Emergent Layers, Chapter 1: Scarcity, Abstraction & Abundance

This is part 1 of a four-part series, Emergent Layers. If you haven’t read the introduction, I invite you to do so here.

There’s a basic but powerful notion that all money is made at points of friction. I make money when I sell something for $10 that cost me $5. What entitles me to do this? Some sort of friction: after all, in a frictionless world, the sale would converge to a price of $5. Making money over the long run — i.e. being durably profitable — means that a person or company is able to sit at a point of friction that is defendable and unavoidable. Where does this friction come from? How does it emerge, and how does it disappear? One good starting point is to examine the differences between scarce and abundant elements, or as Nassim Taleb classifies them in The Black Swan, non-scalable and scalable entities.

Borrowing from Taleb: let’s consider the fate of Giaccomo, a 19th century local Italian musician living just before the advent of recorded music. Musical performance at this time is a decidedly non-scalable affair: if you want to be musically entertained, you need to be present to a musician in person. As such, Giaccomo cannot scalably export his work, but neither can the big opera singers in Milan who might otherwise compete with him. Geography and physical proximity represent a strong point of friction — with only a handful of other musicians in town, Giaccomo can set a fair price and earn a decent profit so long as his vocal chords remain in good shape.

Now imagine what happens with the invention of the phonograph. Suddenly poor Giaccomo is competing against the Milan big shots! His unit of trade (his voice) has been abstracted away into the etchings on a wax disc. As far as the residents of the town are concerned, this is a great development. They can now pay a fraction of what they used to, and in return receive an endlessly replayable recording of a superior artist! But for Giaccomo, this sucks. Physical proximity, which used to be a point of friction off of which he could extract earnings, is now easily circumvented; it becomes much harder for him to make a profit, or even get paid at all. Even if Giaccomo were able to get access to his own recording equipment, it would be to little avail: a new point of friction has emerged, distribution, with which he has no skill in dealing.

Consider three very important things that have happened here:

  1. Musical performance, formerly a tangible, scarce, non-scalable element, was abstracted away via technology into something scalable. The result was very good for ordinary people, who could now be entertained by the world’s greatest artists in their own home for less money than it took to pay Giaccomo for an in-person performance.
  2. It became very difficult for Giaccomo to make money! When this phase change took place, the point of friction around which he extracted his profit — physical proximity — ceased to matter. Making money off of music became a winner-take-all affair very quickly. From Giaccomo’s perspective, this was a Black Swan event — impossible to see beforehand, retroactively explainable, and of grave consequence. Giaccomo could protest, “it’s not fair!”, and he’d be right. It’s not fair. And that’s what makes it interesting.
  3. A new scarce and non-scalable element emerged out of the new scalability of musical performance: distribution. An entirely new industry came to life, which we now know as record labels, who sit at the newfound point of friction and extract profit.

This parable is useful for us for two reasons. The first is that it compactly demonstrates what happens when technological change abstracts away a scarce element, a point of friction thereby vanishes, and business models rearrange as a result. Generally, the result is good for the end user, but bad for those who depended on that point of friction to make a living. The second is that it illustrates very poignantly the difference between making money off of something scarce versus making money off of something abundant. They are entirely different exercises.

Now let’s return to present day. Throughout the rise of modern technology, its impact on the world has been led by a select group of companies that also happen to make dynastic amounts of money. These companies do not make all of this money because they are working marginally harder than their competitors, in the way that Giaccomo might compete with his fellow local musicians. They make this money for three reasons: they are the only game in town, they set the price, and the world has to play.

Examples of these dynastic companies over the years include Intel, Microsoft, Cisco, Google, Apple and now Facebook. There is no doubt that the impact these companies have on the world is enormous: they are not only disproportionately valuable, but also disproportionately influential in shaping the future’s course. Yet one has to wonder: how have these companies reached such a state? What entitles them to be the only game in town, in a way Giaccomo couldn’t even imagine? Why can’t anyone manage to compete with them effectively?

The word ‘Monopoly’ is appropriate here. But there’s something very different about Google, for example, compared to the companies of last century that monopolized scarce resources and gouged customers. Google doesn’t monopolize a scarce resource. Google abstracted away a scarce resource into something scalable and abundant: information and indexed knowledge available on the internet. They don’t exert traditional monopoly power by withholding a resource and inflating prices: Google exerts their power by making that resource even more accessible, even more powerful, to every one of its users. When more information gets added to the Internet, Google gets stronger, not weaker. Facebook doesn’t exert monopoly power by restricting who can be friends with whom; they exert their power by abstracting away the social graph and serving it so completely that if you want to reach those users, they’re the only viable option. When more people come online, Facebook gets stronger.

One foundational principle of the tech world is that as it builds upwards and outwards into the rest of the world, it’s doing so by building on top of these abundant resources and progressively leveraging them. We can think about the world that we know and understand today — with its constraints, and business models and maturing industries that are generally understood by all — as forming a layer, which we’ll call layer i. In time, as certain elements become abstracted and subsequently abundant, others emerge as newly scarce, or in play for new reasons and in new business models. The critical skill for understanding how this works (which is worth practicing!) is being able to work one’s way up and down between stack layers so as to understand when an abundant and scalable element has blossomed at layer i of a stack, and its scarce, non-scalable counterpart has emerged at a new layer — which we’ll call layer i+1.

In order to understand the technology stack properly, it’s best to start at the very bottom and work our way up through progressive layers of increased abstraction, so we can get a feel for how things layer on top of one another:


The original scarce resource at layer i: computing power on purpose-built chips. Back in the wild early days of transistors, the more functions you wanted in a product, the more single-purpose transistor density you needed. This “function density” was built up and competed over by the early semiconductor firms: Shockley, Fairchild, and so forth. Then some people (at Fairchild and then subsequently at Intel) said, Hey, let’s abstract away the function of a microchip into the instructions we gave it — in other words, make it generally programmable. Now, the number of different operations you could do on a chip became limitless, so long as you could write the assembly language for it. Intel became huge by building microprocessors, getting a sufficient head start, and then ensuring that everything got compiled for Intel assembly language. Computing power became an abundant resource (as we can empirically see in Moore’s Law). Intel became dominant and mega-profitable, while a new scarce resource emerged at layer i+1: PC hardware.


The original scarce resource at layer i = PC hardware. In the early days of PCs, manufacturers could compete along many axes of performance — memory, speed, functionality, and so forth — while being sufficiently differentiated from one another. But it was very hard to standardize common functions and applications that people could run across any computer, making it difficult for these use cases to grow rapidly — until Bill Gates and Paul Allen realized, Hey, there isn’t a software industry yet but there’s gonna be, so we should start it. Microsoft abstracted away the capabilities of a computer into software, so now anyone else could write their own software on top of Microsoft’s software without having to worry about the underlying machinery. PCs became an abundantly available commodity, and Microsoft became dominant and mega-profitable. A new scarce resource emerged at layer i+1: the ability to connect these PCs and get them to talk to one another.


The original scarce resource at layer i = network access. Everyone wanted to participate in the early internet, but the ability to actually network a node to another node and get them talking to one another was a nightmare. With traffic on the internet attempting to grow exponentially, it’s a huge problem to try to build around existing network protocols when you know they’re going to be obsolete in 18 months anyway. Cisco abstracted away all of this by building and selling networking equipment that could tolerate this changing environment, making the internet something you could “just connect to” and it would work. Internet access became an abundantly available commodity, and as things consolidated around Internet Protocol, Cisco became dominant and mega-profitable. A new scarce resource emerged at layer i+1: an understanding of the information contained on this network.


The original scarce resource at layer i = indexable information on the internet. There’s now all this stuff on the internet that nobody knows how to organize- AOL, Yahoo Directory, Excite and so forth all had their various solutions, which kind of worked for a bit but then got hopelessly outmatched by the exponential growth of web pages. As a result, if you wanted to find anything, you had to use these portals stuffed with features that serve you all this noise and garbage but not what you’re actually looking for. Then Larry and Sergei figured out, Hey, let’s use links to abstract away the relationships between pages on the internet, so that indexable info could increase scalably and become abundant. Indexed Internet knowledge became an abundantly available commodity, and Google became dominant and mega-profitable. A new scarce resource emerged at layer i+1: relationships between the people who consumed that web content.


Scarce resource at layer i = connections between humans using the internet. The internet was awash in people and content, but authentic human interaction was still relatively scarce and difficult. As such, all of the attempts at connecting people to content and advertising and services were feature-stuffed, spammy, bloated and bad. The critical step forward that Facebook accomplished was abstracting away the “reciprocal friendship” into a functioning social graph. And we’ve seen what’s happened since: Facebook, and social connectivity in general, has exploded and become a newly abundant resource. Facebook became dominant and mega-profitable.

And so this cycle goes forth — from scarcity to abstraction to abundance, and then newfound scarcity. We can project this framework into the future if we wish, although great caution is required. (We will work through how to do this thoroughly later on.)

One critical aspect of this layering is that at each higher level of abstraction, the lever with which one can create value and extract profit becomes successively longer. You can see this by looking at market cap per employee of these dominant companies:

Intel: 106k employees, 55B revenue, 149B mkt cap

Microsoft: 120k employees, 93B revenue, 429B mkt cap

Google / Alphabet: 60k employees 75B revenue, 510B mkt cap

Facebook: 13k employees, 6B revenue, 320B mkt cap

More recently, Whatsapp sold to Facebook for $19 billion of $FB a few years ago, in what turned out to be a great deal for both parties, with a double digit number of employees! Abstraction is a powerful thing.

A non-obvious but critical point to appreciate here is that for of the first n movers mobilizing around a scarce element, the arrival and eventual dominance of the last mover will be seen as a Black Swan event of sorts. By abstracting away the scarce resource instead of organizing around its scarcity, these companies become the first to be fully playing in the sandbox at level i+1, as opposed to the non-scalable scarcity-governed sandbox at level i, where Giaccomo lives. To be sure, some (or perhaps a lot of) luck goes into any given company emerging as the last mover — many things have to go right, and we tend not to hear about companies who independently arrive at the right idea but fail to thrive for whatever reason, luck or otherwise. Furthermore, as we’ll see later, sometimes those last mover companies don’t initially realize what they have on their hands at all. But until they actually explode upwards in scale, it’s not obvious at all who they’ll be, or what they do, or why they’ll be any different than the first n players. It’s easy for Giaccomo to compare himself to other musicians in town, or even to the great musicians in Milan. But he doesn’t think about how he might compete in an era of recorded music; he doesn’t know the right questions to ask.

As a more recent example: the last decade saw plenty of startups go after the transportation market, and I’m sure all of them described themselves as “scalable” in their investor decks. Meanwhile, the whole valley was busy passing on Uber because it was initially just a better way to do a black car service, and few people understood the true scalable potential in abstracting away the driver-rider trust required for UberX. The take home lesson here should be taken to heart: when the first n companies go after an issue, no matter what language they use in their pitch, their business models typically don’t truly venture beyond the constraints at layer i that anybody can see and understand. They’re easier to work through, make more sense to “rational investors”, and require fewer non-linear leaps of thinking to understand. As such, when the last mover emerges at level i+1, they’re a Black Swan event: few people foresaw their opportunity, their impact is enormous, and everybody rationalizes what happened after the fact.

This cycle from scarcity to abstraction to abundance at level i and newly emergent scarcity at level i+1 doesn’t simply proceed in a straight line. Alongside this ‘trunk’ of technological progression, we see branches sprout off that spawn many great and valuable companies with winner-take-all dynamics of their own. By thriving in an environment of newfound abundant resources, offshoot companies often find other new or adjacent scarce resources to be quite conquerable from their new powerful vantage point. The Giaccomos of these adjacent industries usually don’t stand a chance — the new tech companies are harnessing the leverage of the entire tech stack, and as such have been eating into the rest of the world at an accelerating rate. Ultimately, the companies that win make money through entirely different business models and with entirely different constraints than their predecessors.

We can summarize this cycle concisely in a one-line takeaway:

At level i+1 of the stack, the newly valuable resource is that which emerges as scarce out of the transition from scarcity to abstraction to abundance at layer i.

In part 2, we shift shift gears and look at the level of the individual customer: why they have the needs they do, how they’re overserved and underserved, and what makes for a potentially explosive market. Then in part 3 we’re going to put those two sides together.

You can read Part 2 here.

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