The importance of a common vocabulary in venture capital

Many of the debates within venture capital are driven by nothing more than the lack of standard terminology.

Investors will argue over ideas with no hope of reconciliation, because they simply do not share a common definition for the concepts involved. Worse still, these shifting definitions undermine decades of research and understanding.

A common antagonist in these scenarios is “consensus”.

In one corner, you have the Thielian purists, who insist venture capital is a game of being “contrarian and right”, and consensus is intrinsically toxic to returns.

In the other corner, you have a more modern view of consensus in a larger market, which sees it as a necessary force to pull downstream capital into companies.

Both observations have merit, but only one talks about consensus in a practical manner.

If venture-backed companies must develop consensus to encourage downstream investment, then consensus just means “obviously a good company”. That’s fair, but not very useful.

On the other hand, the traditional view of consensus is a binary market condition. You are either in a consensus category, and experience the associated momentum of investment, or not.

The latter is clearly more meaningful. Consensus is not incremental and individual, it is a binary and relatively slow-changing market condition.

This is a minor distinction, but an important one.

Consensus, as a term for the momentum-driven behaviour of investors, is a major force in private markets. It has been studied across cycles, with decades of valuable analysis produced.

Consensus, as a term for individual companies becoming more obviously attractive, is a fairly meaningless concept and actually obscures what we already understood about consensus.

This confusion leads well-intentioned people to make statements like “consensus is good, actually”, which is a self-evident platitude under the modern definition, and mind-numbingly dumb under the traditional definition.

If venture capital is to evolve into a sophisticated asset class, it would be helpful if there was a shared understanding of the key concepts, and a familiarity with the underlying principles.

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Catching Outliers: Committee Voting and the Limits of Consensus when Financing Innovation

Andrey Malenko, Ramana Nanda, Matthew Rhodes-Kropf, Savitar Sundaresan

This paper studies how different levels of consensus in VC investment committee voting rules affect performance. It shows that a low-consensus “champions rule” (one partner can unilaterally approve) is optimal for early-stage investments with heavy-tailed returns because it better catches high-performing outliers, while higher-consensus rules (majority or unanimity) perform better in later stages. Supported by a survey of the 50 largest U.S. VC firms and theoretical modeling.

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And the Children Shall Lead: Gender Diversity and Performance in Venture Capital

Sophie Calder-Wang, Paul A. Gompers

This paper examines how excessive internal consensus and groupthink in homogeneous VC teams harm performance. Using an instrumental variable based on VC partners’ children’s gender, it finds that greater gender diversity reduces conformity, improves decision-making, and leads to significantly higher deal success rates and fund-level excess returns.

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How Do Venture Capitalists Make Decisions?

Paul Gompers, Will Gornall, Steven N. Kaplan, Ilya A. Strebulaev

This large-scale survey of U.S. venture capitalists documents the prevalence of high-consensus decision rules inside VC firms (roughly 50% require unanimous votes, 20% use consensus with veto power). It highlights that the performance implications of these varying levels of required internal consensus remain an important open question for future research.

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Herd Behavior in Venture Capital Market: Evidence from China

Rui Zhang et al.

This paper investigates market-level herding (a form of consensus where VCs follow each other into the same deals and sectors) in the Chinese venture capital market. It finds that such herding behavior has a statistically significant negative effect on VC firms’ exit performance.

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The Non-consensus Entrepreneur: Organizational Responses to Vital Events

Elizabeth G. Pontikes, William P. Barnett

This paper analyzes how “vital events” (spectacular VC financings or bankruptcies) shape collective beliefs and drive consensus or non-consensus market entry. Using data on 4,566 software startups (1990–2002), it finds that consensus entrants (herding into hot markets after positive events) are less viable, more likely to exit early, and less likely to receive funding or go public. Non-consensus entrants (entering stigmatized markets after negative events) face higher scrutiny but are significantly more likely to survive, secure funding, and achieve IPOs.

(top image: The Intervention of the Sabine Women, by Jacques-Louis David, 1799)

Venture capitalists have a bad habit of overanalyzing the status quo and plotting their strategy around “new normals”.

This is self-defeating behaviour, for a number of reasons:

1. VCs routinely invest on horizons of a decade or more, while the future is mercurial.
2. Markets are cyclical. If a particular dynamic is biting hard today, that may signal change.
3. Simple, coherent narratives are compelling, but that does not mean they are accurate.

Here’s a simple truth which may spare investors some time and anxiety:

Temporal market perspectives are worthless. They are either well-intentioned but misdirected or they are being used to sell a particular version of reality. At best they are a waste of time and at worst they are a distraction from sound strategy.

One group of investors is anxiously venting in the groupchat about round prices and competion from “tier-1” firms.

Another group is reading Charles Stross, talking to founders and contemplating the future.

Be the latter, their returns are better and they have more fun.

To illustrate with one example of a prevalent temporal narrative:

“The market has concentrated into platform firms with huge brand power, they now dominate the best deals. Fewer companies matter each year, so access is an edge. Small and emerging managers must adjust to this by finding ways to access these companies.”

Here’s an allegory from the beer industry to illustrate why it is silly to build a 10-15 year fund strategy around this reality:

In the 1980s, it was a widely held belief that competition in the US beer industry was over. The market was reduced to 43 breweries, each with household names and economies of scale. Smaller breweries either worked on contract with them, or went out of business. This example was used in Michael Porter’s “Competitive Strategy” to illustrate incumbent advantages.

It was precisely these conditions which enabled the craft beer boom of the 1990s:

“Brewers took to brewing only one style. I call this type ‘industrial beer’. Industrial beer became a blight on the beer world and almost eliminated all varieties of competition. Worse, the industrial brewing establishment took to brewing even paler, ever more tasteless beers, such as high alcohol ‘malt liquors,’ ‘dry beers’ and now ‘ice beers.’ Today’s craft brewing movement is a reaction against that mongrelization of beer.”

Fred Eckhardt, brewing writer, All About Beer

Why the Microbrewery Movement? Organizational Dynamics of Resource Partitioning in the U.S. Brewing Industry (Carroll & Swaminathan, 2000)

As the industrial brewers grew, they focused on generic styles of beer that were widely appreciated by the public. In doing so, they abandoned a core audience of enthusiasts who had to look elsewhere for quality. The subsequent growth of a quality-oriented craft beer industry found traction with the public, leading to a boom for smaller brewers.

This is “resource-partitioning theory“, which is generally used to describe the “barbelling” of mature markets, which divide into large generalists and small specialists, leaving a hollow middle.

Many are already talking about barbelling in venture capital, as if that change is afoot. It is not. Venture capital is not yet a mature market. There is no barbelling, just a decimation of small and mid-sized firms in favour of a growing industrial VC complex.

Barbelling is what comes next if the market is allowed to respond rationally.

If everything proceeds as it should, venture capital will reach a productive equilibrium. This would reflect the market organising itself around the desired outcomes of driving returns for investors and supporting innovation.

However, none of this is a given. The narrative outlined earlier is aimed specifically at holding back this shift in favour of further agglomeration; organising around fee income incentives.

It tells LPs that small managers are a struggling category. It tells GPs to give up on the traditional boutique venture strategy in favour of catering to the incumbents. It frames today’s market reality (limited exits, larger winners) as a permanent change that benefits the largest firms.

None of this is true. In fact, a typical and rational response to the rising cost of capital (i.e. interest rates rising since 2021) is that private companies would seek earlier exits. A greater volume of exits, happening earlier, would specifically benefit the smaller boutique venture strategy.

Essentially, the only threat to small and emerging managers is that they are talked out of doing their job well by opposing interests (and unwitting middlemen).

They must either learn to discern fact from fiction, and friend from foe, or simply ignore the distractions.

The same is true for LPs, who ought to be smart enough to recognise the market cycles and time horizons on which venture capital operates. The are equally vulnerable to simple narratives that can negatively shape allocation.

The venture market must resist being talked out of positive evolution toward a more productive end state.

But the vast majority of today’s AUM has been accumulated on the premise that the status quo will persist or deepen, so the naysayers are loud and persuasive.

In summary:

Greatness is idiosyncratic; it doesn’t care what anyone else thinks.

Allocate consistently and rationally with a strategy that delivers the best possible returns.

These are the only permanent truths of venture capital.

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(top image: “Pinel, médecin en chef de La Salpêtrière, délivrant des aliénés de leurs chaînes”, by Tony Robert-Fleury)

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Addendum: a brief story about wine which carries a similar message:

“Up until 1976, everyone was certain that only the French could produce truly great wine. They had too many advantages of culture, expertise and terroir. If you really understood wine, you drank French wine.

This status-quo shaped opinions around the world, and the wine industry had become comfortably centralised around French producers.

Then a blind tasting event was organised in Paris by a British wine merchant, Steven Spurrier, pitching French wine against American upstarts. A panel of French wine experts was assembled to judge. The concept seemed so hopeless that some journalists didn’t even bother to show up and cover the event. There could be only one possible outcome, French domination.

At this event, now known as the “Judgement of Paris”, American wines won both categories. The judges were so embarassed that some tried to change their scores. It fundamentally changed attitudes in the industry, improving the market for other regions.

The French wine industry took this loss because they were seduced by their own marketing and insulated from their competition. It had been impossible for them to conceive of anything but total victory.

The lesson here is not that the French don’t make great wine — they do. The lesson is that to understand what “great wine” looks like, you need to be open to options from anywhere, and you might be surprised.”

The lesson here is that at the point when the market appears to be organised around a particular status quo (not just producers but merchants, reviewers, infrastructure, etc), there is the the greatest opportunity for disruption.

The future will be funded by solo techno-capitalists

It’s night in Amsterdam, morning in Silicon Valley. Today, fifty thousand human babies are being born around the world. Meanwhile automated factories in Indonesia and Mexico have produced another quarter of a million motherboards with processors rated at more than ten petaflops—about an order of magnitude below the computational capacity of a human brain. Another fourteen months and the larger part of the cumulative conscious processing power of the human species will be arriving in silicon. And the first meat the new AIs get to know will be the uploaded lobsters.

Lobsters, by Charles Stross (2001)

In the opening pages of Charles Stross’s Accelerando, Manfred Macx walks through Amsterdam sporting a pair of augmented reality glasses that feed him constant information. Patent filings, academic preprints, economic signals and the tremors of markets not yet born.

He doesn’t work for a firm, or manage a fund. He gives ideas away, connecting technologists with capital, primarily for the benefit of positive reputation. The most valuable resource.

“Stross’s game of “What If” is both intense and absurdly optimistic concerning the unstoppable nature of innovation permeating and transforming society. But that’s part of Macx’s character, he pushes these things in places where they’d be most useful, hawking his ideas because he’s a philanthropist who’s abandoned the concept of intellectual property, so he’s purposefully undermining it. In this universe, information wants to be free so badly, a genius can learn to trade ideas as a type of goodwill currency, and it works incredibly well for him.”

Review: Accelerando

Stross wrote Accelerando in 2005, though the introduction (and the character of Macx) were first laid out in his 2001 short story, Lobsters, published in Asimov’s Science Fiction.

Twenty years later, examples of this “solo techno-capitalist” archetype have proven incredibly successful, reflected across a group of individuals that each own a track record dwarfing any comparable institution.  

Cyan Banister, who applies a childlike breadth of curiosity, covering everything from cybersecurity to psychedelics and frontier biology with her appetite for frontier knowledge.

Peter Thiel, whose investing is built on the philosophy that most VCs are incrementalist cowards, when the real returns are derived from contrarian visions of the future. 

Elad Gil, who compressed the advisory function of a growth-stage firm into an individual, using operator principles to move with greater conviction than any organisation. 

Oren Zeev, who manages over $2.5 billion with no office, employees or management fees, making investment decisions within twenty-four hours from a coffee shop in Palo Alto.

Charlie Songhurst, who blended a macro-analyst’s perspective on global power structures with an angel investor’s appetite for volume, assembling a global portfolio of hundreds of companies.

No army of associates or partnership teams. Instead, what these individuals rely on is the ability to consume more information, across more domains, at higher resolution, than any committee-driven process would allow. They are early examples of the Macx archetype; solo cognition engines whose performance is derived from irreducible idiosyncracy applied to the entire surface area of possibility.

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It’s 2029. A woman in Lisbon wakes up and, before her feet touch the floor, her ambient system has already processed 340 new company filings across seven jurisdictions, cross-referenced against her thesis clusters. Fourteen are flagged as a match. The system knows her blind spots better than she does, because it has been trained on every decision she has made (or not made), and their outcomes, over the past six years.

One is a quantum photonics company in Delft. The system has pulled the founders’ publication histories, patent filings, and a network graph showing their proximity to two researchers whose previous startups she backed in 2026. It has also flagged that the company’s pre-seed round is being led by a manager in Seoul whose portfolio otherwise appears entirely opposed to hers, which she finds interesting. She sends a message. By lunch, she has committed.

She manages an open-ended fund, with no employees. Her LPs include three sovereign wealth funds, a university endowment, and an algorithmic allocation platform that routes capital to managers based on a rolling evaluation of risk-adjusted returns, portfolio distinctiveness, and what the platform’s documentation calls “cognitive alpha,” a proprietary measure of how much a manager’s decision-making diverges from consensus while still generating top-decile outcomes. The platform does not care about her brand, her pedigree, or the size of her team, only the irreducibility of her judgement. 

One of the sovereign wealth funds has informed her it will route future allocation through the allocation platform to increase exposure to similar managers, and the others will follow soon after; she has advised them to do so. 

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This will come to be known as the Macx Threshold.

It is the point at which individual cognition, augmented by AI, becomes a more efficient vehicle for capital allocation than any structure designed to aggregate human judgement. It’s not that committees are stupid, but the function they evolved to perform (reducing variance and ensuring consistency) is precisely the function that destroys alpha.

Venture capital rewards outliers; outliers are best recognised by outlier minds, and outlier minds, by definition, do not survive consensus. The same is true for any pursuit of alpha.

This level of algorithmic allocation, once a thing of science fiction, is an increasingly tangible solution to a real need. Indeed, the reason institutional capital flows to large funds is not because large funds produce the best returns (the evidence overwhelmingly shows that they do not), but because the operational cost of identifying, underwriting, and monitoring dozens of small managers is prohibitive for a pension fund or sovereign wealth fund that must deploy billions. It’s a decision driven by habit, administrative convenience and venture capital’s lack of courage to challenge that status quo.

An algorithmic allocation platform that continuously evaluates thousands of small managers against standardised performance metrics, portfolio construction benchmarks, and differentiation scores, eliminates this bottleneck. Capital can flow to the best-performing idiosyncratic managers as naturally as it flows to the best-performing stocks in a quantitative equity portfolio. The platform handles the mechanical tasks like capital calls, distributions, compliance and reporting, so the manager can focus on their strengths as an investor.

The Macx archetype is the atomic unit of venture capital. A single mind augmented by tools that enhance range and throughput. Each manager curates their own view of reality through personalised systems that filter, synthesise, and present information accordingly. One might operate through spatial interfaces that display business relationships and technological convergences. Another might prefer dense textual streams, a descendant of Manfred Macx’s scrolling glasses, processing hundreds of abstracts and filings per hour with machine-assisted comprehension. A third might work almost entirely through conversation, maintaining an ongoing dialogue with an AI system (perhaps embodied as a robotic feline) that has internalised their philosophy and offers Socratic counterarguments.

Each of these individuals is doing something that a large, consensus-driven organisation cannot, by applying a singular, irreproducible perspective to the problem of finding what is new, what is real, and what matters.

For the entire history of venture capital, the connective tissue between institutions and managers has been formed of relationships and reputation at an organisational scale. This has structurally favoured incumbents and penalised the new, the small, and the strange. Today, the possibilities of AI have clear benefits to the latter, and pose a real threat to the former. 

The future of venture capital is not with the large organisation, which is often just a crude tool to execute lower quality knowledge work at scale.

All such industries are due for a shake-up, and even the investors who have backed this technology aren’t immune from the consequences.

(top image: “Newton”, by William Blake)

The megafund narrative of the last few years has been that these firms provide a solution to the big institutional LP allocation problem; you can park a huge pile of cash and get private market exposure with returns above the cost of capital with minimal stress.

It’s a reasonable premise, and in a world where foundation labs are incinerating billions of dollars there’s even an obvious customer for funds of this scale.

So, we talked about a bifurcation not only of strategy but also of LP base, tapping pools of capital that would otherwise go to some larger bracket of PE before meddling with tiny venture funds. There was some overlap with “traditional venture”, but it didn’t feel threatening.

Then a few things started to change.

First, the big platforms scaled their activity at seed and pre-seed, launching scout programs and accelerators.

Second, platform partners and firms pulled back from their own LP activity in small and emerging firms.

Third, their partners went on a podcast tour to promote the idea that big funds can perform just as well as small funds.

Finally, some have apparently began telling other LPs that small funds are a losing bet, discouraging investment.

Whatever was written from 2023 to 2025 about “bifurcation” appears to have been mistaken. Narratives about a “barbelling” of the market were false. Instead, it appears to be a straight drive toward extreme consolidation.

As a result, even excellent firms on the boutique scale are struggling. Track record is of little value in the face of a dominant narrative that the market has changed forever.

There are a number of innocent explanations. It could simply be bullish enthusiasm for growth and scale. It could be a mistaken projection of AI capital requirements onto all future technology investing. It may all be a hangover of the bad practices of ZIRP.

Another possible explanation is that the big platforms are taking advantage of a frosty market to kill off the competition from small firms, who offer an unfavourable comparison and a constant reminder to traditional LPs that venture capital simply does not scale.

Venture capital does not scale

As funds get larger, they will trend toward worse performance.

There’s a simple mathematical basis for this, in that it’s harder to deliver greater multiples on larger amounts of capital.

There’s a simple incentive basis, in that the career dynamics of a large firm favour finding good looking consensus bets which implicitly offer worse returns.

There’s a risk basis, in that success is rooted in identifying idiosyncratic qualities and that judgement doesn’t scale; you can’t just throw more people at it.

From every observable angle, and for obvious reasons, this is true, and yet the individuals managing large funds would have you believe otherwise; that there are “economies of scale” to be exploited in venture capital.

The fact that there are widespread debates about “kingmaking” in venture capital is the largest and reddest of flags in relation to this. It’s a topic that would be laughed out of the room, were it a room of competent and well-intentioned investors.

It should not, for example, be surprising that the size of early stage rounds is not predictive of success, for if venture capital could be so predictable there would be no need for a venture capital industry in the first place.

It’s an open secret that platform teams are there to manage a larger portfolio of investments for the GPs, rather than to significantly move the needle for founders. In the questionable scheme of venture capital “value-add”, it’s no great edge.

It’s pretty absurd that any of this requires explanation. The idiosyncracy and unpredictability of success in venture capital are self-evident; the industry was built on these two pillars.

Changing the victory condition

It’s clear that venture capital doesn’t scale, and why.

But what if the goal was not to optimise for cash returns, but for predictable markups and volatility laundering at scale?

What if “venture capital”, as a product for large institutional allocators, morphed into a mostly synthetic asset, designed to manipulate portfolio metrics in a manner that exploits their short-term incentives?

In this world, everything is upside down.

Instead of finding outliers and fighting toward an exit, investors just fire capital into the biggest gravity well they can find.

Consensus becomes a superpower for capital coordination, offering simple narratives to sell LPs, pulling more money into the market that will concentrate into the obvious opportunities.

In that world, everything “big venture” touches turns to gold. Charts only go up and to the right. There’s zero friction.

The ideal portfolio in this context is a load of archetypal Stanford/MIT/Harvard founders building AI/SaaS in San Francisco. These companies will be able to most easily raise more capital, regardless of fundamental performance or idiosyncratic quality. With enough money, they may even figure out a business along the way.

You just need to push exits out to 12+ years, and then you can raise 3-5 subsequent funds on your paper performance before anyone starts questioning fund 1 exits. And once you’re at fund 4+, nobody cares about fund 1 anymore anyway.

And every now and then you’ll land a big exit to talk about on podcasts for years after.

The four lies of synthetic venture

To enable this reality, you begin by telling a number of lies.

First, you tell people that there is an ideal founder archetype; the type of person for whom greatness is inevitable, and while there’s only a handful you know where to find them.

Second, you tell people that being based in San Francisco provides such an incredible edge that you’re just not serious if you choose anywhere else.

Third, you tell people that the clear opportunity of the day is (insert category), and that’s where all of the next great companies will come from and you have unique access.

Fourth, you tell people that venture capital has economies of scale and that the ideal firm is a top-to-bottom lifecycle partner to founders with huge reserves and platform support.

It’s a simple checklist of founder, location and company type which becomes the focal point for capital, regardless of any genuine idiosyncratic quality.

Finally, you build the most obviously large “venture” firm in San Francisco, index every deal that matches these criteria and herd vast swathes of capital behind you.

Markup velocity grows, your portfolio booms, the thesis is proven.

Congratulations, you’ve invented the megafund.

Adapting the hypergrowth playbook

Research on historical venture outcomes is clear that all of the behaviours described above are associated with worse returns.

Venture capitalists make predictably bad investment decisions by pattern-matching founders.

The best returns are found outside of San Francisco.

The largest outcomes are rarely in the obvious categories, as excessive attention on a particular category drives up prices but erodes returns through enhanced competition.

Fund size has a convex relationship with success.¹

It’s an outlier business, as everyone knows.

Implicitly, doing anything that feels “obvious” is going to generate less alpha, providing less opportunity for outperformance. Eliminating risk with herd behavior will always have a commensurate cost on returns.

The cognitive dissonance occurs because observers have always assumed that generating returns is the goal of venture capital, albeit perhaps lower returns at a larger scale.

However, if your goal is just to grow as large as you can, as fast as you can, to dominate the market and shut-out competitors, then you will gladly market these lies to exploit the deeply flawed relationship between LPs and GPs with a fake product.

In doing so, you will concentrate the market on fewer firms, and fewer companies. Exits will suffer, innovation will slow, and performance will droop, but you will get super fat and happy on your management fees as competence and competition wither out of the market.

Sound familiar?

(top image: “Joseph’s Bloody Coat Brought to Jacob”, by Diego Velazquez)

1. Small firms have greater volatility, the greatest chance of extreme outperformance, but $250M to $400M firms appear to be the most consistently performing bracket for early stage venture capital. [↩]

Debunking the supply constraint of “great founders”

“Increases in venture fund-raising which are driven by factors such as shifts in capital gains tax rates appear more likely to lead to more intense competition for transactions within an existing set of technologies than to greater diversity in the types of companies funded.”

Short-Term America Revisited? Boom and Bust in the Venture Capital Industry and the Impact on Innovation, by Josh Learner and Paul Gompers

There is a stuctural paradox in venture capital, in the ratio of available capital to funded companies.

Research shows that in hot markets, when capital availability is high, venture capitalists tend to cluster around “obvious” opportunities — limiting who can access that money.

On the other hand, in cooler markets, there’s a broader spectrum of interest as investors return to hunting “outliers” — but less capital available to fund those opportunities.

In periods where the most important companies are likely to get funding, there’s implicitly less capital available to them.

“In hot markets, characterized by high investment activities and abundant capital, the landscape shifts dramatically compared to cold markets. […] This optimism propels VCs to find new ventures as legitimate that resonate with the heated market sentiment and capitalize on the prevailing momentum. At the same time, “too much money will chase too few deals”, leading to intense competition among VCs for promising investments and sparking a fear of missing out.”

Venture Capitalists’ Decision-Making in Hot and Cold Markets: The Effect of Signals and Cheap Talk, by Simon Kleinert and Marie Hildebrand

There’s a number of explanations. Clearly, it’s much easier to raise money from LPs if you’re doing the “obvious” thing. It’s also a faster route to generating markups, with a prayer that you’ll score a historic exit before the music stops.

In the past, these cycles were characterised by the inverse relationship between deployment and returns, and the inverse relationship between consensus and discipline. Periods of scorching the earth, and periods of carefully planting seeds.

That cycle was broken in 2022 by the emergence of “AGI”.

There was no correction for the large platform firms who rode the narrative to entice capital from larger and less experienced LPs. At the same time, they retreated from LP activity in the small and emerging firms that were being decimated.

The market has become exceptionally top-heavy, exacerbating the founder:capital paradox as more capital is concentrated in consensus-focused investors. Relative to scale, the volume and diveristy of investment is at an all-time low.

This is measurable in the behavior of the large firms, who have narrowed the focus of their investment, despite representing a greater share of the volume in early rounds in recent years.

The result is a narrowing of the entire market.

Not only does this result in “beta to the center“, it is also structurally limits how many new companies can be discovered each year.

Where small firms once might have focused on finding outlier investments (especially in cooler markets), many now focus on serving “hot” companies to the giants downstream.

“Most seed VC firms are not really investors, but rather brokers of ‘hot’ companies to larger VCs. Most care little about whether a company is a good business, but care a lot about who could lead a follow-on round in 12 months”

Ed Suh, Founder & Partner at Alpine VC

Essentially, the negative aspect of hot markets (clustering around obvious opportunities) now persists across all markets, as large firms have “escaped the cycle” and many small firms do what they feel they must to survive.

The market is already reshaping itself around this new reality.

The surge in scout programs is one reflection, as surviving investors seek to fill an origination gap left by the decline in small and emerging funds. Example’s like Sequoia’s early scout programs show this can produce results.

However, scout programs must be carefully managed to avoid incentivising ambitious future VCs to chase heat because they believe it will accelerate their career (or just don’t know better).

“VC can 2x, 5x or 10x over the next 10 years and we will meet the demand, with the smartest people of our generation.”

Garry Tan, President & CEO of Y Combinator

Similarly, many accelerator programs are in the process of scaling to meet this demand. Indeed, when done well, accelerators provide a valuable service of giving signal to companies which investors may otherwise overlook.

However, many accelerators see VC engagement as the north star for their success, rather than just a consqeuence of finding great companies, producing similar heat-seeking incentives.

In truth, both of these solutions can help shore-up an unstable venture market, but neither is a complete replacement for the coverage and competence that could be provided by a large and diverse network of GPs.

Here’s the bottom line: we do not know the ceiling on the supply of great founders, nor the ceiling on capital, because we much more quickly hit a ceiling on the number good investors.

Any time you hear an investor saying that venture is constrained by the number of great founders, what they’re really saying is that they are constrained by their ability to find great founders.

Similarly, beware investors who say there are too many venture capital firms. There is an obvious lack of good venture capital firms, which is partly down to restricted market access. It is not a competitive and meritocratic environment.

(top image: Johann Georg Platzer (1704-1761), “The Death of Samson”)

Polish-American scientist and philosopher Alfred Korzybski is remembered for his statement, “the map is not the territory”.

The map-territory concept, which runs parallel to Baudrillard’s concept of hyperreality, reminds us not to confuse the abstract with the actual. The map is not the territory. The menu is not the meal. The words are not the meaning.

Consider how this relates to the “literalisation” of the art world, from the mid-twentieth century, as described by Will Manidis:

“The collector doesn’t look at the painting and judge it. The collector reads the critic, then looks at the painting through the critic’s eyes. The painting is not an object in its own right but a theory to be validated. The taste is not in the looking. The taste is in knowing which theory is fashionable to subscribe to.”

Will Manidis, Against Taste

In this context, there is the “territory” of exploring art and how it makes you feel, or there is the “map” of critics’ opinions. The former is more rewarding, while the latter offers a lazy mirage of sophistication and intellect.

Consider how this is reflected in your own life.

When you feel like reading a book, do you explore genres you enjoy, read a page or two of likely candidates, and buy the most promising? Or, do you reach for the books which you are told are most-often read by successful intellectuals of good taste?

Then, consider the influence of signals; the Keynesian beauty contest problem, where judges are asked to pick a winner based on the number of votes they predict each contestant will get. In trying to exercise the preferences of others, their own preferences are distorted and the reality of beauty is detached from the question.

We all like to believe we have “taste”, despite outsourcing many of our decisions to others. We routinely seek the comfort of authority, rather than striving to make better judgements, despite recognising it as a crude proxy — with parallels to Daniel Kahneman’s Hazards of Confidence.

This is rational, in some situations.

If you’ve planned a movie night and have no idea what to watch, by all means look for the movie with the most postive reviews. But keep in mind…

• A well-rated movie is more likely to be good, but it’s not necessarily more likely to be great for you.
• If everyone did the same, we’d have the same small set of movies being watched, forever.

Indeed, research shows that the long-term consequence of such an environment (overreliance on social influence) would be stagnation and a growing concentration of viewership in the top-rated incumbents.

The emergence of a perverse form of “power law”.

“Hit songs, books, and movies are many times more successful than average, suggesting that ‘‘the best’’ alternatives are qualitatively different from ‘‘the rest’’; yet experts routinely fail to predict which products will succeed. We investigated this paradox experimentally, by creating an artificial ‘‘music market’’ in which 14,341 participants downloaded previously unknown songs either with or without knowledge of previous participants’ choices. Increasing the strength of social influence increased both inequality and unpredictability of success. Success was also only partly determined by quality: The best songs rarely did poorly, and the worst rarely did well, but any other result was possible.”

Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market

Anchors and Followers

Ultimately, in every area of our lives, there are “anchors” who connect the map with reality (what is good), and there are “followers” who use the map as a more convenient interface (what do people think is good).

Anchors are those with the confidence to share their truly independent, personal judgement on quality. Right or wrong.

“I know what I like and what I don’t like, and I’m decisive about what I like and what I don’t like”

Rick Rubin

…and if there are too many followers, relative to anchors, you get consensus-driven stagnation; the role of anchors includes recognising the birth of new opportunities, and the death of old ones…

“The audience don’t know what they want. The audience only knows what has come before.”

Rick Rubin

Hyperreality

In a venture capital context, the map is a sprawling network of nodes, between which flow currents of capital and signal. These nodes may be venture capital firms, startups, angels, tech luminaries, or successful founders.

If you go back to the 70s, the map was a handful of disparate nodes with limited current. A huge amount of uncharted territory. Emerging, but inconsequential. Investment decisions were made without any regard for other investors, or even any notion that such regard would have merit. Essentially, everyone was an anchor.

As venture capital has scaled, the map has become the primary lens of our understanding. Who’s investing in what? Which companies raised how much? What do people think about a particular technology? What is in the headlines timeline? Virtually everyone is a follower.

Signal chases capital. Capital chases signal.

Returning to the the Keynesian beauty contest, the consistent winners will not be those who best recognise beauty. It will be those who understand what a drift to consensus will do to the concept of beauty, arrive there first, and advertise it to others.

Clearly, the same forces are at work in venture capital today. The largest firms have become the fastest to understand the map, and the most able to exploit an ability to shape consensus.

However, if everyone is focused on the map, while the actual territory is shifting, there’s a risk of dislocation — varieties of which we saw in 2000, 2007 and again in 2022.

A Brief Digression on Star Power

There are other parallels to draw between the movie industry and venture capital:

• Movie franchises and technology cycles
• Kevin Feige and Marc Andreessen
• Superstar actors and founders

A good example of the latter can be found in Michael Rosenbaum’s conversation with Jared Harris, where Harris talks about a meeting with Danny DeVito, early in his career.

DeVito praised him for disappearing into the roles he took, and wished him luck (“you’re gonna need it!”). Harris was puzzled, if he was doing a good job as an actor, why would he need luck?

DeVito explained, a good actor in hollywood is not a good actor; it’s a recognisable actor. Movie studios want stars.

Increasingly, venture capital behaves the same way. Despite a mountain of evidence that it leads to predictably bad outcomes, venture capitalists look for the “star founder” archetype.

A good founder is not a good founder; it’s a fundable founder.

This all points back to the Baudrillard’s theory of hyperreality; the point at which the map has effectively replaced the territory.

Inevitably, and recognisably, the outcome is stagnation.

Venture capital needs more anchors.

Return from Hyperreality

As elsewhere, the anchors of venture capital are individuals or organisations with trust in their process and confidence in their judgement. Examples include angels like Charlie Songhurst, firms like USV, and accelerators like Y Combinator. They have built confidence on a legacy of success.

Another crucial source of anchor behavior is from emerging managers — that is, genuine emerging managers rather than spin-outs. By the nature of their “outsider” status, and inability to compete in the consensus, they are anchored in reality.

Through their independence, imposed or otherwise, both of these groups exist in the territory of entrepreneurship, rather than the map of the venture market. Their judgment can be referenced against the map to see how far it might have drifted from reality.

Indeed, “anchors” can often be recognised by actions that contradict powerful market trends — not “follower” behavior.

For example, if you were paying attention to Mark Suster in 2021, you might have noticed him selling a meaningful percentage of his fund’s holdings. A sell signal, drowned out by the bull market, but an important anchor to reality for those paying attention.

Similarly, you might look at a firm like 1517 who have been meaningfully investing in industrial technology since 2015. A buy signal, drowned out by the frenzy for SaaS, but another important anchor to reality for those who cared.

Indeed, the extent to which the market noise (the map) drowns out these independent figures (anchors) is a primary driver of misallocation and grift today, and a reflection of the extent to which venture capital has scaled inappropriately.

Y Combinator

The world’s premiere accelerator, one of the more obvious examples above, is such a significant part of this equation that the effect has actually been studied.

“This study examined whether founder backgrounds predict funding outcomes within an elite cohort of Y Combinator startups, where all companies receive similar accelerator resources and network access. The analysis reveals that founder characteristics explain remarkably little of the variation in funding outcomes, with observable founder backgrounds accounting for less than 4% of funding differences.”

Founder Backgrounds and Startup Funding: Evidence from Y Combinator

Whatever has been “mapped” about the star quality of founders, Y Combinator rejects. It has its own process, built and refined over more than two decades. The decisions made in the screening and selection process are anchored in reality.

It’s hard to express how important this is. In a world where lazy credentialism is rampant, Y Combinator provides an alternative and more meaningful source of signal.

Consider that research shows founders will abandon ideas if fundraising is too difficult, in favour of lower quality, less innovative ideas that investors more readily understand.

Alternatively, consider research indicating that venture capital would benefit from providing better access to overlooked categories of founder, rather than simple pattern matching.

Through the strength of its signal, Y Combinator alleviates these problems — driving capital to the best opportunities; the most important ideas, and the most deserving founders.

As long as Y Combinator’s process remains scientific, objective and grounded in reality, it will continue to help drive progress.

It Takes Two

All of this is not to say that the “anchor” archetype is the only useful investor. Big pools of dumb money have their place in driving progress, but they are “followers” that need direction.

Both categories must scale together.

As the venture capital market grows, more anchor investors are needed to ensure that technology doesn’t stagnate.

Indeed, research shows that expanded inflows to venture capital have historically just increased funding to consensus opportunities, rather than opening the aperture of innovation.

“Increases in venture fund-raising which are driven by factors such as shifts in capital gains tax rates appear more likely to lead to more intense competition for transactions within an existing set of technologies than to greater diversity in the types of companies funded.”

Short-Term America Revisited? Boom and Bust in the Venture Capital Industry and the Impact on Innovation

This is why we need the boutique funds. We need more emerging managers. We need more great angel investors.

It’s why the growing concentration of capital in the hands of so few firms is concerning. It’s why the systematic enmeshment of firms and portfolio companies is worrying.

And it’s why we need programs like Y Combinator — in fact, we need more Y Combinators. I hope one silver lining of the recent political turmoil in California is that Y Combinator might decide to expand (back) to Boston. And, in doing so, proves the model can be replicated.

Y Combinator Austin? Y Combinator Miami? Yes please.

If venture capital is to scale, and to continue serve innovation properly, we need to ensure that it remains mapped to reality.

(top image: “The Geographer”, by Johannes Vermeer.)