7 Powers with Hamilton Helmer

Yeah, I would say we're sorry to blow your cover, but it's sounding like that's pretty well blown as no longer the best kept secret in Silicon Valley. I was going to say that the fact that it's the best kept secret says something about my acuity as a good marketer. Who got the truth? Is it you? Is it you? Is it you? Who got the truth now? Is it you? Is it you? Is it you? Sit me down, say it straight. Another story on the way. Who got the truth?

Welcome to this special episode of Acquired, the podcast about great technology companies and the stories and playbooks behind them. I'm Ben Gilbert, and I'm the co-founder and managing director of Seattle-based Pioneer Square Labs and our venture fund, PSL Ventures. And I'm David Rosenthal, and I am an angel investor based in San Francisco. And we are your hosts. David and I had a realization. We talk about seven powers on every single episode. Literally every single episode. And in March of 2020, we actually interviewed Hamilton Helmer to talk about the framework.

But we estimate that only about 2% ever actually heard that since it was an LP episode at the time. So today, to celebrate the LP feed going public, we are releasing the remastered version of that interview. It's a little like getting in a time machine, since that was the last recording we did before the pandemic hit. But every single lesson holds up, and it is a treat to hear about the seven powers framework in Hamilton's own voice and to hear his story behind the book.

When we recorded this, well, A, you're totally right. Like, all of Hamilton's work, it's just timeless. But you were going to fly down, and we were going to do it at the Strategy Capital office, Hamilton's fund that he manages in Los Altos. And I drove down and was there. And then last minute, you said, hey, this COVID thing, I'm a little worried about it. I don't feel comfortable getting on a plane right now. And so you were on Zoom.

Yeah, I've never met Hamilton in person. And you have twice, three times? Oh, at least. More than that, I think. Yeah. We should do something with him early next year. I would. Maybe another reason to get this out to everybody now to get prepared for more coming in the new year. For sure. Listeners, if you like this episode and you want more, we also released a book club that we did with Hamilton from September 2020 as a follow-up.

And just like every other previous LP episode, those are now free and accessible in any podcast player just by searching Acquired LP Show. All right, listeners. Now is a great time to talk about a new partner of ours here on Acquired, Lagora. The agentic operating system that is redefining how the world's best legal teams work. It's sort of obvious that AI is going to completely change the legal industry. I bet most of you listening have dropped a contract into some sort of AI chatbot out there.

Lagora took that insight and asked the question, what if you really built something with that power from the ground up for the legal industry? So the founders did exactly what great founders do, operate with obsessive customer focus. They embedded inside a massive law firm for months. They sat with the lawyers just watching how the work really gets done. And that's how you get features that customers love, like tabular review, where you drop in a folder of hundreds of contracts and it pulls every key term into a grid a lawyer can actually work with.

Lagora's bet here is interesting. Since it lets each lawyer handle more complexity, any given person can increase the quality of their work and do higher value work. And this means that the pie can grow even as each individual task takes less time. And they recently launched Lagora Agent, offering greater intelligence and performance. The agent lets lawyers set an objective. Then it can handle the planning and the execution and delivery of the final product. Legal teams get to maintain full control and transparency since they're still involved where judgment is required.

And Lagora works where you already work. You can use it within Microsoft Word while redlining or drafting. The early Lagora numbers essentially speak for themselves. When they have a head-to-head pilot with their top competitor, they win 70% of the time. Lagora now has over 100,000 lawyers on the platform from 1,200 legal teams in 50 countries. And crazily, they went from 1 million to 100 million in ARR in about 18 months. Truly insane numbers. And that is the real test.

Plenty of things demo well, but the question is whether a busy associate actually reaches for it during crunch time. Or whether a partner trusts it before going into a conversation with a major client. If your legal team wants to check it out, whether you're a law firm or you're in-house at a company, you can learn more at lagora.com slash acquired. And just tell them that Ben and David sent you. All right, listeners. Now on to the interview with Hamilton Helmer.

Before, in addition to writing Seven Powers, you're an active strategy consultant and a public equities investor at Strategy Capital, which is a firm you founded. Before that, you earned your PhD in economics at Yale. And after that, you worked for Bill Bain at Bain & Company, correct? Yes. Before going out on your own. We'll get into all this, but thank you so much for being here and joining us. Yeah, no, my pleasure. My son, Andrew, who's a software guy at Google or had been until recently, told me what an amazing group you were and how everybody at Google listened to your show.

And that do I know these guys? And sure enough, David had reached out to me, so I'm delighted. Ah, thank you. I appreciate it. Before we get into Seven Powers and all of your work in strategy and technology, can you tell us a little bit about how did you get into strategy and develop a passion for it and go from economics PhD student to working for Bill Bain? It's a funny journey. I won't bore you with too many details, but I'd always had sort of an interest in business.

This is audio and not video, but David can look on the floor there and see a rug. And that rug was my first business. So my brother and I started a rug business while I was still in graduate school, designed in New York and woven in Ecuador. And there's long stories behind it. My wife looks back in that period and she said, today it would be called a social enterprise. Back then it was just called a failure.

It's good to have your spouse be your best critic. It makes you better. So I was very interested. But then when I finished my PhD in those days, it was really odd for somebody with a PhD to go into business, a PhD in econ. I mean, you think econ, it's about the business world. It's not. Highly theoretical, mostly math at the time. I loved economics. I still love economics. Fascinating discipline, but unusual. So I had to kind of scout around.

And finally, I ended up isolating strategy consulting as the thing that interested me the most. And there's a long story about how that happened, but I won't go into that. But anyway, I ended up interviewing a Bain company. I think I was the only person at that time to ever cold call the company because there was all Harvard and Stanford MBAs, basically. They'd never seen anybody like me. How big was Bain at that point? A couple of hundred, maybe.

Wow. And my partner, John, in Strategy Capital, I think he was the second hired employee. So he goes back even much further than me. Wow. And this was in Boston? Yeah. That was their only office at the time. And they were growing like stink. And so I had this funny experience where I had nine interviews of an hour each. And there was quite a lot of skepticism. Kind of an egghead. Doesn't have an MBA. So finally, my last interview was with Bill Bain.

And I sat down in his office. I thought, you know, I'm really interested in what he's doing. So I just, I spent the entire interview asking him about how he got it started. What was his entrepreneurial experience? Which always has fascinated me. I forget the name of the folks who founded McKinsey, but they created a whole market. Yeah, yeah, yeah. They're entrepreneurs. McKinsey goes back further. And then BCG came in as sort of a strategy focus.

And then Bain spun out of BCG. And then Bill looks at his watch and he says, oh, our hour's up. I've got to go. And I realized, oh my God, I haven't said anything about myself. You idiot, Hamilton. And so we're literally walking towards the door. He's shaking my hand. I said, oh, Mr. Bain, I'm sure I can do the work here. I'm really interested and it's fine. But everybody here is worried about me not having an MBA, but that's just not a problem.

I'm sure I can do it. And he said, oh, I don't have an MBA either. That was great. And that's how I got the job. So that was in Boston. What brought you out to California and starting to swim in these Silicon Valley waters? In 94, I came out here and I was attracted by the economic vitality, but it's also a family decision. My wife just absolutely adored California from her prior experience. And then I got more and more involved and more techie companies, as you saw from my stuff.

Adobe was a client and Raykem was a big client and so on. It really is amazing how much timing plays into these things. People talk a lot about jobs and gates being born within those sort of same few years, and it really teed them up for the exact moment to start Apple and Microsoft and make them be powerhouses. You moving to the Bay Area in 94, that is an equivalently perfect time to dive headfirst into that community.

Yeah, yeah, it's true. At the time, I was an actively involved equity investor, too. So in a lot of Intel and Microsoft and Dell and Cisco were all big proprietary accounts. And so that made me think a lot about it. But those were very formative years, certainly. Yeah, I mean, it was Netscape, but it wouldn't be long until Netflix was founded. Yeah, I still remember vividly the first time that I saw the internet. One of my clients back east is sort of a techno head like me.

He pulled me into his office and fired up Mosaic and said, hey, this was before Netscape, and said, hey, you got to see this, Hamilton. I went, whoa, this is amazing. Okay, let's get into the fun stuff. Seven Powers, to me at least, the thing that was so enlightening about it was, I see this mistake all the time in Silicon Valley and in venture investing of like, everybody's like, tell me about the TAM, got to target a big market.

But that's kind of only half of the equation of what makes for a great enduring company is targeting a big market. Of course, you have to have a big market. But you also have to have what you call power in the book within that market. You have to have defensibility. You have to have something that makes your company and your business stand out. Can you tell us a little bit about how you define power and how you came up with it?

Yeah, sure. So as I consulted with more and more companies, because I ran my own consulting firm for decades, three things started to become evident to me. One was that really strong performance is persistent. If you look at Intel's results this year and Intel's results next year, the fact that they have high profit margins will probably be true next year. And it turns out there's a lot of empirical work that verifies that, that there's persistence. It's like the exact opposite of hedge fund managers year to year.

Yeah, or mutual fund managers. There's no persistence in mutual fund managers. Now, interestingly, as you probably know, there is persistence in venture capital. And then the next thing, if you've done a lot of valuation work, I'm sure you've done a ton and I've done a ton and I've even taught it. What you learn is it's all in the future. So if you take a company that's growing about 10%, do a standard valuation model, what you find is 85% of the value is after year three.

So persistence and in the future. That says that if you can understand the issues that drive persistence, you're going to understand what drives value. But then as I did more and more consulting work, another thing came into focus, which was that the path to establishing that kind of persistence is not linear. There's a step change. So there's a period when a company can establish that and that window often closes, if you will. And it's the kind of business that you are so familiar with.

It's in the earlier stage. I think you called it in the book the takeoff phase of the market. Takeoff phase, yes. So if you think of a founder, there's this period where there's tremendous flux going on. They don't know who the customers are. Technology's changing like crazy. They have all wide variety of different types of competitors. And in that, there are all kinds of degrees of freedom about how you move. The fact that people even talk about pivoting is just suggesting that it is possible, in fact, to pivot.

Ask Intel to pivot and it won't happen very easily. And they've certainly been trying for a long time. So what that says is there's this moment. But then the problem is, from a strategist's point of view, is that all the information is changing so radically that the person or the group that has to process that is the founder and his team. And it's not hiring somebody like me and making a recommendation or strategic planning or something like that.

It's actually processing all this time. And as you move through space and time, understanding, okay, this direction looks a little better than that direction. And so what that said to me was that what people needed was not advice from an expert, but rather teaching to fish, trying to assemble a way of looking at strategy so that the people on the ground who are really making these decisions have a way of thinking about it that will, it's never perfect, but guide them in the right direction.

But the problem in doing that for me was that providing a mental model like that, as I say in the book, it has to be simple, but not simplistic. It goes simple so that you can retain it, not simplistic so that it's relatively complete. You don't miss a lot. That's a really high bar in strategy. And that's what took me so long. I mean, I wrote the book. It took me 20 years of writing it. And Hamilton, I'll tell you, having read a bunch of business books and having an even larger pile of business books I've bought but haven't read, there's so many different mental models.

Thank you for taking the 20 years to do it because the fact that there is a one-page reference card that sort of assembles this whole thing, it actually does make it so you can reference the seven powers and sort of make decisions in real time. It's certainly much more accessible than trying to weave your own fabric of lots of different theories. What prompted you to decide to write the book? I mean, you've been doing this for so long, you could have just kept this to yourself.

My ideas are my babies. And the greatest compliment for me is other people using them and finding them useful. So I wanted to get it out there, but I'm not a natural writer and I really hadn't published before anything. It was a very hard journey because originally I sort of went to people and said, okay, business book. Well, the advice was don't do anything very conceptual. It's got to be a lot of stories and stuff. And so my first efforts, I think I wrote a full book this way, were kind of fun stories.

And then occasionally I kind of slip in a concept. And I went to publishers and agents, I had a very, very famous literary agent, for example, and I could get no traction at all. I felt like I was hitting a brick wall. And finally, I said, to hell with it. I'm going to write the book that I think needs to be written. The two of you face this all the time, the issue of want versus need.

So which I always admired Steve Jobs for talking about. You don't do breakthrough stuff with market surveys. You have to understand what the need is and then invent. And if you really meet the need, then it's useful. Oftentimes you fall flat. And for me, the need here was this mental model that was simple but not simplistic. So of course, now you're alluding to Charlie Mungerisms here. My biggest question I'm dying to ask you, reading the book and learning about power and this model that you've come up with, how does it relate to moats?

Is power the means by which you create a moat for a business or is it something different? There are two necessary and sufficient conditions for power. There's a benefit. So you've got to come up with something that's better than what other competitors do, but better for you as a business model. It's a better business model somehow. So that's something good. But that happens every day. Every little improvement you see in Starbucks getting a different kind of coffee cup or something.

So that happens often. But the thing that's rare is when you do that and it's material, so it is enough to tilt the needle, but also it satisfies the second condition, which is that not just there's a benefit, but there's a barrier. Which is a barrier means there are lots of smart people out there. There will be aware of what you're doing and they're going to try and take it away from you. And that's how competitive dynamics works.

And so you have to have something that will prevent that from happening, even if they're motivated and capable. I'm a huge fan of Warren Buffett's, as you might imagine. You know, he's a genius, I think. But the word moat to me, although he means more with the word than that, makes you think about the barrier piece. So I think it is fair to say that the seven powers are, for me, a very careful and I hope exhaustive articulation of the nature of moats.

But I think when you're thinking about competitive analysis, particularly when you're thinking about starting businesses, I always tell people, don't focus so much on the competition. You have something unique. And yes, you have to pay attention to them. You don't be stupid. But you don't create a great business by just saying, I'm going to beat the other guy. So the benefit side is also very important. So it's tightly tied. And of course, the whole idea of moats is just was a brilliant concept in their part.

So there are seven powers in your book. And each of the seven powers is a way to create this power. How did you distill these seven? How did you come up with seven? Do you worry that there's an eighth out there that you haven't found yet? Yeah, yeah, yeah. With great pain and time, it's completely empirical. I've probably led 200 strategy cases. I've probably had my students like Giselle and Chen Yi who are sitting here do another 200.

And so far, those seven have covered everything that I've seen. I'm always looking for an eighth. Because also as an investor, if there is an eighth, it's probably really obscure. And it probably means it's not in the price, which probably means it's a good investment opportunity. Good source of alpha. Right, exactly. We won't have time to go through all seven. But maybe a good one to start with, since most of our audience is in technology and most of those folks are entrepreneurs or aspiring entrepreneurs, counter positioning.

This is such a fun one. I know it's your favorite power. And particularly such a fun one because it's, in many ways, the most relevant for startups and entrepreneurs in a lot of markets. Can you talk to us a bit about this? Yeah, I do have a special place in my heart for counter positioning. I have to say, because it's so contrarian and I'm sort of a contrarian person, I guess. A counter positioning occurs if a company comes up with a new business model and challenges often a powerful incumbent with it.

So I'll give you some examples. So Netflix versus Blockbuster. Late fees. Yeah, yeah, yeah. Late fees. So late fees accounted for half of Blockbuster's income. Netflix said we're not doing it. And Blockbuster eventually mimicked Netflix. And who knows? But my suspicion is if they'd done it a year earlier, I'm not sure Netflix would exist. And the place I got to kind of cut my teeth in this was I was a big investor. Big for me, not big for them.

A big investor in Dell in the 90s. And my investment hypothesis was that Compaq couldn't respond quickly to them because Dell was going direct. And Compaq had these lucrative arrangements going through stores. But looking at his investor, I could see that was true. But why? And so that got me thinking about it from sort of a ground up. And eventually I was able to formalize it. Hamilton, one thing to push on there. So it seems like, and I'm remembering from your book, the criterion are basically this new thing is both a good business, but net negative for the big incumbent because of the cannibalization that would occur.

Are there any other things you would sort of add to define that? Yeah. So there are a few flavors of counterpositioning. One is that it's a net negative. And therefore, because their current model is so lucrative that actually even if they did a net present value, they would end up deciding not to do it, even though they'll eventually the business will go to the challenger. And these are not mutually exclusive. It's very often true. I'd say almost always true that there is cognitive bias involved, which is that the incumbent, they've done just great.

Their model has worked for years. I mean, Blockbuster saying, oh, you know, we've got all these stores, you know, people love it. They come in, they can browse. What's wrong with that? And the idea of somebody doing this rough and ready group sending out red envelopes in the mail, they'd say, what the hell? You know, this is just not going anywhere. So they're very cognitively biased towards thinking that their model works. And then there are also agency issues, what economists call agency issues, which means that the person who controls the business may not have interest aligned with the long-term interest of the business.

So, for example, CEO comp is often about this year's performance or the next few years performance. So to upset the apple cart for a gain that will happen four years out, you may say, you know, I just don't want to go there. Obviously, for startups, counter-positioning can be great. And Netflix is a fantastic example. But even remembering a blog post Bill Gurley wrote a number of years ago in the beginning of when Android was starting to take off.

And I think the title of it was Less Than Free, the most disruptive business model ever. You know, you had Android, which cost less than free. They would pay you to use it if you're a handset manufacturer to put it on your phones versus Nokia that's trying to make money or sell their stuff. Even as Google, because they had the separate business model of search, they're able to enter this adjacent market with a completely counter-positioned business model.

Well, Hamilton, listeners who have read The Innovator's Dilemma, this is going to sound vaguely familiar. This would be the power that's most similar to that concept. In the same way that we asked earlier, what's the difference between power and moat? How do you think about counter-positioning relative to that sort of grand theory? I recommend everybody to read that book, Innovator's Dilemma. It's a brilliant book. Christensen was just a scholar of innovation and deeply researched. But it's pretty different.

So if you want to get sort of mathematical about it, there's a many-to-many mapping between the two concepts, which is to say that counter-positioning doesn't imply disruptive technology and disruptive technology doesn't imply counter-positioning. Give you some examples. So I would argue that In-N-Out Brugger's is counter-positioned against McDonald's. There's no technology involved particularly at all. And it's not disruptive in terms of Christensen's philosophy was low end. This is like a objectively worse product. Yeah, so you're going back to Christensen's original book, which I think is the more interesting one, where there's a product that kind of doesn't satisfy everybody.

I mean, you could argue that Tesla's first cars were like that. The other direction is that if something is a disruptive technology, it may not be counter-positioned. So that's straightforward. And the fact that they don't map to each other and the fact that power maps directly to value or there's a one-to-one mapping between power and value means that disruptive technology does not map to value. And the simple thing about that is you can disrupt something and it can be a really lousy business.

Happens all the time. You poison the well, but there's no good endpoint for it. We may be overly cool and girly here, but I think I saw a recent tweet, something along the lines of there is an infinite amount of product market fit for selling dollars for 90 cents. Yeah, yeah, yeah. So just pricing something so that people are attracted to it and losing money. There's no power there. All right, listeners. Now is a great time to tell you about a longtime friend of the show, Vanta.

AI has scrambled the whole security picture. It used to be that you proved that you were secure once a year on audit or a static PDF. Then everyone would nod and you're done. But in an AI-first world, that doesn't hold up anymore. Yep. Your risk surface changes every week now. A vendor turns on an AI feature or someone writes in a new model without telling IT. And your posture is different than it was last week, let alone at your last audit.

Vanta's own research found that around 70% of companies have this quote-unquote shadow AI running with no security review at all. Right. And that's where Vanta comes in. They're the leading agentic trust platform, meaning they've built the thing that closes the gap. And the way that they close that gap is Vanta Agent. Think of it as a GRC engineer. That's governance, risk, and compliance. Except that it's software and it doesn't sleep. It finds the issues, drafts the fixes, and cuts the time that you'd spend on vendor assessments in half.

In half! Which is exactly why more than 16,000 companies today run on Vanta. Companies like Ramp, Cursor, and Snowflake all stay audit-ready and catch the risks that crop up between audits across every vendor, every AI tool, the whole environment. And that's the real value. Trust has to be continuous now, which is why Vanta automates your security, your compliance, and the work to earn and prove trust. We're huge fans of Vanta over here, and literally hundreds of acquired listeners have become Vanta customers at their companies over the years.

So you can get $1,000 off Vanta at vanta.com slash acquired. That's V-A-N-T-A dot com slash acquired for $1,000 off. And just tell them that Ben and David sent you. Okay, next one I want to talk about is in many ways classic, and I think many of our listeners already have thought a lot about this. And no, but we want to ask your perspective on some nuances of it. Network effects. Hugely discussed in Silicon Valley, everywhere. Everybody knows what network effects are.

But one of the things you talk about in the book that I think is so accurate, and I've observed as an investor, you can talk about network effects until the cows come home. But it's the intensity of the network effect that really matters, and it is so hard to know that ex ante in a market. What is the actual degree to which I care as a participant in the network about other participants in the network? And how much do I care about which other participants?

The key thing about it is that they are complex and hard to figure out. So just asserting them gets you 0.001% of the way of understanding what's really going on. And we've seen that when we look at investment opportunities. First place to start, of course, is to try and create a map. Because remember, they're not homogeneous. They're not necessarily linear. They're not symmetrical. So just to give you some examples. So if you think of Uber, this is a platform.

It connects drivers with passengers with powerful utility, much better than taxis. And it changes my life for the better. I sit on a board of a startup up in Vancouver. And Vancouver taxi lobbies are strong or however it's worked. They don't have it. And so I finish my board meeting. I go down to the curb. They've called a taxi. I have no idea whether it's coming. I have no idea where it is. And eventually, I usually just give up and just go to find some corner to hail a cab.

And so very powerful benefits. But does Uber have power from network effects in a way that will translate into meaningful profitability? I would say first order no would be my guess. I'm no expert in this. But first order, I'd say no. And the reason is, is if you think about what's going on, it's that if there is a similarly sized or reasonably sized competitor lift, for example, in this market or others in other markets, that they can achieve a similar network effect.

And if you look at the density economics of as you scale in a region, what we're saying is it's nonlinear. At some point, it flattens out. And so if the market's large enough for more than one company to exist in that flat spot, then it doesn't help you. So you have to look at all those nuances. But one of the unusual things about my book is I've always tried to be very careful to make sure that everything maps back to value.

So if you said, what is the fundamental assumption of this book, it's that strategy and value are mathematically their duels. And so the mapping function from that desire to join the site versus actually being able to monetize it, which is based on how much time you spend on it and all that kind of stuff, is you have to understand that to understand whether there's power or not. The last one we're going to talk about after this is going to be my favorite.

But switching costs, I thought this was super interesting because people think about switching costs as I think tend to be like old school industries or whatnot. But I realized there's a huge amount of switching cost power in a lot of technology companies to take Slack, for instance. Slack has network effects, but also switching costs. We run on Slack. If we were to switch, that would be a huge cost to our organization. How did you start thinking about that and have other people in tech since you published this realize like, oh, this might be a source power I'm not thinking about?

I don't know. I think people had thought about it. There are a lot of subtleties around switching costs that you have to think through. I mean, one is that in general, it creates a win-lose situation with your customer. And so there's sort of a management problem in that. And another is that there's a competitive dynamic, which is if you have something that's attractive and a high switching cost, the competition will try like crazy to create something that mitigates the switching costs.

So you'll see a lesser app have a translator device. But often the imperfection of those, so if you look at EDA, electronic design, automation tools, there are libraries that are associated with those. But if you move from one tool company to another, the translation never works very well. Or every CRM system is like, oh, you export your data out of Salesforce. We'll do it for you. Right, exactly. Or exporting a PowerPoint to Google Slides. A problem that I think all of us probably deal with on a weekly basis.

The translation is never perfect. And thus, if it's a very important presentation or whatever the thing is, you're not willing to switch. Right. But then another subtlety is that, remember, you can only monetize that if there's a repeated economic interaction. So you have to buy more stuff. There's got to be some kind of razor blades aspect to it, right? If there's just switching costs and you never buy anything more, it doesn't matter. Because it's in those additional transactions.

And so that's when you look at ERP companies, why they acquire so many different things. Because these are different tools they can interact with. They are real. A place where they can be especially strong is when they become embedded in a company process. So we were talking before about there's a company that sells lab equipment. We were talking about 10X Genomics before, for example, where a piece of equipment gets embedded in how people do things. They not only get used to it, but there's a whole process designed around it.

And switching it out is really hard. How about, I'm just curious, because you've been thinking about this, what do you think about, or what would be an example? I mean, Slack's an example, and there's a question of whether it's still sufficiently monetizable. Yeah. Well, I was wondering in particular with this, for SaaS companies, is SaaS a business model innovation that, if you have a switching cost source of power, can work really well together? Because the monetization, it's not like old on-prem software.

You sell a big Siebel installation. Boom, that's a lot of money up front. Now you've got to sell more stuff in the future. With SaaS, you're just constantly selling all the time. Yeah. So if a SaaS model has really good switching costs, boy, does that help. I mean, it really helps. I actually think the way that these companies are financed are predicated on switching costs as a primary source of power. I mean, you think about people are willing to sell these things at such a low per seat per month price, or even let's say annual price.

I mean, people are not necessarily hiring field sales reps, but they're hiring people to do inside sales because once you get one of these SaaS systems in, there's just an expectation of repeat. And when you go and you capitalize these business in the way that venture capitalists value them, it's kind of predicated on that. The expected churn rates are fairly low. Yeah. The thing you have to be careful about in these kinds of businesses is customer acquisition cost.

So as it becomes more known that there are these high switching costs, people understand that there's essentially a cash flow future associated with each customer. And they'll start to say, oh, yeah, well, we should sign them up for free or actually with a bounty. So what happens over time is that actually the value of the switching cost becomes arbitraged out by the acquisition cost. That's why if you go back to my power progression, that's why the switching cost is in the takeoff phase, because that's the period in which the true economics are not yet reflected in the acquisition price.

And so you have to combine it with something that gets you the customers in the first place because you don't have the customers in the first place. And either you do that through something that's superior or you do it when the pricing of it hasn't fully arbitraged out the value. See, there are lots and lots of businesses where people just pay too much for customers. And it turns out to be a really lousy business, even though it has switching costs.

It's interesting. That also really makes me think more of Slack. Slack came on the scene. They were the first real innovator in this phase of consumer grade mobile messaging is also useful in businesses. Let's do this. They acquired tons and tons of customers in that phase, built a big company that's going to be enduring now, public company. But now they're competing to the death with Microsoft and Teams and the ability to economically acquire customers is at least not what it used to be.

Yeah. So the two, you have so much experience. Let me ask you this question. So on counter-positioning, one of the things that is really interesting is this whole software eats the world thing. Do you think that in general companies that are highly software-centric in how they approach a business, that for an incumbent that isn't that way, that for them to adopt has to blow up their model so much that it's counter-positioned? It's not only that software eats the world on the benefit side, but the barrier side is that if you develop a company from the ground up that's software-centric, is that just a really tough pill to swallow?

So a great example is current auto companies. So versus Tesla is the fact that they've thought about software, built things up from that level. And now if you look at the engineering models of a BMW, boy, it's tough. Is that generally true, you think? I've been thinking a lot about this recently, actually, as it pertains to a couple of different investment opportunities I'm looking at. And a distinction that I draw is if the value of the incumbent can actually be replaced by a technology product rather than a technology-enabled product.

And to illustrate this, let's say a technology-enabled product is something like Redfin, where there's lots of ways they can apply technology to make the process better. But at the end of the day, it's a traditional brokerage with a person who's showing you the house. And it's the same business model with pretty similar fees on the transaction of the house. And you look at other businesses like a pure technology business like Netflix, where it's a digital service that's distributed digitally.

It's software all the way through. And if you're thinking about, do the existing incumbents stand a fighting chance, my answer would be yes against technology-enabled businesses. Because they can tech-enabled just as easy as these new entrants can start tech-enabled. Not just as easily, but it's possible to compete on that vector. But when it's a pure technology product that's being sold, that is the actual value proposition to the consumer is this unique piece of technology. That's when I think this unavoidable fate starts to happen.

Yeah, very, very interesting distinction. Oh, one thing I should have mentioned before about counter-positioning that your listeners should always keep in mind, which is really critical. It's the only one that's a partial source of power. Which is to say that, remember, power, when you think about it and try and figure out if a company has power, you have to look at power versus every type of competitor. So existing and potential, but also direct and functional. So people that satisfy the same need, but a different way.

And in the case of counter-positioning, it doesn't answer the power question for potential competitors because other people can mimic the same. So I gave the example of Dell before. Dell's power went away, of course, because ultimately everybody could do the same. And so if you look at counter-positioning and you want real durability in addition to that, you want to have another source of power. When we're looking at companies, it's very common that one of the either potential or existing competitors are, you know, Amazon's trying it out or Microsoft or Google or somebody and often in a vertical integration play.

And so then you have to think through, can they do it? And also there can be counter-positioning issues involved, something like that. And of course, Slack is straight up against that kind of stuff, you know. So there's something else that I've been thinking about. I'm curious to get your take on if you've seen good research on it or if it's come up in your career at all. In general, when I'm looking at the competitive landscape for a company that we're starting at Pioneer Square Labs in the studio, I'm trying to figure out who are we going up against.

The ideal situation is there's incumbents, big companies that are 20 plus years, you know, they're mature companies. And there's maybe one or two other startups that are in our vintage, but there's not somebody that's like three or four years old. And my logic on that is always we're competing on a completely different playing field than however, to put it in your language, however, that incumbent got power and whatever that opportunity was for them to create something new and novel.

And I'm perfectly fine competing maybe either with a different strategy or to try and out execute someone that has the same resources I do. But I don't want to compete against someone that's three, four years ahead of me in approximately the same technology vintage with the same sort of world available to them who just has a lead and may actually be started something at the beginning of the window that is now closing. Does that square with how you would think about that?

Completely resonates. Completely resonates. So what happens in the takeoff phase of a business, think about what's going on. There's more customers than product. Nobody knows exactly what the right model is. And in certain markets, that means that there can be quite a few competitors that are kind of viable. And in some markets, actually, if they're really incredibly robust, there can be wildly profitable companies. So I thought, were there 300 automobile companies and there were probably, I don't know, 100 PC companies or something.

I remember, I had this great experience. This was back in, let's see, it must have been 19, boy, this will really date me. I think it was 1984 or 5. I was out visiting Silicon Valley because at that point I was back in Boston. And I'd already started my own business. And I was visiting a company called Chromemco. And they were on this incredible trajectory as a PC company. Cash positive, growing triple digits, I think, and doing really well.

They just cut a big deal with Sears for distribution. And so one of their founders toured me through their facility out here. And we finished. And I said, well, Roger, thanks very much. That was really enjoyable. I appreciate that. But what are you going to do when there's a shakeout? And this cloud came over his face. He almost threw me out of his office. I mean, it was that bad. He said, there'll never be a shakeout.

It's not going to happen. Because they were in this period when the rising tide was raising all boats. And you have this tremendous feeling. And yet their claim to fame was they're the largest S100 bus computer company. I mean, who cares? Right. You know? More PCI slots than anyone. Right. Exactly. And so what you could see in the situation you're describing, Ben, is that their companies are doing just fine. They're getting customers. But competitive arbitrage hasn't really taken place.

And what you're worried about, which makes sense, is that if somebody is several years ahead of you, and it's one of the middle phase types of power, which is most common in tech, network economy, scale economy, switching costs, those are the three most common ones. If it's one of those, then your size matters. And so if they're ahead of you, when push comes to shove, when the market settles down, you will not be in good position.

And so I'd say an exception to that is that if you have a company like that, and you see that they're just gaining enormous relative market share, there might be some other company that's earlier, but there's something about their business model that just doesn't work as well. Like Google versus Exciter or whatever. Right, right. And so if that's the case, then there's the second order question, which is why is that happening and will it continue? But that's more of an edge case.

And so I agree with the basic idea that that's kind of a watch out. I'll go one step further, which is that an even more interesting investment opportunity, they don't come along very often, but is one where it's almost a category of one, where a competitor somehow there's something about the way they are that there's nobody really quite like them. That's reassuring in a lot of ways, if it's working, if it's cash flow positive. Ah, this is the perfect transition to my favorite part of your book.

In cases like that, often a power is a cornered resource. And as you say, I think this is actually quite rare in tech, yet I think people in tech think it's not rare. A classic example is a patent. You know, you're in biotech, you have a patent, you have a cornered resource, you have it, nobody else can have it. I'm curious, well, A, your thoughts on cornered resources in general, but in particular, something that just really spun around in my mind reading this is lots of people in tech, especially lots of VCs, think that executive talent and founders are a cornered resource.

And you make the point in the book that executives are not cornered resources because their value can be arbitraged by the market. I think that actually the value of founders gets arbitraged too in Silicon Valley, because if you have a superstar founder, they're going to raise money at such a high price. Yeah, just to sort of a comment on leadership. So leadership is unbelievably important. And it's unbelievably important in strategy because, as I said in the book, all strategy starts with invention and building up something around that.

And there really is a difference between companies with truly great leaders and ones that aren't as great. And so it matters. But the question you're dealing with is sufficiency. Is it enough? And the example I start my book with is a perfect example for this. It's a little old for you guys, but it's Intel. So they had two businesses. They started as a memory company. They started with the best of the best. I mean, they had Gordon Moore, Bob Noyce.

Right, right. And then it brought in Andy Grove. And so on the invention side, Bob Noyce. On the execution side, Andy Grove. And on the process manufacturing side, Gordon Moore. I mean, this was the all-stars. And yet their memory business was not working because they had no sources of power. And other people could come after them. And despite their great leadership and probably being first in and all kinds of financial resources, it just wasn't enough. And that ended up having basically a massive race to the bottom with tons of new entrants who were able to spin up everything that Intel had and compete against them.

But then if you go to what they did eventually have power in, which is CPUs, again, leadership really mattered. So they have come up with this idea for central processor. And the question is, is this a big deal? Do we back this? You know, and most of the board was against it. Their head of sales was adamant that this would never turn into anything that was. And he was a sharp guy. I don't mean to me.

Adamant that this would never turn into anything. Andy Grove was dead set against it, I believe is correct. And Bob Noyce went out and kind of talked to people. And this is the nature of invention. High uncertainty bars, very large bandwidth, deep insights. And he finally said, no, I really think this eventually is going to go somewhere. And then the chairman of the board, what was his name? I can't remember. Was it Arthur Rack? No, Rosen or somebody.

I can't remember. Anybody. He backed Bob Noyce. And they committed to it, even though they really didn't have the cash. And it was a very hard thing for them. And so there's a case where leadership really mattered, but it wasn't enough. And so the question here is sufficiency. If you take a great leader and put him in a different business, that doesn't massively reduce the uncertainty bars that the business is going to be success. Yeah, that makes a lot of sense.

How do you square that with Pixar, which is another example in your book in the cornered resources segment, where the combination of John Lasseter, Ed Catmull, and Steve Jobs being sort of the best visionary and source of capital with Steve, the best animator and storyteller with John, and then the best technologist with Ed. The Pixar brain trust, and you look at all the directors on down that they did recruit, really was their main or a big source of power for them cornering those people?

resources. Am I missing that there was another big source of power for Pixar? No, no, no. I think there's some subtleties to that story. I just have my own view about this. And I talk about this a little bit in the book. You have to come up with great stories for good animated films. The brain trust itself was insufficient to guarantee that. And the marker for that is how many directors had to be replaced that were into their projects.

And so then you go back and then ask, what was in common with the directors that weren't replaced? And with the exception of Brad Bird, who's a whole story by himself, a brilliant guy, the answer is that it was this core group of people that worked together that came up with the original Toy Story movie. And that they were sort of a band of brothers. And together, they had an experience of what it meant to create really compelling animated films.

And that was their string of successes that followed from that. And that the fact that there was a brain trust at that time, they weren't able to transfer that into other directors. But then later on, what happened was you saw when Disney acquired Pixar, some of that sensibility, they did revise Disney animation. And more recently with Pixar, I'd say that the prospects for a new pool of directors is very good. But I think the original corner resource, and it wasn't arbitraged out because those people wanted to stay together.

So certainly those directors offered jobs in other animated studios. I'm sure they all were. But they said, no, no, I'm staying with Pixar. So if Bob Iger could have just hired Ed and John, he wouldn't have bought Pixar. Yeah, yeah, exactly. And I'm a huge fan of Iger's. I mean, I think as a strategist and he made three critical Disney decisions, all of which I thought were brilliant. And I think his Pixar decision was he realized that at the heart of Disney was animated films and that even though the price, an investment banker would say, this is really expensive.

He realized that actually they had to revive that or the whole Disney franchise was at risk. And so it was worth a much bigger price. We're huge Iger fans on this show is all. Oh, are you? Yeah. Yeah, yeah, yeah. And his book is incredible. And we try to be a little less partial, but both of us, whenever we get going on anything Disney related, we'll be here for a few hours. All right, listeners. Now is a great time to thank our longtime friend of the show ServiceNow.

If you are running a large enterprise, AI agents are likely spread across every team and deploying them is no longer the hard part. Yeah. The hard part is knowing what permissions they have, what employees are using them for, or what decisions AI is making. AI security for an enterprise at scale is not a small concern. Like, the risks are real. Exactly. And the challenge with AI is governing it, securing it, measuring it, and making sure that it actually delivers value.

That is why ServiceNow built the AI control tower. Yep. AI control tower gives enterprises a single place to see, manage, govern, and optimize AI across the entire business. And it works with any AI, not just theirs. Every device on your network, every permission across every system, every AI agent, visible and secure in one place. And ServiceNow can do this because they've spent more than 20 years building the operational backbone of the enterprise. The workflows, governance, approvals, security controls, and institutional knowledge that power how work actually gets done across IT, HR, customer service, finance, and security.

ServiceNow already runs more than 100 billion workflows annually and trillions of transactions for more than 85% of the Fortune 500. So when companies need a place to govern AI at enterprise scale, they're building on a platform at the center of how their business already operates. And in a future that isn't going to be one AI, it's going to be thousands of AI agents working across every function of the company. But the question is, who's managing them all?

So if you're trying to turn AI ambition into real business outcomes and make it work safely, securely, at scale, go check out ServiceNow.com slash acquired and tell them that Ben and David sent you. The potential for power often comes in the sort of flux and change and takeoff state in the market. I'm curious as we move towards the end here, have you come up with any good mechanisms for identifying when opportunities for power exist in given markets?

Do you just kind of keep a radar screen operating and be like, hmm, okay, well, these are interesting areas of flux that are happening and new companies can be built? Or I'd say there's a little bit of secret sauce in that from my investment perspective. That'll be the next book. Yeah, right. So you have to subscribers have to pay more. Yeah. So it's kind of what you would imagine. I mean, you're in the thick of it.

It's a rapidly advancing technical frontier that's seeming to change the possibilities in all space. So I was mentioning to you before I started, genetics is very interesting to us. Of course, we have no insight into therapeutics, but that whole field, you can tell that the incredible cost decline of sequencing and other aspects of it creates the possibility of doing things that were never cost justified before or time justified. You look for things like that that are step changes.

And then I think there's an awareness of how technology flows through an economy. Last Friday, I had lunch with one of my old professors at Yale, Dick Nelson, who's this genius level person on technical change. He's one of the deep thinkers on it. And I think what you see is that you start with a technology with sort of its most gross or macro application, and then it works its way through. So if you think about Moore's law or Silicon as being one of the drivers of everything.

So first you go straight to where it's chips, it's the chips themselves. And then the chips work the way into devices. And then devices work their way into applications. And so if a technology is fundamental, it moves through different phases where it actually becomes, or businesses around it become economically viable. So think of Netflix, for example. Again, so if they tried to do streaming when they had started their red envelope business, you had to have storage, you had to have the internet, all that stuff.

And so there's a time as technology moves through that it becomes commercially viable. And then there's, of course, precursors to this, which are scientific stuff. So think of quantum computing. So first, of course, you got to figure out quantum mechanics, then you got to deal with entanglement and all this stuff. We're probably not ready for applications just yet. But hopefully there will be a time where people are now reviving hopes again about fusion based on different models.

I like that. That's a good transition too. Last question. What are you working on now? What's next for the seven and maybe more powers to come? Yeah, yeah, yeah. Well, first of all, I would love to find another power. So far I haven't. So every company that we deal with faces this question eventually is that, okay, if I'm successful, I've established a company with power. What's next? So act two. And what I'm trying to figure out is do we have anything that's interesting and valuable to say about that?

And I think from the first step of it, I think we do have something, which is to be a little more forthcoming about some of the subtleties about what really comes under a power umbrella. I'll give you an example. A natural place to go would be geographic expansion. Let's go into another market. Well, it turns out if you think of that in power terms, you get very different answers. So if you think about Uber going into a different geography, it doesn't matter because the economics are a physical density scale economies.

And if it turned out there was high branding and there are a lot of foreign visitors that matter, but it doesn't matter. Or like impossible to build that fixed cost technology asset. Right. And so it's all about market by market. So to be honest, their mission statement of transportation of everybody around the world doesn't really map to power. And I think they probably know that now. They're smart and able. Now, if you look at Netflix, it's a different matter.

And so if you think of Netflix going into a different geography, the question there is, remember, the key competitive advantage there is scale economies. So there's fixed content that they can drive across more subscribers. And so the cost per subscriber is less. And content's a big part of cost. So that's a big, big advantage. So if you go into a different geography for them, the question then is, does a reasonable percentage of our content from geography A apply to geography B?

And even if it's only 20 percent. So let's say you're going into England and 20 percent of your U.S. content applies. If you're versus an English-only competitor, 20 percent times that large amount is a gigantic deal. And then the dynamics of it become even more interesting because if they're unbelievably granular data, they can then actually tilt their content development to have more crossover. So thinking that through of how to extend power where the power umbrella fits is something that's really interesting.

And it's important economically, of course, because getting power is really hard. And if there are any places that you can take advantage of, and it's sometimes unusual. Think of Disney going into theme parks. Back to Disney again. Here we are. As you were mentioning, it made me think of Disney. We talked about this a little bit on our Disney Plus episode. Fox actually, I think, did this really well, what you were describing with geography and power.

Of over the last 10 years or so, it's only been around for 10 years, I believe Fox locked up all the streaming rights to Indian Premier League cricket. And you would think like, oh, well, that's relevant in India. Well, no, that's actually relevant all around the world. And so that was a big part of the Disney acquisition of Fox. Right. So the fact that if you get a high probability of power, it's a step change in the certainty about the value of the company.

And so anytime you can extend that to more customers or more situations, then the question after that is, okay, what's beyond that? And that's a deeply researched area. There's a lot in that. I'm not convinced yet that we have a lot to add to that. That's book three. Yeah. We'll think about it. Well, Hamilton, where can listeners find you? If they're interested in Seven Powers, where should they go? Seven Powers is for sale on Amazon. So I suggest you go there.

Is that your preferred method of acquisition of the book? Yeah, yeah, yeah. Just that. That's the right place to go. And as we started the interview off saying that I was this best kept secret, which means I'm just terrible on marketing questions. So maybe that's the wrong question to ask at the end. Well, great. Well, listeners, everybody should check out and read Seven Powers. It is well worth your time. Or listen. I listen to the book and the thing that makes that doable because it is an economics book, a very nicely distilled economics book.

But boy, there's some formulas in there. I love the insert. There's this great PDF that comes with it that gives you the sort of handy dandy filled in Seven Powers card along the way and sort of writes out the formulas. So it makes it very digestible. I'll just end with a funny anecdote, which is there is a question of whether I put any math in the book at all to speak of. And then in the end, I put it in the appendix so that you don't have to read it, but it is there.

And the reason I use it is just for sort of precision of logic. It makes things very clear exactly what you're talking about. But the reader response has been utterly bimodal. You know, there's some people that say, God, that's great. I had one. Well, Daphne, for example, you mentioned Daphne Kohler. She said that was the one of the best things she read was the mathematical appendix took out her positioning. She said she didn't really understand it until.

And then other readers say the complete waste. I don't know why he did it. Tell me more stories. Right. So I guess you're I know where you stand now, Ben. Well, thank you. Well, the best readers like both. All right, listeners. Now is a great time to talk about one of our favorite companies, Statsig. Yes. Long time acquired partner. There is a reason why the best product teams at companies like OpenAI and Notion, Atlassian, Figma, Rippling, Brex, and more rely on Statsig, whether they are iterating on their core product features or shipping AI powered experiences at scale.

Yep. In the crazy speed of today's AI world, shipping fast is just table stakes now. It's basically trivial to build and deploy your app constantly. The real advantage is how quickly you learn what changes actually created value for customers and how fast you can use that signal to guide what you ship next. Whether it's a feature tweak, a pricing change, a performance improvement, or an AI update like a model change or prompt adjustment, they're not relying on instinct.

They're measuring what actually moved engagement, retention, and ultimately revenue. And as more teams build with AI, that learning loop becomes even more important. Building with LLMs introduces non-determinism into your product experience. The same input doesn't always produce the same output, and behavior can shift in subtle ways in real-world use. So doing offline evals will give you part of the picture, but you can really only understand the impact once your product is live with real users, and then you can measure how their behavior actually changes.

It's very different than the way that you would ship features in a pre-AI world where you knew exactly what the software was going to do in production. Yeah, exactly. So this is where Statsig comes in. It brings experimentation, feature flags, and product analytics into one unified system so teams can ship safely, test rigorously, and directly link what they changed to how users actually behaved. The result is a tighter feedback loop and learning that compounds over time so you don't just ship more, you ship better.

So if you want to make learning your competitive advantage, whether you're building new AI experiences or just evolving your existing core product, go to statsig.com slash acquired to get started. Well, listeners, as mentioned, if you liked this interview with Hamilton and you're like, I need more Hamilton Helmer in my life, good news. In the now public LP feed, you can find a recording that we did of a book club with a bunch of people on Zoom, all of our LPs at the time on asking questions.

We led most of the discussion and then opened it up to the group. Pretty fun to get to have that discussion with Hamilton. So you can just search Acquired LP Show in any podcast player and find that. Other than that, I'd say if you want to come talk and hang out with the rest of the group, join at acquired.fm slash slack. And if you're looking for that next great thing that you want to go do, we have personally curated some great jobs that we think are interesting at acquired.fm slash jobs.

And you can go there too if you aren't looking for something, but you think you might be in the future. We have a place to raise your hand and say, hey, look for something cool. So you can drop it in there too. Oh, and last thing though, before we go, we have to say, everybody's still listening at this point. If you haven't already, just go buy the book, buy Seven Powers. I literally have about 100 copies of it sitting in my garage.

I've read every single one. Quite the super fan. I am a huge super fan. Buy the book and also leave a review on Amazon. I think you're the first review or the top review. I think I'm the top review. I at least was. Let's go back and check. But seriously, Hamilton's work is just incredible. We can't wait to do more with him going forward. And a huge thank you to him for joining us here. For sure.

Well, listeners, we'll catch you next time. We'll see you next time. We'll see you next time. We'll see you next time.