The Science of Scaling & AI - Mark Roberge

Normally I go into a long list of who the person is and what's going on.

“Sure, I could talk about Mark exiting out of HubSpot and the fact that he's runna fund and the fact”

that he's a professor at Harvard and the fact that he's been rigorous and broken down the science of scaling in such a way that I've already changed how I operate my businesses after I got off the call with him. But that's not the exciting part of this episode. This episode is absolutely my favorite of the year because he breaks down not only where AI is going to be for the next 30 minutes but where it's going to be in the next 30 days and more so than next 30 years. How it's

a fundamental change of how we run our orgs, how it changes leadership and how it changes scaling across the board. This is one of those episodes where you stop, take a breath and then re-list into it. That shows starts now. All right, we're going to welcome back to the show Mark. I'm excited to have you on that. Thanks Charles. Great to be able to jam with you here. So for the four or five people on this planet that don't actually know who you are which is wild to me. Could you give it a little bit of heads up? Who

are you? What'd it be done? Oh, come on. There's a lot of people that don't. Yeah, I guess at the foundation, I'm a tech entrepreneur. I've just found very like variant ways to express it. So in the

first part of my career, probably about 15 years, I started three companies, three or four. The last

one is the one I'm most known for, HubSpot. I was the fourth employee there joined as the first sales person and then it was the founding CRL through the IPO over a nine-year period that I ended back in like 20, 13. In the, the goal to take a minor break, I was fortunate recruited to join the faculty, full-time at Harvard Business School, to teach sales to the MBA program, build and teach the sales program, which I still do 13 years later. So that's been a blast and has been quite

instructive to some of the things that we're going to talk about here in the pattern recognition that comes from that post. And then eight years ago was approached by a gentleman at Bestimmer, venture partners to start the first VC for running back by the best sales and marketing leaders in tech, which we have done. It's called Stage 2 Capital. We have four funds that we have raised and deployed across 150 startups and that also has been quite instructive to what we're about to

talk about today. Yes. There's a lot there. There's Hubside. There's Harvard. There's Stage 4. There's a bunch of stuff you're doing. That's moved around. You and I have started it to kind of the same start line but then you outran me within about three seconds. So thank you for that. Oh, come on. Just different expressions. Yeah. And actually, I forgot Charles, which part you are talking about today too. I've written two books. One of the sales acceleration form of the

12 years ago after HubSpot and more recently published the Science of Scaling, which we can, you know, we've been today. We'll talk a little bit about it. And I've donated the proceeds to all to both of them to different causes. The most recent one with Science of Scaling, 100% of donate to mental health. So we might be able to take a little tangent on why they're donors. Let's go

“right into that tangent if you want to. Let's talk about what we're doing. Let's do it again. It's all”

good. Yeah. All right. So everyone talks about the scaling and how important this is and all that, but most we were terrified of AI right now. And they don't understand that artificial, it doesn't

mean artificial intelligence. It means it always isn't correct at the moment, but that's going to

change. And the next, you know, 12 to 36 months. How do you scale and leverage AI versus just being terrified of it? That's going to eat you alive. Oh, yeah. Everyone's talking about that right now. I have to do a lot of thinking about that as a part of my job. It's also a part of my just natural curiosity. I love tech in the way it can change society for better and for worse, you know, leaning into the better and mitigate the worse. And that's part of what we're trying to do. Let me give you a

construct. Probably it's hard to know how long of a period this construct is. I think like when we had the shot, heard around the world in November of 2022 with the release of chat, GPT, the version of what viral. I mean, at the time, if you remember, people were predicting like,

“no humans would have jobs in 18 months. You know, like, so I think like historically so far,”

I feel like Silicon Valley has been probably a little too aggressive on their prediction on timing. Okay. So we have that backdrop. This is going to take longer than the techies are predictive. But it's going fast. I mean, every quarter, it's like, it's crazy to think back three months ago where we were and where we are today. And so let me give you sort of like a longer term view of four potential phases that are specific to go to market, but can be extracted to other functions.

Okay. So phase one is really the elimination of all work besides humans talking to humans. So you still have human sellers talking to human buyers, but a lot of the other work goes away. That's pretty much measured by selling time. You know, selling time is an industry standard

And over the last few decades, best in class or bugs have gotten that to like 25 or 30%. Which sounds embarrassing and low and it just kind of shows the upside that we have. And I do think even this year, some best in class adopters of AI in the sales ore can get that to 75% and that's going to be a profound improvement in productivity. Okay. So we'll circle back to that

“because that's the shorter term opportunity that I think you're asking about Charles.”

Phase two, I do think at some point we will have AI agent sellers. We're starting to see some signs of that in the tech. I think it will start with like what we see today in product lead growth, very transactional, maybe SMB simple sales. I don't think it'll ever get there in like the big

million dollar deals. I think you'll you'll still have humans evolve, but I think we'll start to see

a trend in that phase two. Phase three will have AI agent buyers. If you're doing a new ERP assessment for a large global organization, I just think AI today can do a much deeper and more accurate assessment of the needs of the ore than a hundred-person global committee and can assess vendors without being contaminated by stake dinners and golf outings and you know Taylor Swift tickets, whatever. And so

“so I think we'll have that in the next later on. And then finally, if you want to talk star track,”

I think the phase four is the functional boundaries within an ore blur. I think if you extract

the organizational design back to first principles, the reason why we have a finance department

and a marketing department or product department and an engineering department, a sales department, is because of human limitation. You know, you don't see a lot of people who study finance and then go code and vice versa. And so we build these departments around our, you know, what we've studied and and the experience we've built up, which has advantages, but also disadvantages. Those boundaries create inefficiency. You know, finance would love to be closer to revenue,

product would love to be closer to customer support. You know, like there's, there's just a lineman. I think in phase four, those will blur and you'll start to see organizations that almost operate more like GMs of business units with that are very agent-enabled, very cross-functional. And so like whatever, we can talk about, yeah, but let me circle back Charles to your short-term question of like, you know, what, what does it look like in like sick the next year? And you know,

I show up to a lot of board meetings and people are like, hey, good news, like, we are so AI-enabled in our sales org. Like we are so AI-advanced and I'm like, prove it to me, dude, like, how are we

“measuring this? And so that's what I'm kind of been working with the ecosystem on is how do you”

measure in 2026, how AI-enabled your sales team is? And my working hypothesis now that I have a decent amount of conviction on is the two input measures are one selling time, which we talked about.

So first off, measure selling time, right? So like use AI to like see how often your reps are

either in meetings with people with a calendar integration or on zooms with people with a zoom integration. What are we going to do it? And try to get that to 75%. And then the other one is your rep to manager ratio, which historically at least in tech has been seven to one. And that varies if inside or outside, whatever. But like today's AI can coach reps better than humans, most human managers. And so you can push that to 15 to one if you if you've adequately enabled AI as a

deal support and deal culture, okay? So that the combination of selling time going from 25 to 75% and the combination of the rep to manager ratio going from 7 to 1 to 15 to 1, I think at least will double productivity per rep. So if you had Marty and Jane produced in 250k a quarter for the last three years, they'll be produced in 500k. At least, which would be profound. Now that's like pie in the sky. I'm happy to dig in Charles to very specific use cases on how it works, but I'll let you

take it from there. Yeah, so there's a lot of different things there. Like how the silos are the orgs are starting to blur. So you know, marketing sales and then you've got tech and you've got accounting. And I still love that HR still is its own silo on its own and no one still wants to talk to HR. Makes me happy. That's just me ripping on HR. From there, when we get into the AI side,

And before we even jumped on the console recording, we talked about how what's happening right now

isn't what life's going to look like politically or economically in the next 30 years. And there's a value this idea of just can we survive through the next garbage that we're dealing with right now. The influx of how things are changing right now politically or economically. How do you see that also playing into it? Because everyone's talking so much about AI right now. Not understanding that we have huge ways of how we operate across the world from data centers to politics to power,

“to all those other things are changing pretty intensely. So how do we survive the nest?”

Fortified. Yeah. Let's go there, Charles. I rarely get to on podcasts, but dude, you're a guy

that we can do this with. And we have to take off. I should probably take the vest off

because when I'm about to do this clip, I am not Marker Bears, Managing Director of Stage 2, Professor at Harvard. I am Marker Bears United States citizen and Ukraine. Okay, so this is just me, guys, all right. And if you try to twist a shame on you folks. So yeah, I mean, it's crazy how much effort time capital is going into building AI and not thinking through and how society can adapt. Correct. And that's troubling. And that's part of why I'm donating

the proceeds of my book to a mental health because I do think that all of us in tech need to do more to balance that. Don't just build, but help society adapt. We can't delegate this to

Washington or academia. Not because they're not qualified, but because they're just not close enough

“to it, to really understand at the level that you need to to look ahead and help society adapt.”

And with each tactical revolution, let's like we most recently live through the internet one, we do come out the other sizes of species evolved, but it doesn't come without its scars. And you know, we are still experiencing them from the internet way of specific and social media. And they're going to be worse if they aren't mitigated in AI. Yeah, so, you know, when we go, we talk about social media. Like, oh, we're going to be more and more connected. Then if you look at

the patterns of the last couple of years, people who want to do early exits, which is a nice way of saying, you know, often themselves radically increase because loneliness increase, isolation increase and bullying increase and all of these things because we're being fed dopamine hits that are coded very specifically based off human behavior to make us react a certain way. The positive for that for the companies are we're glued to these little screens. Because if I were to told you because I'm old enough

in '48, if I were to told you when I was 15, 16 years old, then I'm going to be staring at a screen for 10 hours a day. I'm like, you're out of your mind. Go outside, the graphics are better. But as someone who was on Microsoft Trainer, I got to see upfront. I'm like, this is fundamentally changing how human beings exist, how we interact with each other, how we interact, how we make money, how we connect with human beings with each other. AI is just the amplifier of that, where I used to say,

alcohol is an amplifier if you're a jerk before you drink and I give you much alcohol. You're going to be a bigger jerk if you're a goofball and I give you a bunch of alcohol. Say, "Vix, everything with money." AI and tech is that force multiplier as well, where it just takes off and it scales it and I do agree with you. It's evolving us at a rate that I don't believe we as a species can keep up with

“fast enough without some help. Yeah, and I think like if you want to go there and this is”

an area where we can talk later more tactically about the principles of the book on like how to scale revenue, which I'm one of the most well-read I think in the world if I could say that humbly and I can speak to you in depth there. One of about to speak to, I'm not certainly at that level. I'm not an economist, I'm not like a politician, but I am a tech entrepreneur. I think I'm decent at vision and I've also had been curious about this for many years because I don't want to bring

a tech into the world that harms society, so I think it's important that we think about this. My personal opinion is you have to zoom way out to like almost a multi-thousand-year view. I do think this movement around AI is not comparable to the transition to the internet. It's comparable to when we went from a nomadic species to an agricultural one. It's comparable to when we went from feudism to democracy and if you look at the deep histories there,

there was a lot of skepticism as to whether that could even be had and there were multiple generations of massive pain in the transition. If you look at the history of moving from nomadic to

enough animals to eat if you just stay in the same place?" How are you going to protect yourself

“from attack if you stay in the same place? Everyone's going to know where you are, and they tried”

it and everybody went back to nomadic because not only did those things happen, everyone was

dying of disease because as a species we'd never lived in close quarters with animals for so long

that we didn't adapt. People gave up on agricultural for three generations, but after living through a hybrid they eventually figured out and got there. Now when you look at feudism, we got kings and queens with walls and we were protected. Now as someone like Adam Smith comes around with the wealth of nations and is like, "Hey, if you make people free, if you give them free will, everyone will be better off." It's a thing called capitalism. And they're like,

"What are you talking about? You're going to let the peasants decide?" You're going to create

like mass hysterical, like craziness. And yeah, United States was this wonderful experiment, was it easy? No. In 1840 we were killing each other in a civil war. Do you think people thought like democracy was working? When you go through these massive ships, if not mitigated with massive intelligence, you go through generations of pain. Yes. And the pain that is coming upon us is we have a very difficult situation. And I'll speak specific to United States government

“and some of this can be applied to other government entities. I believe in our long-term mission,”

which is human rights and freedom. I believe in that. And I think we have been the world leader on that mission for centuries. So I want to see us continue to drive that mission. It is questionable on the short recent years, how well we've done it that. But like that mission is going to be tricky because our version of democracy and capitalism are economy is likely not compatible with AI, a post-AI world. Our version of capitalism is like 2% GDP growth, 4% unemployment, you know,

start work at 22 and at 65, work 8 hours a day, 5 hours a week, 2 weeks vacation. Which by the way, why is it that way? It seems all right. Why is that? And that's not compatible.

I don't think with a post-AI era. Now, on one hand, and this is the first risk we have as,

you know, a country is the first in sync as well stop it and slow it down. Turn it off. And that's actually being discussed. That'd be awesome. But we're also in the midst of a military war too because it's almost like nuclear weapons are being developed. Because whoever builds the best AI can also build the best AI army and take everyone else over. So if we stop it or regulate it, we significantly run the risk that other entities are become better AI and we'll take us over.

And those entities may not believe in human rights and freedom. So we have to go as fast as possible. But at the same time, we have to adapt our society and economy to the realities of post, you know, AI. And that's really tricky. It's almost like a higher form of entrepreneurship where you're almost like building the plane layer flying it. Now, the last thing I thought I'll leave you with Charles and this massive zoom out and lesson to your thoughts is this issue becomes perhaps slightly

easier to conceptualize a positive outcome when you really think about what the goal of our economy is. Because the entire discussion is around GDP growth and employment. And no one is talking about surprisingly rigorous metric called the happiness index. Because I just wonder if like,

“are we really trying to be like economically accelerated and employed or we're trying to be happy?”

And I'm not suggesting socialism or anything like that. What I'm suggesting is like, we aren't by this metric. We aren't happy. We fall into 22 in the list of countries.

during the day and driving Uber at night just to look for Ford rent. Like we're just not happy.

“And when you look at this like what AI just like AI can do the things we talked about a second”

ago on sales and totally it can do that in our lives. Like we can have we can work two days a week five hours a day so that we don't have to outsource our kids and our parents anymore and have time for hobbies that actually lead to happiness. We can have a better quality of life because of that. God forbid we don't have a job. We don't have to be on food stamps living in a brick house. We can actually live in a nice condo with free healthcare and shop at Whole Foods. And we can have a lower

tax rate. It could go down to 5% with a smaller government, less socialism. We can have it all be more free. And I just think like if we can reframe this around the pursuit of happiness and health and not employment and GDP, things start to make sense. Yeah. So there's very little of what you just said that I disagree with. You know, this when I discuss AI and they say how big is this culture that I'm like this is the equivalent of the discovery of fire. I'm like yes going to fundamentally

change everything. And everyone's worried about the current title way that's hitting them. Not seeing that there's six or seven after that one that are coming and you've got to learn to yes. If I sat down and I told you the late 90s, hey, there's this new thing. It's the internet. It's going to take over the world to change how we do business. And if you're like no, I'm not going to adapt to the internet.

That's just not that's not what's going to happen. I'm never going to go on one of these

screens. I'm not bringing the internet in my house. You're so well. It just you cannot stop it. It is coming. It is a title wave. It's a situation is you're going to have to ride this wave and adapt to it or you're just going to get your gone. It's over. It's a fundamental change in the human species. So I agree with that completely regretably when you talk about if we're going after employment and and GDP versus happiness statistically. And just if we walk around, I'm around

individuals who make more money than I know what to do with. These are very successful entrepreneurs, most of the people are billionaires. I would say the majority of my people who are clients at least

“don't have bad days. They have days where they don't want to have any more days. And that's why”

I would love to be a mental health side of this is most of the guys are miserable because to dumb it down to the audience, think about walking into a bar and you ask of our tender for a glass of chocolate milk. And he says, here's a glass of orange juice. No, I'm sorry, chocolate milk. Okay, here's two gallons of orange juice. No, no, glass of chocolate. Here's three hundred

gallons of orange juice. You're never going to be happy because all you wanted was you're

trucking them up. But most of us have no idea what that chocolate milk is. That's going to be make us happy. And on top of that we're in a society that says, no, you don't get to decide what chocolate milk you want. I need you to get out the zero to our country. Work all day, go to sleep, you know, be around your family for 27 seconds. And then repeat that for the next 40 years. That's going to create problems. And there's going to be growing pains across the board.

But I agree with you. There is this idea that we have to look at it as it's inevitable. We have this inevitability of AI. How do we start going towards where we think we want to go versus where other people want to go? Just some people to your point, the Uber drivers and the people working full-time shifts. They're like, I'd love to be happy right now. I'd love to be driving somewhere and heading towards that, but my car is on fire. And there's a lion in the back seat

trying to eat me. Can we get rid of it? Can we put the pin in the grenade first? So I get there's

this conceptual idea of, I want to be happy and let's change it. And this is how I sleep and run like therapy. And we were just in the glasses and the type of food and going to eat it, whole paycheck and said, you know, all of that, I get that. But there's so much of society, even outside the United States that is just trying to put the pin back into a live grenade.

“And that's going to create growing pains. And it is what it is. So I think it's a long-term play”

above and beyond even what's happening on the very micro-political right now, which I will leave alone on this podcast because I don't discuss those things on a recorded line. I think they're outside of what's happening right now. The long-term play is no matter what, we are going to have some serious growing pains. It's a society that you knew back in the early 2000s. It doesn't exist anymore. Just like society that I grew up with in the late 80s or in the 90s, that's gone to,

you know, that nostalgia is nice, but that's not where we're going. We've invented planes, we know how to fly, no one's taken a boat, made out of wood across the ocean anymore. We're in it a different world. So I grew with all of that. I want to get back to what you are known for, so you can't put the jacket back on and we can talk about the logos and all of that to to play fair. There are things that you're really well known for and that you're really well

read on. What are the things that drives you is what I'm curious about? What is the passionate thing that you're like, "God, I wish more people do this about economics, about scaling, about these the questions that when you got those couple students at home and they come over here and they want to ask you questions and you're like, "These are the questions that I love the most. I wish I could talk about this more because this is what they're missing. This is what isn't in the books. When we

you're like, "God, guys, forget everything I teach publicly. These are the conversations. I wish you guys knew this." Yeah, okay. So let's get back to like today and let's get back to like, you will change something in your business after this podcast, like within the hour. Okay, so it's really about the scaling and turning scaling of revenue from this like, "Lick your finger, put it in the air. Do it how open AI or Google did it to actually a science."

And this has, you know, this work has been something I've been working on for 10 years. I never

“intend to honestly write a book. I literally just like go out when people ask me to do speeches,”

just like you Charles. I speak about what I'm seeing and I do that. I probably create a new speech twice or two or three times a year and usually launch it in like a big venue like South Buy or Sastro whatever. This particular work dated back to a speech at Sastro in 2019. And again, I've done, I did 20 speeches, 20 big new speeches before 20 big new speeches after this one happened to just go massively viral and people ask me to keep writing, I keep speaking about it and eventually like

Stanford's like, "Can you write this up?" Right? And it really was a reflection on like having

been in the board room for so many of these companies watching some go IPL and many go bankrupt.

What was the common theme? And the most common theme was the strategic decision on one

“they decided to scale revenue, which in a B to B context means add sales people and a B to C context”

means five extra marketing budget and how fast they decided to do it. And it's actually been absurd how how hazard it is. It's crazy how many classes we have in college on how to account for an accruly revenue and next to zero classes on how to scale it with the same rigorous frameworks. And that's really what this journey has been about is to to bring those frameworks so that people can calculate using their own data when they should scale and how fast. Okay, so let's let's

extract that back to a couple principles. Oftentimes when I start this out with an audience and your class, whatever, I'll just be like, "All right, well when you read this scale?" And a common answer is when you're product market fit, which I like. Product market fit, I'll credit Eric Reece with the Lean Startup at the beginning of the century and really evolved us as entrepreneurs from building products, haphazardly and a lab to co-building products hand in hand with customers

in an agile way, beautiful, beautiful change to product development. And the out of that came that's a word product market fit, which is cool. But when I asked 50 people to define product market fit, I get 50 different answers, which does not do well for a rigorous framework we're trying to make a credit in the season route, right? So, and in fact, most of those answers are either when I have 100 customers, when I have 500,000 in revenue, or when I have 1,000 in bond needs,

“all of which I think are wrong. You can define however you want by my fall of question to each of”

those answers is like, "What if you have those things?" But half the customers turn and don't like your product. Do you have product market fit? Well, no. But the founder will say, "I'll just adapt the product to their needs." I don't know, but I'm like, "Okay, well, how will you know when you got it?" It's like, "When they don't turn and I'm like, exactly. Product market fit is not about selling people, getting revenue, closing customers. It's about the customers realize

in the value you promised. And that is best quantified by retention, whether you're a software company and they come up on an annual renewal and renew or you're a sweatshirt company and they buy the fall addition and then they buy the winter addition. That's when you know you have product market fit. And so like we can unpack that more, you know, the book goes into like, "How do you create a leading indicator around that?" And like codified the whole thing just like you

wouldn't ink and statement or cash for though. But that's really the first goal of that decision

is a more rigorous definition of product market fit rooted in customer value creation and retention. So if you've got one and just to get to people out there, let's say you've got a product that's you're driving in thousands of new subscriptions every month, butterer. And you're crushing it and your turn rate on that is 90 days. And you're like, "Hey, I'm known for this. When you're having

and owners, what are the first steps you do? Because I want to make this reduce and I want to

“make this scientific because again, this is it's proven. This is what works you do this. You do”

this, you do this. Churray chute and most of the industries for almost everything, it's huge. There's only there's very few people have cracked that code and that people who have cracked that code are seeing some crumbles in that foundation as well because the market changes and what people want changes. So there's always this adaptivity to it. When someone's in this like, "Hey, I'm doing a great job getting people in the door, top of my funnel is full, we're converting,

we're closing them and they were spitting out for whatever reason." Even if they have phenomenal service, even if they're doing ABCDE, how do you reset there? We're like, "Oh crap, I'm losing people. We have spent all this. The LTP on these individuals is just, it's collapsing. What are some of the things that you've seen that could be kind of, again, back to rigorous because I love

“that word, that you can go through and mark that out?" The first one is instrumented, so we understand”

the second one is like diagnosis and fix, okay? So the instrumentation is critical here because

often times this measurement of retention is a lagging indicator. You know, you just said it Charles, like I've got these subscriptions coming in and like 90 days later, or a 100-day days later, they're not renewing. So you can't make a bunch of fixes and then sit around for 90 days and wait to see what happens. So that's the first step as we have to bring that measurement back to a leading indicator. And I call that the leading indicator retention, okay? And as a rigorous

framing, I suggest that you define it as "P% of customers do event every T-time." Okay? So now I've I've honed this in on the decision of three variables, P-E-N-T, okay? Now let me just like try to bring that to life to conceptualize a bit. For slack, it was 80% of customers send

“2,000 team messages every month. That's beautiful, right? So like imagine Stewart at the founder”

of Slack being like, you know, there's five engineers in the room, they're about to put the first

version of the product out. And he's like, "Our first goal is to get to a million in revenue."

Like you can see how the organization would react. Higher bunch of salespeople try to increase ACVs, whatever. Or, "Our first North Star metric is to get 80% of our users to send 2,000 team messages every month," totally different set of actions. We're really close Microsoft on post sale activity, user happiness, like what bugs are preventing that from happening. Right? So that's the first step, all right? So like, for HubSpot, it was 80% of customers

use five or more features in the platform every month, okay? So like we can we can talk about how you make the decisions on those. But point number one is, take that long-term metric of attention and bring it back to something you can measure one month after a customer signs up. So we know if we're fixing it, okay? The second part is now you can diagnose why that's not happening. And so you have a couple options there. Like let's just say half the people are

churning. Half the people aren't hitting that lead indicator of attention. Right? Well that means half of the more. So oftentimes you can like look at them from a persona or segment perspective. And you can like, oh my gosh, everybody who has more than 50 employees is hidden it and everybody under 50 employees is not. Well great. Let's now only acquire people with more than 50 employees. Right? So like that's a very simple example, but like that's just really a refinement of what we call

the ICP or ideal customer profile. So sometimes you can do it in that way as long as that ICP, that segment that's doing well, if that's big enough for you to scale through your growth aspirations for the next three years, you're good. Because you'll be able to scale and hit those goals for three years and that will also give you time to open up the other segments where it's not working to run experiments to tweak to adapt so you can increase that tab and grow even further.

Okay? So that's one. Other ones are just like, you know, sometimes there's product gaps. You got to do that. Sometimes there's onboarding opportunities. The biggest one where the most common one where people look last is how it's being sold. If you're selling, because I part of it's like what we already talked about, which is who are you selling to? And part of it is like, how do you sell it? Are you being, are you lying about what it takes to set it up? Are you lying

about the extreme value they will get? Are you including IT or whoever's needed to set it up in the pre-sale conversation? Like I don't have to do any of these to get the contract, which is the

the user from seeing the value. Right? So, so those are, that would be it. Is number one, you've got to extract the long-term retention goal back to a lead indicator attention that can

measure in the first week or month of a customer's experience with you. And number two, using that,

“you need to diagnose the situation and make some changes to the ICP, the onboarding, the product,”

or the sales process. So, what I like about this is it's very rigorous and we changed our goal from the beginning. We changed the target and then moved it back into and that will obviously affect the target in the long run. It's kind of like the conversation of we have right now where trains are trying to become more like planes and that's it's a guy who's wrong thing to do. People who want to get their fast are willing to deal with discomfort and not have tables. People want to be on a

train, want to have their first class experience, they don't want to be crawled in or do that. So, when you see the Amtrax and you see the trains across the company or across the country, trying to be more like planes and like you're going to lose your more expensive. Your slower,

you're never going to make it. Let's redesign this and because the first class experience,

“I got a table and I get to sit, I have a laid-down chair and I get food and this is amazing.”

Then I have this very nice person bring me amazing food. And if I'm on Swiss Air, I get moving pick ice cream, which makes me very happy and doing all that. But if I'm on a train and I'm on Amtrax, you're trying to make it more like a plane. Stop it. Stop it. Boston to New York, Amtrax. Make the Wi-Fi work. Please, please, a decent one. Hello, it's the whole differentiation. I will take your stupid train if you don't make it like a plane. If I wanted to be on a plane,

it's not that complicated. So, understanding what your clients really want. That changes retention. Have fun, Amtrax. You could use all of this and you're looking forward to meeting, what is you out, you even more. Stop trying to be planes. So, where are some companies that you see this mistake all the time? Where they're trying to be planes? Where you, again, for that example,

“where you see AI or software companies or the people who are, you know, the biggest mistake”

for any of these industries like, "God, you guys, just stop doing this and have some terrible acts." Right. Oh, it's a really good question, especially now, because we are in this like clay Christiansen's innovators dilemma moment, where we've had, we've, we're on the brink of a massive technology shift, which Clay's work has shown that the news start-ups actually win most of the time relative to the incumbents because of what he calls an innovator's dilemma.

And so, you know, we can probably conceptualize this best by looking back 20 years to the rise of the internet and what the innovators dilemma's were then. Now, keep in mind in, you know, the B2B software layer where I spend most of my time, the number one CRM in 1998 was Seabull, the number one HR platform was people soft and the number one IT software platform was BMC. If you look at the market share capture in the last 20 years in those categories,

their capture is a bismal compared to sales force and hub spot in the CRM stage compared to workday in the HR days stage and compared to servers now in the IT management stage, all cloud first startups, right? Why is that? What were the innovators dilemmas? These can often be technology shifts, business model shifts, distribution shifts, whatever. All three of those were drivers. First one pricing. All three of those incumbents, it was like, here's a floppy disk,

give me $4 million. Sales force was like, here's a log in, pay me 500 bucks a month.

They couldn't copy it. It would have killed their stock price. Everyone would have left. In an innovator's dilemma number two, the entire sales team was like, good looking outside sales reps. Sales force and workday were distributed through MQL's past to an inside rep. It was two politically disruptive to do that. Number three, they had to rebuild the floppy disk product to a cloud product. McKinsey was literally in there being like, it's going to cost you a

billion dollars to rebuild this. We just interviewed 500 CTOs in 1998. None of them said they would ever put their data in the cloud. No one's going to buy this thing. Innovators dilemma, the rest of history. So the question now is, what are the innovators dilemmas that today's no name AI native startups that are happening at Caltech and MIT and Harvard today? We'll take over the category,

listening to customers exactly on what they want, you will be iterative and fall into the

incumbents world. Customers are terrible. Yeah. Customers are terrible visionaries. That is your job. Yes, listen to customers that's the near-term value, like show them the vision, evangelize it,

“whatever, but to your point, like you, you have to be close to customers, but you can't let them”

dictate your vision and business strategy completely. You have to be a visionary especially in this moment. So here's the question I have on this one because I run to this all the time where people come in and like, hey, can you help me scale? There is conversations where I'm like, yes, but not you. In other words, you're so big over here and you're doing this that if I make these changes, I won't make it out of your board room alive. Your staff will lynch me. It's not going to happen.

To make these scaling changes that you need to do, an example of this is Citrix, that the conversation in that world, I was like, guys, it's over. Give the best parachute you can can to your staff. You do the best and you can't do them. It's over. You're too big of a ship to do it to turn on a dime. There's a lot of people who when they look at the science of scaling and they were like, okay, I've read the book and I'm going to do this and

it's going to be amazing. You're like, that's adorable. That would work if you're a pigeon,

not if you're a triceratops. Just it's just the new. How do you deal with that and that of the people come in? It's like, hey, I'd love to be able to do this. I read your book. I understand what you're saying. This all makes sense, but I'm a cruise ship trying to do a 180 in a puddle. What are you doing? Great, great context because it's a good and just to give people the context here during the time between HubSpot and Stage 2. I spent five years as a senior advisor at BCG

doing about a different engagement every quarter with companies that were doing north of 10 billion in revenue, global helping them with this situation. And I've also like, you know, done a lot of 10-genial work around, it speeches, etc. And so this particular work, the science of scaling is not just for brand new startup, build new product today. It is also the way that a 10-billion-dollar company will bring a new product to market or take their existing product to a new market. Either way,

you follow the same steps. Okay. Now, the implementation strategy is kind of what Charles is digging into here, which is it's not advisable to completely blow up the org and just try to push this into

“the core org. Sometimes you have to do it if you're just dead in six months and you have to like,”

you know, the sneak just needs a big answer quick. But that's like, uh, hopefully a Hail Mary

you never have to deal with. What instead you should be doing is running small experiments separate

from the core or as separate as possible. And this is right out of Clay's work and also got a name Michael Tushman in the Ambit Dexter's organization if you want to check out his work. Where you're running his experiments to almost essentially disrupt your shelves. Okay. So like, the problem like we talked about Citrix for a second, the problem with a lot of these large incumbents is when they're thinking about how to redefine the sales in the AI era,

they do what I call an inside-out strategy, which is like, okay, what do we have as leverageable assets that we can bring to the AI opportunity? That's what causes you to get disrupted.

“Because the right answer is you have to like remove everything we have and just say, okay,”

what if we were starting a company from scratch, clean slate? What would we build, knowing what we know about the problem, the way this problem will be solved in a very AI mature area, era. That's the answer. Now it's like, how do we go through the difficult work of having this to get over there as fast as possible? And usually what that entails is, let's take 20 engineers and 10 go to market people, support sales, marketing, whatever, and like open up an office as far away

from headquarters as possible. Maybe we even acquire a small startup to do with it. And like, let's give them some sandbox. Maybe like we're struggling in the southeast, let's take the southeast away from the core business and give it to this little group and see if they can create the vision that we just did brand new product, new distribution, new price and model, whatever, and see what they can do. The board's not going to be all up. The board's going to

be psyched about that. It's like, it's like 0.01% of your span and 0.01% of your revenue. It doesn't matter. But then let's be clear in the principles of the science of scaling. We just talked through a couple of them of the milestones they have to achieve and like hopefully they succeed and then we can give them the Northeast and then the Northwest and then the Southwest and then we can give them Asia.

not essentially cannibalizing yourself systematically and you're giving that team a shot to go after the right answer as opposed to being, you know, distracted by the competencies of the current legacy

org. Right. You're having this self cannibalization first before the market does it to you.

It's the idea of, hey, you might be the best hockey players in the world and you show up to the

“rank, but if that rank is now a pool, all of those hockey players are done. It's over. So you have to”

be able to pivot and do it beforehand because, you know, again, using Citrus as an example, Sorry, y'all, y'all, j'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y'all, y Well, it's not an ice rick anymore, deal with it.

What are some specific scientific or back to our term of this, this podcast, rigorous ways? Because when I think about this, most businesses, it reminds me of the movie, it's probably going to be too old for this reference, but there was a movie called The Last Star

Fighter, and there were sitting there spinning out, and at the very end, it's like, we're about to smash into this play, and what do we do? And this thinks smash is in front of his eyes, like, we die.

Most people are in the humor.

Most of these people are like, that's where you're going. You don't have this. How do you innovate? How do you teach your squad that, okay, we've got to innovate through this? Is it through acquisition?

Or what are the ways that you normally do it? Yeah, any of them can occur.

“I think in this AI where I'm talking to incumbents,”

I do prefer acquisition, because to your point, I do think that one of the biggest innovators dilemmas for this cloud to AI shift. He's not necessarily going to be in the product offering or the pricey model, those will play a part.

But they're going to be how the actual company runs. Right, like, kind of the stuff we were talking about in the beginning with phase one, two, three, and four, getting to that GM model, if that actually comes to life, your current staffing is not set up around that.

And so, like, if that, if we have a significant evolution, rapid evolution and it's happening in how a company is structured and runs. And that changes the optimal hiring profile and skill set of an engineer and a seller.

It's going to be a lot easier for a brand new company to have that answer and run in that way and pass those advantages onto the customer than it is for Citrix to retrain everyone or reorg the company around it.

So I think the org design and skill capabilities internally is the biggest innovators dilemma.

“And because of that, I do think you have to solve”

this through acquisition to acquire that talent, nucleus from the beginning, keep them separate, let them run at the right answer and systematically cannibalize yourself. And the other transition to that is being very aggressive

on your corp-dev team and your venture arm. Like, probably triple your budget there, triple the staffing. That increases the amount of years and eyes you have on the ground of what innovations are happening in your category.

It allows you to make investments, make acquisitions

to basically codify this.

So that's kind of my move with the big companies right now. So one of the things that people are talking about what's in their orgs is personnel and leadership. That because the entire ball game has changed and just to stay with the example,

it's no longer an ice drink, it's not a swimming pool. Leadership and how we interact on human behavior is going to evolve as well. The way that we interact and we led back in the early 90s is very different how we do it now.

I'm very blessed to be around some individuals who are operators. And they talk about how their leadership had to change from when they were downrange and Vietnam versus when they were in Iraq versus what we have now. Those things were changed.

We're implementing one of the notorious ones that it's this concept of extreme ownership and using decentralized command. And it's worked very well for very long time. AI is disrupting that as well.

What do you see from the human behavior side from the leadership side? When you're building these org charts, which are now completely different and we're no longer siloed except HR, you go stay over their HR.

These other silos that are connecting and they're doing this, how are you seeing leadership silos change as well and how do you leverage that in scaling? - Yeah, I mean, I think there's like, one, you're reversing the specialization movement.

In 1992, in the R&D org there was one role

“and it was engineer here, like computer programmer, whatever.”

And now it's product manager, fun and engineer, back an engineer, designer, data analyst, data scientist. Like, it was the right thing for that time. But we're starting to see trends where like PMs are being asked to do more of the deployment, right?

Because of the advancements of like, in simplification of product development. So that has a pretty big implication on the org as well as the leadership is, leaders are really hiring more like founder types, athletes

as opposed to specialists, right? And you see the same thing in the go-to market arena. Like, we had one role in 1992 and it was salesperson. Here's a phone book, here's a territory. - Good luck.

- And sell some customers and renew them, right? - Right. - And like, fast forward 25 years, we have STRs and AEs and ANs and CSMs and SCC, super specialized. I think we're going back.

I think we're going because of AI. Like that specialization has some disadvantages starting with a terrible buyer experience who gets past from one person to the next. - Right.

- So like, we're going back because the advantages don't offset the disadvantages in a post-ARA. And that has a massive implication on the leadership structure that you don't have these siloed departments that need to be aligned.

You instead are measuring almost like many business owners. The amount of you many business owners, which has an implication on your hiring model, your ramp model, how you hold them accountable. - I think the concept of going back,

we started with this idea that, hey, we went through no matter, not no matter if I'm backing up, this going back, circling back to that. And that brings me to, because you are connected to Harvard, this is this idea that we have right now

that college is garbage and no one should do it and it's a dead institute and it's just, the time has passed and it's not something valuable anymore. Most of the people I meet who are young,

they're like, I'm never going to college.

Why would I waste that money? That's stupid. That's where I was going, yeah. Do where are you at that ball game? Where's like, should we do this at all?

- There's a lot of like, it's just so friggin' expensive. And I have some colleagues, Steve, for example, is doing some great work on this at Harvard. Where I do think like, I hate to say it, but some of these like lower tier colleges

are just as expensive and just don't have the career promise that it's gonna make sense. So like that, it's just very, I'd rather see you do other stuff than do that. Now like, I'll stand behind today's Harvard MIT Stanford,

like that, especially if you're coming out of like, not much. Like it is such a transformational experience.

“I think it's worth it, even though it's expensive.”

And you'll be shocked like the actual real cost to people, the amount of grants and scholarship that is given is extraordinary. And that's not really talked about as much. So I just like, so we have the facts there.

But yeah, I mean, if we zoom out and in the same way that during this discussion, we've blown up and reinvented government economy and so let's go at it with education as well, while we're at it.

Yeah, dude, seriously, you're 18, and you go through four years of school and that's it. And then you're done and in school, you're learning how to be like CEO of a company as a 21 year old, that's stupid.

Like really, and you come out with these stupid, like you studied like 17th century Eastern Europe history and spent $400,000, it's crazy. - Makes no sense. - I mean, this needs to be you graduate high school,

you go to one year of school to prepare you for the next eight years of your life. They've been in individual contributor. Then you go back to school for a year to prepare for the next eight years of your life,

which is basically managing people.

Then you go back to school for a year to prepare for the next eight years of life, which is basically running companies. Then you go back to school for one more year to the next eight years, which is the final quartile

of your career, which might be boards and vester, like chairman, like a philanthropic, whatever. Like, it needs to be reinvented.

“- I agree, I think it was about to be reinvented.”

I don't know if it's the one, eight years things, but my undergrad is an FAU, which is just tiny little college, which FAU does not stand for Florida, Atlantic University. It stands for Find and Mother of the University. And it was garbage when I was there.

And sorry, so that when I lectured at Yale

this is a completely different experience. It's a difference between, hey, here's Taco Bell versus, here's the four seasons, I was like, oh my God, this is not the same. Why are they now being charged the same?

So I agree, so thank you, let me ask that. The next one I wanna ask is, there's a list of books because I believe books and the best things I've ever invested in other than my health. You mentioned a bunch of people.

For some of them who will never get into the Yale's

and never get into the Harvard's and won't be able to sit with you. If they're going to Jesus, I clearly, this is a different way of thinking, that operates differently, and that's producing results

differently and innovating differently. Are there certain books that opposite of their own

“that you need to use a list of go read these now?”

This is the core stuff, you'll get the same, it's a goodwill hunting idea. I got the same education for a library card. What are the ones that you're like, please go read these as fast as you can?

- Yeah, I know that answer cold for, I need to learn how to sell. Like I'm a founder, I need to learn how to sell. I would like to, perhaps, there's always any sell in my career.

And my go-to is a 120-year-old book,

Dale Carnegie's "How to Win Friends and Influence People"

is phenomenal. I love Neil Rackham's "Spin" selling. And I love the work of Sandler, which has been codified in a book, and I love the work recently of Jaco

at Winning by Design. I think his most recent one is revenue architecture. So if you're deep in the go-to market front, that's what I like. As a founder,

we teach the principles of lean startup with Eric Reese at Harvard.

“So I think that's an important, like, rooting,”

everyone loves Ben Horts's book. The hard things about, or I forget the name of it. And I think that's good. I think I'm just trying to think of other influential ones

for me, like I'm a pretty spiritual person too. And I'm a deacon in my Christian church, but I also aggressively read Islam and Jewish works of Jewish, Buddhism, and I love Hindu. And so, if you go down that route,

I love autobiography of a yogi. He's pretty predictive of what's going to happen in this AI era, actually, which I think is a cool work. It's actually the reason I was turned on to it

was I was reading the biography of Steve Jobs. And there was one book he read every year of the last 20 years of his life, and it was the autobiography yogi. So I saw he stumbled across it.

But I think just to zoom out of your question, Charles, I think it's just in terms of, if I consume that out to be how do you educate yourself, it's just that it's dramatically changing.

I just think like, first off,

carve out five percent of your week for personal learning. Like a lot of people just get caught up, and it makes sure you schedule that. And you can just like, star, I don't actually use you start with a book.

I usually start with a question in problem. And five, 10 years ago, I used to go out in social media and read the blog articles about it, and sometimes that led to a book. These days I start in an LLM and triple down in,

“I like perplexity because I think the advice is sourced well,”

so I can click through to the actual sources and check their validity. And that sometimes leads to a reading of a book. But it's really that mechanism that I think is power if we have zoom out your question to how to stay educated.

- I also think starting with the question versus the book 'cause it's the most people don't do. It's like, okay, what is the question I'm trying to answer? Like, yeah, sure, I could read everything about anatomy, but if I'm just trying to figure out how to fix

a scientist infection, why would you start with the actual thing and then kind of pull up? - And you see, you call it even left like what's your point? Like, I want to be a great founder. How do I learn about me and a good founder?

Like, just prompt that, start reading. That might lead to a book, but it might lead to like 12 articles that may actually in aggregate be more valuable to your development.

So, we've gone through the process of how to educate yourself, where the world's changing, the idea that, everything's about to change them, that how to scale. The last one I want to go into is funding. Right, a lot of people get into it.

Like, how do we fund, how do we go into that? When we're standing in front of VCs or we're running into certain capital companies, I know you're connected to this. When people run into that, what are the things

that you wish people would know? Especially as, 'cause you see this over at Stage 4. You know, one of the things that you're running into and that you're like, "Guys, this is a different ballgame "when you come to this world, when you try to come into this

"and we're doing acquisitions, they're funding "or where you're going down with this, "what are some things you wish your people "with no more about before they approach you over at Stage 4?" The biggest thing is like, in the same way

that you only focus your efforts in sales on qualified accounts

it's the same thing you have to do with funding sources, both from the category as well as the individual firm. You would be shocked how often I have to talk entrepreneurs out of taking venture capital, because they will make way more money faster

if they don't. Like, just more wealth is created outside of venture capital companies, just to get that straight. Bootstrap, family businesses, private equity backed. So just because VC says, "No, doesn't mean it's a bad idea

"and you shouldn't do it and you won't make a ton of money." Okay, let's just like conceptualize this for a second. We built HubSpot, Halligan was our co-founder, CEO.

“I think you own 5% of the company when we have public.”

We have a public at a billion dollars.

It took nine years, that's a 50 million dollar payday. Great, okay. I've talked to an entrepreneur last week that is building a feature within the go-to-market stack. I forget what it did.

I think it helped you uncover the intent of a buyer. Okay, I'm like, "Dude, this is cool. "Don't raise venture capital." If you raise venture capital, our asset class invests in companies

that have the potential to exit at north of a billion dollars. If you raise venture capital, they're going to force you to a 100x your product footprint to match HubSpot and Salesforce, which is going to be tremendous risk in take 10 years.

Your chances of pulling that off are low and if you pull it off, you're going to be so diluted. Let's say you pull it off and you exit a billion,

just like howling it did amid the 50 million dollar payday.

He made a lot more with the journey after believe it, but great, great payday.

“And what you should do is just build the product”

that you're telling me about. Go from 1 million to 3 million to 10 million over the next three years. Sell it to Salesforce or HubSpot for 120 million. And you own 90% of the company.

And you made a hundred million dollars in three years. Correct. Versus maybe. Yeah, it's a different bowl there. Yeah, so it's like, yeah, you can pull together

our friends and family million dollar round to get you going, pay yourself a little, put get some engineers, whatever. So the first point is all in the mindset of like qualifying your investor.

That's the asset class. What type of capital is right for my opportunity? Let's say you are good for venture. Let's say you are. I talked to a buddy yesterday.

He's building out like a, like, you know, I think it's like a financing marketplace type thing. Okay. That's a venture back deal.

That could exit a multi-billion dollars.

“You have to find the VCs that invested that stage”

and that type of company. Like people, I get notes all the time. Like, hey, Mark, I'm building a pharmaceutical lab in Japan. That's really cool.

That's probably going to be, like if that pulls off, it's a, that's not what we do. Right, we like, we have a huge endowment that gave us like hundreds of millions of dollars. The reason we got the money was because we said

that we invest in B2B software companies all over the world, everything from pre-seed, just starting to build the product, up to series A, we deploy four million dollars for between eight and 15% ownership. If I was like, oh, hey, we just invested, you know,

two million dollars for one percent of a company. They'd be, they don't even care what the company is. They'd be like, what are you doing? Right. If I invest in a pharmaceutical lab in Japan

from the most brilliant pharmaceutical person in the, they be like, dude, what are you doing? That's not what you told us you were going to do. So, so when you're, when you're, even if you are venture back, make sure that you are not the first deal

that that firm has invested in at that stage in that category. Now, I love all that. There's so many radical technical things that you're giving people, very rigorous, very proven. There are gunna people who want to just,

spend time with you and track you down and connect with you and read everything out of your brain. That just, it is what it is. I'm, I'm one of them. So, if we want to track you down,

because again, it's a little different. I have actually two differently. If people want to track you down and they want to connect with you and they want to learn more.

How do they find you? Yeah, just, I'm most active on LinkedIn. Just go there. I've been there for a long time and I am playing around with Instagram and TikTok morse.

It's probably easier to get my attention there. I'm just trying to make sure that, you know, the, the young talented techies in college. I don't know where they are. I'm trying to, like, just stay relevant there.

So I do some fun videos there that I think are educated as well. But any of those work, I do my best to keep up with those things

And if I could Charles just before we wrap, you know, I just want to mention two things. One, we just scratched the surface on the work of science,

“the scale, and I think that the audience got a good view”

on some of the ways I view the world. What we talked about with Elenecator Attention Essentially. That's chapter two of 27 chapters just so you know. You know, these are all in, like, the rigorousness of answering one should we scale and how fast.

So if you do want to check out the book that be great. And as I mentioned, all the proceeds are donated to mental health for two reasons.

The second reason, the first reason we discuss,

which is, it's just crazy how much energy is being put into building AI, but not understanding the societal impact. I think all of us in tech need to do a better job of diversifying our time and energy with also the societal impact.

And this is my little thing for now. Is the donating extension of the book, the work around that. And I'll do more as time unfold.

“And the second reason is because mental health”

has been a big part of my life. It's crazy that when we evaluate, when we interview a candidate who is a cancer survivor, we elevate our perception of that person. But if we find out that the candidate, you know,

had a massive struggle with mental health five years ago.

We may have concerns about hiring them, because the stigma still exists, even though both are genetic and out of their control and curable and all that kind of stuff. And so I have been a caretaker directly to loved ones.

I've also been a patient. And I'm lucky to have the credentials, the society values on my resume. So I can be transparent about that situation where many have to suffer in silence. And so that's the other reason, you know, why I am donating the proceeds.

And I appreciate all the support from the community. And Charles, thank you for the platform for me to be able to say that on. Yeah, absolutely.

“I think people don't understand the therapies that give to give to yourself.”

And there is a difference between depression and depression. So one of the things that I had to work through with that in all my stuff was sitting down and being told, hey, you're not depressed right now. You're just depleted. You're just, you're just, you're spent.

You're in adrenal fatigue. You've been running from something. It's just so there is that ballgame. So if, for those of you listening and, you know, I've been coaching and doing this for 20, something years,

there's not a single one of my clients that has ever come to me.

When they're like, hey, I want to make a hundred million dollars

that we don't immediately end up at some sort of mental health conversation. Because the people who are getting that that $50 million dollar ballgame, most of them, again, they don't have bad days. They want to have days where they don't want to have any more days. And having that conversation and sitting down with them and, you know,

really embracing them and saying, yeah, we've been there before, we get it. And, you know, if you're out there, I'm not a therapist in any way, shape or form, but make that call. It's important. Track down the person, have the conversation, start going that ballgame.

It's much more common than you know. And therapy is absolutely the gift that you give yourself. And I would recommend it to everybody other than the book. You know, go track down this book. Because I need to go track it down to read your book now.

Because I've got to take it. So Mark, I appreciate it more than I could possibly tell you. This is the conversation that I could go for probably another five or six days. And I'm sure the audience is going to want me to bring you back and have more conversations. Thank you so much for, for, for jumping on and sharing your time.

I appreciate it more than I could tell you. Thanks, Charles, appreciate it. Thanks for tuning into the podcast. Mark talked about companies that were the best in the world at what they did. Like the best hockey team on the ice.

But then the ice turned into a pool. All that skill stopped mattering. Back in 1998, Siebel led the way in CRM. People soft led HR and BMC led IT software. None of them saw what was coming.

Sealsforce, workday and service now took over. Because they built something different from day one. Instead of trying to protect what they already had. That's the real risk with AI right now. It's not about keeping up.

It's about knowing when the game itself changes. See you in the next one.