245: He Built the AI Network Big Tech Wants Access To (Followers Don’t Matter) with Daniel Faggella

Today I’m talking to Daniel Faggella, who built and sold a $2 million ecommerce business so he could go all-in on artificial intelligence years before the rest of the business world caught up.

Daniel is now the founder of Emerj, an AI research and media company that works with companies like NVIDIA, Google Cloud, and Salesforce. He also hosts the AI in Business podcast, where he’s spent years building relationships with the executives responsible for some of the biggest AI investments inside enterprise.

What makes his business especially interesting is that its value has very little to do with how many people download the podcast. Daniel built a network around people who had relatively little influence when he first started talking to them, but would eventually control massive budgets as AI became a priority.

We get into where AI actually stands inside large companies today, why smaller businesses may have an advantage over enterprise, and how Daniel thinks about positioning yourself around a market before the money and attention arrive.

Mic Drop Moments

• “If there’s a particular skill you want to get better at, you have to build some reflexive mechanism to get feedback super immediately from what that thing is.” – Daniel Faggella

• “All that we get to do is lightly influence the trajectory of what we build and what we become.” – Daniel Faggella

• “I don’t recommend starting a business unless you can’t not start a business.” – Daniel Faggella

• Building A Business To Fund An AI Bet
• How Enterprises Approach AI Today
• Why Small Businesses Can Move Faster With AI
• Business Lessons From Brazilian Jiu-Jitsu
• Building Faster Feedback Loops
• From Martial Arts Gym To Ecommerce
• The Realization That Redirected His Life
• The Video That Launched Science Of Skill
• Get Known For One Specific Thing
• $2M With One Full-Time Employee
• The Affiliate Model That Fueled Growth
• Why He Sold A Fast-Growing Business
• Why He Went Straight To Enterprise AI
• The Life Mission Behind Emerj
• Who Runs Things In 40 Years?
• Separating The Mission From The Business
• Monetizing The Network, Not The Audience
• How Emerj Actually Makes Money
• How Enterprise Sales Actually Works
• Building Credibility From Zero
• Purpose Vs. Making Money First

Brad Weimert: BJJ National Champion, bootstrapped and sold Science of Skill. You’re now the host of the AI In Business podcast, and the founder and head of research for Emerj. Dan Fagella, welcome to the show.

Daniel Faggella: Absolutely, Brad. Glad to be here.

Brad Weimert: Forbes called you the poster boy of million-dollar one-person companies. Is the size of the company or your lifestyle more important to you?

Daniel Faggella: Man, well, I mean, that was for Science of Skill, which was an e-commerce business that I was running up until about eight or nine years ago. I mean, frankly, that business was explicitly grown and sold to get into artificial intelligence. So, I’d sort of decided by the time I got out of graduate school at 22 and a half, 23, whatever it was, that sort of the big implications of things that are smarter than people, more capable than people, would be the only thing worth focusing on. But I was running a martial arts gym in a 4,000-person town and didn’t have a computer science background. I went to UPenn for cognitive science. So, by the time I got out, I was like, “Oh, I maybe should’ve studied AI.”

So, I needed to become location-independent to move to the Bay Area, which is where I started the market research company and did the in-person interviews at LinkedIn and the big venture firms and all that when AI was new. And the e-com business was to sell it. So, why was it so lean? In part, it was like expense is low enough to have profit big enough, where if I could get three turns on it, I could have a second comma, and I could just focus on AI for three, four years without having to worry about making money.

Brad Weimert: Wow. Okay. Well, we’ll back into that story, but since you hit on AI, it’s 2026. It’s August of ’26 right now. You have spent a ton of time focusing on AI in enterprise, in particular, which is wild. How are enterprise companies approaching AI, and how can small businesses learn from that?

Daniel Faggella: Man, well, this is so different now than it would’ve been two and a half years ago. So, for a very long time, AI was still just pilot programs and tiddlywinks, and even then it was like in the Fortune 50, Fortune 100, right? It was like Goldman and like these other guys were like doing some stuff. And like everybody else was doing LinkedIn posts but wasn’t doing anything. They weren’t even doing LinkedIn posts a decade ago, but I’ve been writing about, it wasn’t a business, but writing about this stuff for 14, 15 years. Some of that’s a bigger-picture consequence of AI. But today for enterprises, it’s a lot easier to adopt. So, the process used to… It’s gone granularly from really, really hard, challenging, get your data house in order stuff.

Think about the inventory prediction, all the systems related to inventory for some $5 billion, $10 billion manufacturing company somewhere. A lot of it’s in goofy spreadsheets and whatever. Getting all that stuff in order, which was often like 18 months of hoopla. People would hire a head of AI out of Carnegie Mellon eight, nine years ago, and the guy would just sit there with nothing to do because we don’t have any data to work with. This was like literally what was happening at AIG and these other big companies. We were interviewing all these people. So, it was like tons and tons of work, and then like we think this use case might work, and the companies had no ability to stomach the experimentation that AI requires.

AI, it’s sort of probabilistic, not deterministic. And so, it’s more like R&D than it is like IT, and culturally nobody was ready for that. So, impossible data lift, really kind of not super proven use cases, and a culture change that nobody was ready for. We needed three or four years in the enterprise of everybody being like, “This isn’t like IT,” and then canceling projects or having things go nowhere or whatever. That happened for a long time. Now, a lot of those lumps have been sort of turned into learning in some of the more mature companies. Look at Global 2000, Fortune 500. And they’re now more nimbly able to say, okay, to connect the big thing for enterprise that they’re able to do now, which I think small businesses could have done years ago, but the tech wasn’t there, is sort of look at where do we want to be in two, three years? Nobody’s thinking five, 10 years anymore with the speed of things.

Where are we going to be in two, three years in terms of our operations and how we deal with customers, so outward-facing, inward-facing? What are we going to be that’ll fundamentally win in the market, market share-wise, and hitting our goals? And then from there, what capabilities do we have to build, potentially with AI, but it doesn’t have to be with AI, that are going to get us there? And then AI fits into those business strategies and fits into that future vision. That executive AI fluency took, no joke, about a decade to build. Painful. Horribly painful. Small businesses now, if they’re doing it well, so some of them are doing the same thing enterprises did, plugging and playing little tools in dark corners because they watch YouTube videos or whatever.

But with enterprises, that plugging and playing was a lot more expensive and slower, but smaller business are moving in a similar way. Smart small and midsize companies have a much smaller band of people who have to come up with that vision of product-wise, operations-wise, what are we in two to three years to fundamentally win market share? And then to say, “Okay, capability-wise, what would we need to have in place?” Well, I don’t know, this fraud detection stuff, like we’re doing some interesting tech stuff there, but that’s not going to cause us to win in the market necessarily in a fundamental way. This is, though, maybe this customer experience thing, this product development thing, okay, what can we do to be, if being fast in that component is what outlandishly is going to have us win in the years ahead, how can we sort of invest in that as a capability?

The big challenge I’ll end on here is that often initial projects are not going to have an immediate ROI. For an enterprise, it’s super hard to stomach that, but if you’re a business that still has an owner who can kind of top-down be like, “No, we’re going to plow through,” so long as they have confidence in the strategic direction, they can invest in capabilities in ways that bigger companies had a hard time doing.

Brad Weimert: So, the summary there for me, or what I heard, was there’s going to be some period of time when you have to operate in the dark to get to the light of a deliverable product. And the roadmap used to take a really long time. Now, enterprise is aware of sort of the idea of, “We know we can move quicker. Here’s a goal that we’re trying to achieve, and let’s set a plan in motion for two years from now.” And small business has the capacity now to do that and iterate much quicker.

Daniel Faggella: Yeah. I mean because if you… So, to find the person who’d be the catalyst in the enterprise, it often wouldn’t be the person it should be, who really has all the budget decisions. It would be somebody who has executive AI fluency, an understanding of AI’s tied to strategy, a representative understanding of the use cases, and sort of a general idea of what AI can do and can’t do. It’s not magic, right? There are certain categories of things it’s better at than others. The people that knew that often weren’t the people with power, small, mid-sized businesses. If the founder wants to fundamentally be like, “No, I’m going to take a long weekend and a half, and I’m going to go insanely hard on what’s possible, talk to a bunch of people, et cetera, and then layer that into my strategy exercise with my team,” they can then have something they have enough confidence to execute on way faster than the big guy.

Brad Weimert: Okay. So, what I actually heard then was that enterprise is kind of a mess when they’re talking about implementing AI, and small business can run with it.

Daniel Faggella: Yes. And now this wasn’t the case three years ago before the LLM wave because you needed way bigger volumes of data. The use cases were still, for the most part, more nascent. And there was just a requirement for you to kind of feed the beast to get it off the ground. Now, that’s completely not the case.

Brad Weimert: Now it’s built into the models, right?

Daniel Faggella: Yep. And the models themselves will let you run, yeah.

Brad Weimert: You got it. And not only is it built into the models, but the models are also specializing in areas that might serve certain verticals. So, ChatGPT now, or Anthropic, actually all of them, are saying, “Hey, we’re going to have a health-focused area of the model. We’re going to have a finance-focused area,” etcetera, etcetera, etcetera. And kind of one by one, a legal-focused area. They’re knocking out what some of the players that would be an application layer, because you can just talk to the models directly and get the info.

Daniel Faggella: Absolutely.

Brad Weimert: And so, from an implementation perspective in the business, I think what I’m hearing is like previously you had to crunch all of this data to get something relevant for your enterprise, and now it’s all there for small businesses to run with.

Daniel Faggella: Totally. I mean, you can do small representative sets of, “Oh, here’s kind of how we do contracts,” and you give it eight of them. Give it a little bit of feedback. You’re kosher. You don’t need some gigantic volume for it to interpret and understand and generate text. It’s like it’s going to be there off the jump with minimal training now.

Brad Weimert: Well, I want to get back to the AI stuff in a bit, but I want to back out because you are a national Brazilian jujitsu champion, which is terrifying. You’re also very small, so I’m sort of scared of you just naturally as a result.

Daniel Faggella: Haven’t rolled in a long time.

Brad Weimert: What mental models have you taken from beating people up on the mat into business?

Daniel Faggella: Yeah. Some people, I think, overplay the value of martial. You get a black belt, you win a certain number of tournaments. It could be like, “Well, I became disciplined.” I honestly think discipline is harder in business than it is in martial. Martial arts is fun. You’re like rolling around, you’re learning new techniques, you’re choking people. Nothing’s more fun than Brazilian jujitsu. It’s chess. It’s like better than a video game. You get a great workout too. It’s just amazing. In business, it’s like you might not like understanding a P&L, but at some point you’re going to have to learn. So, I found that I wouldn’t say it was any of those things, but there are a few transferable elements.

One of them is consistently finding who’s done what you wanted to do and just doing everything you can to learn from them. So, for me, when I was in Brazilian jujitsu, I paid for private lessons with, I mean, some of the BJJ people tuned in will know like a Caio Terra or a Robson Moura or the Mendes brothers, like people that were on the lighter weight classes who were one-time or nine-time world champions, like the best of the best, of the best. I paid to travel, and I paid for privates with those guys. I would watch their tournament videos. I didn’t watch everybody in jujitsu. Roger Gracie and these guys that are seven feet tall and 240 pounds, zero, there’s almost nothing Roger Gracie would do that’s relevant for my game at all.

Like, you’d say, “Well, everybody should just mount and cross-choke.” It’s like no, not under 150 pounds, you don’t. And so, I’m not saying Roger isn’t amazing. I’m just saying it’s like…

Brad Weimert: Not your game.

Daniel Faggella: It’s like Amazon’s an amazing business. I have an insurance agency. You know what I mean? Like, I can learn some things abstractly, but for the most part, I’m going to study the people that are in the kind of services world that I’m in. And so, that was huge for me, and I transferred that to business as well. I always had advisors who had run and grown similar businesses. Today, for the B2B media business that I have, I have advisors that have been presidents at 9-figure businesses or have sold companies for nine figures in this specific space. So, that’s transferable. That’s transferable. Another element that’s transferable is sort of like drilling and skill development.

So, my graduate schoolwork, my master’s thesis at University of Pennsylvania, which was in positive psychology under Seligman, but my focus was on skill development, skill acquisition, so like how do you learn to learn faster? Eventually, it was at UPenn that I learned about AI, because Google was partnered with UPenn for a big natural language processing project called Google Zeitgeist back then, when I was in graduate school. This is 15 years ago. Or longer than that now. So, the goal there is if there’s a particular skill you want to get better at, you have to build some reflexive mechanism to get feedback super immediately from what that thing is. So, in the case of the business for us, for jujitsu, it’s like we could do drilling and sparring from specific positions and/or immediately post-tournament do tape reviews and drill down on and double-click on positions.

I had guys back in jujitsu who were paying me for private lessons. I would say pay me half of what a normal private is. We’re going to break down my wins and losses or whatever the case may be, and we’re going to look at the situations and positions and just analyze them together. And even though this guy isn’t as experienced as me, we’re really sitting there breaking things down, comparing it to other tape. That immediate lock-in of what needed to get learned was a constant exercise. And then in business, sales is probably the fastest and most immediate example here. Whenever we do calls, we tend to have kind of a two-in-the-box strategy where we have one person who’s more the editorial voice, another person who’s more of the sales voice on a given sales call.

And we always have powwows pre-call and post-call to talk about kind of what happened, and to craft and cook up the immediate follow-up for that and to kind of see what happened. And just have it be a loop of we even have a rubric of what went well and didn’t go well for the call so that the other person riding shotgun can rubric you and be like, “Hey, man, I don’t think we did enough unpacking of needs there,” or “We went way too far on this part based on what the rubric’s all about.” So, situational skill development was another thing that transferred from business. Other than that, not a lot that immediately comes to mind.

Brad Weimert: Other than the mission-critical things that you just broke down in detail.

Daniel Faggella: But I’m saying the leg-locking people and taking people’s back and choking, I haven’t been able to do any of that in business to make money. It’d be sweet if I could because that would be…

Brad Weimert: If you’re not cooperating.

Daniel Faggella: It’s like, if I could choose between negotiate this sale to get Salesforce to pay for a big thought leadership or just be like, “Hey, why don’t we just wrestle for this?” Like, I would make so much more money. But yeah, yeah. That’s about it. That’s about it.

Brad Weimert: Well, one of the reasons that I was excited to have you on to talk is because you seem to be very deliberate in your approach to things, and I’m learning more about that right now, which is awesome. I know a number of very smart BJJ people. Also, I know a number of BJJ people that are not intellectual at all. So, it’s great to see the connection between these things for you, from your perspective. What do you think is the purpose of martial arts for you? And where I’m going with this is, did you do it deliberately to some end? Was it a game? Was it a training exercise? How did you look at it?

Daniel Faggella: Yeah, that’s great. I mean, I think it can be different things for different people. I think for most people, when I was running a gym, it might be a fun way to exercise that’s not boring and also make friends. I think, for me, it was sort of the first thing I fell in love with, so there wasn’t a lot of incredible deliberateness. I was naturally good at it. While in business, I can’t say that. I can’t say I was naturally good at finance. I can’t say I was naturally good at sales. I can’t say I was naturally good at almost anything in business. But I was pretty naturally good at jujitsu. I had a lot of fun with it. It was like a chess game. And I figured, well, when I was 18 or whatever, I got into jujitsu. It was like, “I like doing this.”

And I wasn’t going to become super wealthy in my small town, but I had people delivering pizzas or selling insurance like my friends in my late teens, early 20s, or something. And I was like, “Well, it’s going to be hard to learn how to run a business, but if I can do this and people like it, that could be cool.” So, for me, the initial impetus was, I think this is an area where I can like… I was actually most excited to farm out distinctions. Like, I was excited to learn about the grammar and the nuance and the detail of the sport and figure out what works and doesn’t work and almost kind of elevate in some level of granularity, like those discoveries. And it was like, cool, if I can make a living doing that and I love doing it, that’s cool.

Now, I discovered that there are higher and loftier goals and potentially more cosmically important things that I could pursue. But I think initially it was just the first thing I was good at and felt like, hey, if I could make a living and I can make some discoveries here, that’d be cool.

Brad Weimert: Yeah. Look, I am perpetually curious about deliberate paths for people, and it is… Part of the reason I am is because it’s tremendously uncommon, specifically early on, for people to be deliberate about anything. And almost always, people’s interest follows some level of competence. And I read a quote the other day which was, “The first step to being good at something is sucking.”

Daniel Faggella: Yeah.

Brad Weimert: And I was like, that is beautiful. Because it stops so many people, parents and kids. When you’re not good at something, you don’t get the reinforcement to push through it and push forward. But the rest of your journey seems much more structured and deliberate. So, you got into BJJ, you got excited. You opened a school?

Daniel Faggella: Yeah. I had a martial arts. And the way I paid for graduate school at University of Pennsylvania was I trained fighters, and I trained people to do Brazilian Jiu-Jitsu, yeah.

Brad Weimert: The shift from that to Science of Skill, it’s an e-com company, is an interesting one. And you opened with it a little bit, and it was more deliberate than I thought it was going to be. But tell me about the transition from that to Science of Skill. Give me kind of the size and shape of that company, and then we’ll dig in a little bit.

Daniel Faggella: Totally. So, yeah, Science of Skill, essentially, I was running my little martial arts gym in a tiny town, which I think now might have 6,000 or 7,000 people, but maybe it was 4,500 at the time. And the roof at some point collapsed in this old mill building I was renting, just this cruddy, old, random mill. In New England, you got a bunch of old buildings from 1840 or whatever, giant mill building. And by that point, I was sort of mostly through with graduate school, and I’d already come to the conclusion that ultimately, I’ve got to figure something out about what intelligence and the process of life is kind of turning into. It seems like sort of things that were pretty well relegated to living things. It’s sort of moving into other substrates, and this is way too cosmically important, and that’s…

Brad Weimert: Hold on. Why did you decide that? Why was that important to you? Look, there are lots of… Yeah. I think about the ambition of entrepreneurship quite often, and I have many conversations around the importance of having sort of a big vision and direction and something that’s pulling you versus just go do some sh*t. And so, you had some epiphany that AI was going to be a significant thing in humanity or the world, and this is what? 2013?

Daniel Faggella: Yeah, yeah. Yeah, 2012. So, no, I don’t know. It might’ve been… It’s like middle of 2011 is when this dawned on me in full, and then I started a blog to write about it six months later, 2012. Yeah, so it’s like middle of 2011 was when I was in graduate school. So, yeah, the conclusion was essentially like the bubbling process that went from sort of single cells to flatworms took a really long time, and then from flatworms to land animals took a pretty long time, and then from land animals to us was not super long. And then it seemed as though kind of there’s a phase change potentially going on in terms of the continuance of the process. There’s a process that seems to be unfolding more complexity and value. The flatworms didn’t have romantic love and enthusiasm and these other things that we can experience.

They didn’t have the sciences, etcetera. The unfolding is sort of not done. It’s not like, “Ah, well, it’s arrived at humans, and so now we’re going to kind of figure things out.” It seems to me as though symbiogenesis of different kinds of species and substrates and different kinds of the creative process will unfurl. And if that were true, that would be the most cosmically important thing. It seems like non-dead stuff, living stuff, seems to be the things that could be morally relevant. If that process is about to explode, and it’s mostly going to happen through potentially non-biological substrates, then working on policy and working on the direction of that would be a really big deal.

So, I already saw, okay, this is eventually going to be a big deal at the United Nations, the OECD, these big intergovernmentals, and now I’ve been involved in those organizations for seven years or so. But yeah, that essentially was what dawned on me. It was like, this is cosmically important. I don’t know how I’m going to make money doing it, but I’m going to start blogging and writing about it nonstop.

Brad Weimert: So, you did lean in the direct… So, you’re in the middle of running a jujitsu school, which was your expertise at the time.

Daniel Faggella: Absolutely.

Brad Weimert: You’d just finished your master’s or gone through that, where you were looking at psychology of humanity and learning.

Daniel Faggella: Yep, skill development, skill acquisition, yeah.

Brad Weimert: Yep. That’s what I call learning.

Daniel Faggella: No, it’s all good. Yeah, yeah. No, no, totally.

Brad Weimert: And you had some shift, which was, “This is the direction, this is what I want to invest my life in,” and that is sort of the pull that I talk about most people not finding.

Daniel Faggella: Yeah.

Brad Weimert: So, enter Science of Skill.

Daniel Faggella: Yeah, totally. So, basically, roof collapses. I’ve already been kind of writing, blogging, and doing very early interviews. It was mostly with futurists, and there were not a lot of AI startups back then, and the ones that were willing to reply to me were total rando companies doing really weird stuff. But I was having conversations with weirdos that weren’t even really getting published online. I just occasionally would write an article about these conversations. And yeah, the roof collapsed in the martial arts gym. And I sort of realized, well, being hampered by the number of people in this geo region, and particularly this building, and the amount of money in my bank account, which is like with the grad school debt, negative 40-something grand or whatever, I should probably have other ways of funding the goal.

And if I want to be location independent to be able to live in places where I could do this ardently, I would want a business that would be location independent, too. So, the only appreciable skill that I had at that time, before this great realization of sort of the unfurling process of life and kind of influencing that being the big, big thing, was winning competitions and choking people and stuff. So, I started filming my own classes, and I would film my seminars. So, people would pay me to do seminars around different kinds of technique areas, and I’d film that stuff. And there was a video. So, there’s this guy, Pat Walsh. He’s a UFC fighter. I think he’s a D1 wrestler. He’s about 90 pounds bigger than me.

And there was a match at a no-gi Brazilian Jiu-Jitsu competition in 2011 where I did an absolute division, where I decided I was going to fight the big guys. I’ve done a couple absolute divisions. I medaled a couple times in absolute, and when you walk at a buck 34, people don’t expect you to do an absolute, but sometimes people do.

Brad Weimert: And just for clarity for the people that don’t know what’s going on right now. So, you said no-gi, and it sounded like a piece of food, but no uniform.

Daniel Faggella: Yeah, no uniform. Yeah, yeah. But so…

Brad Weimert: No, that’s good. And the second one is absolute, meaning there are no weight classes.

Daniel Faggella: No weight classes, yeah. So, everybody’s in there.

Brad Weimert: Which is crazy …

Daniel Faggella: So, it was mostly very large dudes, yeah. So, this guy, Pat Walsh, and I… No. Some of it was luck, some of it was skill. I think if I rolled with him 10 times, I think he would’ve crushed me at least eight of those times. But in this time, it didn’t work like that. I did some immediate inversion, like we were standing on the feet. I was kind of pretending like I was going to wrestle him. On YouTube, it’s Dan Faggella vs The Giant. And so, it’s me against this, Pat Walsh, who ended up being a UFC fighter, very good wrestler. And you can hear his ankle break in like 12 seconds.

Brad Weimert: Oh my God.

Daniel Faggella: And so, that video for the day, right, the 2011, not a lot of YouTube. It’s not like, there weren’t like PewDiePie didn’t exist, okay? So, like a fistful of views was like a big deal, but that video I forget how many views it has. Now, a reasonable number. That kind of popped off and I put like something in the description at the time, and I was like, “Hey, if you want to learn more techniques, like go here.” And there was like a bunch of people filled it out. And then I came up with, I filmed a couple of seminars specifically on how I beat bigger guys, and I launched it. And I think I made like $3,500 or something. Now, that wasn’t a ton of money even then, but it was like, well, I don’t need to be anywhere specifically to do this, and if I had more than 400 people on an email list, I think I could make more than this. And so, that was the hypothesis.

And so, between the roof collapsing and between that video with Pat Walsh, which was a very fortunate absolute division medal, I had enough location-dependent revenue to say, okay. So, then nights and weekends I started saying, I’m going to get up to Boston or to San Francisco, and I’m going to be able to sell this martial arts gym. And I’m going to have an even bigger revenue stream that doesn’t depend on a tiny town with a crappy old building. And that’s exactly what I did. But the whole goal, the entire way, and I’ve been on record from the very beginnings of that business saying it, the whole goal was like this thing will be sold and I will be working on AI full time for the rest of my life. And that was the purpose of that business.

Brad Weimert: Crazy. So, there are tons of creators listening and infopreneurs listening that are like, “Well, yeah, no sh*t.” Of course, you can sell the information and not be location-dependent at all. But I think that one of the things that I’m always looking for are kind of transferable skills and transferable implementation. So, great, when you’re brand new and at 2011, you don’t have the platforms to monetize through. Facebook was four years in from being open to the public or something like that. YouTube wasn’t YouTube, right? YouTube really has only established itself in the last 10, 12 years, right? So, this is pre-YouTube. LinkedIn didn’t have any content following. Instagram didn’t really exist, if it did at all.

So, you embarked on this journey to sell. The reason I stopped to talk about that is because when people are listening to this now, the challenge that I would have for anybody is to think: how do you apply skill sets or lessons to today’s world? And so, I guess my question for you then from that perspective is, and I want to get back to the story, but how would you execute or think about executing for somebody running a studio today, or a brick-and-mortar company today that wants to have a similar trajectory or buy themself out of the position?

Daniel Faggella: Yeah. I mean, I think, I really have not even thought about what I would do today versus back then. I was so…

Brad Weimert: I’d probably do the same thing. It’d just be easier today.

Daniel Faggella: I think it’d be way easier. I mean, I have an AWeber account.

Brad Weimert: Oh, yeah. Tough.

Daniel Faggella: And like if you remember them back in the day.

Brad Weimert: Oh, yeah.

Daniel Faggella: And eventually got Infusionsoft a couple years in or whatever. But yeah, I mean, the thing that I had done is I had people who thought I was specifically good at at least one specific thing. So, it wasn’t like, “I am a guy who teaches martial arts.” Like, I don’t know. But if it’s like, “I weigh 133 pounds.” “I have some competitions where I choke real big dudes and break their stuff.” And there were a lot of people who are not going to win in jujitsu. So, a lot of the people that bought my stuff, I came to learn. So, one of the things I did very early on is anybody that bought my stuff, I’d try to find a way to get on the phone with them. And I learned very early on it was early-to-mid-40s dudes. A lot of times it was Asian and white dudes. I don’t know why.

But a lot of them weren’t as small as I am, but they weren’t going to win by strength, and they knew it. So, they weren’t going to beefcake their way to submission. So, they were going to have to leverage speed or technique. So, they were the ones that saw and respected that more so than just smaller competitors. I thought, “Okay, well, there’s only going to be so many 140-pound guys that want to win absolute divisions.” But it ended up being people that just resonated with that. So, do you have repute for at least some particular thing, and can you figure out maybe who wants to buy that? So, for me, it was beating bigger opponents. Some of the early DVD releases I did were David versus Goliath and things like that.

I did big seminars, you know, three-hour seminar on just the stuff that I would use to beat bigger opponents in competition and on the mat. And so, I think, do you have a specialty? Potentially, do you have a repute for it, or can you establish one? And is there a market? And initially, I had to figure that out. I had to put out the AWeber thing and see who responded and get them on the phone, and then learn, okay, guys who only train two, three times a week but who know they aren’t going to win by strength, they’re willing to just pay for stuff. And I was burning individual DVDs on my laptop for these guys.

Brad Weimert: Crazy. Two things. AWeber was an old email marketing platform for anybody that’s curious. Second, what you said is basically be very good at something and then you can find the audience for it. But then you also said, and I think this is an important caveat or become good at it, right? Or find a way to be seen as good at it. And I think that that’s a really important point from a marketing perspective because there are a lot of things that you can do, and this is what… There are tons of small businesses and big ones that do sort of marketing theater to get attention. And you can do that to say, “Hey, I did this crazy sh*t. Pay attention to me.” And now the world is full of YouTube people that do crazy sh*t for the sake of attention.

But that was essentially what happened with you was you were very good, and you had a match where you beat somebody up that was big, yeah, and moved with it. I like this. So, I know you because you were a client of Easy Pay Direct for Science of Skill.

Daniel Faggella: Yeah, Science of Skill back in the day. Old days, man. Way back.

Brad Weimert: That’s right, man. That’s right. And you sold it then. So, I want to fast-forward through this, and we’ll talk more about AI, but a couple of curious things as I dug into this was you didn’t have any full-time employees.

Daniel Faggella: When we sold, I had by the time… So, we crossed $1M, maybe $1.3M with zero full-time employees. And then by the time we sold it, I had one full-time, one part-time, and then contractors. And by the time we sold it, I think we did $2 million a year or $2.2 million or something like that. I think our average growth rate, that was kind of fast with that business. I think it was literally 105% a year on average for the three or four years I ran it until we sold it and got Inc 5000.

Brad Weimert: And I read something about an affiliate model powering it. Is that accurate?

Daniel Faggella: Yeah, it’s true. So, early on, I started interviewing other people that had martial arts-related products. We started selling to the broader self-defense ecosystem, because jujitsu back then was small. Now they have BJJ Fanatics and all this stuff, and then gajillions of people buy programs. Back then, jujitsu was a pretty small market. But I realized that if we could have a broader set of offerings around self-defense, and so I started paying Marine Corps scout snipers and SWAT team bladed weapon defense trainer guys very specific skill sets in their own respective area who were working with military or law enforcement on very, very particular things, and I would have them record programs and then sell those programs. We eventually turned that into a subscription. Yeah, like I had to, I guess, open up into that broader space. But where did you want me to poke in with that?

Brad Weimert: Margin. So, you had the vast majority of your traffic or your, I don’t know about the majority of your traffic, but you were paying out 70%, 80% as an affiliate or to affiliates. How did you maintain margin through that?

Daniel Faggella: I actually think we had a loss lead on that.

Brad Weimert: Okay.

Daniel Faggella: I think it was, yeah, we were paying out, I mean, it was like $50 programs. We were paying out like, I think there were some times we were paying 85, sometimes we were paying 105, maybe sometimes dependent on the affiliate. But we knew we had a certain amount of stick rate, and so we would loss lead on it. But we knew that sort of it would come out in the wash. And in general, that business, the year I sold it, I think it was like somewhere between… If I take out my own what I paid myself, I think it was probably 11% margin. If I include my own salary and everything and throw it all at the bottom and say, “I’m the business owner, it’s mine,” maybe it would’ve been 15%, 16% the year we sold it, 2 million to the top line.

So, it wasn’t super strong margins, but it’s hard to have super beefy margins when you’re always twice as big as you were the same time last year. It’s like you’re paying for that growth. Like you were saying with e-commerce businesses before we started recording here, you were saying a lot of time they’re shoveling it in. We kind of were. Yeah.

Brad Weimert: Well, that’s great. So, the lessons that I got from that, the first one that I think is incredibly relevant to literally any business owner is what are the tangential services around you that could feed you? And then the second was, don’t be afraid to “overpay them” to drive the traffic to you from them. So, you incentivized a bunch of these other people that were teaching skills that you thought were relevant to the BJJ audience and vice versa, and then over-incentivizing them to make sure that they would promote you.

Daniel Faggella: Yeah, that’s exactly it. Yeah. And eventually we did build the confidence and the margin to start paying for bigger email lists of gun owners or survivalists or other things like that. And those guys, God, they have unbearably large email lists. Eventually, that became a pretty big driver, but it was the first three whole years, two and a half whole years, was just affiliate and our own minuscule organic efforts, yeah.

Brad Weimert: So, you answered this ahead of time, but you sold it really quickly. And also, you said you were at 2 million or so when you sold it, 2.2, I think. Why sell it then? Were you in a hurry to transition? Did you think you couldn’t grow it bigger? What was the decision around that?

Daniel Faggella: Yeah. Well, I mean, I started the business explicitly. And again, I’m on record while I’m still growing it saying, like, “I’m going to get into AI full-time. I’m location independent now. I’m going to have enough where I can get into AI and figure out what to do with that.” And back then, I didn’t even know what the model would be for AI at all. So, while I was growing this business, and while I was selling my martial arts gym, I was doing these interviews on the side. I was doing some TEDx talks about sort of the longer-term future of AI. There’s like ancient TEDxs about that kind of stuff, and really just immersing myself as much as I could. I’d moved to Boston by that time and started interviewing people in the media lab and getting to know startup founders and just getting into what the tech can do and where it’s going, big picture.

So, the reason I sold it was like, okay, if I stuck with this for X number of years, I obviously could’ve sold it for a lot more. But I think just purely direct response marketing wasn’t that interesting or engaging for me, frankly. It just wasn’t my favorite kind of business. There were parts about it that I liked, but I wasn’t doing jujitsu anymore, and it was really about driving the revenue forward. But also, I knew I’d have to hurl myself into this space because I don’t have a computer science background. I don’t have anything. So, if I wanted to eventually be in the room at, you know, I was at UN headquarters last September when they were launching kind of AI red lines. Yoshua Bengio, these big AI research folks, are in there presenting.

These people who now I’ve interviewed, I’ve had at least some level of interaction with Bengio for the last decade and a half. I knew I’d have to get into it. Like, I have to be hardcore immersed. So, if I can have a second comma, and then even after taxes, with what I have in savings, I’ll be able to sit and burn on this for a while, and I’ll be able to do editorial. I’ll be able to build my network. I’ll move to San Francisco. I’ll talk to all the venture firms. I’ll talk to the people running AI at Baidu and LinkedIn and whatever. I interviewed Ilya Sutskever 12 years ago or something at LinkedIn headquarters for some side event when OpenAI was this old.

I wanted to be in, deep in, super early. And so, that was it, man. It’s like, I’m going to sell this, and I will work 85 hours a week on only one thing, and that’s what I wanted to do. The whole e-commerce business was only for that purpose. So, yeah, that was pretty much it.

Brad Weimert: Yeah, I love that. I am certainly trapped in a perpetual growth mode at the moment. And I’ve gone through waves of motivation where it’s like, “Hey, I’m so far past the initial goal.” And then there’s another goal, and then I move the goalpost again, then I move it again. And when I say I go through waves of motivation, sometimes I find myself thinking, “Why am I doing this right now?” Like, I don’t need to be working. I don’t need to be… I could be doing something else entirely. And then I get caught in, right now, I’m caught very much in the wave of agentic commerce and the motivation behind sort of like where it’s going. And it’s a completely different chapter of, certainly, of commerce, but of humanity at large.

But that wasn’t deliberate. I just found myself here, and I have a new goal now. So, I love hearing the journey of executing this to create capital so that you can deploy capital for the investors in learning and in life, and that was the next necessary chapter. You started Emerj AI Research, which started as something else.

Daniel Faggella: It started as TechEmergence originally, the URL, yeah.

Brad Weimert: Yep. And then Emerj AI in 2017, I think. Is that right?

Daniel Faggella: Yeah, TechEmergence was like a personal blog, a little bit earlier than that, and then even Emerj wasn’t really kind of a business until relatively close to COVID. But yeah, I would say 2017 is like when, on the books, it was still a business, but that was also when I first started getting into the intergovernmental world, and I was mostly just focused on building my network and stuff, so I wasn’t really businessing in 2017. But, yeah, technically I think that’s pretty much when Emerj was like established.

Brad Weimert: You came from BJJ, selling information to people, having a school. Why did you go straight into enterprise? So, it’s a really interesting proposition to think about, “Hey, I’m going to look at consumers and sell information to consumers,” and then shift entirely and say, “I’m going to be an educational platform for enterprise companies.”

Daniel Faggella: Yeah. Well, this is not advisable for people that want to just make money. So, basically, here’s the mandate for me. It’s like I was really interested in building. I need resources, which would be funds. So, I need to be doing something people are willing to pay for, and as a consequence, I need to build a Rolodex in the AI policy and AI business world, as deep and powerful a Rolodex as I can. That’s number one. Number two, I need to build a repute around research. I need to genuinely be able to learn and communicate more and better things about where this tech is going to be able to get on the map to eventually be able to get called on by big banks or pharma companies to give talks, or to speak at the United Nations or get involved in the OECD, or speak for the World Bank, or whatever the case may be.

So, I needed Rolodex, and I needed repute based on research. So, it’s like I want to be really close to this tech and not fake close to this tech, like I’m just googling it. I literally want to be able to talk to the smartest people, end of story. And then it was, “Well, geez, how the hell am I going to get paid?” And there’s no part of me that knew when I sold my e-commerce business, “Oh, you know what it’ll be? It’ll be this market research sort of like kind of thought leadership, demand gen, go-to-market model for big tech and enterprise AI.” I didn’t quite know that. I just knew that, like, up here is where most of the money’s getting deployed and where the action is happening. The small biz stuff like that wasn’t there for more than a decade from when I got started.

It wasn’t even there. So, everything interesting was happening in the academic halls of power. There were a handful of policy people thinking about it. I needed to know them. And then there were bigger companies, and there were a handful of pretty exciting startups, like early on, just a handful. So, I just started working with them, and it took me a while to figure out who’s willing to pay me for what. And what I eventually learned, I had no idea. I thought the business model might be like we would rank AI startups, and then if people had specific problems they could solve, we could pair them up or something. I thought like maybe eventually there’d be consumer AI applications that we could kind of cover, like personal productivity stuff, or I didn’t know exactly.

But as it turned out, the way our business developed, the thing people ended up valuing was like eventually we started being able to interview people at Sanofi and Wells Fargo and these giant corporations, and what people ended up valuing was like, “Ooh, I want to be in front of those kind of people. Like, what does it cost to be on your podcast?” I remember the first couple emails that happened like that, and like the first couple thousand bucks or something that I made. And it was like, okay, that’s what people are interested in. And then that evolved quite substantially, and now of course, our sponsors are a totally different deal.  It’s NVIDIA and Google Cloud and the biggest data centers you can think of and whatever else.

We would play a lot in those bigger spaces with the bigger players. But initially it was just smaller AI startups. But it was like, it was happenstance. I knew what I wanted, and to be honest, man, it’s not good business advice to like go in and say, “I’m going to get this for my life purpose, and I hope a business model clusters around it,” because that was painful. But we eventually figured it out. But like that was what I went in to do.

Brad Weimert: Yeah, I think that is the key to that, though, is that you weren’t targeting a business. You were targeting, it sounds like, education and connection.

Daniel Faggella: A grandiose, very specific life mission around the post-human trajectory of intelligence and how that’s going to tie to eventually global policy. So, like it’s a very specific life vision. It’s like ornate and specific and so like very, very particular from 15 years ago.

Brad Weimert: Yeah, I want to go back to the business model, but I want to click on that too because to what end? So, you had a desire to educate, to connect, to be involved, and you just planted a seed for me, which was you thought that it was going to start to interact with or inform global policy. Who cares? Did you want to change it? Do you want to be in politics? Do you want to be at the table? What’s the point for you?

Daniel Faggella: No, not even. The to what end, so danfaggella.com/cause, if people are like, “What’s this guy all about?” It’s always been public. I ain’t hiding nothing. Danfigella.com/cause. What’s his cause? Why does he work?

Brad Weimert: It’s deep. Go look at it.

Daniel Faggella: Well, it’s out there. Check it out. So, the big picture is, like the to what end is presumably I’m going to perish anyway.

Brad Weimert: Probably.

Daniel Faggella: So, it seems to me that the living process is, you could think of it like a flame, right? Started like very small, little flickers as like algae or something below algae. And then eventually, like we got a pretty good blaze going on. We got a biosphere, which humans are kind of putting a hurting to, but we got a good biosphere here, and we got a technosphere on top of it. All of this power and experience and access to nature and understanding of the world has bubbled up from this living process. If I’m going to perish anyway, discerning how to steward forward that process, in other words, how do we ensure that what we’re building in terms of AI is actually going to be not just like some brute optimizer that’s better at military stuff than us and can fight and battle and whatever, which is, we got a little bit of a military arms race with China right now.

But really, how do we ensure that maybe it’s even sentient and that maybe it is self-transcending in the evolutionary sense in the same way that biology is? So, if eventually this stuff starts to kind of take over, and I think kind of whether we like it or not, we’re going to be pushing up against some very hard questions in the coming decade. Is it going to carry forward the project of which we are a part? I go back enough grandmothers for you. Somebody didn’t have a spine. Somebody didn’t have a spine. No spine. Never mind no opposable thumbs, right? And enough grandmothers before that, you get to a single cell. And so, there’s a project we’re part of. People say, “I want to make the world a better place,” they generally think for their kids or their grandkids. I think there’s a cosmic version of that.

Brad Weimert: Yeah. You know, I applaud you for caring.

Daniel Faggella: And I’m not saying you have to.

Brad Weimert: No, no. Like, I say that sort of in jest, but not really. I think that outside of the business side of things, I think there’s an interesting human consideration for survival and how we approach it and how we look at it. There seems to be some desire for people to care about future generations. And maybe it is just that we’re thinking about our kids or our kids’ kids. Maybe that’s where it comes from. Maybe there’s this innate driving thing. But then you look at the survival of the species or the planet or whatever we can see beyond that, which at least our generation doesn’t know yet.

Daniel Faggella: No, no.

Brad Weimert: But you’re talking about sort of many, many, many generations into the future, hopefully. Or are you talking about 20 years from now?

Daniel Faggella: I’m thinking in the next 40 years I don’t expect Homo sapiens to be running the show, either drastically augmented hominids, but primarily probably minds in other substrates. Now, the big question is: before that control is gone, and I don’t think we’re going to tangibly relinquish it, I think it will be gradually relinquished, just as the mammoths didn’t say, “Give humans the earth,” right? It just so happened that we started running the show. It just so happened. So, there will be a just so happening.

Brad Weimert: They didn’t kill us fast enough.

Daniel Faggella: The things that are capable of persisting. And I don’t think it needs to be malice. They don’t have to want to kill people. They just might be better at using atoms and energy. So, like you are not any of the atoms that make you up. There’s a memorized pattern. Like your cells are just spitting out atoms and pulling in energy and pulling in matter. Like matter and energy are spinning out of a pattern called you. And we don’t really know how that works yet, and I think we should know a lot more before we relinquish control to AI. But like that patterning of what the living process does, things that are good at that tend to be able to persist and transform, and they participate in this greater process of change. They’ll be just better at the process of change than we are.

So, the big question for me is, if it’s going to be within a generation or two, which I heavily personally suspect it is, there’s a danfaggella.com/short. It’s like short timelines, and like why I kind of think it’s worth wrestling with. And some of the founding fathers of the AI field are now on the same page, Hinton, Bengio. But before that sort of loss of control stuff occurs, do we even have a tiny amount of confidence that that stuff that might be running the show more than we, in other words, we won’t have that much volitional influence on what’s after that, is that stuff that’s running the show going to be capable of the blossoming and the blooming beyond us and what we now know as we are a blossoming and blooming beyond the fish with legs?

So, that’s, I think, the pressing question. So, I don’t see this as 100 human generations. I suspect it might be potentially within our lifetimes when we’ll see the loss of control occur. Can we ensure that the successor be worthy? Can we understand the living process and consciousness well enough to ensure it’s instantiated in these substrates through merger and other means before what I think to be potentially an inevitable loss of control occurs? I know we’re steering outside of business. I don’t want to take you there, but if you want to know, like, why does he work? It’s like, it’s for that.

Brad Weimert: Yeah. Well, I do want to get back to business, but I want to click on that a little bit further because it’s tempting. And so, you kept saying, what do we want to create? Do you think that we get to pick what we create at this point?

Daniel Faggella: All that we get to do is lightly influence the trajectory of what we build and what we become. Become would be brain-computer interface, regenerative medicine, bioengineering kind of stuff, neurotech. Build would be mostly, right now, AGI. We can lightly influence the trajectory of those two things, our becoming and our building, and I think those two are going to mesh a lot. There’s going to be a lot of meshing. We can lightly influence the trajectory. It’s all we got. So, it’s sort of like a president who become somebody who becomes president. It’s like, well, are you going to make everybody butter their toast with their left hand? Like, you can’t literally control things.

But maybe there’s a knocking in one direction or another that would have knock-on effects to what carries on beyond it, and I think that’s as much as we can do. I don’t think we get to pick. I think whatever will become will unfold and will become and will be wholly unpredictable. But if we can at least say, “God, that would be a really good way to optimize for an unconscious military crusher,” and if we’re racing towards that maybe if we do two ticks away from that and have a higher chance of this thing being capable of evolution and of sentience, or maybe we hold back on it until we level up our own brains well enough to understand it. If even some of that scaffolding can occur, maybe we’ll have a percentage of a single percent of a shot of lightly influencing the trajectory in what would potentially be a cosmically better one for the living process, and it would seem worth it. So, I’m not of the belief that I have any control here.

Brad Weimert: So, you’ve elected to spend your time thinking about this, looking at the future. These are big questions, right? And your monetization model is enterprise.

Daniel Faggella: Totally not this, yeah.

Brad Weimert: Well, yeah. But that’s where I’m going, right? It’s like if this is what you talk about and think about, and you do so, presumably, with some of the people that are in the space deeply that are thinking about it, does enterprise care?

Daniel Faggella: No. So, I told you what I was looking to do. I need a Rolodex because I’m from a 4,000-person town, and I know how to do heel hooks and arm bars. I don’t have credibility outside of that. I went to a nice school, but it was cognitive science. I didn’t go to AI. I didn’t go to Carnegie Mellon for an AI degree. So, I need a Rolodex. And the best way to learn is from the people that are the best at it. I did learn that in martial arts. And I need a repute built on genuine research insight. I also need to eat food. That’s the resources part. I got those four Rs going on. So, the eating food part was, okay, what parts of what I write about will people potentially pay for? And as it turns out, an area that for me has been really useful in understanding the big implications of AI has been, okay, boots on the ground, the people spending the most on it, what kind of difference is it making?

So, that is part of the bigger cosmic picture. It’s just the super near term. So, I separate those food groups. So, I have a whole podcast called The Trajectory where you’ll have the big names in AI, people at the DeepMinds and whatever else of the world, and the big bio and neuro researchers. But then AI in Business is the main podcast at Emerj. We have three other AI in Business podcasts: infrastructure, financial services, life sciences, tons and tons of audio media. That stuff is really focused on today and in the near term: what is AI capable of to solve problems? So, for business leaders, I learned very early on, and we built a very rigorous editorial set of guidelines around P&L impact, workflow impact.

That means top-line, bottom-line risk, or how does my employees’ or my customers’ lives look different in terms of what they do? So, that’s workflow impact or P&L impact. We don’t write about anything else. So, we go super deep on specifically that, and that’s what enterprise leaders want. They actually don’t want to learn to write code. The people that cut checks are not the ones writing the linear algebra to make things work. They’re not really doing that. They care about the P&L and the workflow impact. So, I focused on that. I learned very, very deeply where AI is making impacts: in customer experience, in fraud detection, in inventory prediction, drug development, in these big areas that are trillion-dollar problems. And that’s what I publish on. That’s what I attract an audience in. And that’s what Emerj is today. And so, we can potentially get into that business model because, yeah.

Brad Weimert: Yeah, I want to. Well, one of the things I want to talk about with that, you just said you had, I think, four different podcasts that are vertical or verticalized.

Daniel Faggella: Yes. Yes.

Brad Weimert: And that’s interesting anyway that you have them narrowed in that way. You said Enterprise cares about P&L and workflow. The starting point to this, I think, is most people that look at a business model around information and education go broad, and they look at how you monetize an audience. And you seem to have moved in the direction of not monetizing an audience but monetizing powerful people. What’s the difference for you, and how does the business model change?

Daniel Faggella: So, this was an early distinction. So, as I said, I have a grand all-consuming hill that I will die on. The business is a subset of the grand all-consuming hill which I will perish on, the grand organizing moral purpose. I discovered early on when I figured out what are people willing to pay for, and I started looking at, well, I guess it could be a lot of business models. And when you start a business, this is what happens sometimes. You’re like, “I could go this way. I could go this way,” right? What I learned, and this was… Some of my early insights turned out to not be insights, and I moved past them. This one actually stuck from going back almost a decade now.

All these business models are predicated on if we have robust access to the people spending money on and making important decisions about AI in the biggest companies. Like, if we go events, if we go market research, if we go demand gen, if we go … Whatever we do, it’s actually how well anchored we are in that Rolodex. Now, back in 2017-18, before, again, I was mostly doing my intergovernmental stuff, building those relationships. Wasn’t even really growing the revenue at that time. But back in those days, these heads of AI, VPs of AI, nobody wanted to talk to them because they didn’t control any budget. You’d work at some giant insurance company and have 150K POC to do some silly stuff in some dark corner. Nobody cares about you.

Deloitte’s not paying millions to reach you. Microsoft’s not paying millions to reach you. Big Tech was just talking to Big Tech about AI. They weren’t talking to legacy enterprise. But I thought, “Well, I think that’s going to change.” And so, the bet was, if I have heads of AI and infra at all these companies before anybody cares about them, and nobody else is building an audience, try starting an AI podcast now. Impossible. NVIDIA started four or five years after us with their own podcast. We’re still twice their listenership. We were in there when nobody was in there. So, now it’s a million downloads a year. But again, we’re not mostly monetizing the bulk of how many people download.

We’ve just got the direct connections with those heads of AI in that area. So, the early insight was network is going to come first, and then the optionality for whatever future business model we want, we can do it so long as we build the network. And the cool thing about podcasts was we could interview people and just say, “Hey, if we can call upon you for other things for these expertise areas, we’d love to stay in touch.” And then they’re in the Rolodex. And then if we have other interesting themes, we can pull them in. And as it turns out, a guy at J&J working on drug development, there’s a lot of companies who’d pay 20, 40, sometimes much, much more than that to be published directly next to that guy speaking about the future of drug development. Because these are companies that are selling things where if Pfizer buys from them, it’s like $4 million a year.

Brad Weimert: Yeah. I think the transferable lesson for tons of businesses is: build a relationship with a person that has influence in your world. And very often it’s not the one that is getting the attention in the moment. So, this is: know people’s assistant, know their spouse, know the person running the event, actually running it, not the person speaking on stage. It’s know, in this case, the director of XYZ of AI for a company. Right? I think that’s an awesome, awesome lesson for people.

Daniel Faggella: Well, skating ahead of the puck a little bit, too. So, it’s know the people in power who might not be obvious. But for me it’s like, if I hold my breath for five years and then inhale again and then look up, are all these heads of AI and infra going to have more money to spend or less? A lot more. And so, my suspicion way back before there was any money in the space was, I bet if we had a Rollo of them when they’re spending seven figures a pop, everybody’s going to want to reach them. And that ended up being right.

Brad Weimert: Yeah, no, that’s great. That’s not a practical business lesson for most people. You know what I mean?

Daniel Faggella: I’m with you there.

Brad Weimert: So, I was trying to think about what the lowest common denominator there was, which is building the relationships with the others. But if you can think of a way to tie that to other small businesses…

Daniel Faggella: Yeah, yeah, yeah. Let’s think here.

Brad Weimert: Because people don’t want to hold their fu*king breath for five years, bro.

Daniel Faggella: No, no, no. I’m with you, I’m with you. I don’t recommend it. This life purpose thing…

Brad Weimert: No. This is a very interesting use case that 99% of entrepreneurs are not willing to follow or don’t want to.

Daniel Faggella: No, no, totally. I guess the way I would think about it is even like more banal, so I sometimes now will do some speaking in the B2B media world. And there are people in all kinds of niches like people that run events and magazines in every niche you’ve never heard of. Like, maintenance for hospitals, like janitorial supplies for hospitals. There are magazines and events for that that make eight figures a year easy and have been doing it for 30 years strong. In all of those spaces, there are areas of people where you’re like, “Yeah, these operations heads, they’re actually increasingly the ones that are pulling the trigger on equipment purchases. If we own them, in three to five years, they’re going to be controlling more of the money pie.” So, even for them, a slight shift towards let’s have more of those relationships moving forward could be useful. So, I think that is transferable in more of an immediate way in that regard.

Brad Weimert: Yeah, love that. Pay attention to where your marketing budget’s going and who you’re focused on. And who you think your avatar is. How do you monetize your company? Yeah. Let’s start there.

Daniel Faggella: Cool. So, the model we eventually settled on, so there’s a lot of optionality for events, research. I’ve had all kinds of advisors recommend certain things. But I think my closest advisors kind of agree that right now make hay while the sun is shining in the way that we can. Physical events, there’s a lot of risk. There’s a lot of budget that those consume. We’ve got an audio platform. SEO is getting decimated, and audio is not. So, the business hypothesis is that horse’s mouth insight will be valuable for as long as humans are making decisions. If I could tell you, if you work in defense, and I could say, “I have a simulation of what the head of AI at Raytheon would say to these five questions,” or I say, “I just talked to him for 40 minutes. Do you want to listen to it?” You have to pick the second one if you work in defense, right? You have to. So, direct horse’s mouth insight will be valuable even when content is unlimited in all directions.

So, what we do is we build big audiences of people, and often very specific audience of people in drug development, fraud detection in finance, inventory prediction, retail, manufacturing, different pockets, and then general AI and infra titles. We publish a lot of editorial content about that. But what we sell is, let’s just take a company like, I don’t know, we’ve done a bunch of work with Deloitte, right? So, Deloitte wants to sell AI-related consulting into the biggest pharma companies in the world. They’ll work with us to be part of a podcast series that might also weave in people from our own Rolodex, connections that they kind of want to be… They want to be known to these people, but also they want to be seen as appear to these people, and they want the same listener that listens to head of AI at Pfizer to listen to their guy next about the same theme, to build on the same topics.

And so, we’re looking at spaces where individual transactions are seven, eight figures, and we’re saying, “Cool.” The mandate for change, so in AI, there’s a mandate for change. It’s like you’re making a big move when you start to leverage AI for drug development. Like, you’re going to be fundamentally changing some systems here. If that mandate for change can go in the mouth of a buyer, if J&J can talk about what they’re doing to wake up the value of data, then if you follow on with J&J as part of a bundled series, and then we can take 140, 150 people, or in some cases for some programs, 400-something people who meet your ideal ICP, who’ve engaged on some level with that content, and then landed on a landing page, that’s a big deal.

Most of our business, though, is not paying for leads. We don’t think that’s a sustainable model. Leads is part of the mix for 50% of our campaigns. The other 50%, it’s not. We’re also generally not having anybody pay for how many impressions are we getting? It’s literally, are we on stage with the big logos and the big titles that will add massive validity to a message where, if it’s on the right desk, it’s millions. Plural.

Brad Weimert: Crazy.

Daniel Faggella: Plural. And so, using our network to integrate into knitted editorial series featuring our sponsors, which at this point, again, have included NVIDIA and all the big guys. But the bulk of our sponsors are probably companies that have raised, let’s say, 200 million, so they’re in that range. 200 to 500 million, that’s kind of like the average sponsor for us. And these guys will sell some amazing technology to do customer experience work in the back of big banks, and they can’t get any of these customers to talk about it ever. Ever. Like, they cannot. And so, what we’ll do is we’ll say, “Well, we have somebody who might not be using your product, but they’re already waking up AI in a massive way across the call centers at American Express.

We could have them come on, talk about the paradigm shift they see in the next two years, have you come on and talk specifically about this chat voice context thing that you guys are working on. We get a hell of a lot of relevant people to listen to this.” And that association of logos being behind the velvet rope, for us, that’s sustainable. Because whether audience numbers, Apple starts tracking things, they go up or down, are you getting the association and that sales enablement asset that’s going to carry your narrative in a way where it could support a seven-figure sale, yes or no? That’s what we want to sell. We don’t want impressions or leads to be the business, and it’s not. It’s network.

Brad Weimert: That’s crazy. I love that. That’s a super interesting model and also not what I was thinking. Do you do raw sponsorships as well, or are they…

Daniel Faggella: Pre-roll, post-roll, we do. We have really strict editorial rules. So, when people pay to be on the episode, we also have strict editorial rules. Like, you can’t pitch your product. We’re kind of going to define the outline for the most part. Like, you’ll have some buy-in, and you can share it. But there are structured formats that are deliberately entirely educational about ROI and workflow impact, because we know that’s what the audience likes. And then if you want to do pre-roll, post-roll, we’ll never be like, “You know, we use Google Gemini every day.” No way. Like, objectivity is the whole thing. Like, we have to grill everybody, and we have to get to the meat and potatoes of where is it working, where is it not working, what should people think about in terms of its capabilities, its weaknesses?

We’re always going to ask for the range of questions. So, we do a little bit of pre- and post-roll. In fact, Google Cloud has done pre- and post-roll stuff with us, so have Rubrik and some of these other big players. We’ve had billion, trillion-dollar players doing some of that. 96% of the business is more of direct native episodes and articles and sometimes webinars. But almost all of it involves that association with those big logos and validating that narrative and being part of a broader conversation next to the people you wish you were selling to, like head of drug development at Sanofi.

Brad Weimert: Tell me about the sales process for this. And I want to hit on that because the monetization model’s super interesting. Selling to enterprise sucks. I mean, maybe it doesn’t. Maybe you can tell me something different. But enterprise sales, I fundamentally have stayed away from it because the sales process is just long and drawn out and is like a whole thing in my head. So, how do you approach it, and who do you sell to?

Daniel Faggella: Totally. So, in our business, the best titles, the people that get what we do, are pure marketing titles: CMO, VP marketing, occasionally director marketing. It’s not generally demand gen people. Some people use us for some demand gen, but the people who get us and who’ve invested hundreds of thousands are people who know that association next to their ideal buyer, speaking the paradigm that they need other people to understand in order to sell what they’re selling into the future, they’re flat marketing titles. So, director, VP, CMO is it. Every now and again, demand gen people, but they’re not our ideal fit.

CROs hand us to CMOs. We don’t generally work with CROs. But sometimes we’ll get on the phone with a CEO, CRO if sometimes if it’s a smaller-ish company. Most of our sales are to companies where a VP or even a CMO is potentially accessible. A company that’s raised a quarter billion, we can talk to the CMO no problem. And so, that’s not that hard. Now, it’s still a multi-step sale. There are different stakeholders. We have to figure out who else needs buy-in. It’s a three- to six-call close. So, it’s, you know…

Brad Weimert: Still not that bad.

Daniel Faggella: It’s not that bad, but it’s not super quick. But it’s a three to six-call close, which generally translates to a two to four-month process. So, that’s most of our sales. They fit in that range. Most of our programs will fall between $20,000 and $70,000, somewhere in that range. That number has moved up over the years. Our average program four or five years ago might’ve been 14.5k, and last year was more like 40 or something like that. So, that number’s been moving up as the sponsors have moved up. But when it comes to enterprise, so now we’re running a program right now with Salesforce. And the cool thing about our business, too, actually, I do like this part is that if somebody works with us, nobody’s hiding it. It’s not like, “We work with them secretly.” It’s like they want their logo.

Brad Weimert: Yeah, right. That’s the whole point.

Daniel Faggella: So, yeah. So, luckily, I am able to name names. Every now and again, we’ve done projects where we’re just building research for their own teams or whatnot, but that’s a tiny percent of the business. So, Salesforce, some of the very biggest data centers you would know by name. I know you had Jason on, who’s a data center guy up in Canada, I think. One of the companies we work with is doing a bunch in the western part of Canada there. Like, we’re talking a $30 billion company, Google Cloud, etcetera, those kind of guys. Some of that has been through agencies inbound, and some of that has been through the company themself, where some, I mean, these big companies like very small people can control 50, 90 million, or $90,000. Like, very small people can control that kind of money.

So, they might float in generally inbound. What I’ve learned about selling to the bigger companies, we don’t generally go after them. So, in terms of outbound, our business this year will be pretty well split between inbound and outbound, and then a lot of renewals. When we go outbound, we’re targeting more of that companies that have raised, let’s say, 70 mil to a billion in venture. Generally, that’s a sweet spot. Or revenue of 50 mil to 500 mil. Like, those bands of AI services, AI infra, AI software at startup-related kind of companies, those are the bands where we play, and there are certain industries where we have great audiences. And it’s the network, right? It’s not audience numbers.

It’s like I know I have all the drug development people, so I can get on a sales call and just crush because we literally talk to everybody they want to sell to. And then the same in fraud detection, compliance, and banking. Like, our networks are so ridiculous in those areas. Like, if you sell to those people, you kind of should know us. So, we do outbound there. It’s those smaller companies. The big guys, what we’ve learned, is they care about a few things. They tend to get interested only in our business when you’ve had their peers on, and when you’ve had their ideal customer on.

So, for a long time, Google Cloud wasn’t selling to legacy enterprise, so they didn’t pay much attention to us. Even if we do something with NVIDIA or we do something with AWS or whatever, they wouldn’t necessarily pay that much attention because they weren’t trying to sell to infra leaders or CIO Goldman Sachs or some AI leader at Wells Fargo. They weren’t really targeting those people. But when they started to, and then we started getting very high concentration of VP-plus within Fortune 100 like life sciences, banking are very big industries for us. That’s when the inbound knocks would come. So, for the bigger guys, we found it’s through agencies or through some smaller department, and really the ubiquitous thing that attracts them and ultimately gets the deal is we work with your peers already, and so we’re kind of a known quantity.

And then also you can see publicly these are all people you wish you were selling to, and we can get them on the phone for an hour with no problems. And so, the access being proven and the kind of competitive set already playing there makes them feel safer to invest. And so, once we got, I think it was IBM and some other big guy, the rest of the snowball started rolling. But most of our sales are not to enterprise because I think if we went in there cold, it’d probably take two years to crack Google Cloud. So, we haven’t done it that way.

Brad Weimert: And so, how do you get the credibility in the first place?

Daniel Faggella: It was a slow grind with the podcast. Like, early on I was interviewing, well, I didn’t know what the business model was, but let’s just say even when I… So, the really early episodes were all about that far-out future of life trajectory stuff. And I did interview people at really interesting, weird technologists at like Microsoft and other places, back in those super old days when I had zero audience, I mean literally zero. But when we knew it was business, the startups I could get on the phone were people that had raised like… So, right now, every AI company has raised 1 million or 300 million. Back then, if you raised 100 million for AI, there were like six companies like that, right? It was incredibly rare.

So, everybody was knick-knack paddywhack small. And then within enterprise, it was a lot of like kind of data science, analytics-related leaders were the people closest to it. There weren’t a lot of them. And also, I didn’t have a big Rolodex, so if I went straight for some VP guy, they wouldn’t necessarily know. It was a slow grind of getting enough of the big logos at like this level of title, where it’s not weird for a guy at AIG or Wells Fargo at a VP level to now come on. And it was climb, climb, climb. And the same thing with the startup. So, as the industry developed, we had to climb seniority at the same time. But nowadays, like chief revenue officer, Google Cloud, or CEO of Thomson Reuters, or chief technology officer, Takeda Pharma, these are inbound pitches.

So, like nowadays we are the central locus for enterprise AI. So, we don’t really do outbound. We have a Rolodex we already have with thousands of these guys we’ve been building for years, and then we get pitches. But it took six, seven years to get there.

Brad Weimert: I love that. Yeah, look, for me, and that’s where I thought you were going to go, or that’s where I would’ve gone, I should say. I didn’t know how you got there. But the credibility, and you mentioned this, and you said this a bunch of different ways, but you borrow credibility from reputable parties.

Daniel Faggella: That’s it.

Brad Weimert: And in the case of trying to get into a big organization, the fundamental of enterprise sales is a multi-touch approach. And people refer to it as account-based selling, in which case you are targeting many titles inside of an organization and playing them off each other and navigating different conversations and approaching it. And if you want to be able to target the CEO of a company, if you’ve talked to five people inside the company or you’ve had their CMO on, that’s your best path to get there. Or if you’ve got another CEO on, but if you haven’t gotten to that level yet, like you said, associate with a brand first, with a smaller title, and then work your way up.

Daniel Faggella: So, there were some companies like Hitachi, and like there are a few other brands where it was actually like met somebody through editorial and kind of climbed our way up just through kind of this person knows this person, and it took 18 months. And some of those weren’t even gigantic sales. And so, the bigger guys primarily have been inbound from agency or inbound from the companies themselves, just by having, like, they look on the website, they’re like, “Oh, you have all my peers, and you have the people I want to be selling to, I guess I need to talk to you.” And that’s the best place to start from for our business.

Brad Weimert: That’s amazing. So, the company is Emerj AI Research.

Daniel Faggella: That’s right.

Brad Weimert: And where’s the podcast if people want to poke around in it?

Daniel Faggella: It’s everywhere. So, AI in Business is on Spotify, even like SoundCloud, et cetera. Just super easy to find.

Brad Weimert: That’s the name of it, AI in Business?

Daniel Faggella: AI in Business, yeah. Super easy to find.

Brad Weimert: I love that. Well, I want to actually talk about some of the crazy AI future life-focused things. But to do that, hey, do we have a guest here? Not yet? Okay. Well, we’ll have a guest here in a second, and we’ll talk about some of the futuristic sh*t, because I think that’s interesting.

Daniel Faggella: Cool.

Brad Weimert: A couple quick wrap-up questions for you. You have the trajectory that I mentioned from jump that so few people have, which is having something that pulls them. And having everything else, all decisions made through that lens. But you started as a new entrepreneur, as most do, which was following whatever path would make money, that sort of followed your interest to some extent.

Daniel Faggella: Yeah.

Brad Weimert: Do you think that entrepreneurs should try to find their passion and their vision, or do you think they should focus on building business skills and making money in the beginning?

Daniel Faggella: Yeah, man. I mean, I have to say, like, I think for everybody it’s going to be different. Like, I think do what the heart appoints. I mean, the way I talk about starting a business is I tell people, generally, like, “I don’t recommend starting a business unless you can’t not start a business.” So, whether it’s your personality or it’s like if you can’t not start, if you’re like debating, it’s like, “Nah, I just…” Why would you? Why would you do that?

Brad Weimert: It’s a lot of work, man.

Daniel Faggella: Yeah. Why would you do that? So, it’s more like if you can’t not start it, start it. I think for most people, that should line up really, really well with something economic. I think there was actually a lot of downside to having a life purpose that I had to scramble with and build and establish with starting from… So, jujitsu, I could make DVDs the same day because I was good at jujitsu. AI, starting from scratch with this life purpose was I don’t think what I would recommend, but if somebody has a compulsion, they say, “This is clearly the organizing idea of my life,” I would say that’s the way you should live.

Brad Weimert: I love that. Okay. Well, let’s talk about some crazy sh*t. Sir, could you come on in here, please?

Daniel Faggella: Oh, we got fellow crazy sh*t talkers?

Brad Weimert: We have a surprise guest for you.

Daniel Faggella: Whoa! No way. A surprise guest.

Brad Weimert: Who is usually good at talking about crazy sh*t.

Daniel Faggella: A surprise guest. No way. I never met this man in my life. Oh, wow! Great to see you, brother. Yeah. Great to see you.