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 wearing a wearable computer that feeds 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 capitalists, all for the benefit of positive reputation, because he has recognised that the most valuable resource is cognition and access to information.

“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, moving from cybersecurity to psychedelics to frontier biology on the strength of her appetite for knowledge.

Peter Thiel, whose investing is built on the philosophical conviction 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 an entire 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.)

Accelerated payoffs incur a debt against the future

“Serendipity is not always about a single incident at a particular point in time, but requires tenacity, resilience, and the ability to see the bigger picture.”

Dr Christian Busch

If you believe that AI is the next great leap in the story of humanity, you may also recognise that progress is constrained by the capacity of a surprisingly narrow set of technologies:

• Grain-oriented electrical steel (GOES) for transformers
• Extreme ultraviolet lithography (EUVL) for chips
• Single-crystal (SX) superalloys for turbine blades and vanes
• Super heavy-lift launch vehicle (SHLLV) stack

Chip production is limited by lithography. Power is limited by transformers and gas turbines. Moving compute into space, for abundant solar energy, is limited by launch capacity.

Within those four categories are about 13 companies who are responsible for all Western capability. Beneath those 13 companies are roughly 40 major suppliers of critical materials, services or components. It’s a remarkably small pool of esoteric knowledge.

These companies are miles out on the frontier. Their technical moats have endured for decades, only growing deeper as the world has been distracted by financialisation and the internet’s many dopamine vending machines.

Indeed, EUVL was pioneered in the 1980s, by ASML. SX super alloys were pioneered by Pratt & Whitney, and SHLLV by NASA’s Saturn V, in the 1960s. Armco Steel produced the first GOES in the 1930s. It’s all old technology, by today’s standards.

None of these technologies were invented with the notion that they’d play a role in scaling artificial intelligence — and yet here we are.

It’s the serendipity of innovation; magical works from the past, converging on the future.

The Myopia of Greed

“By comparison, ours is an age of stagnation — of slowing median wage growth, rising inequality, and decelerated scientific discovery”

Boom: Bubbles and the End of Stagnation, by Byrne Hobart and Tobias Huber (2024)

Contrast with the pervasive attitude of today, where technology has become an impatient race for domination. Get to scale as quickly as possible, whatever sacrifices are required; all digital, asset light, negative margins, simple narratives…

The notion of becoming “legible to capital“, which could be better framed as becoming “obvious to idiots”.

As soon as companies have revenue, they are weighed and measured with financial ratios. The fattest are hooked-up to power law inflows (investors no longer have the patience to wait for natural power law outcomes) to accelerate growth.

Rather than the endgame of an exit (which now takes far too long), the “winners” are declared early — determined by their ability to consume allocation like a prize bull in a feedlot, not by any intrinsic quality or productive value.

This impatient strategy produces overcapitalised mutants, designed impress on the superficial metrics of private markets, while investors blame everyone else for the weak trickle of liquidity emerging from the other end.

“If only we had an IPO window!”, shout investors who don’t understand the implicit admission: IPO windows are opened by great companies, and exploited by a fast-following of opportunistic garbage.

(If everyone relies on someone else to open the window, it will remain shut.)

“If only Lina Khan wasn’t blocking M&A!”, shout investors who don’t have a single portfolio company worth acquiring, carefully ignoring the number acquisitions by the Mag-7 and any real data about the M&A market.

(If venture-backed companies stop having technical moats and IP value, they will just be raided for talent.)

Look at VC fundraising decks from the last 3–4 years. Note how many blame poor liquidity on the factors above, versus how many take responsibility for being lost in a collective delusion that scorched private markets.

GPs don’t want to admit they were lost in the sauce, because it would create pressing questions about their judgement. LP allocators don’t a reckoning either, because their judgement is also at stake. Instead, they cling to relationships that will keep producing the same outcomes.

Like an addict, the venture industry pretends that bloated funds and rampant enmeshment aren’t an obvious sickness. Just keep the good times rolling, deal with the consequences later.

“Three issues are particularly concerning to us: 1) the very narrow band of technological innovations that fit the requirements of institutional venture capital investors; 2) the relatively small number of venture capital investors who hold, and shape the direction of, a substantial fraction of capital that is deployed into financing radical technological change; and 3) the relaxation in recent years of the intense emphasis on corporate governance by venture capital firms.”

Venture Capital’s Role in Financing Innovation: What We Know and How Much We Still Need to Learn (2020)

Indebted to the Future

In this rot of short-termism, the serendipity of invention has been pushed aside by the immediate payoffs of performative success.

We sacrifice what may be important tomorrow for what seems important today — an obvious category error for venture capital.

Behind the resulting facade of hypergrowth, there is a picture of increasingly poor health.

• Mag-7 companies became dominant because of the immense scalability of technology companies. They remain dominant because nothing better has come along in the last 20–50 years.
• Indeed, the bar to go public today isn’t higher, it’s that venture-backed candidates are lower quality. They grow more slowly, are less profitable, and fail more often than before.
• Ultimately, the same is true in private markets. Fewer companies are absorbing more of the capital because attractive opportunities are scarce and investors are increasingly insecure.

If venture capital has become systematically unable to produce companies that deliver on the promise of technolical innovation, from compounding growth to competitive moats, we will all end up paying the price.

• LPs will pay first, in a decade or so, when liquidity remains poor, also limiting reinvestment in the strategy.
• Public markets pay next, as they are denied the growth that future Mag-7-style companies would have provided.
• Finally, humanity pays the price, as financial markets and technology continue to stagnate.

In truth, it seems that there is very little the future will thank this industry for, and no telling what problems we create for ourselves with the cost of today’s complacency.¹

“Civilization is not inherited; it has to be learned and earned by each generation anew; if the transmission should be interrupted for one century, civilization would die, and we should be savages again.”

The Lessons of History, by Will Durant and Ariel Durant  (1968)

(top image: “The Alchemist Discovering Phosphorus”, by Joseph Wright)

1. That biotech remains the last bastion of real innovation probably reflects nothing more than our persistent fear of death; no amount of stimulation or distraction can defeat the lizard brain. If only it was so obvious how existential innovation elsewhere might be. [↩]

Checking in on the health of venture capital

Yesterday, a prominent former-VC posted a reponse to data from Beezer Clarkson, questioning how we understand the health of the venture capital industry.

His suggestion was that ‘number of active funds’ may not be the right lens, and that the fall may be a natural result of overfunding in 2021/22 and the “barbelling” of venture capital.¹

It’s a reasonable question. In reponse, I’d like to lay out three criteria by which we might be able to understand the actual health of venture capital.

1. Performance – how good VC is at returning capital
2. Progress – how good VC is at driving progress
3. Penetration – how good VC is at finding opportunity

From these three perspectives, we can triangulate the general health of the venture capital industry.

Performance

Broadly, performance appears to have slipped since the early years of the dotcom bubble.

This is nothing new, and no secret. Media coverage over the last 25 years has produced various iterations of “venture capital is broken”, followed by the industry assuring everyone that past performance is not indicative of future results.

“In the early sample (1981–2003), the levered-NDX replicator achieves an IRR of 23%, compared to 19% for the Cambridge Associates VC Index. In the later sample (2004–2024), the levered-NDX’s IRR of 19% exceeds the CA Index’s 12%, mirroring the vintage-level divergence.”

Venture Capital as Portfolios of Compound Options

While it’s difficult to get a good read on the performance of more recent vintages, it’s appears that something fundamental broke in 1997. The industry has yet to recover to the kind of benchmark-beating performance seen in years prior.

The most obvious suspect is the emergence of “scaled” venture capital funds, managing >$1B and firing it into every hot opportunity. On the surface, this behavior appeared to wash out of the market in the crash of 2000, however, there was a dramatic lack of consequences.

Indeed, the capital drought that followed was felt most keenly by peripheral hubs and managers. Those who had the least to do with the bubble ended up paying the steepest price.

Thus the “too big to fail” seed was planted in San Francisco venture capital, to emerge again a decade later.

A common rebuttal to this data is that venture capital is a power law industry, and so averages don’t matter. This is valid from the perspective of an individual firm, but clearly not in relation to the industry as a whole.

“From a public policy standpoint, however, market averages are more important than the individual returns of a few successful VCs, because most investors cannot reliably distinguish between high- and low-return funds.

After all, the notion that high risk requires higher returns is an old one, taught in every introductory finance course, yet the VC system, on average, is not providing this risk premium. Thus, the VC system bears a closer resemblance to another form of risk-taking: gambling.

Gambling also consistently offers low average returns but occasionally produces large payouts that are heavily skewed to a few big winners. And gamblers, like VC funds, tend to place their bets in the expectation that they will win one of these rare jackpots. But policymakers and the public should realize that average returns ought to be higher for risky investments than less risky ones.

If they are not, it is time to rethink the value of VC.”

The Crisis of Venture Capital: Fixing America’s Broken Start-Up System

The net cash flow data also illustrates the problem clearly; an investment strategy that extracts more capital than it creates is very hard to justify. And mirroring Jeffrey Funk’s statement above, continuing to invest in hope of the rare outsized fund return is gambling, not investing.

A major component of this weak performance is that inflated venture capital funds have compromised liquidity.

Previously, at a certain scale companies would have had to go public for further financing needs. Larger fund sizes delayed this, and IPO timelines have stretched from a historical norm of 8 years to the current average of 14.

And it’s not just a question of timelines. Long-term exposure to private market incentives distort businesses in a way that makes them less attractive to public markets (less profitable, higher failure rate, slower growth).

Essentially, venture capital wants to produce fragile ARR printers to harvest markups, and these businesses do not fare well in public markets which value financial health.

“Recent studies argue that the decline in IPO activity since the early 2000s is attributable to the rise of private capital markets. We add to this stream of literature by showing that the supply of venture capital also affects the type of firm going public. Specifically, we show that an increase in the flow of venture capital investment to a state leads to a decline in the average quality of IPOs from that state.”

The Rise of Venture Capital and IPO Quality

Thus, recent venture capital IPOs generally perform poorly and the liquidity endgame has been compromised.

Progress

“When I look back at the last decade, I think the following: There are some very wealthy people, but a lot of their incomes are from financial innovations that do not translate to gains for the average American citizen.”

The Great Stagnation: How America Ate All The Low-Hanging Fruit of Modern History, Got Sick, and Will (Eventually) Feel Better

Since the advent of the internet, it’s hard to pin down much tangible progress that is felt in our daily lives, beyond the cursed device — the mobile phone.

Indeed, while 2009 to 2022 was a period of historically low interest rates, driving down the cost of capital in private markets, the only real outcome was an inflation of fund size.

During this period, the venture capital industry funded the rollout of enterprise SaaS, and mobile apps, and then slowly ground to a halt on new ideas. By the latter half of the 2010s, capital was chasing electric scooter companies, rapid delivery, and questionable crypto applications.

In summary, in the period where capital was most abundant, it achieved the least. Technology was broadly stagnant.

This is largely down to the phenomenon which has been observed repeatedly throughout venture capital’s history: when capital inflows increase, they primary go to inflating “consensus” categories rather than broadening the scope of what gets funded.

“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

The desire to raise funds more quickly, and deploy them at pace to raise again, means the most obvious ideas become the most appealing. This is another impact of the growth of fund size, which has produced a material drag on innovation.

It is fitting, and amusing, that the current shift (LLMs) is the invention of a non-profit initiated by an industrialist, hesitantly funded by VCs (Vinod Khosla famously apologised to his LPs for the OpenAI investment), based on research from a public company (Google).

Penetration

Great opportunities in venture capital are, intrinsically, outliers. They come from anywhere. Any industry, any location and any background. Thus, it is clearly in venture capital’s interest to have broad coverage.

Here we arrive at yet another problem with the large fund model; where the incentives align behind backing “obvious” founders (e.g. male Stanford grads building an AI startup in San Francisco) as a part of the internal promotion game.

Indeed, data shows that while the largest firms represent a growing percentage of early stage activity, they are also increasingly concentrating on “obvious” opportunities — despite evidence for outperformance of investments outside of the main hubs and outside of consensus categories. This is a reflection of choosing network effects and market capture over efficiency.

At the same time, investments in minority founders and female founders have been falling since 2021 — despite the case for outperformance in those groups. This is a simple reflection of venture capital’s reversion to crude archetypes of “fundability” that resrict access to a more concentrated set of opportunities.

This, plus large firms’ reliance on scout programs for deal flow, helps to explain why multiple studies have shown that VCs over index on founder attributes in the “fundable” Adam Neumann archetype. It leads directly to firms making predictably bad investments, and missing predictably good ones.

Even for the remaining small funds in the market, they aren’t necessarily independent. A surprising number have large firms (or large firm GPs) in their LP base, which distorts their priorities towards finding “obvious” ideas suitable for the large fund model. That’s in addition to the large firms role in anointing managers with capital and signal, influencing which strategies are funded.

Indeed, an increasing number of emerging managers appear to be spin-outs from large firms, where relationships are often maintained to trade deal flow for capital.

“Meanwhile, first-time managers continue to grapple with severe headwinds amid a prolonged fundraising slowdown. […] Of the 11 first-time funds that closed at or above $50 million, many had founding team members who were spinouts from a pedigreed firm.”

PitchBook NVCA Venture Monitor Q2 2025

While some of this may simply be the myopic fevor for AI in the current environment, driven by catering to LP interests, it is clear that the general direction is towards concentration and consolidation at a cost to well-distributed opportunity.

Conclusion

Revisiting the three measures listed above, we can summarise the status quo:

Performance is down.

Progress is down.

Penetration is down.

Venture capital is increasingly concentrated in the companies that most easily print markups, at a cost to founder opportunity, technological progress and exit opportunity.

The only group that appears to have benefitted from the last 25 years are the large fund partners, with their expanded fee income.

While there are other explanations that contribute to the trends here (e.g. the general stagnation of scientific innovation), the emergence of “scaled” venture capital during the period of low rates is an obvious unifying factor.

Finally, there is no barbell in venture capital.

There is no independent category of small, boutique firms, offering an alternative to large generalists for LPs. The whole ecosystem is enmeshed and hierarchical.

There are big firms who dominate the market via signal, follow-on capital and LP activity, and there’s a set of small firms who exist in service of the big firms, or in spite of them.

Framing this as a barbell distribution is a misrepresentation of VC that launders the maturity and stability of other asset classes.

(top image: “Untitled (Falling Buffalos)”, by David Wojnarowicz)

1. the death of the undifferentiated middle, as seen in other maturing asset classes that split into specialist boutiques and large generalists. [↩]

Innovation is chaos. Finance is order.

All attempts to finance innovation are torn between these two forces.

allocate, scale, concentrate / experiment, adapt, diversify

You can be a $15B venture bank, deploying across a set of branded thematic funds led by pod-shop style managers.

Or, you can be a $5M solo GP, investing in “weird stuff, early“.

The health of technology and venture capital depends on the balance between the two ends of this spectrum.

---

Fragility

While many systems are entropic (tend towards chaos), financial systems are typically negentropic (tend towards order). There is increasing systematisation and regulation, aimed at developing reliability in the associated activity.

“Negentropy is reverse entropy. It means things becoming more in order. Here ‘order’ means organisation, structure and function: the opposite of randomness or chaos. One example of negentropy is a star system such as the Solar System. Another example is life.”

Wikipedia

In a venture capital context, this is reflected in the emergence of Tiger-style investement strategies, incumbent funds capturing a growing portion of LP capital, and the extreme attention on a few late-stage “hyperscalers”.

This often implies a loss of alpha, as fund strategies converge on consensus and returns converge on benchmarks. Not only do investors lose their edge, they also become fragile; susceptible to systemic shocks.

This direction favours larger firms that represent “institutional stewards” of capital, with more organisational structure and reputational capital to attract larger LPs.

Antifragility

In an entropic environment, resources aren’t allocated by design — they are spread broadly in a manner that increases the surface area of utilisation and opportunity. There is relatively little danger from overcapitalisation or overconcentration.

In a venture capital context, this is reflected in how fund of fund platforms, accelerators and emerging managers distribute capital across markets, industries and geographies.

“Entropic distribution of resources is critical for the health and resiliency of any ‘system’, including entrepreneurship and venture capital.”

Joe Milam, Founder of AngelSpan

Entropic distribution increases the likelihood that those who need capital will get it, at a cost to those who want a lot of capital — who may not. Capital flows out to a wider variety of people and ideas, without feeling the gravity of the “obvious”.

This direction favours smaller managers who represent greater risk, managed through greater diversification (smaller individual funds), and increased alpha via their more extreme divergence from benchmark returns.

---

Walking the Line

There is a case for negentropy in helping to assemble large pools of risk capital to scale important projects in later stages. Whether that should be marketed as venture capital is another question.

It becomes problematic when the negentropic tendency of financial interests creates large pools of capital seeking excuses for deployment. This is a primary driver of unproductive bubbles.

Indeed, finding new opportunities to invest capital is the strength of entropic distribution, through managers that are less incumbered by structure and can more readily embrace the chaos of the unknown.

Today, it seems clear that the industry has heavily biased toward negentropy, first as a reaction to surging capital inflows, and latterly as a reaction to collapsing liquidity (created by that negentropy).

This must be corrected, not only because it’s an unjust outcome for small managers, but because their entropic distribution underpins the entire downstream capital environment.

(Credit to Jordan Nel’s fantastic article about antifragile venture capital, Joe Milam’s message about entropic distribution, and the excellent conversation between Peter Walker and Arian Ghashghai.)

(top image: Lena River Delta – NASA)

Venture capital is a pyramid, not a barbell

With the need to coordinate capital across successive rounds of funding, venture capital is functionally pyramid-shaped.

In theory, you start with small Seed funds, progressively larger funds through the Series rounds, and the largest pools of institutional capital for companies on the brink of exit.

This is mostly explained via crude “fund returner” math, where each investment is expected to be able to return at least 1x of the fund based on the round’s entry price.

This arrangement defies the pattern of most maturing asset classes, where there is an emergent “barbell distribution” of small specialists and large generalists, for three main reasons:

1. The (theoretical) need for a spectrum of different fund sizes to meet the range of capital requirements across the various stages of growth and funding.
2. The lack of independence, as boutique firms do not offer meaningfully different exposure, as they rely on follow-on capital from large firms for their portfolio companies.
3. The LP relationship, as boutique firms are often selected and capitalised by large firms for the purpose of generating market intelligence and deal flow.

In contrast, consider the division of PE:

Small and large are competing strategies. Boutique firms focus on small to mid-cap opportunities for growth potential while large firms focus on driving efficiency in large-caps. Boutiques may exit an investment to a large firm, but they do not share exposure.¹

So, what is referred to as the “barbelling” of venture capital is actually just an increasing top-heaviness, as repeated cycles of consolidation hit everyone except the whales and a handful of annointed/legacy boutique firms.

It’s not the shifting of the distribution outwards, towards each end of a spectrum. It’s the shift of capital upwards, moving it out of the “base” of boutique managers into the hands of large firms. Like a dangerous game of Jenga.

The resulting problem is that small firms are being consumed by the large fund strategy through their reliance on them as providers of both follow-on and LP capital.

Indeed, if you invest in a company today, who do you hope does the Series B? Increasingly, it’s a large firm.

A Seed firm must now prioritise companies with the potential to be fund returners for >$1B funds (especially when combined with LP enmeshment), which is a significant adjustment in strategy — and a major limitation.

This implies a smaller pool of relevant opportunities.

More capital being raised on shorter horizons.

More dilution.

More risk.

Stolen Growth

The growth in VC funds, chasing the incentives of larger LPs and the associated fee income, has necessitated larger exits.

How can an investment strategy manifest larger exits? Simple, hold them longer and feed them with more capital, which solves the allocation problem as well.

Effectively, this is growth transferred from public markets.

Most venture investors (particularly those without many exits to their name) would have you believe this is good; that public markets are burdensome and bad for innovation.

Not only are they wrong, they are obscuring the extreme cost of private capital, and the misaligned incentives in private markets (myopic focus on revenue growth).

In the past, venture-backed companies could exit at a range of sizes and still yield excellent, profitable outcomes. Today, the dumb assumption is that exits need to be huge, which conveniently fits the interest of large firms.

For everyone else, going public is beneficial. It’s good for unprofitable companies, and it’s good for innovative companies. It’s just not good for venture capital, because the large firms need somewhere to put their money.

“We find that less profitable companies with higher investment needs are more likely to IPO. After going public, these firms increase their investments in both tangible and intangible assets relative to comparable firms that remain private. Importantly, they finance this increased investment not just through equity but also by raising more debt capital and expanding the number of banks they borrow from, suggesting the IPO facilitates their overall ability to raise funds.”

Access to Capital and the IPO Decision: An Analysis of US Private Firms

To be clear about the consequences of this:

There are companies that could have achieved modest exits (great for small firms), which would have then compounded in public markets for decades. Many have been denied that opportunity because they seemed unsuitable for the large firm model of venture capital.

The implicit justification is that private markets are a better environment for growth, and so if a company isn’t suitable for private market investors it couldn’t become a good public markets opportunity either. This is incorrect on all counts.

Many companies will be able to hit IPO-ready metrics with less private capital than is force-fed to them today, and will fare better in public markets.

Indeed, there’s a point at which extended time in private markets will erode the appeal of a company for public market investors.

Thus, the increasingly top-heaviness of venture capital is:

• Limiting the range of companies that might be offered venture capital to begin with.
• Holding them private for longer, to absorb more capital and generate markups.
• Producing worse quality exit outcomes for everyone on the other end of the trade.

This is bad for founders, it’s bad for innovation, and it’s bad for the market. The only beneficiaries are those extracting fees..

Two years ago I suggested that venture capital needed to embrace divergence; to split cleanly into small and large funds that are in competition for LP dollars rather than enmeshed with each other.

This change would allow venture capital to grow towards the “barbel” distribution of mature asset classes, and would allow for targeted regulation that eased the burden on small firms while increasing scrutiny on the problematic large firms.

The case for this grows clearer every day.

(top image: “The Sea of Ice”, by Caspar David Friedrich)

(title inspired by a conversation between Bryce Roberts of Indie and Michael Dempsey of Compound)

1. A relationship I’ve argued that VC should emulate. [↩]

Many years ago, I was listening to a VC speak on a panel about how they made investment decisions.

At some point in this talk, he made a point that seemed to contradict many of my assumptions about the industry:

“An important consideration is how fundable an idea is; whether other firms also agree it’s a good prospect.”

The other figures on stage nodded sagely. Yes, an important consideration. 

Poor naive me. I had assumed that VCs were daring contrarians, and it turns out they’re riddled with the need for peer-validation?

Certainly, this wasn’t the attitude of venture capital’s forefathers. When did that change? 

No Consequences

This shift toward structural consensus-seeking is a natural consequence of unabated scaling in a fundamentally unscalable strategy. Cycles of boom and bust have failed to correct this ambition, as they’ve never really reached the core.

Indeed, as the industry has evolved (and the goalposts have moved) the incumbents of venture capital have become free to fail without having to face the cost of failure.

After the dotcom bubble burst, capital pulled back to the “safe haven” of San Francisco and consolidated in the incumbents that inflated it to begin with. The same has happened in every cycle since, most recently in 2022.

These cycles have decimated peripheral regional hubs that were home to vital industrial tech, like Austin’s “Silicon Hills”. They have also been particularly hard on smaller venture capital firms that lack track record and entrenched LP relationships.

So, while the giants of San Francisco’s venture capital scene may briefly decline in an absolute sense, they have continued to accelerate growth on a relative basis.  

There can be no switch it off and on again to restore the health of venture capital, in this context. Instead, there is the cyclical culling of insurgent firms and new ideas.  

“Venture capital firms, old and new, will continue to play a critical role in the innovation ecosystem by funding promising business ideas. These early signs of disruptions suggest challenger VCs will be formidable competitors in the future.¹

The Future of Venture Capital (2021)

If you remove the consequences for failure, and reward raw accumulation with stability, you invite the formation of hierarchies and rent-seeking behavior. The potential for performance slowly falls in line with whatever best serves incumbent interests.  

Venture capital’s bifurcation has been portrayed as “the inevitable death of the center” seen in other maturing asset classes as they diverge into ‘boutique specialists’ and ‘large generalists’.

However, this is not an accurate description of what has happened in venture capital or how the market is structured.

“Venture capital as currently constituted does not follow ‘venture logic’ in any real sense, and comparing it to other asset classes without explaining the particular points of similarity between them is laundering the reputations and structural stability of those other assets.”

Del Johnson

In no other strategy are the “boutique” firms so hopelessly dependent on the activity of “large” firms.

• Large firms may “anoint” a company with capital and signal, herding-in other investors, or they might be vocal about passing. Either may make-or-break a small firm.
• Even if they do choose to invest in a company, they retain the ability to crush earlier “boutique” investors with dilution or reward them with continued syndication.  

Large firms also have a wildly underestimated role in the capitalisation of new entrants.

• Through their LP activity, they influence which managers are able to raise funds, and therefore which strategies and theses may be tested in the market.
• From the firms they invest in, they’re able to collect data on the underlying portfolio companies which may have strategic value for their own investments.

Indeed, I recently conducted a survey of smaller venture capital firms on the makeup of their LP base. For funds raised prior to the crash in 2022, a staggering 93% had a large firm as an LP. This fell to (a still surprisingly high) 68% for funds raised since.

These stats raise a number of questions. To a cynic, it might appear as though large firms enabled the dependence of new entrants and then rug-pulled them when the market collapsed.

Certainly, this relationship doesn’t reflect the nature of the “barbell distribution” in mature asset classes — and is perhaps more “pyramid” in shape.

Hyper-fragility

The concept of “fundability” arose in response to the inflation of funding rounds with software’s appetite for growth capital (particularly in periods with low interest-rates). Thus, the ability to build large, well capitalised syndicates around a company became a core part of the venture capital playbook. 

Thanks to venture capital’s inclination toward “concentration without consequences”, the firms who were most influential in the coordination of these syndicates have been the most likely to survive across cycles.

Their ability to manifest a “synthetic consensus” (creating a localised area of low-cost capital) is now responsible for the majority of allocation into and out of venture capital — despite all of the obvious wisdom that contradicts signal-based investing.

This leaves the rest of the venture capital market with an unpleasant choice:

1. Go with the flow of this commensal relationship for the sake of survival. Deliver for incumbents by executing their thesis, surfing in the wake of their momentum, even if it means weaker ultimate performance for your fund. 

2. Operate as an independent, knowing that raising funds will be harder, securing follow-on capital for portfolio companies will be a battle, the paper growth of your investments will be slower, and if the market tightens up you’re highly likely to be put out of business. 

Increasingly, and unsurprisingly after three brutal years for fundraising, more are picking the former. They’ll “play the game on the field”, serving incumbents by herding into consensus like lemmings to support the anointed winners.

Thus, smaller managers are abandoning the hunt for Alpha, and instead pursue this mediocre strategy of “Beta to the Center”.²

The outcome is growing concentration and the continued erosion of returns across the whole venture capital strategy, particularly for small managers.

The one edge that small managers once offered over larger incumbents, the promise of outperformance, is also slowly being chipped away. 

(top image: “Gargantua”, by Honoré Daumier)

1. Narrator: They were mostly wiped out. [↩]
2. An obvious reference to There Is No Economy but Only the Debt to the Center [↩]

As described in a previous article, risk is the product of venture capital. If you do not understand risk, you do not understand venture capital.

In theory, the greater the risk an investment is seen to have, the greater the payoff if it works out. This is the skill of the venture capitalist; recognising asymmetry of risk and payoff.

In this calculation, there are essentially three categories of risk:

1. Idiosyncratic Risk
   The core of what is traditionally seen as venture capital, associated with investing in unproven ideas.
   
2. Systematic Risk
   The market-related risk in venture capital. The influence of shifts in sentiment or cost of capital.
   
3. Execution Risk
   The risk associated with building and scaling a particular solution, and dealing with competitive forces.

Any startup may have minimal or maximal levels of all three, although there are some relationships to explore.

• As an example of idiosyncratic risk, consider SpaceX. There was no space industry. There was no market map, playbook, or competition. It was like nothing else.
  
• As an example of systematic risk, consider OpenAI. The company’s success is heavily reliant on excitement about AI keeping the cost of capital low for large model providers.
  
• As an example of execution risk, consider Uber. The business clearly worked at scale, but reaching scale (dealing with regulators, unions, etc) was the central challenge.

Each risk category is a spectrum and all startups will have some degree of each. You’d have to go to extremes (e.g. a laundromat) to find a business close to zero risk.

e.g. for all that SpaceX is a champion for idiosyncratic risk, clearly there was also execution pressure. Similarly, OpenAI was highly idiosyncratic at inception, although that has changed over time as the AI market expanded.

Risk Relationships

While each risk exists on a separate axis, there are some risk relationships worth understanding:

Idiosyncratic risk is generally opposed to systematic risk

If a company is doing something truly original, it is unlikely to be relying on category hype to fund their development. Thus, a highly idiosyncratic company usually has low systematic risk.

That said, painfully novel ideas with an unclear path to profitability are less likely to be funded in cold markets. Investors will retreat to the safety of more knowable investments.

To understand this, we have to separate hype (AI, dotcom) from hot markets (early 80s, ZIRP), although often the two overlap. Each introduces a different flavour of systematic risk, one related to technology and the other to market conditions.

Idiosyncratic risk is generally opposed to execution risk

Execution risk is typically a product of highly competitive environments. If building a great company wasn’t hard enough, there is now a clock ticking on market saturation.

Implicitly, this is less of an issue for highly idiosyncratic startups who may be pioneering a whole new category with much more limited competition.

That said, some companies are so painfully idiosyncratic that there is also significant execution pressure. To court investors, they must keep smashing through development milestones.

In summary, there is a U-shaped relationship between idiosyncratic risk, and the two other risks. As covered above, the highest theoretical payoff comes when all three are maxed out.

Scaling Risk

Time and time again, in hot markets, incumbent firms have attempted to “scale” venture capital. That is, to find elasticity in the relationship between fund-sizes and risk, allowing individual firms to dominate large chunks of the market.

Each time, they have failed, because the risks outlined above do not scale linearly with fund size.

• Idiosyncratic risk is inelastic. It is the art of making good judgements about the future, and you cannot improve outcomes by throwing more people at the problem.
  
• Systematic risk is exponential. As you inflate a category or market, you herd-in capital which accelerates growth and raises the stakes dramatically.
  
• Execution risk is an unknown. There is a belief that patterns might reveal founders who excel at execution, but research largely indicates these are misleading.

If risk cannot be made elastic, then neither can fund sizes.

The largest firms cannot bear this reality, because a world where venture capital doesn’t scale eliminates any incumbent advantage; all firms must continually prove their right to exist.

Instead, they throw their resources at financialising the industry, creating a hyperreality where these risks are treated differently:

• “Consensus is good, actually“
  You don’t need to worry about scaling idiosyncracy if it’s not highly valued. In a world where consensus rules, the largest allocators will naturally rise to the top.
  
• “Escaping the cycle“
  Systemic risk already scales well, and a large firm is in the perfect position to amplify that inflation and ride-out the consequences of the subsequent crash.
  
• “The fundable founder“
  If a founder can keep raising money and generating signal, there’s a chance they’ll persist even with subpar execution. Especially with support from a large platform team.

Ultimately, this produces a “smart beta” strategy, reliant on market momentum and performance that isn’t directly connected to the quality of outcomes.

e.g. research finds that large, well-networked firms are more likely to inflate valuations and pump capital into consensus opportunities.

This drags venture capital away from its core purpose: the entropic distribution of capital to opportunity. Instead, it rewards concentration and accumulation, in firms and companies.

As a consequence, innovation suffers and returns slip. As hot markets have driven fund sizes and management fees up, with fewer firms in more dominant positions, technological progress has increasingly stagnated.

A less competitive environment is fundamentally less meritocratic, and the focus on consensus themes and pattern-matched founders excludes swathes of opportunity and potential outliers.

The future of venture capital, and whether financialisation deepens, depends on narrative dominance. If the market continues to reward consensus seeking, concentration and dogmatic belief, the trend will persist.

It’s the kind of existential question which would lead large firms to fund social media bot farms, groom tech influencers, and play a growing role in the media side of venture.

(top image: “Untitled 2”, by Julie Mehretu)