I’m a venture capitalist. My job is to find new, undersaturated talent markets and to invest in those before they even know they are venture-scalable. Content and Creators are what I’m betting on. They are my two loves.

Over the last five years, I’ve been watching billions of dollars being thrown to what can only be described as the “creator economy” and it’s clear that most of those bills were set on fire. I don’t want to blame anyone for that - since “Creator” is something so misunderstood that we can’t even decide on its definition or who is/isn’t one.

Creator is a $200B industry. Creators are rich. Creators need this product.

All assumptions. I’ve invested 1) with, 2) for, and 3) in Creators, professionally. I guarantee that there are maybe four or five investors on the planet that can say that. My biggest takeaway is this: The Creator ecosystem is an underdeveloped ecosystem. It’s been entirely misunderstood and hasn’t matured.

I started this newsletter to continue to find out why.

I started the Center for Creator Policy and Research as a youthful attempt to grasp which pieces legislation, people or efforts can care to nurture the progress of creators.

There are, by my count, thirteen valuable elements to Creator Policy. Most of them more focused on platforms, IP, or some other mythical, magical artist focus, but very few focus on the Creators themselves.

One of the most consequential elements hasn’t been settled at all: how a Creator gets classified, and how that classification gets taxed.

My personal frustration: you can’t underwrite an asset class the law hasn’t decided how to define yet.

In my everyday life, most people identify this topic as just “semantics” or “endless details” - which is the story of my life. But these details are always exactly what determine whether a business survives its own success. This particular detail plays out every day, in real balance sheets and real take-home pay.

We are talking about a tax code with no box for what you actually are. A classification question nobody's bothered to answer that ends up deciding (1) what you owe, (2) what you're liable for, and (3) whether the thing you built is even legally yours.

Taxation and classification, more than almost any policy proposal I've read, still can’t recognize Creators as the kind of economic actor they've actually become. This leads to, of course in my opinion, almost every “Creator business” being priced, invested in, and taxed against a category that it doesn't actually fit in.

That's a ceiling (subsequently, an investment return ceiling) problem before it's anything else. And my most surprising takeaway: the thing making it worse isn't even the platforms or directly the lawmakers (bless their hearts: they mostly haven't been asking the right question yet.) It's the prevailing description (and lack of agreement) of what a Creator even is.

And we know this through the countless, overthought-piece’d out desire to ask: What is the Creator Economy? What is a Creator?

You'll hear it constantly: Creators are the last artists. The reinvention of Hollywood. The heartbeat of human creative existence, standing against the algorithmic tide. While I do love a nice sentence, and I do understand its appeal [and applied optimism], it's too vague, boxing and borderline political to further the understanding of the hardworking people who contribute to an ecosystem I love so much.

Clinically, we can all be on the same page, but we don’t yet really know what we’re looking at. Humorously, I’ve waited years for someone far more academic or qualified to find a definition. I haven’t gotten one yet.

So instead, I’ll ask the question the “last artist” framing never gets around to: before classification, taxation, preservation, or anything else gets fixed…what is a Creator's labor and its value, actually, in the plain economic sense?

Existing Literature on Creator Labor

To be honest, content creator labor hasn’t gone completely unstudied as a broad subject. Media scholars have spent over a decade describing the conditions of this work. Conditions like:

• precarity, unpaid speculative effort undertaken in anticipation of a payoff rather than in exchange for one,¹

• the invisible labor of staying visible to a system a Creator doesn't control and can't fully observe,²

• the emotional toll of an audience relationship that behaves like intimacy and functions like infrastructure.

What that scholarship hasn't answered is a narrower, more structural question: What is economically distinctive about content creator labor?

Not what it feels like, or what it costs emotionally, or how unevenly it pays. The question this piece is asking is more mechanical: what is the actual economic relationship between the labor a Creator supplies and the output that labor produces?

A Classification Problem

How US Law Classifies Creator Labor

Before making the economic argument, it’s worth stating the legal one plainly, because it’s more embarrassing than most people realize.

The United States has no distinct worker classification category called Creator. Legally, a Creator defaults to one of the oldest boxes in labor law:

DEFINITION

Independent Contractor. A worker who operates an independent business rather than working as an employee of the party receiving the worker's services. The applicable legal test varies by statute and context.

Several areas of U.S. law approach Creator work through existing legal categories rather than a Creator-specific classification::

1. Tax treatment (IRS). A Creator earning revenue independently through an ongoing business activity will generally be treated as self-employed for federal tax purposes. If operating as a sole proprietor, the Creator ordinarily reports business income and expenses on Schedule C and uses Schedule SE to calculate self-employment tax when applicable.

   1. The scale of the activity does not, by itself, create a different worker classification. The size of the audience, the size of the Creator’s team, and the amount of income earned may change the Creator’s tax obligations, payroll responsibilities, or choice of business structure, but they don’t alone transform independent Creator activity into employment.

2. Worker classification (DOL or FLSA). When a Creator performs work for a brand or other business, federal labor law does not ask whether that person is a “Creator.” It asks whether the working relationship is one of employment or independent business activity. Under the Fair Labor Standards Act (FLSA), that classification highlights the reality of the relationship: whether the worker is financially dependent on the potential employer or is operating a business for themselves. Control over how the work is performed matters, but it is one part of a broader investigation into the actual economic relationship between the parties.

3. Copyright (work-for-hire doctrine). Copyright law adds another consequence to worker classification. It’s also the public’s favorite to debate: ownership. Copyright generally begins with the person who creates the work. When work qualifies as work made for hire, that starting point can shift to the employer or other qualifying party.

   1. CASE STUDY: The controlling case, Community for Creative Non-Violence v. Reid, involved a sculptor commissioned to make a statue.³ The Supreme Court used the working relationship between the parties to decide whether the sculptor was an employee or an independent contractor for copyright purposes.

   2. A Creator producing content independently will generally begin with ownership of that copyright. An employee producing qualifying work within the scope of employment may not. Classification can then affect how Creator labor is treated and who owns what that labor produces.

Legal Tests and Where Creators Land

Labor and Unit Production

Content creation is first a production activity. A unit of content does not enter the market directly from an idea; productive inputs must first be transformed into an output capable of consumption.

Creator labor occurs on the production side of the market. Commonly tracked metrics arise only after the resulting unit of content becomes available for consumption. The labor and the market response to its output are therefore separate performances.

DEFINITION

Content Production. The process through which productive inputs are transformed into a unit of content.

That labor can take many forms. A Creator may research, write, perform, or direct a unit of content. In larger productions, some of these functions may be performed by other workers. For the moment, the relevant input is the labor supplied by the Creator.

DEFINITION

Content Creator Labor. The productive effort supplied by a Creator toward the production of a unit of content.

Scope Note: Content Creator Labor vs. Firm Labor. This definition is deliberately narrow. A Creator’s total labor doesn’t stop at content production since negotiating a sponsorship, managing an editor, structuring an LLC, deciding whether to spin off a second channel is labor too. None of it is what this definition describes.

Content creator labor is the labor that makes the product. It’s not the labor that runs the business the thing generates. That second category only exists once a Creator starts operating like a firm, which we will talk about another day.

The Content Creator Production Function

Labor alone does not determine what gets produced. Two Creators can each supply one hour of labor without supplying economically equivalent labor. The time is identical, but the productive capability embodied in that time is not.

A Creator may bring technical skill, subject expertise, creative judgment, or accumulated production experience to that hour. These capabilities constitute human capital: the stock of knowledge and productive capability embodied in the worker. This follows the human-capital distinction formalized by Gary Becker in 1964.⁴

Production also depends on productive capital external to the worker, such as equipment, software, and production infrastructure.

Creator labor, human capital, and productive capital are therefore treated as analytically distinct inputs. A Creator’s hour and a Creator’s craft are not the same input, even though they reside in the same worker.

A simplified production relationship for unit of content (i) can therefore be written as:

THE CONTENT CREATOR PRODUCTION FUNCTION

where:

• Q_i = the unit of content produced;

• L_i = Creator labor supplied;

• H_i = relevant human capital embodied in the Creator;

• K_i = productive capital applied to production

Note: This is a conceptual production function used to identify the principal inputs to a unit of content. It is not an empirical model of content quality or subsequent market performance.

Production and Performance

Creator labor is supplied during production, but most measures used to evaluate content are observed after production has ended. Views, watch time, downloads, engagement, and revenue describe the market response to a unit of content; they do not measure the labor embodied in producing it.

This creates a basic distinction:

Accordingly, greater Creator labor supplied to one unit does not imply greater realized market performance:

Additional labor, human capital, and productive resources may improve the characteristics of a unit of content and influence its expected performance. They do not uniquely determine the market outcome ultimately realized.

The weak relationship between labor input and realized market performance is not unique to content production. Workers and firms across many industries operate under uncertainty, and productive effort rarely determines market outcomes with certainty.

The economically relevant distinction is therefore not whether uncertainty exists. It is where that uncertainty is borne.

In many conventional labor arrangements, the worker supplies labor in exchange for compensation that is substantially determined before the eventual market performance of the resulting output is known. Content Creator Labor can differ because the Creator may remain economically exposed to the market realization of the unit after the labor required to produce it has already been supplied.

Labor, Market Risk, and Creator Compensation

Labor arrangements differ in how uncertainty is allocated between the worker and the firm.

In many wage and salary arrangements, compensation is specified before the eventual market performance of the worker’s output is known. A film editor can be paid even if the film performs poorly: the worker supplies labor while the firm bears much of the downstream market risk.

Other arrangements transfer more of that risk to the worker. Piece-rate compensation links pay to measurable output; commissions link it to realized sales; entrepreneurs may bear substantially more market risk because their return depends on whether production ultimately creates economic value.

Content Creator Labor can sit unusually far toward this market-exposed end of the spectrum. A Creator may supply the labor required to produce a unit of content before knowing whether that unit will generate meaningful consumption or economic return. Where compensation depends on subsequent performance, the Creator remains economically exposed to market uncertainty after the labor has already been supplied.

Brooke Erin Duffy’s concept of aspirational labor captures one manifestation of this exposure: work performed in anticipation of future economic opportunity rather than guaranteed compensation.¹ A Creator can know how much time was spent researching, filming, writing, or editing a unit of content. They can also know its production cost. They can observe the performance of similar previous work. But, what they cannot know (with the same certainty) is how the market will respond once that unit becomes available for consumption.

The economic consequence is not simply that performance is uncertain. It is that the Creator may bear that uncertainty directly. Labor can be supplied, production costs incurred, and the unit completed before the economic return associated with that labor is known.

Creator Market Exposure

Market exposure describes the uncertainty a Creator continues to bear after a unit of content enters the market. The magnitude and distribution of that exposure vary across creators, platforms, formats, and compensation structures. Several characteristics are especially relevant to understanding its structure.

Characteristics of Creator Market Exposure

Three characteristics are particularly important:

• Volatility: A given unit of content may perform exceptionally well or disappear entirely, for reasons not fully explained by observable differences in production quality. The same level of craft, applied twice, can produce two outcomes that don’t resemble each other at all.

• Nonlinearity: Market returns do not always scale proportionally with either labor input or prior performance. Individual units can generate disproportionately large outcomes relative to the rest of a Creator’s output, producing a return distribution in which a small number of units account for a large share of realized value.

• Algorithmic Intermediation: Much of contemporary digital content is distributed through platform ranking and recommendation systems.

  • Crystal Abidin’s name for this is visibility labor: the continual effort of optimizing for a system a Creator doesn’t control and can’t fully observe.² Her point was about the sustained effort of staying visible. The claim here is narrower: for platform-mediated content, the initial audience a unit reaches can be shaped by ranking and recommendation systems.

Content Creator Labor Spectrum

Labor arrangements differ not only in how workers are compensated, but in the relationship workers maintain with the production process and with what their labor produces.

Content Creator Labor can be compared with wage labor and task-based or gig labor along two dimensions: control over production and potential output retention.

Control Over Production

Control over production is about who decides what gets made. In wage employment, that's mostly not the worker. You show up, the firm has already decided what "the work" is, and your job is to execute inside that system.

Gig work loosens this a little. You're still producing against someone else's demand (a task, a client, a contract), but at least you're choosing how to get there.

Creator labor hands over most of that decision entirely. Subject, format, process, timing, creative direction, how often to publish. All elements where the Creator sets all of it. Nobody assigns a video.

Note: This does not mean that Creator production is unconstrained. Consumer demand, platforms, advertisers, contracts, and available capital can all influence production decisions.

Control Over the Output of Labor

The second distinction concerns what happens to the output once the labor has been supplied.

A wage worker's output isn't theirs. It never was. A gig worker gets to control how the task gets done, then hands the finished product to whoever paid for it.

Creator labor is different because the labor doesn't end the relationship.The Creator can keep the unit. They keep earning from it, keep the rights to it, keep whatever it generates even long after the actual work of making it is over.

The comparison can therefore be represented as a spectrum:

Most labor arrangements sever worker from output the moment the paycheck clears. Creator labor, when it works the way it's supposed to, doesn't sever anything.

[Worth saying plainly: this is illustrative. A Creator under a bad licensing deal can lose all of this. A contractor in a different industry can retain plenty of it. Occupational title was never the right variable: the actual economic relationship between worker, process, and output is.]

Content Creator Labor, at its best, combines both: high control over what gets made, and continued control over what it becomes.

Path Dependency in Content Creator Labor

The distribution a Creator draws from isn't fixed either. Content Creator Labor does not occur under identical economic conditions from one production cycle to the next since prior production can change the conditions facing the next.

A Creator producing their hundredth unit of content may therefore enter production with resources, information, and relationships that did not exist when they produced their first.

Past Output Changes Future Production Conditions

A unit of content can leave behind effects that remain relevant to later production. Depending on the outcome, prior production may contribute to:

• Audience relationships. An existing base of consumers, familiar with the Creator and their work, who may encounter future output.

• Demand knowledge. Information about consumer preferences revealed through prior performance.

• Production experience. Knowledge accumulated through repeated production.

• Financial resources. Prior earnings that can be reinvested into subsequent production.

  • Financial resources provide one mechanism through which prior market outcomes can alter future production conditions. Returns from earlier units can be reinvested into labor, productive capital, or other production resources, changing the environment in which subsequent Creator labor is supplied. Financial capital therefore contributes to path dependency even though it is not itself Creator labor.

• Accumulated content and IP. Prior output that can remain economically relevant alongside new production.

The production of one unit can therefore alter the starting conditions of the next.

Robert Merton coined “cumulative advantage” in a 1968 paper about, of all things, why eminent scientists get credit for work their junior collaborators actually did.⁶ His version was narrower than mine: recognition begets resources begets more recognition, and two researchers with comparable early ability end up with wildly different careers for reasons that have almost nothing to do with ability.

All you have to do is swap “citations” for “subscribers” and the mechanism doesn’t even need modification. It just transfers.

The one real difference is speed. Merton was describing something that unfolds over a career: decades, tenure clocks, whole academic lifetimes. A Creator's hundredth unit can show up eighteen months after their first. Same mechanism. Different clock speed entirely.

Cumulative Advantage

So path dependency isn't neutral. It tilts.

A Creator who already has an audience, a name people recognize, a decade of production reps, and some cash to reinvest is not standing at the same starting line as a Creator with none of that, even if you handed them identical talent and identical footage. Same input, wildly different odds.

This is the part people usually get slightly wrong in both directions. It's not "the rich get richer, full stop". An established Creator can absolutely misfire, and a nobody can absolutely break through. Cumulative advantage doesn't rig the outcome. It just loads the dice before the first one gets thrown.

Which is a less satisfying story than "the algorithm decides everything" or "quality always wins eventually," but it's the more accurate one.

Audience-Trained Stochastic Performance

The term audience-trained is important. Uncertainty does not enter the system independently of consumer behavior. Once a unit of content is distributed, consumers begin revealing information about demand through their behavior: whether they choose the content, how long they consume it, whether they return to it, whether they share it, and whether they continue engaging with the Creator.

Platforms can use these signals, among many others, to inform subsequent distribution.

HISTORY TIME: Matthew Salganik, Peter Dodds, and Duncan Watts worked on this in 2006:

• STUDY: identical songs, shown to different groups, with only one variable, whether listeners could see each other’s downloads.

• OUTCOME: Quality set a floor and ceiling.

  • The worst songs rarely topped the charts, the best rarely bombed, but within that range, which song won came down to who liked it first, and whether that early signal got amplified.⁵

  • A song that flopped in one run became a hit in another, nothing about the song itself explaining the gap.

That’s the mechanism this section has been describing without a name for it: early audience response becomes an input into what happens next, rather than being an accurate report on quality.

Stochastic and Randomness

I can feel it coming… before anyone gets sad: stochastic doesn’t mean arbitrary.

Skill matters. Resources matter. Timing, distribution, existing audience relationships, competitive conditions… All of it shifts the range and probability of outcomes. A highly skilled Creator can improve the expected performance of their output without determining the realized performance of any single unit.

That’s the distinction: influence. Creator labor can improve the odds, but can’t decide what happens.

Which is why both are true at once: better Creators outperform worse ones over time, and any single unit of content is still hard to call in advance.

What Is Economically Distinctive About Creator Labor?

What Is Economically Distinctive About Creator Labor?

None of these five things are, individually, interesting. That’s the annoying part.

Production control? Any freelancer has that. Output retention? So does anyone who didn’t sign away their rights. Market exposure, temporal separation, path dependency… economists had names for all of this before “Creator” was a LinkedIn job title.

What's actually new is that all five of them show up in the same worker, at the same time, in the same job. Not sequentially. Not across a career. Simultaneously.

• Production control. The Creator determines what gets made and how.

• Output retention. The Creator may keep an economic stake in the unit after production ends.

• Market exposure. Compensation can remain contingent on how the market responds, not just on the labor supplied.

• Temporal separation. Labor and its economic return often land in different periods.

• Path dependency. Past outcomes reshape the conditions for future production.

Pull any one of these out and you’re describing a freelancer, a gig worker, a wage employee with an weird bonus structure. Leave all five in, at once, in one person, and you get a category the tax code has no box for and the law hasn’t bothered to finish defining, even despite millions of people currently living inside it, filing Schedule C, and hoping their accountant figures it out for them.

No single characteristic here is unique to Creator labor. Their combination is. That’s not a rhetorical flourish [I promise]; it’s the actual finding. You can’t underwrite, tax, or legislate a worker type you haven’t described correctly, and “the last artist standing against the algorithmic tide” was never going to get us there.

And that’s what Creator labor is. What happens once that labor starts running a business is a different question and a different piece.

1. Brooke Erin Duffy, (Not) Getting Paid to Do What You Love: Gender, Social Media, and Aspirational Work (New Haven: Yale University Press, 2017).

2. Crystal Abidin, “Visibility Labour: Engaging with Influencers’ Fashion Brands and #OOTD Advertorial Campaigns on Instagram,” Media International Australia 161, no. 1 (2016): 86–100.

3. Community for Creative Non-Violence v. Reid, 490 U.S. 730 (1989).

4. Gary S. Becker, Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education (New York: National Bureau of Economic Research, 1964).

5. Matthew J. Salganik, Peter Sheridan Dodds, and Duncan J. Watts, “Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market,” Science 311, no. 5762 (2006): 854–856.

6. Robert K. Merton, “The Matthew Effect in Science,” Science 159, no. 3810 (1968): 56–63.

I’m a venture capitalist. My job is to find new, undersaturated talent markets and to invest in those before they even know they are venture-scalable. Content and Creators are what I’m betting on. They are my two loves.

Over the last five years, I’ve been watching billions of dollars being thrown to what can only be described as the “creator economy” and it’s clear that most of those bills were set on fire. I don’t want to blame anyone for that - since “Creator” is something so misunderstood that we can’t even decide on its definition or who is/isn’t one.

Creator is a $200B industry. Creators are rich. Creators need this product.

All assumptions. I’ve invested 1) with, 2) for, and 3) in Creators, professionally. I guarantee that there are maybe four or five investors on the planet that can say that. My biggest takeaway is this: The Creator ecosystem is an underdeveloped ecosystem. It’s been entirely misunderstood and hasn’t matured.

I started this newsletter to continue to find out why.

The Hidden Assumption

Measuring Attention as a Point Event

Early in my venture career, I was given what sounded like a straightforward assignment: map an entire catalogue of niche Creators.

At first, the work felt almost mechanical. Find the Creators, organize them by niche, compare their channels, and determine which ones were most relevant to include. But the longer I spent looking, the stranger the exercise became. Over the weeks, it all started to blur together. Finding the niches was genuinely fascinating: a real window into what people actually want to consume. But the Creators within those niches? Remarkably alike. Similar formats. Similar upload schedules. Similar audiences. Even their performance on a given day frequently looked almost indistinguishable, which is a very annoying thing to discover when your whole job is finding the difference.

The expectation, I assumed, was that I would develop conviction. Look at each creator's channel on a particular day, decide who mattered, who was emerging, who wasn't, write it up, done.

I finished the project. I presented it.

My conclusion was, I'm told, not what anyone wanted to hear: I suggested we wait.

And so we did.

Several months later, we went back to the same group of Creators, and that's when the differences finally showed up. Some had quietly built catalogs that kept pulling in attention long after publication. Others were living entirely off their most recent upload, with everything older basically going silent the second it stopped being new.

Over time, I noticed, of course, the rankings changed. In my opinion, Creators or their niches had not fundamentally changed, but because we had finally observed enough of their content to see how it behaved through time.

The original snapshot had concealed the only variable that ultimately separated them: time.

It’s a very obvious understatement that a single screenshot of their analytics never told the whole story. What mattered wasn't where they were or are today. These founders are alive and their portfolios (channels) are ever living, shockingly, no matter how frequently they post. Content is a moving vessel.

Now, as mentioned in the previous article, most content markets are built off of measurements. Very obviously, views, impressions, reach, watch time, engagement, downloads, and click-through rates have become the accounting systems of the content economy. But, to me, they mean too much when you stare at them at face value. They currently determine advertising payouts, influence recommendation systems, guide creator strategy, and increasingly shape how investors evaluate content businesses. And this standardization has been super helpful…

Why Metrics Matter: A platform must be able to aggregate billions of interactions into a common set of units. A Creator must be able to compare one upload against another. An advertiser must be able to compare one campaign against the next. Measurement requires a shared language.

This though, is limiting. The idea of a unit of attention (metric) treated as equivalent to another unit of attention (another metric) is too simple to be treated as the determinant of a successful comparison.

Still a view is treated as a view, an impression is treated as an impression, a minute watched is treated as a minute watched.

This standardization assumes:

Assumption

1 Unit of attention = 1 unit of attention

Meaning, the entire content and creator ecosystem, not just platforms, to aggregate attention into common units.

And, by the way, this assumption isn’t entirely irrational. Without it, measurement would basically be impossible. Platforms wouldn’t be able to report performance and the general markets would struggle to compare across units of content, or even assets. So the issue isn’t that the assumption exists. The issue is when we forget this is an assumption, or a snapshot, at all.

Summary: Platform metrics provide a snapshot of attention at a particular moment in time. They describe what has already happened. They do not necessarily describe what will continue happening, nor do they fully capture the economic state of the underlying content asset.

Attention continues to exist after consumption

From the perspective of the metric, both events appear identical - even when the economic value is different.

The truth is content is a moving target. Creator as an industry is an ocean to navigate. It’s very difficult to grab within one short sitting.

So what do we do if attention has to be understood through time?

Most content metrics measure attention at the moment it is allocated. For the sake of this piece, let’s allow for economic value to emerge through what happens after allocation.

Attention Allocation Across Time

Platform metrics observe attention at the moment it is allocated. A view is recorded when it occurs. Watch time is accumulated while content is consumed. Granted, we don’t have assurance that an “impression” is measured the instant it is served across all platforms.

Regardless, these metrics provide an accurate record of allocation, but they do not fully describe the economic value of a content asset.

Consider two pieces of content that each receive 100,000 views:

• The view is recorded immediately

• The watch time is recorded immediately

Yet the economic state of that content asset continues to evolve days, months, or even years after the original allocation of attention

OUTCOME — from here, either unit of content can go on to:

• Continue receiving new attention

• Retain previously allocated attention through recall.

The value is in the evolution through time.

These possibilities reveal a limitation of treating attention as a completed event. At the moment of allocation, both content units appear to be identical in value. But, as time passes, their value states begin to diverge. One unit can continue generating attention and future consumption, while another gradually loses relevance.

Very simply: The thing that changes is the economic state of the asset.

This distinction suggests that attention should be modeled as something that unfolds across time. Looking like:

Definition

Let A(t) represent the economically meaningful attention associated with a unit of content at time t. Unlike a static metric, A(t) recognizes that attention is capable of persistence, accumulation, decline, and renewal following its initial allocation as a state.

Economically Meaningful Attention. Attention that retains the capacity to generate future economic consequences for a content unit, including continued consumption, recall, recommendation, redistribution, behavioral change, or future monetization.

If attention is a temporal economic state rather than a completed event, the next question is straightforward: How does that state evolve?

Attention Decays

Most attention dissipates after allocation. The rate at which attention decays attributes to its overall economic significance.

Most content receives its greatest concentration of attention shortly after publication, followed by progressively lower levels of consumption as time passes. This decline is observable across nearly every content market, regardless of platform, format, or creator. While the rate of decline varies considerably, the tendency itself is sufficiently widespread to be considered a core characteristic of attention markets.

Most Creators would interpret decay as failure. But in economic terms, decay is the expected consequence of scarcity. It’s only natural for consumers to continuously reallocate their finite attention toward newly available alternatives, causing previously consumed content to lose relative prominence over time.

In the absence of forces that sustain or regenerate attention, the economically meaningful attention associated with a unit of content approaches zero over time.

The core question is then: why some content declines more slowly than others?

The presence of decay does not imply that all content behaves identically. Some units lose attention within hours, while others continue attracting attention for months or years. The distinguishing characteristic is therefore its rate of decay.

This relationship can be represented by modeling attention as an exponentially decaying function:

The attention decay rate (δ) measures the speed at which economically meaningful attention dissipates following allocation to a unit of content.

Higher values of δ indicate more rapid declines in attention, while lower values indicate greater persistence.

Content assets may therefore receive identical initial attention yet produce substantially different attention trajectories solely because they exhibit different rates of decay.

Although the attention decay rate provides a useful mathematical description of temporal attention, it is often difficult to interpret directly. The value of δ indicates how rapidly attention dissipates, but offers little intuitive sense of the duration over which a content asset remains economically relevant. For this reason, it is often more useful to express persistence in terms of an attention half-life.

Expressing persistence as a half-life allows content units with different attention trajectories to be compared using a common temporal measure. Rather than describing content as "long-lasting" or "short-lived," half-life provides a standardized metric for evaluating how long attention remains economically meaningful. Two content assets may receive identical initial attention yet differ substantially in half-life, indicating that one retains economically valuable attention considerably longer than the other.

The distinction between exposure and persistence becomes clearer when content assets are compared directly.

In simple terms, a half-life shifts the economic unit of analysis from the magnitude of attention to its direct persistence.

Although, yes, the long-run tendency is toward declining attention, content assets do not actually decay uniformly.

Time, Space and Content

I started writing this to argue the value of understanding time, the vast space of content markets and how that impacts value not only of the Creator, their portfolio, and (as a precursor to) the formula to which they are both valued on: the sum of the value of individual units (with sprinkles).

One hope, is to start feeling these depths and take them further into account when deciding which contents to work with, for, or allocate resources towards.

Traditionally, there has been a silent debate on the ever-seeing hand of the platform’s corporate team can “industry plug” an individual as successful vs. the people supporting the person, or content, to significance.
Here though, the aim is to question not only the value, but by what metric specifically we can begin to understand success. Whether it’s the value of brand, execution of production, strategy, community reign, or management of the content portfolio to at least maintain the optics of the perceived success.

Applied to the real world: platform metrics measure attention at allocation. This paper argues that attention should instead be modeled as a temporal economic state. Once attention is viewed through time rather than as a completed event, persistence becomes an observable and measurable characteristic of content performance.

This changes the unit of analysis. Content assets can no longer be compared solely according to the amount of attention they receive at publication. They must also be evaluated according to the duration over which that attention remains economically meaningful. Time therefore becomes an economic dimension of content performance rather than merely a chronological one.

Persistence alone, however, does not determine economic value. It is one input into valuation. The next question is therefore not how attention behaves through time, but how the economic output generated by that attention should be measured.

This is one of four essays I wrote coming back from Thea & Jimmy Donaldson’s wedding. Hope you enjoyed!

I’m a venture capitalist. My job is to find new, undersaturated talent markets and to invest in those before they even know they are venture-scalable. Content and Creators are what I’m betting on. They are my two loves.

Over the last five years, I’ve been watching billions of dollars being thrown to what can only be described as the “creator economy” and it’s clear that most of those bills were set on fire. I don’t want to blame anyone for that - since “Creator” is something so misunderstood that we can’t even decide on its definition or who is/isn’t one.

Creator is a $200B industry. Creators are rich. Creators need this product.

All assumptions. I’ve invested 1) with, 2) for, and 3) in Creators, professionally. I guarantee that there are maybe four or five investors on the planet that can say that. My biggest takeaway is this: The Creator ecosystem is an underdeveloped ecosystem. It’s been entirely misunderstood and hasn’t matured.

I started this newsletter to continue to find out why.

What is the value or a “good value” of a Creator and the content it/he/she creates?

Two years ago, I remember sitting with a set of what now would be referred to as Creator P&Ls. I had also started to think about metrics that actually matter if I wanted to do this better and faster.

The task of that day was diligence and memos for two similar Creators and their respective content portfolios in a specifically interesting (and lucrative) niche market. Diligence for a niche Creator isn’t the hardest thing to wrap your head around: one commonly finds themselves more in love with the niche than the Creator most times. And, to the right fund manager, one can reason his/herself to write the check on the premise of wanting “skin in that game” alone within their own investment portfolio.

I, though, felt defeated that day. Both Creators were interesting, especially since they were compelling on the phone. But in data rooms, I had yet to find the narrative on what could be inviting as an investor. After a few hours, things started to blur.

Creator 1/Channel 1: “X tutorial of Y in 2025”…

Creator 2/Channel 1: “X tutorial of Y in 2025”…

I decided they were practically carbon copies of each other. I felt it to be a waste. Not because they were copying each-other, but because I knew they spent their talents probably competing against each other as creative souls, rather than the founders they pitched themselves to be on the phone.

Then, something interesting happened. I decided to compare to stop trying to find edgy-differences, of which there were few, and started to compare their ability as portfolio managers and operators dead on.

I decided to diligence not just the channel, but the videos themselves. So I scrolled the beginning and end of both channels and wrote down key performance metrics of each individual unit of content and decided to go pound-for-pound on each similar video, text post, or appeared-on interview. Although tedious, I was settled to find they [interestingly] performed differently. I found, and quickly tried to understand why, two “pieces” of content with similar production quality had completely different yield outcomes as units. Especially while the sentiment was that they had “similar channel performance.”

One had millions of net new views within the last year on C1/Ch1/V1. The other, C2/Ch1/V1, while in similar millions, recently had barely moved.

Why did two seemingly identical content assets produce different outcomes?

My job is to focus on the founder, of course, but Creators have the ability to upload/offload content (minus the appearances, which only would scale brand strength) that can strengthen the metrics, performance, and business of the channel.

That was the moment it became clear: the transaction in these systems is (this might sound obvious) simply sometimes for the attention generated.

We tend to think of markets in terms of money. Meaning: prices rising and falling. Goods being exchanged. Supply meeting demand. All of the things one can learn in an entry-level business class in college.

Hate to be the bearer of bad news, but I don’t think content markets end up looking like that…

In reality, you can watch a video, scroll through a feed, or read an article without paying any currency. At the point of consumption, no money changes hands. That has led to a persistent assumption: that content is somehow outside the logic of markets?

For the spoiler…it isn’t.

And before anyone thinks I’m about to try to justify new scientific learnings, yes, these are themes that are documented in media economics, generally. Attention, especially for the performance marketing folks in the room, has been documented, analyzed, and deliberated in academic settings before, BUT I want to try and see if those start for content, specifically.

And it’s my newsletter… so I can do that. :P

So here’s the rocket science: The transaction in content markets is attention.

A Market Without Price Still Has Currency

So, content markets (similarly to attention markets) operate without set price. Meaning, a user can watch a video, read a post, or scroll through a feed without paying anything at the point of consumption. There is no explicit transaction, no visible exchange of money. Since this is integral to… most markets... from the outside, it can look like the market mechanism is missing. But, thankfully, the absence of price doesn’t imply the absence of an actual exchange.

Consumption still requires a transfer of a scarce resource. Each interaction, every click, watch, and moment spent, represents a decision to allocate time toward one piece of content and away from others. And that decision has reason (mostly) and cost.

Exchange with no Cash

I thought I was going crazy spending so much time trying to find how one unit of content trumped the other. In the end, this piece won’t say that the typical impacting factors that make up an either (a) amazing (b) impactful/influential or (c) financially yielding were absent. There very well could have been one trait in particular that outweighs another. But, for the sake of us mortals: the viewer had seen a difference to get to the difference.

In traditional markets, price makes exchange visible. A buyer transfers money in exchange for a good or service, and the transaction is recorded in monetary terms. In content markets, the transaction is less visible but structurally similar, reemerging as a re-denominated exchange. This looks like:

1. A user giving attention.

2. A piece of content receiving exposure

Attention Scarcity (historically)

Happy to share there have been some smart people who have worked on something like this before. The modern concept of attention scarcity, overall, begins with Herbert Simon.

In 1971, Simon wrote, “In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is attention.”

This was the first formal recognition that:

• As information supply increases,

• the binding constraint shifts to the consumer

In the 1990s, digital systems begin to expand. Economists and theorists alike start to grapple with:

• information overload

• search costs

• and filtering mechanisms

And in comes another college punned figure: Hal Varian. Not Van Halen.

A Transaction of Time through Attention

Let’s bring up another obvious, but under-realized element: time. In content markets, consumption requires time. And time is limited.
A user cannot watch or read everything. And especially not all at once. It’s probably arguable that [Capitan Obvious on Her Way]: they cannot engage with every piece of content that enters the system, or market of content. Even when content supply expands and without without cost to consume, attention is staying just as scarce as always.

Each click, or moment of consumption, is a decision under constraint. And each decision allocates time to one unit of content. Thus, taking away from all of the others.

That tradeoff of is the transaction itself. This looks like:

What’s missing?

There’s a decent amount of theories that direct attention or (even more devious of a comparison) ““media”” economics — barf. Most discussions of digital content still focus on production: how content is made, how platforms enable distribution, or how Creators differentiate themselves. We seemed to skip a core chapter:

Fixed Time, Fluid Content

In a classical marketing habit, every individual does operate under a fixed time endowment. There is a proven-only-so-many-hours-in-a-day, and that limit does not change as the supply of content expands. This is the source of scarcity in content markets. But we’re going to be economically sound here in this house. Leading the distinction as follows:

What matters, however, is how time itself is distributed. Two individuals may possess identical amounts of time while allocating it in entirely different ways. The economic question is therefore not how much time exists, but where attention is directed.

Cold reality is: what matters is how that time is distributed.

Where:

• T = total available time

• Where A_i represents attention allocated to content unit i

This relationship captures the fundamental constraint of content markets: every allocation of attention toward one piece of content necessarily reduces the attention available for another.

Content supply will continue expanding without limit, while attention remains bounded by time.

And then beyond Time

One of my favorite brain-meets-reality thought gums to chew on has been something surfacing Dunbar’s number (humans can maintain only a finite number of meaningful social relationships) or Miller’s working memory, or even some Cognitive Load Theory (the capacity to process new information is constrained) in processing limits. So you can see where this might go.
Even if an individual possessed unlimited time, there remains the question of whether they could meaningfully interpret, retain, and contextualize everything they consume. Human cognition is not totally, infinitely scalable. In simple language: we, as a species, do not simply consume any kind of content; we will process it, compare it against existing knowledge, assign meaning to it, and decide whether it deserves future attention.

Existing research in psychology (and recollection to some basic level AP psych education) has long recognized that individuals face limits in memory, recall, and social cognition. People can recognize thousands of faces, yet maintain meaningful relationships with only a specific fraction of them. They may even encounter hundreds of names, specifically, throughout their lives while actively remembering only a subset.
The information itself is abundant, while the capacity to organize and interpret that information remains constrained.

Content markets appear to operate under similar conditions: a user will scroll past hundreds of posts in a single day, watch dozens of videos, or encounter thousands of pieces of content in a month. And only a small portion of that content becomes part of their active mental model of the world. Or what I would define as any type, phase, or depth of true influence (let alone significance) to another. Most information is discarded almost, but innocently, immediately after consumption.

Creators are therefore competing for retention, recall, and cognitive significance. The highest-value content is often not the content that receives the most exposure, but the content that successfully occupies durable space within a consumer's mental framework.

Attention can be allocated momentarily and still not interpreted meaningfully.

And more bluntly: the true constraint in content markets is not be time spent alone. It may also be the finite capacity to interpret, retain, and organize information.

If that is the case, Creators are competing for something more valuable than attention itself. They are competing for a limited amount of cognitive space within the minds of consumers.

Consumer Choice in Content Markets

The great news is we can find comfort in normal market definitions: every market requires choice. Scarcity forces selection. Consumers do not purchase every product available to them, nor do they consume every service that enters a market. The same applies to content consumed.

A consumer opening a social platform is immediately confronted with an abundance of options no matter the platform. Videos, articles, podcasts, livestreams, clips, and posts compete simultaneously for a finite amount of attention. The vast majority will never be consumed. Some will receive a few seconds of consideration. A small number will receive meaningful attention by, yes, the larger consumer group to that platform (solidified through performance metrics compared to other content on that same platform), but also the individual.

At the risk of sounding like ChatGPT, it truly is like this: The economic problem facing the consumer is therefore not access, but allocation.

Traditional markets often ask:

Which good should I buy?

Content markets ask:

Which content deserves my attention?

The distinction can seem small, but it changes the structure of the market entirely. And publicly, as a group, we have yet to test what this means. Because attention is scarce, every decision carries an opportunity cost. This is especially true to rising average number of units of contents consumer or percieved per individual user as seen through screen time and advertising performance per platform rising. Choosing one piece of content necessarily means rejecting another.

Formally, if attention is allocated to content unit (i),

Attention Opportunity Cost

Where an increase in attention allocated to one content unit reduces the attention available for competing alternatives.

This relationship is the foundation of competition in content markets. Creators are not competing against every Creator equally. They are competing for marginal units of attention at the moment of choice. Every click, view, listen, or watch represents a consumer selecting one alternative from a larger set of possibilities.

And most importantly, the competitor isn’t always another Creator.

A YouTube video competes with TikTok. TikTok competes with Netflix. Netflix competes with a book. A book competes with sleep. All activities that require time and cognitive perception ultimately participate in the same attention economy because they draw from the same finite resource.

This means content markets are substantially larger than creator markets alone. Creators are not merely competing against each other. They are essentially competing against every alternative use of consumer time.

Viewed through this lens, content performance becomes easier to understand. Success is not simply a function of production quality, distribution, or creator reputation. Success occurs when a piece of content consistently wins allocation decisions against competing uses of attention.

Moments of Choice

Attention markets operate through a series of discrete decisions.

Much of economics, ultimately, is the study of choice under constraint. Individuals face limited resources and decide how to allocate them. A consumer doesn’t purchase every good available in a market. And a firm can’t pursue every investment opportunity.

Every time a user opens an application, refreshes a feed, performs a search, clicks a thumbnail, or scrolls past a post, a choice is being made. Most of these decisions occur within fractions of a second. And yet, collectively, they determine the allocation of attention across the entire market.

From the perspective of the consumer, these moments often feel insignificant. Clicks feel automatic. A scroll may seem unconscious. Economically, however, these actions represent allocation decisions. Each moment of choice determines where a finite unit of attention will be directed and which competing alternatives will be rejected.

In this sense, moments of choice function as the clearing mechanism of content markets. They determine which content receives attention, which content is ignored, and ultimately which Creators capture value.

Creators Compete for Marginal Attention

80% of the time when I mention that I study Creators and Content for a living, people are confused on how that can be different from any other business. You can just look at follower count. You can just ask them how much they make.

Content markets, even, are often described in terms of views, subscribers, followers, impressions, or engagement. And while these metrics can be useful measures of performance are the result of unit-level competition.

A common falsehood is that these metrics are the object to focus on, but my warning is that we’re smarter than this. The object being competed for is attention.

Here are some hard truths:

1. Creators are competing for marginal units of attention at the moment of allocation.

2. Every consumer possesses a finite quantity of attention that can be distributed across competing alternatives.

3. Because that attention is scarce, Creators must compete to secure a portion of it.

   1. Hell, sometimes they even compete against themselves within their own portfolio.

4. This competition occurs continuously and until the end of time. Metrics never stop.

5. Each piece of content is implicitly compared against every available alternative.

6. A decision to allocate attention toward one video simultaneously represents a decision not to allocate attention toward another.

The Result: content markets are fundamentally relative rather than absolute.

The performance of a piece of content depends on the quality, relevance, and attractiveness of competing alternatives.

This distinction helps explain why content performance can vary dramatically even among seemingly similar assets. Two videos may address the same topic, target the same audience, and possess similar production quality, yet produce different outcomes because they compete within different competitive environments.

Competition is for Units

My favorite thought exercise is to challenge the notion of strong Creator rivalries. Over the years, there have been efforts from platforms or high-ranking Creators themselves to call for a more unified creator community. And while this comradery can be warm and fuzzy, it is also honest to the economics of the content market itself.

Rivalries are silly because Creators are not only competing against other Creators.

All activities that require time draw from the same finite resource. As a result, content markets extend beyond individual platforms and Creators. They form part of a broader attention economy, in which, every potential use of consumer time acts as a competing alternative.

Viewed through this lens, acting as a Creator changes the goal of content away from merely to attract attention. The goal is to win allocation decisions repeatedly enough to accumulate attention over time. Views, followers, and engagement emerge only after those decisions have been won.

Clicking under Constraint

From an economic perspective, a click represents the transfer of attention from the consumer to the content asset. Before the click, attention remains unallocated from the consumer’s side. After the click, consider attention to have been committed to a specific alternative and removed from competing options. It’s out of that ring.

It’s important to recognize that content markets usually analyzed using outcomes rather than what should be considered decisions. Why is this? Views, watch time, and engagement are measured after attention has already been allocated. The click represents the moment at which allocation actually occurs.

Content markets therefore operate through countless decisions made under constraint. Each click reflects a judgment about how a scarce resource should be used. Collectively, these judgments determine how attention is distributed throughout the market and which content ultimately accumulates value.

Attention Allocation vs. Platform Measurement

Platforms do not directly measure attention allocation. They do measure observable signals that occur after, during, or around attention allocation.

Views, impressions, watch time, downloads, and engagement metrics are accounting records of consumer behavior, but not the attention themselves. The true economic-like decision occurs when a consumer decides to allocate a scarce resource toward one piece of content instead of another.

So I wanted to point out the obvious: Different platforms define and record engagement differently. A one-second TikTok view may be counted as a view, while a podcast download may be recorded without any guarantee of consumption. A user may read an entire post on X without generating meaningful engagement, while another may accidentally trigger a view metric with almost no attention allocated at all.

The market mechanism operates through attention allocation and the platform merely records traces of that allocation.

Content markets appear different from traditional markets because money rarely changes hands at the point of consumption. Obviously, this isn’t to say that money isn’t made but in a non-direct pulley system from creator to consumer. A user can watch a video, read an article, listen to a podcast, or scroll through a feed without paying a dollar. Still, an absence of literal money does not imply an absence of exchange.

Attention is scarce. Consumers allocate it under constraint. Every view, click, listen and watch represents a decision among competing alternatives.

• Creators compete for it.

• Platforms attempt to measure it.

• Market outcomes emerge from its distribution.

Content performance becomes easier to understand through a lens like this. But also, not all attention behaves in the same way. Some attention disappears the moment it’s allocated. Other attention continues generating value long after the original interaction has ended. Understanding this distinction is essential for understanding why some content dies quickly, why some remains valuable (and lucrative) for years, and why specific Creators build durable businesses while others remain dependent on constant production.

Hope you enjoyed this! Finalized this on a train to Milan on 6/13/2026. Happy Birthday to me! Xoxo

I’m a venture capitalist. My job is to find new, undersaturated talent markets and to invest in those before they even know they are venture-scalable. Content and Creators are what I’m betting on. They are my two loves.

Over the last five years, I’ve been watching billions of dollars being thrown to what can only be described as the “creator economy” and it’s clear that most of those bills were set on fire. I don’t want to blame anyone for that - since “Creator” is something so misunderstood that we can’t even decide on its definition or who is/isn’t one.

Creator is a $200B industry. Creators are rich. Creators need this product.

All assumptions. I’ve invested 1) with, 2) for, and 3) in Creators, professionally. I guarantee that there are maybe four or five investors on the planet that can say that. My biggest takeaway is this: The Creator ecosystem is an underdeveloped ecosystem. It’s been entirely misunderstood and hasn’t matured.

I started this newsletter to continue to find out why.

The popular claim that “the internet democratized content” usually bundles together at least three different propositions:

(a) production is cheap enough for many people to participate,

(b) publishing is open enough that gatekeeping is minimal, and

(c) distribution is technically global, so the market behaves like an open competitive arena.

Those first two propositions are often true in a narrow, technological sense. The third, about market structure and competitive outcomes, does not automatically follow.

Economists typically evaluate whether an arena is “free” by looking less at whether participation is allowed and more at how allocation works and what outcomes that allocation produces. Perfect competition is the usual baseline model: many buyers and sellers, free entry and exit, and “all relevant information” available to market participants (meaning: no systematic information advantage that changes who wins).

I support platforms as key components to online US GDP, creators of new jobs and markets and the likes of which any open capitalist would support the hand that feeds them. I also want to have as said capitalist an understanding of how the economy works.

In microeconomic theory, markets are evaluated based on structure and tested with real-world outcomes. A market may allow participation while still showing core structural constraints that meaningfully shape the all-so-enticing competitive outcomes. Therefore, before before we can figure whether the content economy is “free,” I decided, for fun, to dust off some college textbooks and define what freedom means within traditional economic analysis.

The Distinction Between Production Freedom and Market Freedom

This starts from a simple conversation with an institutional LP with enough traditional financial education that reasoned exploring investing in Creators as firms, or at least Channels as Cash-Flow Portfolios. The conversation flowed as follows: “The content economy clearly exhibits production freedom. Barriers to uploading content are minimal. Equipment costs are historically low. Platform access is global.”

They had interest in buying up specific channels of which, at that moment of time, were performing well for the expectation he had at the moment. My role was to help their analysts learn models that I had been working on to prove a perfect, juicy monopolistic outcome because of the health of a Creator HoldCo. Still, something didn’t sit right. I had been in enough pro-Creator or at least enough pro-Creator-Capitalist group chats to know that there is still some insider-baseball to be played. There is some arbitrage to be found separate from perfect content execution. Simply put, great content businesses do not grow on healthy vines.

We started to run through risk. And while, yes, I will tell you all day how amazing investing in HoldCos work. You’re going to get different use cases depending on what you want to do with these units of content, channels, or firms.

I decided to run through why these businesses or channels die and what the definition of that can mean if the content itself is truly scalable and yield-yummy without constant production of new units of content. A core outcome after some hard conversations with operators in my groupchats, traditional friends, and even a few smarter-than-me economist buddies ended up on: Production freedom does not automatically imply competitive freedom.

This is one of the strong misconceptions of the content or creator ecosystem: you make lot of money because it’s so free and open and easy. But how free can it be? If a Creator company does what nobody (audience, investor, fan, whatever) wants (die), where does that inevitable death come from and how can you avoid it?

Off of the bat, there is human-error that we’ll get to one day. Recently, my thought and business partner Thea and I have been doing some Founder Sustainability content with Harvard’s Chan School on how to literally prepare Creator Founders for the human-error associated. Took me back to days doing crisis-comms-like prep working with traditional software founders that had simple, yet very true phrases like: touch grass.

So what can the structural bottlenecks be?

Firms can produce freely in most markets but cannot access customers without the spooky and often hated "intermediaries” controlling distribution channels. Off the bat, I want to clear some more air that platforms are not the enemy. The partner managers, or whoever has the guts to do the relationship management between Creator and platform are often good-natured and incredibly helpful. Some might say software founders would be gleeful to have this level of hands-on communication from their distribution overloads (Google, Apple, etc. We might even one day think up what that would look like.)

The frustration, though, is normal to hear when we think of “funnels” or “bottlenecks” overall. We can even nerd out and go through a lot of historical parallels: railroads, telecommunications, broadcast spectrum, and energy infrastructure have all functioned as either innovation or distribution bottlenecks. Hell, I even get mad at poor road management near my parents house in Long Island (potholes and the likes). In each case, the story is the same: production was decentralized while access to consumers was mediated through a controlled infrastructure.

We don’t like this because they are the holders of another not well loved concept: scarcity. Typically, the scarcity lies in tandem with production (or in this case, creation). In digital content markets, the scarce resource is the ability to secure attention.

The good news is attention scarcity is a topic that’s been of concern for decades. Attention scarcity ends up totally transforming distribution into the primary economic constraint. Operationally, it works like this: Once attention becomes scarce, coordination mechanisms must allocate it. If we’re talking platforms: that allocation is governed by always scary-sounding algorithmic ranking systems.

Here’s my expected take: the presence of ranking is not itself problematic. It’s usually a secondary, reactionary way of sorting an already sorted pile. Ranking is a necessary response to scarcity. The question is whether the ranking mechanism ends up preserving, protecting, and defending a competitive neutrality or ends up embedding a structural asymmetry.

What Economists Mean by a Free Market

In classical and neoclassical frameworks, a free market is defined by “decentralized exchange under conditions where no single actor exerts coercive control over participation or price formation.” More specifically, economic freedom tends to rely on several structural conditions:

1. Low barriers to entry and exit. New firms can compete without prohibitive capital requirements, regulatory hurdles, or control over essential infrastructure.

2. Diffuse market power. No single firm can meaningfully influence price or suppress competitors.

3. Information symmetry. Participants possess adequate information to respond rationally to incentives.

4. Competitive mobility. Firms can scale or decline based on performance rather than structural exclusion.

5. Decentralized coordination. Market outcomes emerge from distributed decision-making rather than centralized allocation.

The benchmark model of perfect competition, as formalized in later neoclassical frameworks, functions as a baseline for what we’re trying to do today. Let’s now give a solid college try to apply these to content markets.

PS. There is a reality to a test like this: markets that deviate from these criteria may still be dynamic and innovative. They may still be productive, but they are no longer structurally free in the classical sense.

Information Symmetry (or Asymmetry) and the Hayekian (Not Heineken) Problem

One of the strongest theoretical defenses of free markets has been articulated by a college throwback name: Friedrich Hayek. Of which, at the time, I promptly decided to call this a Heineken problem, of course. Decentralized price systems efficiently aggregate dispersed information. In competitive markets, price signals coordinated behavior without a pre-planned central planning system. So who the heck is pricing content and does that exist?

Short and sweet: Creators do not receive a transparent price signal for distribution.

(Note: They receiving exposure based on, okay yes, pretty opaque and probably dense weighting systems. The exposure, of course, has an ever-changing price (which, one can guess can be CPM) determined by ad-interest, conversion metrics, and overall the Ads department of a major platform. That, however, is not the primary metric we’re looking at.)

Platforms feel like Apple, sometimes. I’ll give everyone that. So the informational feedback loop is pretty hidden. Even someone who spends every chance she gets to stumble around a Youtube or TikTok engineer still can’t figure out exactly what is going on algorithmically or even who makes the criteria to determine an event worth changing it. This brings a woo-woo religiosity to platform algorithms. We are scared of the things we do not know. So, my invite to the platforms would be: if you want to make the rules, that’s awesome. They are probably SO justified and have rigid criteria around those decisions. You can let, if not the public, then the Creators more in on what’s going on. This can also help with the issue as a platform-supporter, even I find tough: I’m finding out a lot of these on deposition calls in front of Senate with some underlying tone of scary, rather than getting my insider baseball.

This introduces a very critical question: if market participants (forget audience members…. operators and Creators) cannot fully observe the rules governing distribution, can the system be considered informationally symmetric?

Information asymmetry is one of the core sources of market distortion in textbook traditional microeconomic theory. When one side of a market has materially superior knowledge about the allocation mechanism (in this case, the algo), competitive conditions shift. For accuracy and probably legal purposes, I’m not going to say that certain creators are given this information with platform-malicious intent. I will say that there hasn’t been a strong challenge on how information symmetry strengthens the importance of not only Creators, but platforms in serious economic consideration.

Put simply: In the content economy, platforms possess complete visibility into ranking mechanics. Creators do not. This asymmetry probably does complicate the claim of market freedom.

Who cares?

The central issue is not whether platforms allow participation. They really do. I can bore you with numbers, but you can see it for yourself on your own FYP. sixteen, seventeen, eighteen-year-olds normalizing being millionares whether through faced or faceless content. It seems like the logic is simple, well communicated and understood. Content creator = good. More content = good. Platform = money.

The issue is whether access to meaningful distribution and yield [which would sound like sustained visibility capable of generating economic return] is competitively accessible under transparent and symmetric conditions.

In other words: Are creators price-takers in an open competitive environment or are they participants in a pre-mediated system where infrastructure owners accidentally force-shape exposure?

If production for the content is open and available but distribution is structurally intermediated, then the content economy may resemble a more platform-coordinated market rather than a frictionless competitive one.

So other than for investment purposes, why are we supposed to care?

As someone who works on, yes, investments but also policy and research about whatever content or creator world you think of while clicking on this, I can tell you firsthand the market classification of content and creator(s) directly influences both interpretation and policy.

Platforms almost (actually almost) universally hate being moderated or any type of political involvement. Which is fair, I can’t think of many historically that do. And while there are still so many cases for why it is “bad that it is not” we should also argue why everyone feels that way.

Part of the reason why C-CPAR started was for all of this.

There is something very good that is happening within the platform ecosystem for people, money, and policy. And, if it helps them, a market characterized by diffuse competition and transparency requires minimal intervention. A market characterized by concentration and structural asymmetry invites different full-stack treatment altogether.

And that’s my take on moderation and policy at the moment. The fact that the interest is there shouldn’t be a bad thing, but it should be a validator that the ecosystem does work as a market on its own.

Back to textbook world we go: let’s try to operationalize a criteria of market freedom and do what every economists thinks they can do with limited data or transparency: test them against observable characteristics of the content economy. The topics are: concentration ratios, entry mobility, informational transparency, and a structural advantage.

Two Levels of Competition in the Content Economy

You’re going to hear me talk about a flat market a lot. I’m sure there’s a more formal word for it, but for a moment, let’s consider all individual units of content that can be accessed individually. Oftentimes, when we think about the general creator economy, the personality and story and production stays at the forefront.

But if we can consider a flat-base portfolio of units of assets = channel, we an make an interchangeable definition of “unit of content,” and can start seeing how the content economy works as a market and economy, rather than the individual mechanics of each platform. If the content economy is to be evaluated as one solid market, it must be evaluated using the same structural criteria economists use to define markets elsewhere.

Market freedom typically is assessed through observable features: concentration ratios, entry costs, information symmetry, and pricing power. So we’re going to try our best to see how the content economy matches up.

One reason the debate around whether the content economy is “free” feels muddled is that we often collapse two very different layers of competition into one. But they are actually not the same.

The creator economy operates on two overlapping competitive planes:

1. Unit-level competition. Where individual pieces of content compete for exposure.

2. Firm-level accumulation. Where exposure aggregates into durable scale and economic leverage.

Unit-Level Competition

At the most immediate level, competition in the content or creator economy occurs at the level of the individual content unit. Whether a video, a post, a podcast episode: each individual unit enters the allocation system independently. Platforms do not (in most cases) allocate exposure based purely on who the creator is. They allocate exposure based on how the individual piece of content performs.

Ranking systems ingest behavioral signals: click-through rate, watch time, completion rate, engagement, session continuation. Behavioral signals determine how widely that specific unit of content is distributed.

Note: User preference is … like you… believe it or not…multidimensional. It includes long-term trust, reputation, intellectual depth, community belonging. So ranking systems are typically going to optimize for signals that are measurable at scale and in total real time. This ends up making something called a measurement constraint.

Hal Varian and others writing on information goods have long noted that digital markets are governed by ranking and filtering mechanisms because information overload must be resolved algorithmically.1

Proving it

And this section might be for my Dad. How can we measurably prove some element of what we’re talking about? In traditional economics, we observe theoretically how values and exchanges move.

Competition on a unit level is - shocker - very granular; making each upload is a new trial and each piece of content has a probability of exposure that is conditional on performance.
Formally, we can think of exposure at time (t) as:

What everything stands for:

Where Q represents performance metrics observable to the platform. A creator with 500 subscribers can have a video outperform a creator with 5 million, if the content generates stronger engagement signals. Small accounts can go viral and new entrants can break through. Legacy status does not guarantee distribution of a weak upload.

More importantly, on a per-video basis, the allocation system resembles competitive sorting rather than centralized assignment. Content is then competing on measurable performance. And, suure, if we were to stop here, the content economy sounds open: each product competes, consumer behavior determines amplification, and firms must respond to demand signals.

Firm-Level Accumulation

The system does not reset to zero after each upload. Instead, it makes exposure accumulate.
A creator who receives 100,000 impressions on one video does not return to a neutral baseline for the next. They retain (again, this varies per platform, but let’s assume one whole market for a minute) some fraction of that exposure in the from of subscribers, recognition, familiarity (brand), and algorithmic history. Over time, these accumulated exposures begin to function as economic capital.

Aaand now we get to the second later. While individual pieces of content compete at the unit level, exposure aggregates at the firm level. And once aggregated, that exposure can influence future allocation probabilities.

In its simplest form, unit-level exposure might look like this:

Where exposure for content unit i at time t depends only on the quality or performance metrics of that unit. But in reality, exposure may look more like this:

Where S{c,t−1} represents the prior scale of Creator C.

Scale here means: subscriber base, historical watch time, past engagement rates, brand recognition, data sophistication, cross-platform spillover, and production capital.

Fig 1. The top row represents unit-level competition. The bottom box represents accumulated firm-level scale. The feedback arrow illustrates the structural condition under which prior exposure influences future exposure probability. This is the compounding mechanism.

HARD IF, if prior scale influences current exposure probability, even marginally, then competition itself shifts from purely trial-based sorting to path-dependent accumulation.

There is still potential to invest in creators that have moat. They can have the following, as either firms or founders, no matter what your definition preference can be. (I know we haven’t gone over Creators as Firms formally yet here, so just throwing it out there.)

A “Moat” as a creator can be the following: higher initial impression allotments, faster engagement sampling, greater click probability due to brand familiarity, higher advertiser demand, stronger cross-platform spillover, etc. Over time, of course, exposure converts into durable economics leverage, also referred to as momentum. This is where the content economy begins to resemble other attention markets (music streaming, publishing, venture capital) where outcomes follow a power-law distribution.

In short: Unit-level → Firm-level → Compounding → Structural question → Transition to concentration.

If individual pieces of content compete on measurable performance, the system may appear meritocratic. Sure, a strong upload can outperform a weak one, even regardless of creator size. But there are thousands of examples of small accounts can still break through. The presence of unit-level competition does not automatically guarantee firm-level contestability.

The structural question is this: Does unit-level meritocracy translate into firm-level mobility? In other words, even if each piece of content is evaluated independently, does the accumulation of exposure over time create actual durable advantages that are difficult to displace?

If exposure at time t depends only on current performance Q{i,t}, then competition remains unit-based and contestable. But if exposure at time ttt depends partially on prior scale S, then outcomes become path-dependent.
Path dependence means that early advantages (whether from timing, format, luck, or initial amplification) can compound. A creator who achieves scale gains structural benefits:

• Higher baseline click probability due to familiarity

• Larger initial sampling pools from subscribers

• Greater advertiser demand

• Stronger cross-platform spillover

• Capital to invest in production and optimization

These emerge naturally from scale. If upward mobility is frequent and rapid, then concentration can reflect ongoing competition. And, if upward mobility is rare and incumbency persists, then firm-level compounding begins to resemble increasing returns markets; industries where early scale advantages dominate long-run outcomes.

And I know everyone is going to think this sounds like complaining or whining, but actually it’s a moment of clarity we have to have with ourselves on how pure of a market a capitalist is playing if given the cards to do so. If you can take anything away from here, it should be: there is still arbitrage within the creator ecosystem, either in talent or information, or preference, or anything that would require for one to be informed on how to play it.

From Compounding to Concentration

The Wrong Denominator

I’ve heard a lot of numbers trying to quantify the creator and content economy. $250B, $300B, or even half a trillion. Regardless of whatever shiny number can show how impactful or large, I know using ecosystem valuation as the denominator when discussing income concentration is a category error. We should focus on total creator or unit of content income.

In industrial organization, defining the market incorrectly produces distorted conclusions. A firm that appears small relative to the entire economy may be dominant within its actual competitive market. By this, if the top 1% of creators capture 25–30% of total creator income, that is economically meaningful; even if it represents a tiny fraction of total social media advertising spend.

The structure of competition must be evaluated at the level where firms actually compete: in exposure and revenue.

Modeling Creator Income Distribution

If firm-level compounding exists, we should expect to see it reflected in income distribution. Headlines cite figures like “the creator economy is worth $250 billion,” and from that conclude the market must be diffuse. The truth is that the majority of this data is not clean, non-biased or large enough to really evaluate. If you’d like to work on something here, send me an email.
But from what we have, the $250 billion figure includes: platforms, agencies, software providers, creator tooling, marketing infra, and ad intermediaries.

Across multiple reports suggests a few consistent facts:

1. Median annual creator income hovers around $15,000.2

2. Nearly half of creators earn below that threshold, with Linktree reporting that approximately 46% earned less than $1,000 annually.

3. Only a small percentage, often estimated around 4%, earn more than $100,000 annually.3

I know what you might think, those numbers alone imply skew. A market where the median is $15,000, but a visible subset earns millions is not symmetrically distributed. To estimate concentration meaningfully, we need to approximate total creator earnings and distribution tiers. Again, I cannot stress enough that this is using non live-time data and the data given to us. So we’re going to build a conservative model.

Let’s attempt a model

Assume roughly 2 million actively monetizing creators globally. That figure is debatable, but it provides a working scale. Now divide income into tiers consistent with survey medians and observed earnings dispersion:

Again, this is assuming a lot, so !Illustrative!, but it’s a solid attempt to understand distribution.

Heavy-tailed income distributions require increasing returns. In markets where distribution scales at near-zero marginal cost, small differences in exposure can translate into large differences in income. Sherwin Rosen’s “Economics of Superstars” demonstrated this dynamic decades ago: when one performer can reach millions at little additional cost, even modest differences in perceived quality generate disproportionate earnings dispersion.

Fig.2 The straight line represents a scale-neutral system: prior scale increases exposure proportionally. In such a system, doubling your size doubles your exposure.

What we do not know is whether prior scale materially influences exposure probability. If it does…then firm-level outcomes become path-dependent.

This could sound like bad news, but surprise surprise it is good news for a capitalist. There’s a shape of a power-law! It resembles the distributions observed in other increasing-returns markets (venture capital, book publishing, music streaming) where small differences in visibility compound over time.

Question still stands: Do new creators regularly enter the upper percentiles? Does turnover occur within the top income tiers? Or does scale harden into durable advantage?

If firm-level compounding exists, we should expect income concentration. But the question still stands as to why? And to answer that, we have to examine how per unit and per firm distribution actually works. If content operates as a market, then creators are not simply participants. It means that they are core producers within a system where distribution, information, and scale determine outcome yield. The content economy is large and accessible, but still questionably structurally competitive.

That distinction will define how creators are valued, financed, and ultimately built into firms.

I’m a venture capitalist. My job is to find new, undersaturated talent markets and to invest in those before they even know they are venture-scalable. Content and Creators are what I’m betting on. They are my two loves.

Over the last five years, I’ve been watching billions of dollars being thrown to what can only be described as the “creator economy” and it’s clear that most of those bills were set on fire. I don’t want to blame anyone for that - since “Creator” is something so misunderstood that we can’t even decide on its definition or who is/isn’t one.

Creator is a $200B industry. Creators are rich. Creators need this product.

All assumptions. I’ve invested 1) with, 2) for, and 3) in Creators, professionally. I guarantee that there are maybe four or five investors on the planet that can say that. My biggest takeaway is this: The Creator ecosystem is an underdeveloped ecosystem. It’s been entirely misunderstood and hasn’t matured.

I started this newsletter to continue to find out why.

A Shift in Venture Models

Why I’ve focused 16.3 months studying early-stage holding companies and why you have one, and why you’re going to miss these deals.

Shift in Venture Models

Historically, there are two camps in the startup ecosystem:

1. Focus on one thing or

2. focus on the big thing.

The hardest pill to swallow is: Most times the biggest thing might have multiple moving parts.

Both approaches worked in an era when distribution was scarce and products were hard to build. But the world has very, very obviously changed.

1. Social media has made distribution accessible to anyone with a story worth hearing

2. AI has obliterated product-building costs (at an early-stage level) while multiplying product proliferation

Traditional venture capital, by contrast, is still structurally wired in single company investments with high-technical risk but potential exponential upside. This, as we all know, has produced high failure rates, by wasting resources on “let’s try it out” early-career founders. All while limiting innovative optionality for the most innovative founders by focusing on just one shot on goal.

Early-stage holding companies around individuals (founders or Creators) provide multi-shot optionality from day one.

Definition: Creator Holding Company
A creator holding company is a firm structured around an individual, where content generates distribution and cash flow, and that capital is deployed across multiple businesses, products, and investments.

Why Early-stage Holding Companies

For the “we back Founders” type, this model is no-brainer. You invest in an individual for the exposure to anything they launch, and double down on what they (and you) think will hit. Giving them the ultimate freedom and alignment to VCs they actually want on their cap table in the early-days.

For the “we back what is working” type, underwriting the holding company surfaces the true breakout opportunity faster, while spreading early-stage risk to someone else, but still stay relatively early.

Different bets demand different structures, resources, and leaders. The hiring construction can seem (for the companies that grow very fast) that each section requires a section “owner” (what I call a GM) that focuses on the distribution, ownership, product and money-flow on what the big picture is. Not only can these growing areas have different accounting and legal profiles (one area gets sued or goes under), but also can be broken down and sold to whoever the innovation-universe feels like would be the best owner of the business. Also, a founder can do a sell-off to shed (for what’s not relevant anymore), financially stay alive, and refocus) without jeopardizing the parent company.

Creators as Firms

As a startup-focused definition and on a microeconomic level, Creators form as firms from the start.

Even at a small scale, the Creator of the firm is spending more time allocating Creator resources (distribution, brand, financial, operational, etc.) to fit the higher goal (the purpose of the holding company, which can be related or unrelated to the content made.)

• Content generates strong, repeatable cash flow

• That cash can be reinvested into businesses with higher upside and contribute differently to the larger swing of the HoldCo

• For high-growth Creator-Founders, the channel is not the business, it’s the data-core (distribution or data-intake) engine for the business.

Creators as Founders

The financial ecosystem has begun to recognize this reality: around $3B investment minimum thrown into Creator holding companies varying from venture capital, private equity, and debt on the IP or owned-businesses separate form the media.

The best creator-Founders understand two things:

1. Distribution-first necessity. Attention is gasoline. Without it, nothing else ignites.

2. Risk volatility. Creator businesses are extreme. They are like a stream of gas waiting for a match. They can be instant rocket ships or instant failures.

They also care about the following, in order:

1. Data: obsessively measuring audience response and retention

2. Product: building what the data validates

3. Distribution: scaling reach across both consumers (easy) and enterprise (even easier)

The two archetypes to optimize for: distributive and community-focused. I wrote about this here. How they differ:

1. Distributive Creators. The gift of “growth.” “Is the founder operationally gifted at distribution (can make a “viral” unit of content clean, without their channel, almost with their eyes closed)

2. Community-based Creators. The gift of “retention.” Can build a deeply loyal, high-retention audience whose spending power compounds over time

Accessing the next MrBeast

Community-based founders are more of a bet on the willingness and quality of their audience to purchase, rather than the tenacity and operational ability of the Creator themselves.

In the case of finding the next MrBeast, investors and Creators need to see the content itself as a business discipline.

Jimmy Donaldson was the first person to find the scalability of content worth more than just something to sell a product, but content itself can be venture-scale.

I know this business pretty well at this point. The MrBeast company, to me, is a data company and guided a lot of my thesis. The team takes data seriously.

Algorithms shift daily, but the MrBeast team relentlessly continues because they digest data, apply learnings, evaluate results, and try again. This process-driven approach is what separates a lucky hit from a scalable company.

A venture-scalable Creator knows this is how you make the content side of the business robust enough to where they can start building new sides to the business. To back the “next MrBeast,” investors must see content not as marketing, but as a core R&D function of the firm.

Content as a Product

Let’s say the inklings of an early-stage holding company is content-heavy in complexity. How do you underwrite this?

• Judge Creators the way you’d judge operators (Can they make something “viral” or can they retain a sense of narrative & community?)

• Evaluate the quality of an individual unit of content & the portfolio of multiple units

• Measure the scalability of the (content) product production & deployment process

The question isn’t “is this video good?” but “can this founder reliably generate growth the way a great trad startup reliably ships software products?”

Examples

Here’s a lot.

Why Now

1. AI lowers the cost of building products, but raises the premium on distribution.

   1. Creator-firms own distribution channels (consumer or non-consumer facing)

2. Consumers incredibly trust individuals over corporations.

3. More young people have aspirations in becoming Creators than tech founders. (→ High-growing founder-TAM.)

Thank you for taking the time out to read this. REPLY to this email to let me know what you think about this piece OR feel free to find me on X.

— Em.

I’m a venture capitalist. My job is to find new, undersaturated talent markets and to invest in those before they even know they are venture-scalable. Content and Creators are what I’m betting on. They are my two loves.

Over the last five years, I’ve been watching billions of dollars being thrown to what can only be described as the “creator economy” and it’s clear that most of those bills were set on fire. I don’t want to blame anyone for that - since “Creator” is something so misunderstood that we can’t even decide on its definition or who is/isn’t one.

Creator is a $200B industry. Creators are rich. Creators need this product.

All assumptions. I’ve invested 1) with, 2) for, and 3) in Creators, professionally. I guarantee that there are maybe four or five investors on the planet that can say that. My biggest takeaway is this: The Creator ecosystem is an underdeveloped ecosystem. It’s been entirely misunderstood and hasn’t matured.

I started this newsletter is to continue to find out why.

The Audience.

Creators and Capitalism don’t mix well, publicly, because audience members don’t like knowing that they’re seen as customers.

The good news is: with time, passive consumers are becoming active. That means that more consumers are creating (product: online or off) — becoming Creators — making them more forgiving of the act of selling and especially selling things one would make entirely online. An ad-read or a merch-drop is less disappointing when you do it too. With time, this self-actualization is encouraging viewers to become Creators of content and products.

This is what led me to writing Creator=Consumer in New-Age Consumer.

Capitalistic Acceptance & Persona as the Prize

An Acceptance (or not) Spectrum

One of the greatest indicators of a great Creator-Founder is either their:
1. audience forgiveness level or their 2. pain tolerance for a lot of criticism. This is because, even in the world of Startups, there are very few teams that can ship, recoup, iterate and re-ship product to fit customers demands that match the same velocity that Content & the Content Marketplace throws individual pieces or content or their Creators in.

Simply put, some people have the ability to build things publicly easier than others and take customer (or prospective customer) feedback at scale.

This can be anonymous. This can be from people who don’t even like the idea of buying this. The point is: the volume and intensity of feedback far exceed that of traditional startup launches. Audiences range from begrudgingly accepting a Creator’s capitalist pivot to fully embracing it. But what tips these scales?

There are three ways Creators can set themselves up for success in building and selling product (capitalistically):

1. Iterative Expectation

The Work-in-Progress. Document the business as something that’s trying, tweaking, adjusting, and evolving. Not something final. There is an implication from both the viewer and the consumer that the product is either 1) a work in progress that requires [expects] feedback 2) something quickly shipped for quickly-shipped (Startup) sake and 3) the Founder is not just doing this for fun. It might also be for money. Which means…

2. Say it Soon

Preparation matters. Creators who telegraph their ambitions early set the stage for their audience to know the Founder and his/her ambitions. In the wild, we don’t see this as something that angers an audience. It does give the Founder the space to build a business if they want to and to… not, if they change their mind in the future.

It’s not just readiness, by the way. It’s also enthusiasm. I’m-building-this-for-my-community -you) is a personal expectation built from the Founder to the audience member. There’s still room to argue about price sensitivity, of course, but regardless. I’m-documenting-my-journey-here-for-you-to-learn-or-get-inspired is still providing a value.

3. Persona as the Price

Be about the Capital. Creators who have reputation as serial entrepreneurs, engineers, scientists, inventors, etc. might have an easier time. Zoom in on Creators whose online identity is tied to winning at capitalism. Gary Vee’s his whole brand is hustle and profit, and his community eats it up. Or take someone like Alex Hormozi. Their fans don’t just accept the capitalism, they root for it because the persona is the capitalist triumph. The more money they make, the more the brand delivers.

Explore how some online communities form around the idea of financial success as a shared victory. X is a goldmine for these. Just hit $1M in revenue posts get floods of positive replies. Fans feel like shareholders in the journey, emotionally invested in the next milestone. An overly artistically driven brand doesn’t get to share the advances to this part of the Founder’s journey, which is overall a shame.

What makes one group cheer while another boos?

The Psychology of Rooting. Digging into why fans root for capitalist Creators is a thick layer:

• Is it vicarious success or living through someone who’s “made it”?

• Is it validation of their own grind?

• Or is it a middle finger to gatekeepers, like “Look, we don’t need Hollywood or corpos—we’ve got our guy”?

  It’s a lot of things: in a world of economic uncertainty, watching a Creator turn tweets into millions feels like a win for the little guy. And what could anyone with existing tens of thousands of monthly revenue and millions of followers possibly be the little guy? You could tie back my old boss’ shift away from industries to individuals, if you want.

  It’s important to bring up that there still might the dark side of the cheer. Don’t scam people. They’ll hate you for that and rightfully so. Oh, and also…

3. Double down on what happens

Regardless of how the business performs, what you make or what you don’t: You’re basically as on-the-line as much as whoever your CEO is. Own your work. Do not, by any means, chicken out on what you and your team make.

This is not about you anymore. If you’re plainly reading this, it’s just not. It’s either your team, your product, or your audience (community or not) and you need to focus on exactly that. Focus on the Product. Focus on what you do, which (even for the most successful Creator Founders) is to make product and if it hits, then it does. If it doesn’t, then you explore where to make it better.

Audiences might love rooting for winners, but they’ll ditch a loser, or a fake, just as fast.

Thank you for taking the time out to read this. REPLY to this email to let me know what you think about this piece OR feel free to find me on X.

— Em.

Where to Start

I’m a venture capitalist. My job is to find new, undersaturated talent markets and to invest in those before they even know they are venture-scalable. Content and Creators are what I’m betting on. They are my two loves.

Over the last five years, I’ve been watching billions of dollars being thrown to what can only be described as the “creator economy” and it’s clear that most of those bills were set on fire. I don’t want to blame anyone for that - since “Creator” is something so misunderstood that we can’t even decide on its definition or who is/isn’t one.

Creator is a $200B industry. Creators are rich. Creators need this product.

I’ve invested 1) with, 2) for, and 3) in Creators, professionally. I guarantee that there are maybe four or five investors on the planet that can say that. My biggest takeaway is this: Creators is an underdeveloped ecosystem. It’s been entirely misunderstood and hasn’t matured.

Here’s Why:

• Lack of coverage = overgeneralizations. “Creator has shifted in the last five years from a hobbyist to an entrepreneurial endeavor,” is not a fully true statement. Just like “If you read an ad, you’re not a true artist.” There are tons of misleading statements and misrepresented facts that have yet to be challenged due to a lack of coverage and discourse where those conversations typically happen (newsrooms, universities, publishing, etc.)

• An elitist Creative community. Over the years, the term “Creator” and “Creative” have been used synonymously. They are not the same… and to conflate them is out of touch with the incentives and the realities of both groups. To test this: ask any Creative-purist and they will be appalled for their work or themselves to be compared to the most famous and lucrative Creators. So, although there is overlap, and yes, all of these platforms have the ability to amplify great art, but the individuals [Creators] and outcomes [Content] are not the same. Without this distinction, we find ourselves (The Creator Ecosystem) continuing to build and invest aimlessly with a group still stuck on similar issues to the offline Creative Community: artistic complexity and integrity… community impact, etc. If those were the real issues: I doubt any Creative-purist would ever sell their art and definitely never put their pure work next to a Mukbang video.

  Art without financial legs puts true artists at the mercy of their financial fitness… typically burned out until their wits’ end and then slammed into bad contracts with predatory terms. I think it’s a narrative encouraged by those that make those contracts.

What can we all agree to argue on?

1. How can Creators benefit from capitalism without compromising their creativity?

2. Who truly profits from the creator economy?

3. Are Creators “laborers” or “owners”?

All of these answers surround one idea: Creators as Founders.

It’s the venture industry’s fault for turning Creators off to identifying as Founders. Now years into this job — I have true founder friends. It’s given me access to a core truth: very few software owners are Founders. Being a Founder is an expressive act.

This is an observation, not an experience truly learned since I have started things, but I have not Founded something so new, risky and so totally it becomes something. Founding, not running or owning or starting, seems to be a very holistic attempt, even if it starts with one feature, product or business. That is something especially venture investors have been ignoring, which is why we’re turning over rocks until they’re dull. This applies to the types of talent that’s seems to be interesting as much as ideas tried. Maybe even more.

In this movement, we’ll be using holistic early-stage holding companies as a way to give Founders exactly the capitalistic freedom they need to make big decisions (traditional or not). These kinds of expectations are self-selecting, since not many people want that level of pressure to grow into something so huge.

Here comes my Creator observation: Creators can see Content as their first product to something larger. Content also scales in a way that, as an investor, I could underwrite and access as an asset to their business.

Where is the capitalistic advantage?

Not too far off from the traditional startup scene, there are really two puppies that have maximum potential: the Talent (Founders/Creators) and whoever gave them their first financial break (VCs/Management).

If there’s anything that’s really changed in the last five years, it’s management. Management has become open to changing from a service business to an investment vehicle. And good for them.

The next biggest thing that’s changed in the last five years is venture capital. I’ll write an entire post focusing on how VC has changed from an investment vehicle to a service business. I’m, of course, alluding to the rise of incubators, venture studios, accelerators, etc.

Again, this is not a diss. I own an accelerator. But changes this big have 1) growing pains and 2) changes in the relationship with the talent they work with.

This is Part 1. In Part 2, we’re going to focus on where it hurts & who really has a hard time thinking about this: The Audience.

Thank you for taking the time out to read this. REPLY to this email to let me know what you think about this piece OR feel free to find me on X.

— Em.

It’s not that I’m not going to write about anything personal, but recently, I realized Creator Business is actually very personal to me.

For the past three years, I’ve been justifying the venture, startup, and technology excitement around content and content creators as a whole. If you’d like to see where I’ve started intellectually on it, you can find it here. If you’d like to see where I’ve started politically on it, you can find it here. But I don’t think that’s really the first and most urgent place to start.

Over the past two years, I’ve seen New-Business deals (incubations, investments, licensing, joint ventures, etc.) that can make or break Creators as founders and their entire businesses. These can make other people millions of dollars regardless of whether the Creator makes money or not.

In short, I’ve realized that there’s a bit of “catching up” to do on the New-Business side of Creator as a whole. From structure, building, hiring, fundraising, etc. everything is being made up in real-time, but there are also themes from the traditional startup side that’ll set Creators up for success. At the end of the day, as an investor, Creators are evaluated with the same “Founder Potential” benchmarks as traditional investing in traditional founders. The day-to-day work; however, is different.

This newsletter, like all of my socials, will be a team effort. I’ll probably permanently document this in a stand-alone blog in about a year. For now, this is a live-time process to better understand Creator Business.

If you are a Creator or someone interested in the Creator space, please absolutely email me absolutely any questions. I’ll even add some Q&A/Advice sections to some pieces, if there’s interest for that.

Let me know your thoughts and thank you for reading along.

Best,