Morning Brew Founder's $100B Bet on Al Transformation (Why He's ALL-IN)

If we didn't call ourselves an AI transformation firm, we wouldn't be able to attract the talent that we've been able to. Every executive feels pressure

able to. Every executive feels pressure to have a point of view on AI. Is there

a way to actually make AI work? One of

the most limiting factors in AI right now is and the final thing I'll say is I do think the AI thing is very much like >> guys today we have a very special conversation with Alex Lieberman founder of Morning Brew which you guys may have

heard of exited that a few years ago and now he's going all in on his AI transformation partner 10X he's brought his co-founder on and we're going to be having a very very very interesting discussion an important discussion on

the current state of the AI agency and AI transformation partner industry where things are going what the opportunities are how they are approaching it within 10X and also sharing on my side what doing at Morningington. Aai. So, if you

are anyone even remotely considering starting some form of AI services business or agency or you're running one yourself right now, this is probably one of the most important conversations you can have heading into 2026. So, I

definitely enjoy the combo. I'm sure you guys will as well. Alex, mate, great to meet you finally and Arman likewise. I'm

super excited to get into this. I think

there's a lot of uh important discussions to be had around AI agencies, transformation partners, where the whole market's going, the current state of the industry. So, um, I'll let you guys give a a little intro for the people who don't know you.

>> Accidental entrepreneur. I, uh, was going to work in finance my whole life.

Uh, my dad was a trader on Wall Street.

Mom was a trader on Wall Street. Grandpa

was a trader on Wall Street. Uh, and so I grew up like aspiring to work at a bank as a trader and then started a side project when I was in college at the University of Michigan. Uh, that side

project turned into Morning Brew. We

sold the company in October of 2020 to Axelspringer uh which is like a media holdco owns business insider Politico uh and a number of other businesses uh

especially a bunch in Europe. Um I

stepped out of the CEO role in 2021. Uh

was in a chairman role until end of 2024. Spent a lot of time soulsearching.

2024. Spent a lot of time soulsearching.

Um after soularching I thought I was going to spend the rest of my career like building a venture studio where I'd incubate businesses. I'd use my audience

incubate businesses. I'd use my audience to drive distribution both uh in terms of building uh kind of the early team as well as driving customers. I'd bring in a CEO. They'd run the thing. Once there

a CEO. They'd run the thing. Once there

was a sense of stability or product market fit, I'd pop out and do the next thing. That was that was the plan. But I

thing. That was that was the plan. But I

think as as it goes with a lot of venture studios, if you look at the model broadly, um venture studios kind of operate in a power law just like

venture firms do, just like most things in life do. And when that happens, the very honest question uh occurs, which is

if one business is growing significantly faster than all of my other businesses.

Not that there's anything wrong with the any of the other businesses, but the the opportunity cost of your time goes up significantly um to obviously spend all of your time on the one business that is

uh accelerating. And so that's what

uh accelerating. And so that's what basically happened is um after launching 10X, the business was a rocket ship.

Obviously, it was um just so much market pull from businesses trying to understand how to navigate this new technology. We've been building for the

technology. We've been building for the last what are month 7 months roughly. I

we talked in terms of weeks. What did

you say 33 weeks? Two weeks ago.

>> Yeah.

>> Yeah. Um and it's been a ton of fun. For

the first time in my career, I'm surrounded by engineers. Um which has been so fascinating. both the way that they work having an impact on how I work

now, but also in kind of understanding what my preconceived notions were of engineers and a lot of those stories being broken by the by just sitting behind and working with the folks that

uh are at 10x now. So that's the the quick spiel.

>> Yeah, sweet. And uh Arman, if you can give a little bit of context on your side and and how you two met, that would be interesting to know as well.

>> Yeah, so thanks for having us. I'm

Arman. I'm a software engineer by training. I studied electrical and

training. I studied electrical and computer engineering at Carnegie Melon and then I taught there as an adjunct professor in their school of computer science. Um then I went to Google and I

science. Um then I went to Google and I helped them scale their cloud and AI tools internationally. After Google, I

tools internationally. After Google, I went and I started a few different venture-back startups and the most recent one, Alex was one of the first investors and I was a solo founder and

so I basically relied on Alex for a lot of just like co-foundery type conversations and moments and we got really close through that and we believe

pretty deeply that AI is the most fundamental technology change that's ever happened and it's really really difficult to go through that change as a business and the goal for ten NX is

basically to help companies adopt that change.

>> That's sweet. Um, and you guys, if you've been watching the channel a while, you know Nick, our head of consulting, so he's here to here to jump in and um, and share some of the source that we've been doing at Morningside as well. But I want to kick this off

well. But I want to kick this off looking at just the guess why you guys are all in on this at this point. Um,

obviously, Alex, you've had a you've had that soularching moment. You've gone

back and forth and I I imagine it's pretty relieving now to feel like you found that thing that you can fully set into as I mean like every entrepreneur wants to have that one clear goal that you're working towards, right? So, how

have you sort of found your way to this and what's the the size for you that this is really the opportunity? Well,

people who are not not fully aware, you can give a bit of context on like AI transformation partners um similar to what we do at Morningside and sort of why you've landed on this. Okay, guys,

very quickly, if you're an aspiring entrepreneur and want to start your own AI business and you haven't already joined my free school community, it's down there in one of the links in the description below. has my full free

description below. has my full free course on how to start your own AI agency as a complete beginner and you're surrounded by over a quarter million people who are also striving towards the same things. There's no better place on

same things. There's no better place on the planet right now to be surrounded by like-minded people and you get free weekly Q&A with me where you can ask questions directly to me about how to start and scale your business. I'll see

you in there. Very simply, uh 10X is an AI transformation partner for mid-market and enterprise businesses. Um we

basically have two kind of core services that we offer. One is strategy work where we help companies basically understand their key bottlenecks and

problems and then map those to AI use cases that can unlock those bottlenecks and kind of the output of that is a 12 month AI roadmap uh that if they want to

execute on it can actually result in production grade use cases to unlock these bottlenecks. The second part of it

these bottlenecks. The second part of it is execution. And so, you know,

is execution. And so, you know, historically in management consulting, a lot of the the big players Yeah. Yeah. Exactly. The Mckenzies, the

Yeah. Yeah. Exactly. The Mckenzies, the Baines, the BCGs of the world typically do 3 to 12 month studies that cost tens of millions of dollars and that's it.

You get, you know, you get a 50-page deck served on a uh on a platter and it's like good luck. And I think one of our fundamental beliefs is where consulting's going. you just can't you

consulting's going. you just can't you cannot just do strategy work uh for a variety of reasons and so then we also obviously have the team to execute on the roadmap that we deliver for clients

and the way we execute is a combination of AI engineering as a service as well as building AI native products and we can go into why we operate in that way

but basically there's a lot of our customers who actually were working on traditional deterministic software for and the way we use AI is just to accelerate the work that our engineers

are doing and then there's another obviously um pocket of customers that the work we're doing is building agents agentic workflows or net new AI products

that are either customerf facing or improving the workflows of their business and that is kind of uh how things are split within the company.

>> Yeah, there's a there's a lot there and we've gone through a lot of the same stuff at the moment. It's like, okay, you've got the consulting offer, you've got development offer. Obviously, you

can't really do one without the other.

As uh Nick will probably be bobbing his head along, too. Like, um it makes it very hard on his side if we were to pull away and say, "Look, let's just really focus on the development." It's like, "No, these these these companies we're working with, they want both." And it's kind of a non-negotiable. It's hard to

sell the consulting um if you're if you don't have the the stuff to follow up with. and also there on the uh on the

with. and also there on the uh on the products and that's definitely uh part of the strategy for us at Morningside is is saying treating this as as a research lab partly as well for uh software

opportunities to build some sort of product that's specific to the industry and for us we're we're very big into sports at the moment and we think there's a bunch of great opportunities uh within sports. Um, but as for your

your focus right now, is it just we're going to dial in the the consulting process and development, get that working well, make sure we've got good teams there, and then are you kind of is the big play for you guys here talking$undred billion dollar company.

Is a big play here scaling to I guess either scaling up to enterprise and being able to get huge contracts there or is it doing volume with mid-market companies or is it going through

mid-market or enterprise to find a a larger SAS play potentially that can scale to that? So there's a a bunch of This is why I love the the model so much. It just feels like you've got

much. It just feels like you've got every freaking player you could ask for.

Um it's like if you just keep progressing as you are, it's it's pretty hard to not not find something. Um so

yeah, where where you guys headed?

>> I've wanted to start this company since I was a sophomore in college for the reason that you said like if you think about what we're actually doing, right?

What is this business fundamentally? If

you were an alien and you came down and you saw what we were doing and you didn't understand the words that we were saying, all you could do is look from the outside in, you would see that we are hiring

brilliant people and renting their time.

When you have brilliant people in a room, really cool things can happen. And

when I was a sophomore in college, I read this book called The Innovators by Walter Isacson. I would recommend to

Walter Isacson. I would recommend to everybody to read that book. It truly

changed my life because what you realize when you read this book is like they basically walk through from the from the day that Adah Love Lace and Charles Babage conceived the idea of a computer

and programming all the way to modern times. And I actually I told Alex when

times. And I actually I told Alex when we first started this to read that book.

I was like, I need you to read this book. And he read it on his baby moon of

book. And he read it on his baby moon of all of all times, which maybe was not the best time to read it, but he read it. And so I reread it as well just so

it. And so I reread it as well just so that I could like refresh like why am I telling this guy to read this? It's

interesting. It all leads to AI and this was before >> they called it they basically called it very first 100%.

>> Yeah. It's crazy.

>> Totally. Like he ties the bow on this book with artificial intelligence. And

so what you notice is every single innovation from the day of Ada Love Lace and Charles Babage to modern day I think it ended with like mobile and then AI was the next step. You notice what does

it take to innovate? And really it's like put brilliant people in a room, put a forcing function on them so that they have a direction and then give them freedom. And this freedom could be

freedom. And this freedom could be financial freedom. It could be

financial freedom. It could be explorative and and and creative freedom. It could be a number of

freedom. It could be a number of different things. But what you notice is

different things. But what you notice is that this this idea of a center for innovation has changed its form factor over the years. But that that fundamental equation looks the same.

Right? Many years ago, Christopher Columbus was arguably on a research trip, right? He was funded by the

trip, right? He was funded by the government to go and do research and then ARPANET many years later was also a research project funded by the government for defense, right? And so

defense government like this was often the traditional way to do it. Then we

organized into universities again funded by government but then research like private money started coming in and recently we see these corporate funded research institutions, right? What's

really exciting about this is like the equation that you just talked about, right, is exactly that. It is let's generate cash flows to support a team that can then identify IP to build,

right? We see that as the exact that is

right? We see that as the exact that is the road map is like how do you generate the cash flows to support that research.

But that is the core step. You have to generate the cash flows, right? And so

our number one goal is what are the aliens seeing? They're seeing a pool of

aliens seeing? They're seeing a pool of geniuses. How do we get that pool of

geniuses. How do we get that pool of geniuses? Well, you need the cash flows

geniuses? Well, you need the cash flows to support them. And so, building that business, building that solid foundation, that has to be the goal so that we could have the freedom to have fun and go do that research afterwards.

>> So, you're saying this is kind of like your your alternate route to okay, I mean, let's let's raise let's raise $50 million and try to like build something big. It's like, let's try to build a

big. It's like, let's try to build a team and the cash flows sort of alongside each other. let's be able to vet the great talent and let's try to get in as as as you know as an agency you're getting very hands-on with these problems and and for the the big de

projects we've got going right now it's it's validation in real time when you get to build it and you see that the companies apply it and it's like okay so there's something there and they're willing to pay for it and you see it uh right in front of you

>> basically Arman and I had like three criteria so we had like this end goal in mind that Arman just outlined and then we had basically like three criteria that informed like what what's the way

we sequence The business criteria one was how do we stay in control of our destiny? Because I think for both of us,

destiny? Because I think for both of us, the number one thing, the number one reason we're entrepreneurs is we want freedom. And we want the freedom to do

freedom. And we want the freedom to do whatever the [ __ ] we want. Number two is we need to figure out how can we attract truly the best technical talent at a

time when the best technical talent is getting paid tens of millions of dollars.

And um the third was and this was really like I would say my my own fears and and needs is I loved building Morning Brew

but advertising as a business model is just historically not a great business model. It's one of the fundamental

model. It's one of the fundamental reasons that venture doesn't typically invest in media businesses is because let I'll just use any media company

example. you do $100 million in ad

example. you do $100 million in ad revenue one year, at the start of the next year you're starting at maybe 20 million if you're l if you're lucky. You

have to build back up 80% of it just to get to flat. And so the other criteria was how do we build a recurring revenue business so that we don't have to fight

for replacing money every 6 to 12 months. And so what does that actually

months. And so what does that actually look like in practice? One, it starts with a consultancy because you don't need money. You don't need to raise

need money. You don't need to raise money for a consulting business. you can

cash flow from day one and a consultancy I would argue is like one of the best petri dishes uh that creates the most surface area for creating optionality

for yourself. The second was the

for yourself. The second was the compensation model for our engineers allowed us to attract the exact type of technical talent that we wanted which is all of our engineers are former founders

who want to bet on themselves. And the

third is how do we how do we get a very big chunk of our business being recurring revenue at a time when most gen AI projects are project based and it

is by doing traditional engineering as a service where we are using AI internally to drive faster engineering work because historically engineering as a service

work is 12-month contracts highly retentive opportunity to grow accounts and you can have those customers for 5 to 10 years and so those three criteria really informed what the path of the business has been so far.

>> So you guys are seeing the the same same pattern as us at the moment and I I'll kick to you in a sec Nick on this. But

what started as okay this is an this is an AI development company an AI agency.

You eventually realize that like that's it's it's literally just like the final piece. It's the cherry on top is the AI

piece. It's the cherry on top is the AI and you've got uh most businesses have no clue what the [ __ ] their workflows are. They are using clunky software. No

are. They are using clunky software. No

one's even using it the same way. And

there's actually like general software development all the way down to like the base. And so you can frame it as a as an

base. And so you can frame it as a as an AI agency and as AI development transformation, but really it's like let's use our consulting team to iron things out. Then let's get some just use

things out. Then let's get some just use AI enhanced engineering and get this stuff done way faster than they ever able to do it previously. And a lot of the perhaps software issues that were unsolvable because the the cost was

going to be so high. And now that could potentially be really the big opportunity here is that dev cost to drop so much. There's this like inertia I guess forcing function similar to what

you said Arman on hey this AI stuff seems like something we should change for okay well now there's all these all this general dev stuff we can uh we can justify as well. Um so I guess it's an interesting period we're in. Um and Nick

you're definitely seeing this on the uh on the consulting side right. If you're

a business owner who's interested in what generative AI can do for your business, you can get in touch with me and my team at Morning.AI in one of the links in the description below and we can start your entire AI transformation process going all the way from the

education and training of your staff to the identification of the best AI use cases for your company all the way through to development and beyond. We

have worked with some of the world's biggest sports teams and also publicly traded companies. So, rest assured, you

traded companies. So, rest assured, you are in good hands.

>> Yeah, I mean I feel like this happens in probably 80% of the projects that that we have these days. Um, it's funny. I

feel like I feel like we enter under the guise of like we're going to optimize your business with AI and often times we leave and they're kind of like oh that's that's what I needed. I just needed like

a system to pull everything together.

Um, and so it's actually kind of a funny balance. Like I don't know you guys have

balance. Like I don't know you guys have have encountered this as well, but oftentimes when we have sort of those roadmap conversations, we do kind of have to like draw the line between like

there's all this amazing AI stuff that could automate a ton of the human work that's happening that your people are doing and I promise it's going to work because we've done all the leg work to get here and I and here's all the here's all the manh hours that your team is

spending on this type of work. But

before you even get there, you you've got to do this before. And so in all of our final sort of recommendations that we give to clients, we've got a very solid chunk in every single one of those

recommendations that's called prerequisites. And we have that in every

prerequisites. And we have that in every single one. And that's probably where we

single one. And that's probably where we spend like 70% of our time when we're with our clients is like we hook them in with like here's all the amazing AI stuff and you can have this voice agent here that's going to do all these things

but now let's talk about the prerequisites and what you really need to get done and we probably spend most of our time in in those calls. I don't

know if it's similar for you guys there as well.

>> Totally. Yeah. I mean it's it's um the actual AI is like it's a [ __ ] API call, right?

It's it's literally one line of code and that is what makes everybody's jaw jaws drop but it took

two months to get the ETL pipeline such that the data is actually clean in a database and then build all the systems around that to make it possible such that that one API call makes everybody's

jaw uh jaws drop and I think that's the case for technology but likewise with processes right yes if you want to use AI like you likewise have to change processes because you like even if I was

not an like like there's very fundamental stuff that you guys can be doing that's much better a lot of what we do is just putting a

mirror up to people and showing them how bad things truly are and they're like oh wow like you're such a genius for for finding this but really just that external perspective is helpful. One

thing I would add is um I think this happens everything you guys are describing this happens for two reasons. One is that every executive

reasons. One is that every executive feels pressure to have a point of view on AI and to uh drive transformation in

their business, but they have no idea what that means. And so they look to someone to tell them what that means.

Then and Arman and I have experienced this a number of times when we ask an executive to give us what is their wish list of AI use cases in their business.

Like if they could snap their fingers and AI would do stuff in their business, what would it be? And like 80% of the things that they are asking for is just

traditional software. 20% is actual

traditional software. 20% is actual things that require the power of Gen AI.

And I would actually argue like this isn't a failing of AI. Uh I think it's actually it speaks to how valuable like there's a reason software has in fact

eaten the world. like it is valuable for a lot of things. And I also think what it speaks to is one of the most limiting factors in AI right now is actually just human creativity. Like we don't have an

human creativity. Like we don't have an ability to think outside of the box that we've been put inside ever since software was created. The other thing that I'll say about just like um the

work that we do for clients is that I just think at the end of the day like similar to what Arman Arman said like I do think people just need a mirror put to to their business and and just Liam

going back to what what you said before like I think that what we're trying to figure out at 10X is like is there a way to actually make AI work recurring

revenue like you have huge like this huge long-standing industry of engineering services. It's a $3 trillion

engineering services. It's a $3 trillion market. AI transformation is a new

market. AI transformation is a new market and it is largely been project based. Now, we're asking ourselves every

based. Now, we're asking ourselves every day, let's say a client does want an agent to be built. We're asking

ourselves, what is the difference between an agent and software? And how

do we make an agent recurring revenue for us in the same way that software was? I think that's what keeps us from

was? I think that's what keeps us from um from spending all of our time on just like AI focused work. And the final thing I'll say is I do think the AI

thing is very much like marketing right now. And it is marketing to your point

now. And it is marketing to your point Liam of like it's the Trojan horse that gets someone interested in your in what we're doing but is not ultimately like that's the sizzle not the stake. I also

think if we didn't call ourselves an AI transformation firm, we wouldn't be able to attract the talent that we've been able to attract. If we just called ourselves the world's best dev shop, I guarantee you we would not have the

engineers in the room that we have. I

was going to save this a little bit later, but I think we've we've pulled right into it. The uh the custom software and like replacing the entire software stack with with custom software because that's potentially route that like even Nick and I were discussing. I

think small businesses are the the clearest example you can think of this.

I think as you start to go to sort of mid-market and then enterprise when they have these massive clunky systems that they really don't want to switch off of is there this general dev that AI transformation partner perhaps goes down the route of if you start with small

businesses it's like okay what are the things you have you have a CRM you have some sort of messaging you have uh funnel um you have like sales team and you have like a calendarly calling infrastructure these sort of key

components is there a like a scrapping of the entire software stack and replacement with an agency uh agency or internal cap capability that is like custom software that truly fits the business and this is all like

speculative stuff but this is definitely one of the the routes it can go and the question is if you bring that sort of up market is that realistic within I mean I think for small businesses it's already happening we have people in my community who are literally offering these things

to uh simple service based businesses and stripping the whole stack out and replacing it with a custom one um so it's it's already there it's just a case of is that the new thing is is is every company going to have their own internal

tech department that just manages their own software and that would be a form of recurring revenue. But as us who steps

recurring revenue. But as us who steps in there, but at it at the end of the day, they need to scrap a lot of the old stuff. And for us as transformation

stuff. And for us as transformation partners and and particularly on the development side, the challenge is often around the integrations and the and the connecting things. If you had a clear

connecting things. If you had a clear set of use cases that you'd identified, then you're able to roll it over to an AI development environment where you could push those use cases into essentially MVP phase. If you're

building from the ground up within your own software for the entire company, it would be a lot easier for it to build those features within a couple of iterations. But as soon as you have

iterations. But as soon as you have different integrations and things you have to worry about, then it gets a lot more complicated. So

more complicated. So >> what do you guys think of of that direction? We've come to that thought of

direction? We've come to that thought of like okay maybe the solution is that consulting cannot be made recurring and so we need

to basically leave behind something that is recurring and that will be some form of software tool. Um, so and we're not the only ones who thought of that

either, right? This is why McKenzie

either, right? This is why McKenzie famously has like this hidden gem of this gigantic SAS portfolio that they've been acquiring for themselves over the past few years, right? Like because they

also have have realized this. I think to your point in the age of AI there's this there's this door that opens up which is you go into a company and they say hey um someone just told us that it's going

to take a year to to change our CRM from one platform to another and then a different agency said that it's going to take a year after that to integrate everything together to give us this one

knowledge base and you can say hey actually in six months we can rebuild everything like that is an actual thing that can happen and that opens up the floodgates to a lot of other

opportunities. Another thing I'll say

opportunities. Another thing I'll say though is that some of these types of softwares like some of these

SAS categories no longer need to exist, right? Like as an example, a data lake

right? Like as an example, a data lake might not need to exist in 5 years because the concept of a data lake is to take differently structured data, bring

it into one system. Well, AI is really good at turning differently structured data into a single structure, right?

Like unstructured to structure is uniquely what AI is capable of. And so

like yes, you can rebuild stuff from scratch. Like the the idea of complexity

scratch. Like the the idea of complexity being a moat is no longer a thing, but also AI introduces this other variable of the fact that some categories will

probably just be deleted. I see this is kind of like the elephant in the room which is the dirty work of realistically a lot of companies are running on outdated tech stack or set of tools that if you were to say let's do a

transformation for you it's going to take a lot of work and a lot of disruption to get in there and as as agencies it's like the the money is probably not going to be in there as much as as some of these other more sexy

AI things which makes it tricky because someone's basically going to have to come in roll their sleeves up and go all right now I have all of this awful interpersonal stuff which we can get to uh leadership, all of the like messiness

of converting a company, especially as you get bigger and bigger bigger over to this new sort of AI native stack and and custom software. Um, which makes me

custom software. Um, which makes me think if you chart this out and we can get into sort of the the future of this model as a whole, but a provider like Google comes in with their incredible like Gemini 3 model releasing, how good

it can do with building websites.

They've obviously got cloud. There's

providers like this where I mean doesn't seem like a bad buy right now even even though they're at all-time highs but where they could feasibly a small business could come on and and chat back and forth with an agent explain what they currently have and go through okay

well we can build your website out and we can connect that to an internal like software that we create for you can select I need chat I need uh I need uh a to-do list I need um CRM of course and

you can select a bunch of these different needs for your business and there's almost like a DIY for small businesses what happens from there for for mid-market and enterprises is completely different. But

um I think that's not not too far off.

And if we're looking looking at this stuff objectively, that's kind of the the trajec trajectory we're on here. And

that takes me to the question of what is uh like Nick and I were talking about before. If you take look at a we're

before. If you take look at a we're development design agencies um and at what point do they die? We've seen some incredible design coming out of Gemini 3 now. Um it can it can design it well. It

now. Um it can it can design it well. It

can build it well. the copy maybe that's the the last piece like actual good marketing positioning but I mean if you give enough context to an LLM it can kind of do a pretty good job of that so and then the hosting and deployment okay that can be taken care of by the

platform so now is that whole industry gone and so what happens to us if we look apply the same lens to AI transformation okay while the development you can feasibly like see that trending towards zero where the

development is there's more so like the selection use case and then uh deployment or like dev within these AI coding environments ments um it's going to become a lot easier for us or we're using existing tools that allow us to

build these things more easily. So

development becomes a smaller portion of the value you provide the consulting I mean like like you saying before very easily like we can do right now using claw code using um creating custom software to automate that process. So

surveys into an agent that can think through it and reason to use cases to development. So if you pass that along,

development. So if you pass that along, where does the actual where does the buck stop? And we've figured out that it

buck stop? And we've figured out that it gets to the human adoption. And this

thing can only progress and move as fast as humans will adopt it and actually be using it. So the training portion of the

using it. So the training portion of the AI transformation partner model is really the the sticking point. And it's

can you you're sure you can identify, sure you can build, but can you actually train people? That's that's really the

train people? That's that's really the only thing is is training to zero. and

the only rock there, the only like tangible thing you've got is how people how fast people can be trained up on it and actually use it. Um, so I thought that was a really insight, a great insight when we came to it. So I'd love

to know what you guys think on that from your side. Maybe I reframe it just on

your side. Maybe I reframe it just on long-term.

>> Yep.

>> Are we seeing this as like a >> are we [ __ ] >> Yeah. Yeah. Are we [ __ ] Is this is

>> Yeah. Yeah. Are we [ __ ] Is this is this an arbitrage play? Is this an arbitrage play for okay, companies are going to be willing to invest now because they realize every every new technology there's a shakeup. You can

either sit around and wait for it to become self-service like the Google thing I just mentioned or you can work with people like us to invest now to try to like in this reshuffleling become the new leader in the market and it's going

to cost more. It's more risk involved but you can either do that or you can sit around and wait until you get the same thing but at a time when it's not as valuable. So is this whole

as valuable. So is this whole transformation partner model a fiveyear period where we got to >> make it make the most of that uh arbitrage before we get also nuked like everyone else is. Yeah, that's what I'm saying.

>> Totally. So, so here's my thought. And

what I'll say is I typically um don't love looking more than like a few months ahead because I just know my level of accuracy goes down significantly. But like my my feeling is

significantly. But like my my feeling is this, which is if we look at big like mid-market or like we're talking to several mid-market companies right now, very large

businesses, let's just say hundred million a year plus that still have onrem servers. We're in 2025

onrem servers. We're in 2025 and and so just thinking about how how far we are into the journey of like

cloud and yet so many companies are still working in the way that companies historically worked in the late 90s and early 2000s. What it just tells me is

early 2000s. What it just tells me is actually your point is exactly right which is like human we are our own worst en enemy. like humans are the bottleneck

en enemy. like humans are the bottleneck in all of this. And so I think to your point for like startups and small businesses, but I think even like we have to delineate what small business

means because I think early stage startups are small businesses, but also like the pizza shop down the street is a small business.

>> I'm not talking like >> boring business, let's call it that. Not

like an industry start.

>> Yeah. So I I do think there's probably this like the the curve of diffusion probably uh follows the size of your business roughly speaking. And so to your question of like is it a 5year

arbitrage? I guess everything in over a

arbitrage? I guess everything in over a long enough time horizon is an arbitrage. Everything is an arbitrage

arbitrage. Everything is an arbitrage over a long enough period of time. But

my I guess my my current feeling is at the mid-market and enterprise level, the length of the arbitrage we're talking about is 10 plus years. Not because the

technology is going to take 10 years to get to a point where everyone shouldn't be replaced, but because humans are going to stay in the way of effectively

replacing ourselves is is kind of what what I believe. And so my hope is if if you give us a long enough timeline, you give us 10 years, I I say shame on us

for not figuring out what's the next arbitrage to ARB when the current one has closed.

>> The interesting part about that is that we have so many different ways of monetizing and solving this problem.

That's what we're essentially diving into this us on our side and your side as well. We're diving into it and saying

as well. We're diving into it and saying there's this problem of these these human issues and so on. Do you guys also have the question in the back of your mind like what is the best monetization model for this? because you know that is it is it volume with mid-market or is it

like huge like enterprise deals I I know you've said about the the retainer model but there's also the the like we've had to kind of flip this on its head and be like look if we're looking at companies who are struggling with uh these certain

problems like a lot of general de maybe they're still not on freaking cloud like all of this the stuff do we really want to pick that problem to solve with rolling our hands up and trying to re rebuild and and like nurse all these

people through or do you kind of flip it on its head and say well given our set of unique skills and abilities. Why

don't I find someone who has running a like I don't know home service or one of these more boring traditional businesses and say look I want to build the AI there's a lot of talk about AI first companies I want to build the AI first

like softwareized version of what you're doing right now so I'm going to give you 10% of my company you're going to come in and give the expertise I'm going to apply my team and we're going to run it with AI appointment setters AI sales reps we're going to use it from the

ground AI customer support and building it around this kind of custom software from the ground up that is much more future facing And so is there more money in that? You know, like these are things

in that? You know, like these are things that I'd be thinking about. It's it's

very hard to know whether you go for massive enterprise contract and deal with [ __ ] there. You go mid-market and try to maybe increase the volume a bit or are you looking for software opportunities more like point solutions

or or narrow software plays within that that you can scale up to the other industry and so >> or do you raise or do you raise a private equity fund uh by a bunch of businesses and then uh you're you're

participating in the upside of the transformation you're doing. I basically

think that like it's a spectrum, right?

So if you think about one end of the spectrum, it is you pay me cash, I do work for you, and then you own the out the the upside or downside of that,

right? The other end of the spectrum is

right? The other end of the spectrum is you start a company, right? And and you take on all of the risk, but you do all of the work. in the middle there is like

like Alex mentioned you raise a PE fund and you're it's like somewhere in the middle where you're sharing upside but also there's other people putting risk right it's like a blended approach there's also the model of like hey I'm

going to approach a company and they're going to pay me some cash right to cover my my cost and maybe some margin but I'm going to take 50% of the profit that I drive them um or cost that I save them

in a six-month window or something like that right so I think it is all a spectrum And I think to your earlier point and sorry even even within that there's a number of different strategies

right even just for the cash flow piece what you were saying is like you can go after a pizza place you can go after the biggest company in the world right and

those are entirely different companies that serve those two places and I think all of like there will be successful companies in all these different places to your point earlier what's so fun

about this space is that you can be so free and like approach this however you want. And the way that Alex thinks about

want. And the way that Alex thinks about like this and and how how we we talk about this all the time is like there will be so many winners in this space and it's totally okay. Like the four of

us are direct competitors, but we will never talk to the same customers because it is such a big space and we can talk and we can share ideas and like it's that's what's so fun about this. I think

the way that we think about it is basically like what is our objective and I really think like by the end of next year I want an army of the most genius

people that we can get our hands on working on really really interesting problems that get excite that get us excited to come to work every day.

Right? And right now we've been able to do that on this end of the spectrum.

Right?

it's harder for us to work on the venture side because that risk puts at risk the team that we're building, right? Like we would need to basically

right? Like we would need to basically put put capital up front in order to do that. So that's less interesting even

that. So that's less interesting even though it sounds exciting. And so I think like is it a better business model? The future will will tell. Um but

model? The future will will tell. Um but

the way that we've been thinking about is is just what is our goal and what's going to help us drive towards that goal. And one one other question I'll

goal. And one one other question I'll just put in front of you guys and this is something we think about all the time is to what extent do we want to build technology as an asset in the business.

Um not just to like launch our own businesses but also to act as the the underpinning the foundation of the work we do for clients. And obviously this isn't a new idea. It's effectively what

Palanteer built their entire business on. But I think it is a new way of

on. But I think it is a new way of thinking about consulting. If you think about traditionally management consultants have like I would I would argue two key differentiators uh one is the relationship they have

with a client. That's probably the number one. And number two is assets in

number one. And number two is assets in the form of playbooks that basically you drop a a a consultant into a new project. But there's been 10 projects

project. But there's been 10 projects like this one and so they become an expert really fast. But this idea of technology um or building blocks of technology as the asset that allows your

engineers to work faster to get the same amount of work done and improves the margins of all the work you're doing is something we think about a lot.

>> So like the core of it you still got the same problems like at the end of the day people are unsure they need uh education on what the the use cases are um but you're just adjusting the the way you're solving it. Nick have you got you must

solving it. Nick have you got you must have something on that. Yeah, the I wanted to touch on the kind of like monetization uh spectrum question for a second cuz I think at least how how I'm

thinking about it and and we're thinking about it at morning side. I think we're trying all of the above honestly in the spectrum that you mentioned there. I'm

on like we've been a dev shop for like two two and a half years and so we've been at that far right give us cash we built for you. We've like that's where we've lived. I would say for the past

we've lived. I would say for the past however long we've been alive and now I would say probably for the best like maybe last like year and a half we're also doing the other side which is like we're we're building our own software

from the ground up. We have our own developers. We're bringing them in and

developers. We're bringing them in and we work on it and we build it like a software and we sell it like a software and we distribute it the way that any other software company would build and distribute their own. But I feel like I

would say even in the past like 3 months that middle ground is one that we haven't really touched and we're starting to do so right now. And I

actually find it probably the most interesting because to me that's where we get the sweet spot of controlling what we're good at which is building AI

and tapping into what our clients are good at which is all of that industry knowledge.

>> I think that's super interesting. I

think like to your point the the really valuable insight there is like what you guys are really good at is think is understanding this technology and what's possible with this technology what you a

client is really good at is just understanding their vertical or their domain of expertise better than 99% of the world and so the question is is based on that truth what does the what

does the best relationship look like to both maximize those strengths and also maximize whatever you define as the ideal upside in that relationship. So,

I'm even curious like in that example, how do you how do you think through what is the ideal outcome of that insight?

Right? So, this insight came because you knew what was possible and this person had insight into what does a scout want and then to that point there's like a few options there. You can just kind of

be a mercenary and build the solution for them. you can be a missionary and

for them. you can be a missionary and like co-own it with them and you co-own the business and then you run it like any business. Um or there's something in

any business. Um or there's something in the middle which is kind of like what Arman was talking about and it's actually the thing in the middle that this model has existed forever whether

it's in media buying or hedge funds is like the 2 and20 model you uh you know 2% is your management fee. So you charge some nominal cost to build the thing and

then you participate in their usage of the tool and you're all incentive aligned because the more valuable it is the more they use it the more they use it you participate in the upside. How do

you think about where you want to live on that spectrum?

>> We don't know >> we're figuring it out also.

>> Um I think it I think it's also highly situation dependent like this is this is another really good example. So so like have the NBA example like in your head.

Let me tell you about another one. Like

there's another one we're working with right now like a very large real estate company in the US.

We're building them something on the mercenary side of things for now. Um

which is basically a voice assist like voice to contract assistant. Let's just

say um throughout the course of us coming through with that project, we're kind of like this this is they they want to take and scale this to not only all

of the agents within that company, but every agent in every real estate agent in the US. Do they have the technical chops to do that? No. They're real

estate agents at the end of the day. Do

they do they do they want to be able to do that potentially? Are they going to need a partner to help them do that?

Yes. And so for those guys, I think for us it's like how do we see that partner and what what does that partner bring to the table? And for for us it's like they

the table? And for for us it's like they have massive distribution help that they bring to the table. Do we know every single real estate agent or real estate company? No. But are we really good at

company? No. But are we really good at AI? Can we build that and help them help

AI? Can we build that and help them help them scale that solution? Yes. So, I

think my answer to your question might differ for someone like that versus an NBA team which is going to be incredibly tight and like secretive almost about

the things that they're building and not going to want to go and spread that for every single person. So, it's like I don't have I don't have a flat answer.

>> Well, I I almost feel like the the unspoken answer is is it a big enough opportunity to underwrite? And and part of what you're saying is the reason the MBA one may not be a big enough under

opportunity to underwrite is partially because of the the how how the use case by design would be contained based on what the team wants. Whereas like

obviously the TAM of what you're talking about for the real estate company is way larger. So it's almost I don't know it's

larger. So it's almost I don't know it's this interesting thing where it's like it's almost this perverse incentive where it's like the more belief you have in the opportunity the the more it slides along that scale. One of the

interesting things we find similar to what you just just mentioned there, Nick, is uh and I've talked about this a lot on the channel is for a long time, I think we we thought we thought dev was a

lot harder than it actually is like uh and and true ROI from dev. And that's

because we were allowing companies to come to us and tell us what they wanted and they didn't know what like either they did they were off the mark on on what it should do and they just like no, we just want this thing. Um or they were

completely missing the much more obvious things like basic transcription or just like changing the the the communication format, changing the modality from like slow manual input to voice is like

applicable across so many different things within a within a company. Um and

just that shift uh we find in basically every company we do an order on that there's some really dead obvious transcription things that are on the same like hours and hours a week for for a given uh employee. So that's been an

interesting shift for us to see like okay if we if we take control of the consulting and identification process, we actually end up getting better outcomes for them and us because it's

going to allow us to find easier dev opportunities with equal or greater upside um and returns for them than this sort of weird thing that they heard about at a conference or they saw on some on their Twitter feed or something

and then now they think that they need that and they were already pretty specific about that. So um you guys must be sim seeing something similar on your side as well.

>> Something we talk about in terms of like the dev work we do is where do we live on the spectrum from CTO to CPO um because like let's just say on the chief technology officer side of things think

of that as like we're just a pure order taker. They they have the project scoped

taker. They they have the project scoped out. There's a PRD. We just file it into

out. There's a PRD. We just file it into linear and we start hammering tickets.

On the other side, on the CPO side, it's like they really look to us as this consultative partner to maybe they have a rough idea of where they want their existing product or new product to go, but they look at as as the expert to

help basically solidify like what is the project, what is the actual PRD and what's the work that should be done. And

I think more and more we try to skew towards the side of CPO or CPTTO because for a variety of reasons we think that

if we are just acting as a pure CTO it isn't necessarily the right expectation we want to set from the beginning of a relationship to your point like we want to feel from the beginning of the relationship like we're a partner where

we can actually share our perspective we if we don't think the way they're thinking about their product direction their stack is correct. And so like we try to make that clear up front. The

other thing is a lot of our points of contact even in the dev work we're doing are not CTOs. Often times what happens is like we are brought in by a CEO or a

C c uh OOO um or even a chief product officer whose view is that they feel like things aren't moving fast enough from a product or edge perspective. And

so if that's the case, the CEO or the the COO or the CFO that we're interfacing with, if they're the one who's giving like product direction, it's it's no shade to them, but like

that isn't their their experience or their specialty. So it just sets the

their specialty. So it just sets the wrong expectation of how we should be engaging them. Um, so that that's on the

engaging them. Um, so that that's on the side of like where we like to live. Like

we we try to as much as possible optimize not being an order taker because of all the the challenges we talked about. One thing I'll just bring

talked about. One thing I'll just bring up on the lead side is we are also very broad in the leads we cast into 10X. And

I think for a similar reason like most of our leads for the business have come from my audience over the last 7 months.

And and the thing I've said to Arman since day one is like every audience like every marketing channel on planet earth, the value decays to zero at some point. And literally like no marketing

point. And literally like no marketing channel has ever uh defied that rule of physics for marketing. And so our job is how do we both extend the the the life

of me as a marketing channel as long as possible, but also how are we planting enough seeds such that there's um acceleration of the value of other

channels that hopefully take kind of like gets into place before I totally plateau. But because of that, I think

plateau. But because of that, I think we've been intentionally broad because we don't want to unnecessarily cut off basically any company that's interested in the work we're doing. But I would

actually argue for 99% of the types of businesses that we run, if you don't have built-in distribution and audience, I actually think our approach is the entirely wrong approach.

>> Yeah. I mean, we've had this as it been like sort of the it's been tricky because a lot of my my advice on the agency side and starting one of these companies, it's like I have

a very unique perspective because my leads are so general and they come from this thing and it's literally just a byproduct of me kind of existing on YouTube that like what I recommend to other people is to niche down and like

if you don't have a massive sort of broad range of of of leads coming in, then you should be niching down. And

that's potentially what we're looking at with the with the sports is very referral based niching down there. Um

but uh yeah, I totally get it. And maybe

the lie you tell yourself as a general agency is or or maybe it ends up being true true for some of us, but we definitely haven't uh seen the final sort of materialization of this is like we'll just be general and then we'll find someone we really like and then

we'll just do that and then something big comes along and pulls you out of it again and you're just being pulled either way by these big people. As

someone with with an audience like yours, you must you must know that very well. Um, and it's there's always

well. Um, and it's there's always something new like, "Oh, we could go this way." And then you're dying from

this way." And then you're dying from indigestion rather than starvation, which is which is a very easy spot to get into.

>> Totally. Yeah. I mean, the way I think about it is like, let's just say someone is actively in market for support on AI help with their business. The first way

they're going to look for that help is they're going to look to someone they trust. And the way they're going to look

trust. And the way they're going to look to someone they trust is either a trusted creator or distribution holder.

or if they don't have that, they're going to look to like a trusted person in their network. So, let's just say I run a finance company. I'm going to reach out to one of my peers that works in finance and be like, "Do you guys

know anyone within finance who specializes in AI product or AI transformation?" And whatever they give

transformation?" And whatever they give me, that's going to be the first call I take. The only reason I'm taking the

take. The only reason I'm taking the call with 10X or Morningside right now is potentially Liam or Alex is a trusted creator who I believe whatever they're working on puts good value into the world. And so I'm like setting aside

world. And so I'm like setting aside that they have to be a finance focused person and I already have that trust in them. But that is not the case for 90%

them. But that is not the case for 90% of people. And so like the guy I was

of people. And so like the guy I was talking to earlier today who he's in Eastern Europe. He um is like an AI an

Eastern Europe. He um is like an AI an ML engineer who's running a a actually like a an ecigarette business in Europe

right now, but he wants to start an AI consultancy. And he's like I want to

consultancy. And he's like I want to start one, but I don't know where to start. Basically what I told him is I

start. Basically what I told him is I was like the example I gave him and I don't know if you guys have explored this world at all is like there's this existing world of software companies having these like huge channel

partnership programs with consultancies right and these big companies the way they slice and dice their channel partnerships like I talked to a channel partner person or a partner manager from

Snowflake two weeks ago he is one of a hundred of him at Snowflake there's a hundred of him and the way they slice and dice it is they have tech partners parters and then they have system integrators and consulting partners. And

then within system integrators and consulting partners, there's basically a matrix. And that matrix on one side is

matrix. And that matrix on one side is size of business that Snowflake works with from like imagine there's like two tiers within mid-market and then a tier in enterprise. And then the other side

in enterprise. And then the other side of the matrix matrix is by vertical. And

for every partner they work with like a 10X or a morning or whoever, they want to place you in a single one of these boxes. They want to be able to say 10X

boxes. They want to be able to say 10X is the mid-market partner for healthcare companies that are trying to do a snowflake migration. And so what I

snowflake migration. And so what I basically said is for a 10X right now or for you guys having that the pitching that partnership with one of these companies is harder because we do many

things. So actually what I was saying to

things. So actually what I was saying to him is okay you're in Europe and you're in like the physical goods business like industrial or manufacturing business right now. I think what you should do is

right now. I think what you should do is given your context you should host a few dinners with manufacturing or industrial seauite level people in your geography

turn that dinner if you can get one customer out of it it's great turn that what's do great work for that one customer get a few more referrals then ideally go to a software partner where

you can fill their gap for like the mid-market industrial focused AI transformation partner and your odds of landing that partnership is way higher than for either of us on this call right now.

>> Yeah, I guess that as a as a good way to kind of wrap things up is we've just talked about how unclear and like how many options there are on the on the revenue side and like how what the actual model is for this whether it's the the partnership or whether it's just

outright dev whether it's like a portion of the upside. At the same time, we've got this like general general disease where the curse of being a general agency where you can't really fit into

one one bucket. You haven't got very like refined processes. It's always very very different between customers. Um,

looking ahead into I mean one that's it's a very very obvious sign that this thing is literally like just popped out the womb and it's it's like screaming its head off right now. Looking into

next year uh years after uh we're looking at a do you expect to see within the next 12 months specialists popping up in different categories and saying hey we're the AI transformation partner for X industry or do you think we've got

a little bit longer runway for that? cuz

I think people will start to see guys like myself and you but the general audiences go like you just said like oh like okay I just but then there's like issues like talent and you know so there's there's a lot of barriers in

there so what do you think the the roll out of those look like? There's a few thoughts. One is like a very meta

thoughts. One is like a very meta thought that I've thought about for a while. But yes, I think um basically

while. But yes, I think um basically let's just say right now there's a thousand AI transformation transformation businesses in the US doing more than a million dollars a year

right now as an example. My guess is that it's going to 10x in the next year and I think it is going to entire like most people who have business sense are going to specialize. I just think it is

the path of least resistance. So I think we're going to see a huge explosion there. I think for businesses like yours

there. I think for businesses like yours or mine, an interesting thing I always think about is like what is the digital of equivalent of a franchise business

like if we're a franchiseor, what does it look like actually where 10X has 10 subsidiaries either that we fully own if if it's not a franchise business or you

know uh are owned by others but in our case I think about us owning it but like that have different names >> taking your and yeah >> or or or different names or 10X

marketing, 10X retail, 10X industrial that all have dedicated landing pages, dedicated case studies for that vertical and are all basically the the service provider for all of those leads is

effectively the same team. And maybe we have pods of our engineers and technical strategists that are organized by the franchisee.

>> Man, that is a [ __ ] ton of work to put to put that together. But I yeah, I think that if you are going to keep General at the top and run off a brand like this, then uh I guess that's the

that's definitely a model worth uh worth looking into.

>> It goes back to the old adage of like no one got fired for buying IBM. It's like

every person makes a decision that where the risk profile looks such that they won't get fired and you're way less likely to get fired if you pick the service provider who's done similar work before.

>> Wow. I think that's uh we could probably wrap it on that. I think that's a pretty good good send off.

>> This has been fun. Could could jam with you guys for hours.

>> Yeah, exactly, mate. Um, no, this has been awesome. Uh, you guys, you the

been awesome. Uh, you guys, you the links for Alex and Aman will be in the description below, guys. Um, really

appreciate your time and appreciate having uh someone we can chop it up within and talk about cuz I mean like like been going deep on here. It's just

anyone's bit where this goes. Y

>> you can say directionally there's going to be more of these service providers.

is there'll be specialists but stuff around like what that that like is there going to be the DIY thing for small businesses is therefore the safe place medium and so yeah like I like you said could talk about this forever but I'll

respect you guys sign we have to chat another time >> this has been great thanks for having us >> thanks guys >> so that is all for this episode of the podcast guys if you want to see something similar that I really think you'd like you can click up here to watch another one and remember if you

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