there's very conservative elements of people trying to protect their positions. It's bubbling up and it's just, it's really hard to resist the knowledge that's being share. You know, I think that one of the challenges that AI represents to normal corporations is that it's empowering individuals that are curious and persistent, independent of what their position is. If you're a smart systems thinker, you're going to find stuff that's so hard to ignore, that ultimately what it's going to, it's going to really uncover people who are toll takers or position holders who in previous regimes were able to win the meeting game or win the, you know, the, the, the, the memo of understanding game as opposed to generate real value. So I find this all very, very liberating.

Michael D. Levitt: Yeah, as you're talking, I was thinking about, and we know that, you know, you type up something or if you have different listening devices in your home, you know, smart home technology, you could have a conversation and Then you're watching, you know, a streaming service and then all of a sudden you start seeing ads for that thing you were discussing, which, you know, uh, great. Okay, we know that's the situation. Okay, that's, that's fine. My m. Wife and I, and I'm not going to say it on the show. We, we say something to see if we can get ads for it. Uh, they're on to us. They're not going to give it to us no matter how hard we try, because they know we're being sarcastic. So we know we. But we keep asking for it and it just doesn't happen. But again, I think it. In going back to the Black Friday example you just gave, where people are searching for things long before, you know, Thanksgiving dinner starts getting planned. And what I find interesting is with all of those logs, uh, from an advertiser standpoint, for example, or even, you know, let's talk about shows for a second. Now, you know, in streaming services, usually if they put it on there, it's going to stay on there for a while. But if you remember, you know, for, for us old people broadcast television, which still exists, by the way, but you know, if a show wasn't getting the Nielsen ratings, then they would cancel it. Well, now what they. Because streaming an episode, um, and storing it and all that stuff, it cost everybody money. Okay? So they say, okay, we're streaming this, but we're finding that this, you know, we're getting a drop off for some reason after this episode. What that. And if it's consistent across all new releases, they can say, you know, what, maybe 12 episodes is too much. Maybe we need to have them condense it down to seven or eight. And because again, these, there's so there's so much gold in the information that we would have never been able to find unless we were just like digging for something in particular. And against leveraging the search capabilities of AI and building up models and all of that, we can get to this information easier. Which then of course, my hope. I cashed out my entire 401k thinking someone stole my identity.

Narrator: A fake email cost me my dream home. After I sent my personal information to a scammer, my AI agent wired thousands

Michael D. Levitt: to an account I'd never seen.

Narrator: When billions of people feel unsafe, that's no longer a security problem. It's an economic one. At Gen, we're building the trust layer for a more fearless planet. With products and technologies from our global brands, Norton, Lifelock, Avast and Money Lion. See it in action.

Michael D. Levitt: @gendigital.com Anyway is that when it comes to shows or products or services or apps or anything like that, the quality of it will be better because it's more in tune with what we're actually wanting. But you know, going back to Steve Jobs, I don't think any of us, uh, wanted a touchscreen phone. We, we were all rocking our blackberries and love and Life and why would we want. There's no keyboard on this now.

Tony Falco: You know.

Michael D. Levitt: Go ahead.

Tony Falco: I'm sorry, Go ahead.

Michael D. Levitt: No, no.

Tony Falco: Yeah. This is such a rich topic.

Michael D. Levitt: Right.

Tony Falco: Because on the one hand you're tempted to absorb to. So if you don't mind, I'm going to counterpoint two extremes of behavior that are both working. I was introduced last year through some advisors to the company to the concept of hyper casual games. Games that rise out of that are almost completely disposable. They're just meant for you to have fun with a little bit and then they drop off. And the hyper casual approach is basically a fitness test or a fitness model for games where you launch a game and, and you try to generate some advertising and if it, if it reaches some sort of escape velocity where you know it's going to be popular, then you take all of the other games that you've released before that are just doing okay and you point all the ads that are running on them m at that game and try to get it accelerated to some big, you know, title. Otherwise you say, nope, it's going to be just another one of our sort of uh, our farm. Our farming apps and we're going to stick it out in the, in the fleet and we're going to put ads on it for whatever the next breakout game is. You're basically trying to find one breakout game in your, in your concentrating your entire network of other games at it. That's roughly what you know. The point here is this constant fitness, you know, what works. Kill it fast. Go to the next thing that's interesting and that's a way of finding content and testing content. And then I counterpoint that to the Wire or Arrested Development. Things that had time to uh, where you got 25 episodes and they, they were able to. To. To. To. To leaven. To. To grow to you know, to. To uh, to. To. To mature. And so there's like, you know, I get both. I get both. And so part of me is like, you know, I think there's certainly good places where you want to. If, if the constraint is to find something, the constraint is to find something and apply A fitness, a fitness measurement to it. And then, and then based on what it does, it plays a role in a network, that's fine. But if you're chasing something else that might have values that are outside of that, or maybe there's some sort of a indicator, um, within the early episodes of Arrested Development that said that it was going to be a quirky, long running cult hit. You know, I don't want to lose the cult hits, right. I don't want to lose the Office Spaces and the, uh, you know, and the, and the Buckaroo Banzais. You know, I want to, I want to make sure that we have room for both. And if you just apply data to it, you know, you may be applying the wrong window. Nobody ever thought Galaxy Quest was going to continue to return money, uh, to its producers 20 years after it was released. So I think as long as we're clear that we're optimizing for a specific outcome, I think that's great. But I also think that whether it's just, we're just using the wrong measurements or the humanistic kind of, you know, patience to see things emerge in our collective consciousness, which sounds a little more hippie dippy than I wanted it to. The point is that data has its place and metrics have their place. But I think that, uh, as long as you go on with curiosity as opposed to prejudgment, you're going to find really amazing things in your data right now. Things that we've never been able to find. And AI enables that. And any corporation, uh, that makes roles, seniority, politics more impactful and more important than being able to surface knowledge and being able to surface innovation. It's going to get exposed by AI. Uh, it is, yeah.

Michael D. Levitt: It's quite the truth teller in many instances. And that's a good way to put it. Yeah, it's, it's interesting to see. I'm, I'm enjoying it and I've been playing around with it for a while now, but I'm, I'm enjoying on, you know, the discovery or the creativity side of things. Or, well, I didn't think of it that way. Or that's an interesting, or excuse me, interesting way to present that. Or a lot of times they'll say, okay, give me the contrarian view of what I'm, um, saying in this article. What, what am I missing here? And it's, it's pulling from a reservoir that is, you know, deeper than the Pacific. And it's. Okay, uh, let's, let's see what we got here and it's. I, I love how you mentioned curiosity because I think that's where we're going to see some amazing innovation curiosities. What has been kind of the backbone of all innovation. You know, somebody had an idea or a concept or a thought and they said, wonder if we could do this? And we're. I still tell people we're in the early days of all of this, really. It's. I, I worked for an Internet market research firm in, you know, 2000 to 2003. So those were, you know, the dot com era days. Uh, that was a fun ride if you worked in it. Boy, oh boy, oh boy, did you make some money then. You know, it's like, well, yeah, I shared this story before where I was working IT for an organization. A recruiter had placed me. I was in Chicago, which was, you know, one of the IT hotbeds, you know, not, not as big as Silicon Valley, of course, but it was still pretty popular. And recruiter would place me and I'd be, you know, happy in the job and making some decent money. And he, he'd call six months later and say, how's the job going? Let's go.

Tony Falco: I like it here.

Michael D. Levitt: A good team. It's like, do you like it? Yeah. Do you really like it? And I go, all right, Dan, what are you hinting at? I've got this role here. Okay. And, and thankfully, we didn't have any type of agreement where I had to stay long. Said, all right, it's double what you're making now. You have my attention, Daniel.

Tony Falco: Yeah.

Michael D. Levitt: Because I was in my 20s. I'm like, you're like, okay, I'm, you know, I'm jumping up and, you know, making more money than my dad ever did. I'm like, okay, yeah, let's, let's, let's go with this. And, and, you know, rode that wave. And then reality hit and, you know, it's like, okay, well, let's get back to whatever this normal thing is. But, uh, as we wrap up, where do you see things going again because of your vast experience and knowledge? And experience and what we, what you saw, you know, throughout the, you know, the birth and the rise of the Internet and the dot com era and everything that has transpired since then and, you know, deep involved in what we're getting with the data and AI and everything else. Anything you're seeing or you're expecting to see over the next few years that you think, you know, the rest of us may not be seeing yet, you know, don't give away the kernel. Secret recipe, but I'm sure AI can give that to us anyway. But just, you know, what are some things you're. You're seeing on the horizon?

Tony Falco: So, first of all, you're very kind to credit me with that kind of insight. I think one of the things I've learned since the beginning of this is to have some humility. I, famously, I went to school, same university. I went to the Naval Academy, and David Robinson was there. And I remember telling somebody, he's too skinny. He'll never be a professional basketball player. So I've never. After that, I've learned never to trust my pronouncements. But I will say this. You said something, uh, at the conclusion, uh, of the last question, as we began to chat that I think is super important. You said, you know, I play around with this. And people often say that as if that is, you know, they apologize for playing around with it because we think the technology is something that has to be engaged with this seriousness or this purpose. And I remember all of the times that I was just goofing around with simple things like HTML and, you know, you'd find something to say, oh, you can double your, your B rate by using this. Or, you know, like, you know, you just, you. It's. We're. We're wired to play around with stuff and to learn stuff. And I think people need to be really free, feel free to play, because play is where learning starts and where you find out what you're really passionate about. You know, this is an opportunity for people to reset what their passions are. And there might be somebody who, you know, who's working, you know, as a. As a chef and wants to become an accountant or is working as an accountant and wants to become a chef. You know, somebody wants to write a cookbook. Somebody wants to write a book about how to be. How to manage your finances when you're, when you're a chef. I mean, the whole point is, like, this is a chance for people to explore and to really find out what else they can do. You know, I think play and curiosity are so intertwined. You know, you see a little kid out there, you know, with a. You know, just the other day we were out for a walk, and we saw a little girl in our neighborhood with a. With a sheet wrapped around her, uh, her shoulders, and she was a superhero, and, and she was doing really important stuff. And that, to me, is. That's the right attitude to approach this. What's going on with this thing? What can I do with it? What are its limits? Let me find out what its limits are. And I think your curiosity and your sense of play are going to take you to places that are unimaginable. And I think that one of the most interesting and exciting things about where we are right now is it's really hard to predict. And so maybe m. Don't try to predict. Maybe try to follow what you're passionate about and it'll take you to the right place for you.

Michael D. Levitt: I love that. Never stop playing and let that curiosity flow and try to break it. You know, it's like it's.

Tony Falco: Try to break it. Yeah.

Michael D. Levitt: And, you know, come up with some things and, and, you know, create some images and hopefully the waitress doesn't have feet for hands in the images and you'll be good to go. But maybe she does. I don't know. I have not encountered a waitress that have feet for hands. They may exist. I don't know if they new. I'm not making fun of you. It was a wild, crazy example of a meme that I saw not too long ago. So, anyway, Tony, I've loved this conversation. Where can people find, um, you, your company, and everything else you're doing?

Tony Falco: Well, you know, we're. We're at Hydraulics, IO just, uh, you know, with our own curious spelling. I'm on LinkedIn. I've sort of backed off the socials on. Books are a really great place to spend your evenings, let me tell you. So. But I think, you know, where you can find me is find me whenever you go into, you know, think about this conversation, really, whenever you go into, uh, your, your LLM of choice and you just start playing around, I think that's most important.

Michael D. Levitt: I'll definitely have that information. So, Tony, thank you for being. You really enjoyed our conversation today.

Narrator: Thanks for listening to the Breakfast Leadership Show. If today's conversation resonated with you, we invite you to explore the Breakfast Leadership Operating system, a structured approach that increases decision velocity, clarifies accountability, and stabilizes execution across leadership teams. Leaders can learn more and schedule an executive diagnostic by visiting breakfastleadership.com until next time, keep leading with clarity.