Two exciting product announcements I thought you might find interesting:

From today, you can set up a multi-currency, institutional Delaware Limited Partnership structure on Odin, launch the same day and invest in any asset, anywhere in the world

• More information here.

• Customers in the UK and Europe now have a fast to launch (deals live in <2 hours), off the shelf limited partnership structure familiar to investors globally. It is fully tax transparent, works in multiple currencies (USD, EUR, GBP), with banking, accounting, K1, FATCA / CRS and tax reporting built in. For UK/EU customers it’s an AIF and fully compatible with AIFMD (with some caveats on compliance).

• Deal by deal investors, founders and emerging managers in the USA can also now benefit from a US structure their investors will be more familiar with (similar to structures offered by AngelList, Carta, etc), via a platform that understands the nuances of global deals & LPs. Plus they get an epic events space in New York (see below) to engage their investor community, AND (in my unbiased opinion) a much better looking team supporting them.

• Our customers everywhere can, of course, continue to use the UK Bare Trust structure they’re familiar with for deal by deal SPVs. It’s still generally the best setup for smaller syndicates unless they’re US-based. Depending on your location & circumstances, you may be able to use our Delaware structures too - we can discuss and advise based on your circumstances.

• Cost-wise, our Delaware SPVs will start from $6k per deal for simple US deals led by US sponsors. Proceeds depends on deal size and complexity.

• If you’re interested in setting up a Delaware LP structure, drop me an email or click the link below to speak to someone from Odin!

Speak to our sales team

Any fund manager or syndicate lead who is an Odin customer can now host investor events & dinners - free of charge- in the beautiful spaces we have in New York and London. Non-customers in our extended community can also get in touch.

If it’s a mission-aligned event or dinner, we’re open-minded.

Host an event with Odin

When we talk to emerging managers in our network, there are two things, above all else, that they care about:

1. Access to [the right] capital

2. Investing in great deals that deliver strong returns

An often-overlooked way to solve these two problems is to simply get the right people in a room together.

Venture is, at its core, a people business. There is extremely scant data to support your decisions, so instead you run somewhat on intuition. You invest in and with people you trust.

Being able to get to know someone in a relaxed setting, and getting a clear read on what you think of them - are they smart, do you have shared values, are they driven, etc. - is fundamental to making good investment decisions as an LP, and to building the trust that leads to transactions as a GP.

The serendipity of community & networks is also vital to innovation itself. SF has become the beating heart of technological innovation precisely because it has a very high density of talented, creative people who meet in-person. This creates increased surface area for great ideas & individuals to bounce off each other - and for investors to fund what they build. Sparks fly, fires blaze.

This is what our events announcement is all about. Some details:

1. My cofounder Mary is going to be spending April, May & June in New York, joined by Emily - our head of venture operations - from May.
   We’ve got a beautiful apartment in Manhattan, and we’ll be co-hosting dinners, poker nights and other events with investors and founders building cool stuff.
   Obviously, we are new to the US of A, so we are keen to speak to people plugged into the NY ecosystem. Don’t be shy.

2. I’ll be holding the fort in London.
   I believe the youth are calling it Londonmaxxing?
   We’ve recently moved into a fantastic new office a stone’s throw from Covent Garden & Tottenham Court Road. We’ve got a dedicated space for events. We’ll support in hosting investor meetups, hackathons, dinners and more.

So if you’re looking to get your community of investors or builders in a room with other interesting people, give us a shout or fill out this form.

Thank you for reading!

We will return to our regularly scheduled programming Sunday with another banger from Dan. Have a great week.

Cheers

Paddy

Also, we rebranded! Hopefully you like it, feedback welcome.

Speak to our sales team

Host an event with Odin

“Storytelling is literally fundamental to every business. There is not a business that exists that there isn’t storytelling at the foundation and the core of it. Whether it is the moment in time in which a founder has an idea and needs to explain that idea to other people, or they need to go raise capital, or they have a product and need to find their go-to-market. Storytelling is at the core of business building.”

Jeffrey Katzenberg, Founding Partner at WndrCo

In the spring of 2016, Diego Berdakin, the founder of CloudKitchens, sat down for a poker game with Jeffrey Katzenberg. The legendary Hollywood executive had just sold DreamWorks Animation to Comcast for $3.8 billion and was restless for a new venture. He wanted to start a holding company, inspired by what Barry Diller had done with IAC. Berdakin knew someone who had been thinking along similar lines; a former Dropbox executive named Sujay Jaswa, who had recently left the file-sharing company after helping scale it to a multi-billion-dollar enterprise.

“Diego calls me and says, listen, I just played poker with Jeffrey Katzenberg. He just sold DreamWorks to Comcast. He wants to start a holding company. And I did. I wanted to talk to Jeffrey Katzenberg”

Sujay Jaswa, Founding Partner at WndrCo

He and Katzenberg had lunch the following Saturday. By August, they had agreed to build something together, although neither fully understood why it should work. As Jaswa put it: “I’m like a Silicon Valley software guy. You’re a Hollywood guy.”

Almost a decade later, WndrCo manages approximately $2.8 billion in assets and has backed 201 companies across three integrated strategies. It has produced at least eleven unicorns, a hit rate of 5.4% which places it in a similar performance category to Y Combinator.

The WndrCo portfolio includes Cursor, the AI coding tool whose annual recurring revenue surpassed $2 billion in March 2026; Figma, which completed a blockbuster IPO in July 2025; Databricks, valued at $134 billion after a February 2026 raise; and Abridge, the medical AI company that doubled its valuation in four months.

Yet WndrCo remains, by its own partners’ admission, one of the best venture firms in the Valley that few people talk about.

Understanding why requires understanding how two people from entirely different worlds came to share a view of what makes companies succeed, and how that perspective has quietly produced extraordinary results during what might be the most consequential technology wave since the internet.

Quotes from Katzenberg, Jaswa and Wang are primarily sourced from excellent conversations they have recorded with esteemed technology yappers, Molly O’Shea and Logan Bartlett.

Narrative Devices

Katzenberg’s professional life has been defined by the pursuit of new technology for the purpose of telling better stories. At Paramount, working under Barry Diller, he rose to head of the studio by the age of thirty. At Disney, he saw a short film from a small company called Pixar, a piece called Luxo Jr. featuring an animated desk lamp, and became obsessed with what computer-generated imagery could do for animation. He tried to hire the film’s director, John Lasseter. When that failed, he tried to buy Pixar from Steve Jobs for $50 million. Jobs refused. Katzenberg settled for a three-picture deal. The first film was Toy Story.

“So there’s a connection here in this, through every chapter of my storytelling career, you can actually go and see that one of the foundational elements of certainly what I think was my success is how aggressive I was in finding state-of-the-art tech for my storytellers.

Wherever I was, whatever studio is at whatever era I was in, I always look to what are the best tools to be able to realize the most exciting and interesting stories. [...] So I was constantly having these pilgrimages to Northern California, to the tech world where I partnered with Hewlett Packard and Andy Grove and Intel and Steve Jobs on Pixar.”

Jeffrey Katzenberg, Founding Partner at WndrCo

When he sold DreamWorks at the age of sixty-five, Katzenberg found himself at a crossroads. He remembers asking himself what he would do if he were twenty-three again.

“I’d go to Silicon Valley. That’s where fortune and fame is today.”

But, unlike some of Silicon Valley’s most notorious figures, Katzenberg was keenly aware of the limits of his competence. “I know what I know,” he has said repeatedly. “I actually know what I don’t know.”

So, for the journey he was about to embark on, he’d have to find the right partner.

The Outsiders

Jaswa, meanwhile, was having his own crisis of ambition. After leaving Dropbox, where he had overseen the company’s growth from a cold start to $600 million in annual recurring revenue in roughly five years, he assumed he would return to venture capital. He had come to Dropbox from NEA, one of the oldest and most respected venture firms in the country. But something had changed. “I just realised my heart wasn’t into it,” he said. “I like the building.”

A friend introduced him to a book called The Outsiders, by William Thorndike, which profiled eight unconventional CEOs who dramatically outperformed their peers through shrewd capital allocation. Jaswa read about John Malone, about the long-term compounding strategies of patient holding companies, and saw a path that combined his love of building with the kind of durable value creation that pure venture capital sometimes struggled to deliver.

“The Outsiders, by William Thorndike, Jr., is an outstanding book about CEOs who excelled at capital allocation. It has an insightful chapter on our director, Tom Murphy, overall the best business manager I’ve ever met.”

Berkshire Hathaway’s Annual Letter 2012, by Warren Buffet

“If you look at the history of tech, many of the great businesses didn’t start the way we all storytell them,” Jaswa observed. “IBM started as a private equity roll-up.”

When Jaswa and Katzenberg found each other through Berdakin’s introduction, they both saw an obviously complementary relationship. Katzenberg brought a lifetime of storytelling instinct, a network spanning Hollywood, Washington, and the Fortune 500, and a work ethic that borders on the superhuman (he sleeps five hours and fifteen minutes a night, a genetic trait he has had since adolescence). Jaswa brought deep product sensibility, operational experience at scale, and a first-principles approach to talent assessment inherited from his mentors at NEA, Dick Kramlich and Scott Sandell.

“Without Jeffrey, we’re just a bunch of people with reasonable resumes,” Jaswa told Logan Bartlett. “There’s like 500,000 people like us. There’s one person like him.”

Katzenberg was equally generous in his assessment of Jaswa. “If you take the ten ideas that have created all of the value of WndrCo in our nine years,” he said, gesturing toward his partner, “they’re all his.”

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Humble Beginnings

WndrCo launched as a holding company, rather than a venture fund. The initial strategy was to acquire controlling stakes in underappreciated technology companies and operate them directly, applying the kind of hands-on product improvement and go-to-market refinement that both founders knew how to deliver.

Between 2016 and 2018, the firm incubated its first “Build” companies, rolling up sleeves on product roadmaps and operations in a manner more reminiscent of private equity than of Sand Hill Road.

The shift toward a venture capital operating model happened gradually. The firm’s first major outside investment was 1Password, the cybersecurity company, which WndrCo initially considered as a potential acquisition target before deciding to invest instead. That experience opened a door. The partners realised that many of the skills they used on the Build side, the product intuition, the storytelling coaching, the willingness to make hundreds of sales calls alongside founders, were equally valuable when deployed as support for independent companies they backed with minority stakes.

In 2024, WndrCo made it official, closing over $460 million across its first dedicated venture and seed funds. Today the firm operates across three distinct strategies.

• The Build arm acquires and operates companies outright, with eight companies launched since 2018 that collectively generate substantial revenue and free cash flow, providing downside protection and dry powder for new investments.

• The Venture arm leads or co-leads post-product-market-fit rounds, typically writing cheques in the range of $5 million to $15 million.

• A $50 million Seed fund makes smaller, non-lead bets of around $500,000 each, placing roughly fifteen bets per year on the next generation of entrepreneurs.

The firm’s flagship Build company, Aura, a cybersecurity platform, is a good example of the model. Partnered with WndrCo since 2018, Aura announced in February 2026 that it would acquire Qoria, a youth online safety company, in a deal that would create a combined business valued at approximately $2.1 billion in pre-money equity, with combined annual recurring revenue exceeding $300 million. WndrCo remains Aura’s largest shareholder.

The holding company model gives WndrCo an unusual advantage in a world where most venture firms are dependent on management fees and carried interest. The cash generated by the Build portfolio offers the firm a degree of financial independence that most of its peers lack, and allows the partners to be patient with their venture investments in ways that the typical fund lifecycle does not permit.

“The holding company next year will probably be $400 million of free cash flow, extremely profitable and growing really, really nicely, which is kind of an amazing thing.”

Jeffrey Katzenberg, Founding Partner at WndrCo

Mastering the Story

What distinguishes WndrCo from other firms with operator backgrounds, and there are many, is the specificity of the value it offers founders. Every venture firm in Silicon Valley claims to be more than capital, but few can articulate exactly what that means.

Katzenberg’s contribution is perhaps the most unusual. He functions, in effect, as a storytelling consultant and an enterprise sales weapon for the companies he backs. He will sit down with a founder, go through their sales deck, and help them frame their narrative with the precision of someone who has spent forty-five years constructing stories for mass audiences.

Katzenberg will make a hundred sales calls alongside a founder if he believes in the product. He described himself, with evident relish, as having “a bottomless need to sell.” When WndrCo backed Harvey, the legal AI company now valued at approximately $11 billion, its founder Winston Weinberg told Katzenberg in their first meeting that he needed help with his storytelling. “I know my product crushes,” he said. “How do I get that out there into the world?” The same was true of Shiv Rao at Abridge, where the story needed to reach both the health systems buying the software and the doctors using it daily.

Katzenberg’s favourite maxim, borrowed from Walt Disney, is “My movies are only as good as their villains.” He can rattle off the list without pausing. “Ursula. Gaston. Scar. Farquaad. Tai Lung.” The lesson applies equally to business, where without a clearly articulated problem, without a compelling antagonist, the protagonist has nothing to overcome. It is a framework he applies rigorously to the way portfolio companies tell their stories to customers, investors, and recruits.

On the product side, the firm’s depth comes from ChenLi Wang, who has been with WndrCo since its inception and functions as something like a chief product officer across the portfolio. Wang, a Stanford computer science graduate who worked at Goldman Sachs, NEA, and Workday before joining Dropbox, where he ran the core product and engineering organisation, is described by Jaswa in terms that border on awe. When Wang applied for a job at Peter Thiel’s hedge fund Clarium Capital, Jaswa recounted, he scored the highest of anyone who had ever taken their aptitude test.

Together, this combination of storytelling and product craft gives WndrCo a distinctive pitch to founders. Their money, as Wang likes to say, is the same colour as everyone else’s. The question they try to answer is what else they can do.

“Listen, we all look for the cheat code. Our green is no different from anybody else’s. It’s not better, it’s not worse. It’s capital. But when you want to win deals, when you want to be with the best talent out there, they ask: what else can you do for me?

ChenLi Wang, General Partner at WndrCo

Fund Performance

The AI wave of 2025 and 2026 has been a vindication of WndrCo’s thesis, though the partners would be the first to caution against triumphalism.

“New technology just takes time to get moulded and shaped into products and into experiences that actually make an impact in people’s lives. This is really the year where we saw, oh yeah, this is different. AI is going to transform how we do business. And it’s not just people playing around with, hey, look how this is like a show-your-friend-over-their-shoulders type of moment.”

ChenLi Wang, General Partner at WndrCo

The numbers from WndrCo’s portfolio bear this out.

Cursor, the AI-powered coding tool, has been the firm’s most dramatic recent success. In November 2025, the company raised $2.3 billion at a $29.3 billion valuation. By March 2026, its annual recurring revenue had surpassed $2 billion, having doubled in three months, and the company was in early discussions for a new round at a reported $50 billion valuation. Wang described visiting startup offices and counting how many screens showed Cursor’s distinctive tab on the right side of the display. “In a year, if I just did a walk around in an office in twelve months, it just went from zero to 100 practically.”

Abridge, the medical documentation AI, has followed a similarly steep trajectory. After raising $250 million at a $2.75 billion valuation in February 2025, the company raised a further $300 million just four months later at $5.3 billion, led by Andreessen Horowitz and Khosla Ventures. The tool is now deployed in more than 150 health systems, transforming how physicians document patient interactions.

Figma’s IPO on 31 July 2025 was another landmark. The collaborative design platform raised $1.2 billion at $33 per share, giving it an initial valuation of approximately $19.3 billion. Shares surged more than 250% on their debut, briefly giving the company a market capitalisation exceeding $67 billion. Databricks, in which WndrCo invested in 2021, raised approximately $5 billion in equity plus $2 billion in debt in February 2026 at a $134 billion valuation, with a revenue run rate exceeding $5.4 billion. Deel, the global HR and payroll platform, reached a $1 billion-plus revenue run rate and is preparing for an IPO as early as 2026.

Yet Katzenberg is measured about what lies ahead. Asked whether the AI bubble will burst in 2026, he chose his words carefully.

“I don’t know whether it’s AI. Rather than look at it from the extreme notion of what it means for a bubble to burst, I think there’ll be a reckoning in which those that actually are producing real results and are being deployed in really effective and efficient ways, where you can actually see an outcome quickly and it’s real, will win. Not everybody is going to win at this.”

Jeffrey Katzenberg, Founding Partner at WndrCo

He pointed to the staggering sums being invested by the hyperscalers: $700 billion in capital investment over twenty-four months, by his estimate. “On the other side of that, it needs to produce a result,” he said. “It needs an ROI.”

Wang’s view is more positive, but complementary. He believes that even if model development were to stop at current levels, there would remain years of work to be done in productising AI for delightful user experiences.

“Even if you just froze model development at this moment in time, there’s still so much more that we need to figure out and do and productise to actually make delightful products and experiences for consumers, for businesses.”

ChenLi Wang, General Partner at WndrCo

This conviction that the application layer matters as much as or more than the model layer has guided WndrCo’s investment decisions, steering it toward companies like Granola (the AI note-taking tool that recently raised $125 million at a $1.5 billion valuation) and away from infrastructure bets that depend on winner-take-all outcomes at the foundation model level.

The Last Mile

There is an interesting tension in how WndrCo evaluates companies, one that speaks to a broader debate in the AI industry about what constitutes real quality.

Wang tells a story about Granola that reveals something about his sensibility. He was using the product in a meeting where a founder was rattling off the names of competitors in an esoteric domain. Later, when he reviewed the AI-generated notes, every company name had been spelled correctly, even the obscure ones. The product had clearly gone and performed web searches to verify the spellings, polishing the notes with a level of care that most competing products missed.

“Years ago, I read that Steve Jobs obsessed about the back of the circuit boards that went into the computers. He wanted them to look pretty, even though nobody really opens the computers to look at that. And that was sort of his craft and dedication and almost a message he sent to the team.”

ChenLi Wang, General Partner at WndrCo

That attention to craft, the thing that is almost impossible to measure but instantly recognisable when you encounter it, is central to how WndrCo thinks about what makes a great product. Wang has an explicit scepticism of benchmarks as the primary way to evaluate AI companies, a position that places him somewhat at odds with the dominant discourse in the industry.

“The irony is, as many people now talk about AI replacing humans, we have never assessed our best humans based on benchmarks. How many years have parents complained about standardised testing dumbing down their kids? And yet we’re going down the same route with AI. People do very well in benchmarks and they fail in the real world.”

ChenLi Wang, General Partner at WndrCo

His alternative framework centres on what he calls “the last mile”: the ingenuity, context, and workflow design required to turn a capable model into a product that transforms how a specific category of worker does their job. He believes that perhaps 60 to 70% of AI use cases do not actually require frontier models at all, and that the real competitive advantage lies in product craft, not raw model capability.

Katzenberg is emphatic that partners should try the product themselves before taking a meeting. “The first thing you should be doing is just try the product,” he said, with evident exasperation at the number of investors who do not. “And by the way, I can tell you when you’ve actually tried the product.”

Choosing Good Partners

“Partnership to me is honestly, I look at it foundationally as maybe the single most important thing I’ve had in every chapter of my career,” Katzenberg said, listing the mentors who shaped him: Barry Diller, Michael Eisner, David Geffen, Steven Spielberg. When asked which had the greatest impact, he was unequivocal: “Barry Diller. He just invested in me and in my career. I think he believed and saw things in me I didn’t actually see in myself yet.”

WndrCo’s partnership itself, now a decade old, shows no signs of entropy. “It’s more fun than ever,” the partners have said, and the evidence suggests this is not mere performance. They recruited a team of partners whose complementary skills, ChenLi Wang on product, Anthony Saleh on seed-stage pattern recognition, Jeffrey Nykun on analytical rigour, Justin Wexler on enterprise AI deployment, form something closer to a company management team than a typical venture partnership.

“The common thread across everything is that we’re really looking for founders that we think have a chance of cracking an important problem,” Jaswa told TechCrunch when the firm’s venture funds were announced.

In a world awash with capital and increasingly sophisticated AI tools, WndrCo’s bet is that the scarcest resources remain human. The founder with genuine craft, the investor willing to make a hundred sales calls, or the partner who notices when an AI product spells an obscure company name correctly. It reflects their conviction in taste, in partnership, in the belief that storytelling and product obsession are the hardest skills of all.

And their track record indicates that’s leading them to look in all the right places.

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“Venture investments tend to be focused on a few areas of technology that are perceived to have great potential. 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.

Policymakers may wish to respond to these industry conditions by (1) focusing on technologies which are not currently popular among venture investors and (2) providing follow-on capital to firms already funded by venture capitalists during periods when venture inflows are falling.”

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

In January 2026, Andreessen Horowitz announced that it had raised over $15 billion across five new funds, its largest haul to date, bringing total assets under management above $90 billion. A few months earlier, General Catalyst closed approximately $8 billion for its twelfth fund. These are staggering sums that represent an extraordinary concentration of capital, at a time when broader venture fundraising has been notably weak. In 2025, US firms secured just $66.1 billion for new funds, down from $101.3 billion in 2024 and well below the 2022 peak of nearly $223 billion.

And yet, for all this firepower, many industries where capital is most needed remain chronically underfunded. Building a small modular nuclear reactor costs billions and takes more than a decade. Bringing a new cancer drug through clinical trials demands an average of $1 to $2 billion over ten to fifteen years, with a roughly 90% probability of failure. The fusion energy companies that could supply limitless clean power face development cycles stretching decades into the future. These are the technologies on which civilisational progress most clearly depends. They are also the technologies that venture capital, as currently structured, is least equipped to fund.

The question of why this is so, and whether anything can be done about it, has occupied researchers and policymakers for years. Today, as governments across the West embrace reindustrialisation, and the limitations of financialised economies become harder to ignore, it is increasingly urgent.

A growing body of academic work describes a solution (or a combination of three solutions) which would operate in harmony with private investors to strengthen the entire venture and growth ecosystem without repeating mistakes of the past:

1. The government as a limited partner for emerging managers. Addressing the network-driven constraints in venture capital that favour incumbents, reducing competition via limiting the threat of new entrants.

2. The government as a venture philanthrophist for sovereign technology. Addressing the difficulty that highly novel and capex intensive ideas may have in raising capital from the general pool of venture capital firms.

3. The government as a megafund guarantor of growth equity and debt. Addressing the hurdle into public market by providing later stage mezzanine financing which brings down the cost of capital for strategically valuable companies.

Each pillar of this strategy exploits the government’s ability to direct investment on longer time horizons and appreciate benefits beyond simple cash returns.

Impatient Allocation

Venture capital has been, by almost any measure, one of the most potent engines of innovation in economic history. Research illustrates that a dollar of venture capital is three to four times more effective at stimulating patenting than a dollar of traditional corporate R&D. The model is powerful, for a particular kind of company.

“The estimates therefore suggest that venture capital, even though it averaged less than 3% of corporate R&D from 1983 to 1992, is responsible for a much greater share—perhaps 10%—of U.S. industrial innovations in this decade.”

The Venture Capital Revolution, by Josh Lerner and Paul Gompers

The trouble is that the model’s structural incentives push capital towards certain categories of investment and away from others. A traditional venture fund has a ten-year life. Its general partners are rewarded on carried interest, a share of profits above a hurdle rate that must be realised within that fund’s lifetime. This creates a preference for investments that can reach a liquidity event, whether through IPO or acquisition, within that time period. Software companies with low capital requirements, rapid iteration cycles, and high gross margins are a natural fit. Companies building heavy physical infrastructure over fifteen-year timelines are not.

“The decision to continue funding certain compounds or technologies is often based on the likelihood of exiting the investment at a later date. If capital market conditions are unfavorable, or if the economy is not robust, pharma companies and venture capitalists may postpone or withdraw funding until the market environment improves, irrespective of the scientific merits of the project.”

Frequently Asked Questions About Megafunds, MIT Laboratory for Financial Engineering

This creates what researchers call the “valley of death,” a funding gap that opens after initial proof of concept but before a technology is commercially viable. For capital-intensive, long-horizon industries, this gap can be fatal. An estimated 80% of energy startups fail not because their technology does not work, but because they cannot sustain funding through the scaling phase.

Moreover, venture capital is intensely cyclical. During booms, capital floods into whichever category of technology appears hottest, to the point of oversupply. During busts, funding for even promising ventures evaporates. Government programmes designed to spur venture activity have frequently compounded this problem by targeting sectors already awash with private capital, rather than addressing gaps in the market. As the researchers note, many policy steps have had the consequence of exacerbating the cyclical nature of venture funding, rather than smoothing it.

Far too often, the short-term appearance of a successful programme is more important than actual success in driving innovation. This is a direct reflection of venture capital’s wider problem with the incentives of generating markups for fundraising purposes.

“While there were other sectors that held enormous technological promise and where entrepreneurs were struggling to raise money (alternative energy technologies, for one), these officials were drawn, like moths to a flame, to the sectors that were already overfunded by angel investors and venture funds alike. This decision may have been rational for the ATP bureaucrats eager to ensure their program’s survival. But it was profoundly at odds with the program’s mission to identify and rectify failures in the market for funding early-stage technologies.”

Boulevard of Broken Dreams: Why Public Efforts to Boost Entrepreneurship and Venture Capital Have Failed—and What to Do About It, by Josh Lerner

Scaled Funds, Limited Appetite

You may look at the emergence of scaled venture funds and see the beginnings of a solution. Firms like Andreessen Horowitz and General Catalyst now command capital at a scale that was unthinkable a decade ago. Their limited partners include sovereign wealth funds, major pension systems, and other large institutions that are able to invest on longer time horizons. In theory, this should allow for more patient investment in capital-intensive technologies.

In practice, it does not, or at least not sufficiently. The structural incentives of the traditional limited-partnership model remain in place regardless of fund size. LPs hope for returns of 20–30%. The pressure to invest in sectors where such returns are achievable has intensified. As Ben Horowitz wrote in announcing the raise, the firm’s mission is to ensure that the United States wins “the key architectures of the future,” meaning AI and crypto.

General Catalyst, similarly, has framed its latest fund around “applied AI” and “global resilience,” with a strong emphasis on building technology stacks that can be rapidly deployed within existing industries. These are sophisticated strategies, but they remain oriented towards categories where there is already a significant concentration of private capital to drive activity.

Essentially, their strategy to achieve competitive returns at scale is not to exploit larger LPs patience to invest in longer-term projects, but instead to hold “hot” companies for longer, harvesting more of their growth in private markets before seeking an exit, which has a number of negative consequences.

The result is a venture industry with more capital available than at any point in history, yet one that remains structurally unable to fund the technologies most needed for long-term economic security and industrial prosperity. The biggest funds chase the biggest near-term opportunities, and the hardest problems remain ignored.

Sovereign Megafunds

This is where the work of Andrew Lo and his collaborators at MIT’s Laboratory for Financial Engineering offers something genuinely different. Lo’s “megafund” thesis, first developed in a 2012 paper in Nature Biotechnology and subsequently extended to fusion energy, proposes a financial structure specifically engineered for what Josh Brown, CEO of Ritholtz Wealth, has termed “HALO“ companies; Heavy Assets, Low Obsolescence.

Rather than asking venture-style equity investors to bear the entire risk of long-horizon, high-failure-rate R&D, the megafund pools a large number of projects, typically fifty to three hundred, into a single special-purpose vehicle. It then finances this portfolio not through traditional LP commitments alone, but through securitisation; issuing tranched financial instruments that appeal to different categories of investor.

The senior debt tranches offer low-risk, fixed returns, similar to corporate bonds, and are designed for conservative institutional investors such as pension funds and insurers. Mezzanine debt tranches offer moderate risk and return. Equity tranches absorb the highest risk but also capture the greatest upside. The structure is analogous to mortgage-backed securities, though applied to a portfolio of research and development projects rather than home loans.

“In 2018, $254B was invested globally through venture capital financing, while the size of the global bond market stood at $102.8T, more than 400 times larger.”

Financing Fusion Energy, by Alhamdan, Halem, Hernandez, Lo, Singh, and Whyte

The pool of capital available through debt markets dwarfs the venture capital industry by orders of magnitude. By creating instruments that allow conservative institutional investors to participate in breakthrough R&D at a risk level they find acceptable, the megafund taps into a reservoir of financing that has been largely inaccessible to innovation. The ability to finance through debt also carries a lower cost of capital than equity, thanks to the tax deductibility of interest expenses, further improving the economics of the portfolio.

Lo and his collaborators have run extensive simulations demonstrating that this approach produces viable returns. Using historical oncology data from 1990 to 2011, they showed that a $5–$15 billion megafund could generate average annual returns of 8.9–11.4% for equity holders and 5–8% for debt holders, even accounting for the brutal attrition rates of drug development. Applied to fusion energy, simulations of a $10–$30 billion fund yielded projected returns of 7–12%, assuming moderate correlations between projects and occasional breakthroughs.

Crucially, the megafund also incorporates mechanisms for de-risking that go beyond simple diversification. Governments and philanthropic partners can provide “first loss capital” guarantees, effectively backstopping the most junior tranches to give private investors confidence. Lo and his collaborators have proposed that this philanthropic first-loss component would require initial funding of at least $500 million to guarantee five or more years of payments to senior tranche investors. This public-private hybrid design makes the megafund a particularly attractive instrument for government funding initiatives and large institutional LPs such as sovereign wealth funds and public pension funds, which are not only patient and well-capitalised but ideologically aligned with the kinds of positive externalities such as clean energy, public health breakthroughs, and national strategic resilience.

“We further de-risk the megafund by leveraging first loss capital guarantees from philanthropic sources and governments to fund coupon payments to senior and mezzanine bondholders in its early years.”

Financing Fusion Energy, by Alhamdan, Halem, Hernandez, Lo, Singh, and Whyte

This public-private hybrid potential makes the megafund extremely relevant to the current policy conversation. Governments seeking to accelerate energy transitions or secure domestic supply chains do not need to shoulder the entire financial burden themselves; by guaranteeing junior tranches, they can catalyse multiples of private investment. The taxpayer’s exposure is limited to the first-loss layer, while the vast majority of capital comes from private institutional sources attracted by the risk-adjusted return profile of the senior debt. The Israeli Life Sciences Fund already serves as a proof of concept for how government loan guarantees can stimulate private investment.

“The government provided some $50 million as a limited partner. Its funding serves as the first-loss capital through a preferred return scale, which allows for positive returns to other limited partners even if the fund suffers as much as a 10 percent loss. This structure has proved an attractive proposition for the fund managers (OrbiMed Israel Partners LP), who were able to raise the $172 million on top of the government's $50 million.”

Financing High-Risk Medical Research, by Melissa Stevens

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The Discovery Layer

One important qualification is that Lo’s megafund is not designed for inception-stage companies. It operates at the point in the cycle where the technology has been validated at some initial level but still requires massive capital to scale.

This is where small VC firms and emerging managers play a critical role, forming what can be considered the “discovery layer”, the initial interface between capital and innovation. Investors who find, fund, and develop the raw ideas that will eventually become candidates for megafund investment. A seed-stage investor working with a university spin-out developing novel fusion confinement technology, or a pre-seed fund backing a team designing advanced reactor components, are doing the essential work of making scientific breakthroughs “legible to capital”.

Research consistently supports this view. A 2025 study of government venture capital investment across Europe found that redirecting allocated capital towards early-stage investments produced the same productivity uplift as doubling the total capital allocation. The authors documented that government-linked VC financing had its strongest and most persistent effects when focused on young firms, despite the fact that public VC portfolios were systematically skewed towards later-stage companies. Separate research across other EU member states demonstrated that where governments fund emerging fund managers, they may produce above-market success rates and stronger job creation.

Indeed, a 2025 report by the Institute for European Policymaking and the ifo Institute reinforced this finding, showing that the EU’s roughly 100 billion euros of Horizon innovation funding had disproportionately flowed to large corporations with modest innovation records, while single-recipient grants to small, independent firms yielded the best long-term results.

“Any new Framework Program should thus focus on funding ideas, not companies. The key is not more money, but rather leaving space for disruptive innovation by encouraging bottom-up initiatives, especially by small independent companies.”

Funding Ideas, Not Companies, by Fuest, Gros, Mengel, Presidente, and Rujan

A healthy innovation ecosystem, then, would feature small funds scouring early-stage companies for breakthrough potential; developing those ideas through initial prototypes and regulatory milestones; and then passing the most promising candidates upward into a megafund structure capable of sustaining them through the capital-intensive scaling phase.

This complementary relationship could, if properly structured, strengthen both ends of the ecosystem. Emerging managers would have a clearer path for their portfolio companies beyond Series A, and potentially avenues for earlier liquidity, making their own funds more attractive to LPs. Megafunds would have a steady pipeline of de-risked, validated opportunities to absorb. The valley of death narrows considerably when there is a bridge waiting on the other side.

Venture Philanthropy

The megafund model and the discovery layer of emerging VC managers address the two critical stages of large-scale capital deployment and early-stage deal sourcing. There remains another category of technology for which even these structures may not move quickly or deliberately enough. When a government determines that a particular capability is strategically essential, whether in advanced materials, quantum computing, or biodefence, it may not wish to wait for a venture ecosystem to emerge around that technology.

Kyle Briggs, a physicist at the University of Ottawa who works on innovation policy and technology transfer, has developed a framework for exactly this problem. In a 2026 study drawing on PitchBook data covering 9,199 university-affiliated startups across North America and Europe, Briggs simulated the long-term performance of several strategies for investing in the earliest stages of research commercialisation.

His findings reflect a growing consensus about early stage investment in venture capital, where the most important variable in determining success is not the picking ability of the fund managers, but the portfolio size. Broad investment of small amounts of capital in a large number of startups statistically outperforms concentrated investment in fewer companies, by a wide margin. The returns from emerging technology commercialisation follow a highly asymmetric distribution in which a tiny minority of investments generate the vast majority of value. Under-sampling from such a distribution, as risk-averse investors often will, dramatically reduces the probability of capturing those outliers.

“Risk-intolerance creates a negative feedback loop in which under-sampling driven by risk aversion leads to subpar returns, which in turn reinforces the risk aversion that is in fact the root cause of the problem.”

Bootstrapping an Innovation Ecosystem, by Kyle Briggs

If it is effectively impossible to predict which early-stage research commercialisation attempts will succeed, then the correct strategy is not to try to pick winners but to fund widely, tolerate high failure rates, and trust that the statistical properties of the portfolio will deliver returns over time. A high rate of failure is a positive signal, indicating that the fund is investing broadly enough to be confident that it is not missing the valuable minority.

Briggs proposes a vehicle he calls “venture philanthropy”, in which a not-for-profit entity, seeded with public funds, makes small equity investments, typically $50,000 to $250,000, into a large number of university spin-outs and early-stage deep-tech companies at founding or shortly thereafter. Returns from successful exits are recycled into the fund to support the next generation of technologies. Because there is no profit-sharing obligation and no fixed fund lifetime, there is no time pressure to realise returns, making these investments genuinely patient capital. Because the fund is structured as a charitable entity, it can also solicit private donations, sharing the risk between public and private sectors while offering tax benefits to contributors.

The UK’s Innovation and Science Seed Fund provides a real-world example. It is credited with the existence of 78% of the companies in which it invested, and claims £29 of private follow-on capital for each £1 it has deployed.

Briggs’s simulations, using Monte Carlo methods across thousands of portfolio scenarios, demonstrate that this model can be self-sustaining. In his central scenario, a fund investing $4 million per year across eighty companies annually, taking small equity positions via convertible instruments, reaches breakeven at a median of approximately twenty years. The median annualised internal rate of return rises to 11.6% by year thirty and 13.5% by year forty.

More importantly, once breakeven is achieved, the fund enters an exponential growth phase as returns from successful exits are reinvested into an ever-larger number of new companies, and the ecosystem itself begins to compound. The vast majority of individual investments, over 96%, fail. But the realised value of the successful outliers more than covers the cost of those failures, and the broader economic benefits, in job creation, talent retention, and intellectual property kept within the sovereign jurisdiction, compound well beyond the fund’s direct financial returns.

“If seeded with public funds that are then augmented with private donations, venture philanthropy shares the risk of emerging technology investment between the public and private sectors, accepting a high rate of failure, long timelines, and sub-market profits that neither the public nor private sectors would tolerate alone. Because the goal is not profit beyond the need to be self-sustaining and operationally solvent, venture philanthropy measures success in terms of talent and IP retention, training first-time founders, company and job creation, and advancement toward societal goals.”

Bootstrapping an Innovation Ecosystem, by Kyle Briggs

The decades-long timeframe, initial target returns and the sheer number of investments required to reduce variance are mostly incompatible with a private-sector-led initiative. This is precisely why the private sector has not addressed this funding gap, and many emerging technologies have no reliable pathway from the lab to the market. A competitively-minded government, willing to accept modest financial returns in exchange for the broader economic and strategic benefits of a thriving domestic innovation ecosystem, is the obvious enabler.

The American SBIR programme, which until recently funded a comparable stage of research commercialisation, is estimated to create $22–$33 of economic value for every dollar invested. If a government can achieve even a fraction of that return while simultaneously retaining intellectual property and entrepreneurial talent within its borders, the case is easily made. The challenge is they must also be willing to tolerate high visible failure rates, resist the temptation to pick winners, and commit to investment horizons that extend well beyond electoral cycles, which are not natural instincts for public institutions.

The alternative, watching scientific breakthroughs and human capital leak to other jurisdictions, is a far more expensive form of failure.

A Long Time Coming

The problem of short-termism in venture capital and in the broader economy is not new. As far back as the 1980s, researchers were warning about “capital market myopia,” the tendency of financial markets to undervalue long-horizon investments.

“The purpose in writing this article is to focus attention on a phenomenon we call capital market myopia, a situation in which participants in the capital markets ignore the logical implications of their individual investment decisions. Viewed in isolation, each decision seems to make sense. When taken together, however, they are a prescription for disaster. Capital market myopia leads to overfunding of industries and unsustainable levels of valuation in the stock market.”

Capital market myopia, by William A. Sahlman and Howard H. Stevenson

The cyclical nature of venture funding, documented extensively by Gompers and Lerner, has been a persistent feature of the industry since its inception.

What has changed is the broader economic context, and increasing financialisation. Carlota Perez, the queen of techno-economics, has argued that the prolonged period since the dot-com crash represents a historically unusual failure to transition from an “installation period” of creative destruction to a “deployment period” in which new technologies are broadly diffused through the economy. In previous technological revolutions, from the steam age to the era of mass production, a financial crash midway through the cycle prompted institutional reform that redirected capital towards productive investment. This time, that correction has not occurred.

“The most acute impediment to a golden age deployment is the continued decoupling of finance from production. The usual casino of the frenzy periods has remained in force since the NASDAQ bubble, with major variations in form, but not in essence.”

A Long Delayed Golden Age: Or why has the ICT ‘installation period’ lasted so long?, by Carlota Perez

The reason, in Perez’s analysis, is that government responses to successive crises, from the dot-com bust to the 2008 financial crisis to the pandemic, have consistently prioritised the financial system over the productive economy. Quantitative easing pumped liquidity into banks without conditions requiring productive lending. Interest rates remained at historic lows for over a decade, making speculative financial activity far more attractive than patient investment in industrial capacity. As Perez observes, since the favoured banks were not required to use the money to fund the real economy, production investment and productivity increases remained at all-time lows, while the financial world played with derivatives and synthetic instruments across the globe.

This has clear alignment with developments in venture capital over the last few decades. Cheap capital encouraged larger fund sizes and higher valuations, but did not necessarily encourage better allocation. When money is abundant and cheap, the incentive to undertake disciplined, long-horizon investment in difficult technologies actually diminishes. It is easier, and more immediately rewarding, to fund software companies with two-year paths to revenue than to fund nuclear energy companies with fifteen-year development cycles.

"[VCs] furthered the financialization of firms, allocating capital to far from ideal uses and obtaining a share of the gains incommensurate with the risk or labor invested. In sum, VCs deepened asset-driven inequalities by devising a particular handling of abundance, which materialized in building a financial infrastructure for their needs."

Solving the problem of abundance: venture capital and the making of asset-driven inequalities, by Nils Peters

Today, however, the mood is shifting. The reindustrialisation movement, accelerated by supply chain disruptions, geopolitical competition with China, and growing awareness of the vulnerabilities embedded in deindustrialised economies, has created a new political and institutional appetite for productive investment. Governments across the West are deploying industrial policy at a scale not seen in decades.

In this environment, the government’s role as an LP and a VC, alongside the megafund model, offer a framework that aligns private incentives with public goals, directing large pools of institutional capital towards the most consequential challenges.

Putting It Together

Consider how this three-layer stack would operate in practice for a government pursuing an advanced nuclear strategy.

At the LP layer, the government commits capital to a cohort of emerging fund managers who invest across a range of technologies including energy and advanced manufacturing. These managers make hundreds of seed investments across the sector, including in companies developing novel reactor components, advanced materials, control systems, and grid integration technologies.

Simultaneously, at the venture philanthropy layer, the government seeds a dedicated fund targeting nuclear technology spin-outs from national laboratories and universities. This fund invests $50,000 to $250,000 in every credible spin-out attempting to commercialise relevant research, regardless of perceived probability of success.

Five to ten years later, a handful of companies from both layers have demonstrated genuine technical progress. One has developed a novel fuel fabrication process. Another has built a prototype coolant system. A third has achieved regulatory pre-approval for a small modular reactor design. These companies now need capital at a scale that neither small VC funds nor venture philanthropy can provide.

A $20 billion energy megafund, backed by securitised bonds rated for institutional investors and an equity tranche for endowments and sovereign wealth funds, absorbs these companies into a diversified portfolio alongside fusion ventures, grid-scale storage projects, and other energy technologies. The government guarantees the fund’s junior tranche, limiting taxpayer exposure to the first-loss layer while catalysing multiples of private institutional capital. The companies receive the patient, large-scale financing they need. The pension funds receive steady coupon payments from the senior debt. The equity holders gain exposure to transformational upside. And the early-stage investors, both the emerging managers backed by government LP capital and the venture philanthropy fund, have a clear exit path for their positions, improving their own returns and making them more attractive to future investors.

The beauty of this structure lies in the fact that each layer’s weakness is addressed by another layer’s strength. Small VC funds are excellent at discovery but cannot deploy capital at scale or over long timelines. The megafund can deploy capital at scale over decades but cannot source unproven, early-stage opportunities. Venture philanthropy can fund broadly and patiently at the inception stage but produces returns too slowly and too modestly for private investors. Government LP activity can support an ecosystem of emerging managers but cannot direct capital towards specific strategic priorities.

The total public expenditure required is, by the standards of government budgets, remarkably modest. An LP commitment of perhaps $200 to $500 million spread across a generation of emerging fund managers. A venture philanthropy seed of $50 to $100 million in each of several strategically targeted technology domains. A first-loss guarantee of $500 million to $1 billion to catalyse a megafund that raises $10 to $20 billion from private institutional sources. Against these outlays, the government receives a growing domestic innovation ecosystem, strategic control over critical technology supply chains, high-skill job creation, and, over the long term, a financial return on its investments that compares favourably with most other categories of public expenditure.

What this framework demands of governments is long-term thinking, institutional patience, and a tolerance for visible failure. Most companies funded by the venture philanthropy layer will fail. Many of the emerging managers supported at the LP layer will produce unremarkable returns. Some projects within the megafund will collapse entirely. These outcomes are the necessary cost of a strategy built on portfolio logic rather than the illusory pursuit of certainty. The alternative, which most governments currently favour, is to fund a small number of carefully selected projects and companies, demand accountability at every stage, and declare success or failure on the basis of individual outcomes. It appears more responsible on the surface, but is, in fact, far more wasteful on the balance of ultimate outcomes (never mind the risks associated with adverse selection and choking innovative companies with red tape).

Right now, innovation is unable to channel public investment and large institutions to the points in the pipeline where they will have the most impact. The three-layer model described here (government as LP, government as venture philanthropist, and government as megafund guarantor) offers a blueprint for each stage of the pipeline, from the first hint of an idea in a university laboratory to the deployment of a functioning power plant or manufacturing facility. And it does so in harmony with the private venture capital ecosystem, which stands to benefit at the growth stage from government LP/VC activity catalysing opportunity, and at the early stage from megafunds expanding the aperture of what is fundable by providing downstream capital and exit liquidity.

As the world asks how to rebuild its industrial foundations, we must look at how to scaffold this movement with new financial structures.

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When: Friday March 27th
Where: London (Covent Garden)
What: a screening of ‘The AI Doc’

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The AI Doc: Or How I Became an Apocaloptimist purports to be the most important documentary of the year. It features Sam Altman, Dario Amodei, Demis Hassabis, Eliezer Yudkowsky, Tristan Harris, and 40 or so others wrestling with what AI means for the future of humanity.

​We thought it was worth watching with a room full of people who have something interesting to say about it. Far from ridiculing it, we intend to deal with it seriously.

​Whether or not you share its conclusions, what happens when the most powerful technology ever built outpaces our ability to govern it is an interesting question.

​Come watch (it’s free). Then let’s argue about it.

We’ve got 4 spots left.

Now, over to Mr Gray…

“Many of the largest companies in the U.S. by market capitalization, including Apple, Google, Microsoft, and Cisco, were backed by venture firms in their early days. In addition, more than 60% of the IPOs that have occurred since 1999 have been venture-backed. Given that venture firms provide capital to highly innovative companies with the potential to create large social surpluses, distortions in their capital allocation decisions could have important welfare implications.”

Propagation of Financial Shocks: The Case of Venture Capital, by Richard R. Townsend

Every year, Venture Capital Journal surveys the institutional investors who provide the financial backbone of the venture capital industry. These limited partners, the pension funds, endowments, foundations, and family offices that allocate capital to venture funds, collectively shape the direction of innovation finance through their commitments, or their reluctance to commit.

Of the LPs surveyed, 32% said they plan to invest more in venture capital this year, while 58% intend to invest the same amount. Only 10% plan to invest less, the lowest figure recorded in at least six years. On the question of new commitments, 14% said they would make significantly more and 43% said slightly more, both figures up from the prior two years. The headline numbers seem promising.

If you look a little closer, the survey hints at allocation decisions that risk compounding many of todays problems. LPs are retreating from the smallest, earliest, and newest funds at a pace that should concern anyone who cares about the long-term health of venture capital’s engine of innovation.

The Emerging Manager Exodus

The most striking finding in the 2026 survey is that 57% of LPs said they would not consider backing an emerging manager in the next twelve months. That figure was 33% just one year earlier. In a single year, the proportion of LPs unwilling to invest in new fund managers nearly doubled, despite consistent evidence of strong performance in that group.

This was similarly reflected in stage preferences, where only 7% of LPs said they planned to invest more in seed-stage funds, 32% said they would not invest in seed at all, and 14% said they would invest less, leaving 46% investing about the same. Compare this with early-stage and growth funds, where 10% of LPs planned to invest more and 66% planned to hold steady. Capital is retreating to the “safety” of established names and later stages, away from the frontier.

Of course, this is something we have all sensed over the last couple of years, but it is fascinating to see the extent of the issue borne out in the data.

The top three reasons LPs give for their frustrations with venture capital provide some context:

• 31% said returns have not lived up to expectations

• 21% said they were unable to get allocation to the best funds

• 14% said it was too hard to pick winners

In reality, these are three different ways to say the same thing: performance has been disappointing due to an extended period of weak liquidity.

Others cited an inability to invest as much as they would like, inflexible terms, the burden of due diligence relative to small check sizes, and a lack of transparency by managers. These are real concerns, some of which reflect a need for greater professionalization and stronger standards in venture capital.

Problems of Venture Capital’s Own Making

“As a group becomes ten times larger, expenses increase much less than tenfold. As a result, management fees themselves become a profit center for the firm. These steady profits may create incentives of their own which may not be very appealing to investors. For instance, there will be an incentive to raise a larger fund at the expense of lower returns, which in turn may be tied to the greater concentration of capital held by a few investors; an incentive to put funds to work quickly and with a subpar amount of vetting so that a new fund can be raised sooner; and an incentive to focus on excessively safe investments that will not have as much upside but will pose less risk of a franchise-damaging visible failure.”

Venture Capital’s Role in Financing Innovation: What We Know and How Much We Still Need to Learn, by Josh Lerner and Ramana Nanda

The period from roughly 2016 to early 2022 was one of the most overheated in venture capital’s history. LPs flooded the market and the mega-funds emerged. Valuations climbed to levels disconnected from any reasonable expectation of near-term returns.

The consequences of that era are now well understood. Overcapitalization slowed exits by creating an overhang of overvalued private companies that couldn’t go public at prices their investors needed. The IPO market, which was already in decline before 2022, effectively shut for many venture-backed companies. The M&A landscape offered limited alternatives. Distributions to LPs dropped sharply. And in the most damaging cases, the loosening of governance standards enabled fraud and mismanagement at companies that had raised enormous sums with weak oversight.

Lerner and Nanda found that among publicly traded firms worldwide, seven of the top eight by market capitalization in 2020 had been backed by venture capital, and that VC-backed firms accounted for nearly 89% of recorded R&D expenditure among the cohort of post-1995 IPOs still public at the end of 2019. Venture capital, at its best, is an extraordinarily effective mechanism for financing innovation. Their concern was that structural changes in the industry were undermining that effectiveness. The concentration of capital in a small number of large funds, the narrowing of investment focus toward software and away from harder technologies, and the erosion of active governance were all trends they flagged as potentially detrimental to the broader innovation ecosystem.

Crucially, these problems are almost entirely correlated with the rise of mega-funds. The overcapitalization, the degraded governance, the herd behavior, the pursuit of capital velocity to justify ever-larger fund sizes, these are all features of the largest end of the market. The small and emerging fund managers that LPs are now abandoning were, for the most part, bystanders. Where these small firms did participate in the excesses of the boom, it was typically by chasing the same hot themes that mega-funds had already bid up, a reflection of LP demand signals.

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Collateral Damage

“Despite the fact that venture firms are structured to be more robust than most intermediaries, their portfolio companies can still face increased difficulty accessing capital when others that share the same investor suffer a negative shock. This can ultimately lead companies with high innovative potential to fail.”

Propagation of Financial Shocks: The Case of Venture Capital, by Richard R. Townsend

The pattern of innocent bystanders absorbing the damage of a correction they did not cause is not unique to the current cycle. There are clear examples from history, documented in a study by Richard Townsend of Dartmouth’s Tuck School of Business, examining how the collapse of the dotcom bubble in 2000 propagated through venture capital portfolios to companies with no connection to the internet sector.

Townsend’s research focused on non-information-technology companies, firms operating in sectors like biotechnology, medical devices, and energy, that happened to share venture investors with internet companies. When the bubble burst, these non-IT portfolio companies experienced a 26% larger decline in their probability of raising follow-on financing if their investors had high exposure to the internet sector, compared with similar companies whose investors did not. Indeed, after five years, the estimated probability of a company not having raised another round increased by over 8% for the affected group, a difference that, in the venture context, typically translates into company failure.

Critically, these companies were not worse investments. Townsend examined their patenting productivity, both the number of patents filed and the citations those patents received, and found no evidence that non-IT companies backed by internet-focused venture firms were of lower quality than their peers. They were just unfortunate collateral damage. Their investors’ portfolios had been contaminated by losses elsewhere, and the contamination spread to them through a mechanism that had nothing to do with the quality of their own technology or business prospects.

By exploiting the fact that many startups have multiple venture investors, Townsend was able to examine the same company across investors with varying levels of internet exposure. For the same portfolio company receiving capital from multiple venture firms, those investors with greater internet exposure were significantly more likely to drop out of follow-on rounds after the bubble collapsed. A one standard deviation increase in internet exposure was associated with a 38.5% increase in the probability of an investor dropping out, relative to an unconditional dropout rate of just 10.8% in the pre-bubble period. This within-company variation makes it far less likely that the results were driven by unobservable differences in company quality.

The Performance Paradox

The survey data on performance perceptions highlights the extent of LP disappointment. Only 13% of respondents to the Venture Capital Journal survey said venture capital had exceeded their benchmarks for 2026, up slightly from what appears to have been a low of around 6% in 2024, but far below the roughly 46% that was typical in previous years. 53% said venture fell below benchmarks, an improvement from 63% in 2025 but still more than half of all respondents.

The anomalous year in the dataset is 2022, when 68% of LPs said venture had exceeded benchmarks over the last 12 months, the only year where the figure topped 50%. This was driven by the surge of distributions in 2021, the last gasp of the ZIRP liquidity cycle. What followed was a sharp and sustained deterioration in sentiment, with fewer than 10% of LPs satisfied with performance by 2024.

Curiously, in 2020, LP sentiment was also surprisingly low. Looking back on 2019 and facing the uncertainty of the pandemic, LPs could not see the wave of exits on the horizon. That pessimism came just before one of the best years for venture distributions in recent memory. Here, we can conclude that LP sentiment is a lagging indicator, not a predictive one. The survey measures how the market felt at the time, not how it is likely to perform in subsequent years.

If LPs are making allocation decisions based on recent disappointment, they are doing so at a moment when the drivers of that disappointment are already several years in the rearview mirror. The companies in current seed-stage portfolios were not part of the 2021 vintage frenzy, and have not yet had time to mature. Venture fund performance takes approximately eight years to become a meaningful reflection of a manager’s ability. Judging emerging managers by the returns of a period defined by mega-fund excesses is a major attribution error.

The No-Invest Equilibrium

“Like in a bank run, if current investors believe that future investors will withdraw financing from such a project, they should also withdraw their investment, even though all investors would be better off in the equilibrium in which everyone invests. This is not an irrational decision and furthermore, does not depend on information asymmetries. There are simply two equilibria – one in which everyone invests in a sector and one in which no one does.”

Financing Risk and Bubbles of Innovation, by Ramana Nanda and Matthew Rhodes-Kropf

A theoretical framework developed by Ramana Nanda and Matthew Rhodes-Kropf helps explain why the current LP retreat is so destructive. Their model of financing risk, published in a paper that has become influential in venture capital scholarship, shows that the availability of future funding is itself a determinant of present value. When investors believe that future investors will not fund a given sector or stage, they rationally withdraw, because the absence of expected future capital genuinely reduces the value of current investments.

The mechanism works through bargaining power. A startup whose investors cannot credibly signal future funding has a weaker negotiating position with potential acquirers. The acquirer faces a lower competitive threat from the startup, because the startup is less likely to survive and grow into a formidable competitor. This reduces the price the acquirer is willing to pay, which lowers the net present value of the investment, which makes the decision to withdraw capital rational.

The result is a self-fulfilling equilibrium, as the belief that funding will not be available becomes the reason that funding is not available.

Nanda and Rhodes-Kropf demonstrate that this dynamic hits innovative projects (where coordination costs are highest) the hardest. Investors can try to mitigate financing risk by committing more capital upfront, giving startups a larger cushion to survive a funding drought. But doing so destroys the real option value of staged investment, the ability to invest a little, learn, and decide whether to continue. This option value is most significant for the most uncertain, most innovative projects; precisely the kind that small seed-stage funds specialize in.

The paper is explicit that it is the most innovative sectors and firms that need the abundant funding equilibrium to invent and commercialize radically new technologies.

Townsend’s work on the dot-com collapse is a good illustration of this theory. His model shows that in principle, the direction of contagion within a venture portfolio is ambiguous. When some investments in a fund perform poorly, the remaining investments become relatively more attractive, since the venture firm has a fixed pool of capital to deploy. This reverse contagion effect, analogous to the bright side of internal capital markets, would predict that non-IT companies in internet-heavy portfolios should have benefited from the collapse, receiving more capital as their investors redirected resources away from failing internet bets.

The fact that Townsend’s evidence decisively rejected this prediction, showing that contagion was ordinary rather than reverse, tells us something important about the power of the fundraising channel. The theoretical possibility of capital reallocation within a portfolio was overwhelmed by the venture firm’s diminished capacity to raise new funds from limited partners.

Indeed, venture firms in the top quartile of internet exposure experienced a 47.5% larger decline in their fundraising capacity after the bubble burst compared with those in the bottom quartile; a fundraising shock that would cascade to their portfolio companies. The effect was strongest for young venture firms and for firms that had not raised a new fund recently, exactly the profile one would expect if the transmission channel was LP capital commitments. For companies backed by a venture firm that had just raised a fresh fund, investor internet exposure had no statistically significant effect on continuation financing.

Essentially, the damage was concentrated among companies whose investors were dependent on near-term fundraising, the firms most vulnerable to a shift in LP sentiment.

This parallel will be felt by emerging managers who raised Fund I in 2021 or 2022 are now attempting to raise successor funds in an environment where 57% of LPs have declared them off-limits. Townsend’s evidence shows that this kind of fundraising shock will propagate to portfolio companies, reducing their access to capital regardless of their underlying quality, and it does so most acutely for the youngest and most capital-constrained investors.

In summary, when 57% of LPs say they will not consider emerging managers, they are sending a signal that pushes that part of the market toward what Nanda and Rhodes-Kropf call the “No-Invest equilibrium”. Founders become less willing to take capital from emerging managers because they worry about follow-on risk, and co-investors grow cautious. The emerging managers’ portfolios lose value because the ecosystem around them is less optimistic. Returns decline, and LPs cite the declining returns as evidence that they were right to withdraw, completing the circular logic.

The Concentration Trap

“While venture funding is very efficacious in stimulating a certain kind of innovative business, the scope is increasingly limited. This concentration may be privately optimal from the perspective of the venture funds and those who provide them with capital. It is natural to worry, however, about the social implications of these shifts. For instance, promising startups developing renewable energy technologies and advanced materials, which might have broad societal benefits, may languish unfunded.”

Venture Capital’s Role in Financing Innovation: What We Know and How Much We Still Need to Learn, by Josh Lerner and Ramana Nanda

Lerner and Nanda’s research documents just how concentrated the venture capital industry has become. As of their 2020 analysis, the top 50 investors, representing roughly 5% of all venture firms, had raised half of all capital deployed between 2014 and 2018. The partners at these firms are overwhelmingly male graduates of a small number of elite universities, based in the San Francisco Bay Area. This concentration amongst investors also ends up limiting the diversity of ideas that get funded, via the well documented problems of homophily, herd behavior and heat seeking.

The authors note that while this concentration may be privately optimal for individual funds (expanding fee income, easier fundraising from LPs), it raises concerns about the cost to progress when categories of promising technology go unfunded. Additionally, such concentration dramatically raises the risk from a market correction, similar to the post-dotcom retreat documented by Townsend.

PitchBook data confirms this concentration problem has deepened in the years since. The belief that AI is the defining opportunity of this era, and that AI companies require enormous amounts of capital which small firms are ill-suited to provide, has pushed LPs further toward large funds.

There are two problems with this reasoning. The first is that the history of venture capital consistently shows that the hot theme of any given vintage is rarely where the largest outcomes emerge. Venture returns are driven by outliers, and outliers, by definition, are rarely in consensus categories. The second is that consistent allocation across stages and fund sizes is essential to a healthy venture ecosystem and good long-term performance.

“We find that consensus entrants are less viable, while non-consensus entrants are more likely to prosper. Non-consensus entrepreneurs who buck the trends are most likely to stay in the market, receive funding, and ultimately go public.”

The Non-consensus Entrepreneur: Organizational Responses to Vital Events, by Elizabeth G. Pontikes and William P. Barnett

Early-stage managers, including emerging managers who bring fresh perspectives and networks, are the entry point of the pipeline. Without adequate funding at the base, the later stages that LPs favor will eventually run short of high-quality companies to back.

LP’s Accountability for Allocation

Consider the eight categories of challenges that LPs cited in the survey. Returns not meeting expectations, inability to access the best funds, difficulty picking winners, constraints on capital deployment, inflexible terms, due diligence burdens, lack of transparency: many of these can be traced to structural features of the mega-fund era or to shortcomings in LP portfolio construction and monitoring.

If returns have disappointed, the relevant question is what funds those LPs selected and at what point in the cycle. If they were chasing oversubscribed brand-name funds during the 2020 to 2021 boom, paying for access to an overheated market, the underperformance is primarily a portfolio construction failure.

Not being able to access the “best” funds may relate to an inability to recognise promising managers early to secure allocation, or suffering from hindsight bias in relation to fund performance. Finding it too hard to pick winners may reflect a similar failure to develop the expertise required to evaluate firms and make objective judgments.

If terms are inflexible, it is worth noting that LPs have collectively failed to reform venture fund economics for decades, despite well-documented misalignments.

Indeed, Lerner and Nanda note that management fees, originally designed to cover costs for small funds, have become a significant profit center as funds have grown.

Additional research by Metrick and Yasuda shows that over $23 of every $100 invested ends up with the venture firm, the majority coming from fixed fees rather than performance-linked carry. Their study also questions the fundamental logic of larger venture capital funds.

“The VC skills that are critical in helping firms in their developmental infancy are not applicable to more mature firms that are ten times larger and already in possession of core management skills. So when successful VC firms increase the size of their fund, they cannot just scale up the size of each firm they invest in without dissipating their source of rent.”

The Economics of Private Equity Funds, by Andrew Metrick and Ayako Yasuda

In aggregate, many of the challenges expressed by LPs are what a less diplomatic observer might call a skill issue.

The problems LPs face are substantially of their own making, or of the making of the large-fund ecosystem they continue to favor. The small and emerging fund segment, which is bearing the brunt of the retrenchment, is the least connected to the dynamics that have driven the downturn.

Maintaining the Techno-Capital Interface

Nanda and Rhodes-Kropf include a finding that deserves particular attention from LPs looking to structure a venture capital portfolio. They suggest that the mix of investors should shift toward smaller participants during periods of low financing risk, because smaller and more frequent investments are well suited to periods when future capital is expected to be available. For example, a skew toward small funds in the 2014-2018 period would have produced a larger and more diverse set of opportunities to absorb capital at the peak in 2020-2022, reducing fragility and the extent of the correction which followed.

In contrast, the model predicts that smaller investors will virtually disappear from the market during downturns, as the coordination costs to continue funding non-consensus projects are simply too high. This is not a desirable outcome, just the unfortunate nature of how the market suppresses the most innovative projects during the periods when contrarian investment would be most valuable.

Indeed, Nanda and Rhodes-Kropf suggest that some genuinely valuable technologies may require robust financial markets to get through the initial period of development (i.e. Carlota Perez’ “Installation Periods”), because otherwise the financing risk is too extreme. If this is correct, then the withdrawal of LP capital from early-stage and emerging funds is a clear impediment to future innovation. The most radically new ideas, the ones most likely to produce the outsized returns that LPs claim to seek, may be unable to survive the current financing environment precisely because the investors who specialise in finding them have been cut off from capital.

A sensible LP should understand that you invest in small and emerging managers because you trust them to go out onto the frontier and find the next opportunity. You invest in mega-funds (or mid-sized firms who service the megafirm consensus) because you believe there’s a present opportunity that requires more capital. These are entirely different categories, with different risk profiles, and treating one as a substitute for the other reflects a fundamental misunderstanding of how venture returns are generated.

Importantly, any “present opportunity” was, at some point in the past, the “next opportunity”, and relied on frontier investors that provide the interface between capital and technology. If that interface is underallocated, technological progress will quickly stagnate as the stream of new opportunities dries up.

The Cost of Consolidation

The venture capital market went through a period of extreme overcapitalization driven by mega-fund competition and the entry of non-traditional investors. That period produced inflated valuations, weakened governance, and an exit overhang that continues to depress returns and distributions. LPs, surveying the damage, appear to be consolidating their commitments into the very segment of the market most responsible for these outcomes while withdrawing from the segment least connected to them.

The emerging managers who raised Fund I in 2021 or 2022, now struggling to raise a successor, are generally not victims of a meritocracy; their portfolios have not had time to produce meaningful performance data. They are victims of a market correction they did not cause, operating under a standard of judgment shaped by the excesses of a different part of the industry.

The performance of a general partner’s previous private investment funds can predict future fund performance to a degree, but that’s only with at least eight years of hindsight, according to PitchBook’s latest Allocator Solutions report. In reality, LPs typically make decisions about where to commit fresh capital about three and a half years, on average, after a fund’s predecessor has closed—making it too soon to know exactly how the GP’s latest investments will pay out to existing LPs.

Fund performance data unhelpful for LPs when it counts, by Emily Burleson

Nobody knows what the venture market will look like in five years. The LPs who were so pessimistic in 2020, convinced the market was broken, were about to get one of the best years for liquidity in a generation. The LPs who piled in during 2021, certain they understood the opportunity, funded many of the worst outcomes.

The lesson, repeated across every cycle, is that the most valuable thing an institutional investor can do in venture capital is maintain consistent allocation across stages and fund types, resist the temptation to time the market, and support the parts of the ecosystem that the consensus has abandoned. Right now, that means emerging managers and seed-stage funds.

Unfortunately, the survey suggests that most LPs are doing the opposite.

But therein lies an opportunity…

Get started with Odin, your full-stack, digital-first partner for SPVs and fund administration.

“We cofounded the Thiel Fellowship with Peter Thiel in 2010 with a few secrets in mind: young people should be taken seriously, outstanding founders are found without credentials and even in the oddest of places, and that the edges of technology and science can and often are advanced by those least likely to be recognized by sclerotic institutions.”

Danielle Strachman and Michael Gibson, 1517 Fund

When Michael Gibson and Danielle Strachman launched their venture capital fund in the summer of 2015, they named it 1517: the year Martin Luther nailed his 95 Theses to a church door in Wittenberg, protesting the sale of indulgences, and sparking the Protestant reformation that, to a large extent, drove the cultural changes necessary for the development of the modern world.

Just as Luther believed that the medieval Catholic Church extracted wealth by selling pieces of paper that reserved your place in heaven, 1517 believed that the modern university extracts wealth by selling pieces of paper that promise to reserve your place in the workforce.

Gibson and Strachman wanted to finance the heretics, and they had earned the right to try.

For five years, the pair had run the Thiel Fellowship, Peter Thiel’s $100,000 grants to teenagers who dropped out of college to start companies. These supposed failures of the academic world would go on to build generational companies including Ethereum, Figma, and Anthropic.

1517’s debut fund, a modest $20 million vehicle, has (as of January 2026) already returned 4.41x its initial capital in cash to investors, after about a decade. The total value of all of their investments stands at 9.65x. By any measure, this puts 1517 among venture capital’s top-performers, providing clear evidence that they know how to find alpha.

This is the story of how they got started, and what their success reveals about the market’s blind spots.

The Anti-Rhodes Scholarship

“The Thiel Fellowship was a challenge to two big norms: that college was the only right path for young people and that making a real and recognized contribution was something you did once you did what everyone else told you to do: go to school, get a job, and get experience.”

Danielle Strachman, GP at 1517

The Thiel Fellowship was imagined on a cross-country flight. On September 28, 2010, the night before TechCrunch Disrupt in San Francisco, Peter Thiel was flying from New York with Jonathan Cain, Luke Nosek, and Jim O’Neill. The conversation drifted toward his signature obsession, technological stagnation, the thesis that genuine progress had flatlined since the 1970s in every domain except computing.

Someone floated the idea of an “anti-Rhodes Scholarship”. What if you paid brilliant young people not to attend college, but to skip it?

The next day, Thiel announced the “20 Under 20” program onstage. Michael Gibson, who had been hired the day before to help Thiel teach a Stanford Law School course, was urgently pulled in to flesh out the concept. One week later, Danielle Strachman was hired to help build and run it.

The fellowship operated through the Thiel Foundation: $100,000 over two years, no equity taken, no strings attached. The first cohort of 24 fellows (expanded from the planned 20) was announced on May 24, 2011, chosen from roughly 400 applicants.

The establishment’s reaction was vicious. Larry Summers, the former Harvard president and Treasury secretary, called the fellowship “the single most misdirected bit of philanthropy in this decade”, a program to “bribe people to drop out of college.” Jacob Weisberg, editor of the Slate Group, dismissed it as “a white boy’s version of the NBA.” Vivek Wadhwa declared it had produced no notable successes. Critics pointed to survivorship bias, and to the irony that Thiel himself held two Stanford degrees.

Then the results started to come in.

• Laura Deming, 17 years old when she left MIT in the first cohort, founded The Longevity Fund and is credited with making anti-aging research a legitimate investment category.

• Paul Gu dropped out of Yale and co-founded Upstart, the AI lending platform that went public in 2020.

• Dylan Field, who left Brown in 2012, co-founded Figma, the design tool Adobe tried to acquire for $20 billion before Field took it public himself. He is now worth an estimated $5 billion.

• Chris Olah, also from the 2012 class, went on to co-found Anthropic, now valued at roughly $380 billion.

• Austin Russell dropped out of Stanford at 17 and built Luminar Technologies into a LiDAR company that debuted on the public markets at $3.4 billion.

• Ritesh Agarwal, the first Indian fellow, founded OYO Rooms, which grew to more than 330,000 rooms across 35 countries.

• Vitalik Buterin, who left the University of Waterloo in 2014, used his fellowship to develop Ethereum which today has a “market cap” of $235B.

Bloomberg finance researchers Aaron Brown and Richard Dewey assessed the program in 2025, and concluded that every other elite scholarship program in the world, combined, could not match the output of Thiel fellows by age 35. The cumulative value created by fellows’ companies is estimated to exceed $750 billion, with about 40 unicorns from roughly 290 participants. The result is a unicorn rate of about 14%, which dwarfs the venture industry’s baseline by an order of magnitude.

The Philosopher and the Principal

Gibson and Strachman arrived at the fellowship from different directions, and their complementary instincts have come to define 1517’s character.

The Philosopher

“I have no business doing what I’m doing. I thought I was going to be a professor of philosophy. Through a series of unlikely events, I found myself interviewing for a job with Peter Thiel.”

Michael Gibson, GP at 1517

Michael Gibson was born in 1977 and spent his twenties pursuing philosophy at NYU, the University of Chicago, and Oxford, where he enrolled in a doctoral program in ancient philosophy and moral theory. He never finished. He came to believe that academic life constrained the original thinking it claimed to cultivate, a conclusion he describes as his “academic apostasy.” After Oxford, he worked as an editorial assistant at MIT’s Technology Review, covering quantum computing and emerging technologies, and published essays in The Atlantic, National Review, Forbes, and City Journal. His blog posts caught Thiel’s attention.

Gibson’s book, Paper Belt on Fire, published in November 2022, lays out the intellectual architecture behind 1517. The thesis is that a corridor stretching from Washington to Boston, the “Paper Belt”, sustains itself by printing paper: money, laws, media, diplomas. Universities, he argues, are the most corrupt node in the system, operating a credentialing mechanism divorced from genuine talent. He cites research by Northwestern’s Benjamin Jones showing that the age of peak creativity is being pushed later because institutions take longer to bring minds to the frontier of knowledge. The book is also part memoir, woven through with his investigation into whether his father (who died under mysterious circumstances when Gibson was 16 months old) had CIA connections.

The publishing process added fuel to the fire. About a third of the roughly 20 publishers Gibson’s agent approached rejected the manuscript because, in their words, “Peter Thiel is evil”. Another third said some version of “I went to Yale. I love my English major”. The rest simply passed.

The Principal

“Danielle, the foundation has lost their minds. They’re running this new program, you have to get over here.”

Lindy Fishburne, Senior Vice President for Investments at the Thiel Foundation

Danielle Strachman came from the world of K-12 education. She had originally planned a career in neuropsychology before pivoting to teaching. Around 2000, she founded Heightened Learning, a private tutoring practice in San Diego organized around students’ interests and emotional needs. The work led her into homeschooling communities, where she began teaching creative writing in a cooperative run by Christine Kuglen. She was transformed by what she saw; the agency, the curiosity, the sheer aliveness of children who hadn’t been processed through conventional schooling.

Around 2007, Strachman and Kuglen co-founded Innovations Academy, a K-8 charter school in San Diego built on student-led, project-based learning and what was then a pioneering social-emotional curriculum. They wrote a 400-page charter petition and went through the Charter Launch accelerator. Strachman served as Director of Student Growth for the school’s first two years. (The school now serves roughly 400 to 450 students and continues to operate; she remains on its board.)

Lindy Fishburne at the Thiel Foundation, who knew of her charter school work, called with what might be the best recruiting pitch in Silicon Valley history: “The foundation has lost their minds. They’re running this new program, you have to get over here.” Strachman interviewed the following week, started the week after, and became Program Director within a month. As Founding Director of the Thiel Fellowship, she oversaw the first five cohorts, the classes that produced Buterin, Field, Russell, Deming, Gu, Agarwal, and Olah. She built the Thiel Summit community events, which drew roughly 2,000 young entrepreneurs, and created programming for applicants who weren’t selected.

Her business card at 1517 reads “professional fairy godmother”. Along with Gibson, she has developed a vocabulary for the intuitions that guide her judgment of young founders. There is “dog on a leash energy”, the quality of straining visibly against constraint. There is “hyperfluency”, the ability to geek out with experts in a domain and then turn around and explain it to a civilian. And there is what they call the “crazy, crazy awesome” spectrum, which is an admission that it takes years to know whether a founder is insane or brilliant, and the wisest thing an investor can do is stay in the room long enough to find out.

Starting your own renegade VC fund? You do the investing, let us do the admin

Three Hundred Emails

In June 2015, Gibson and Strachman left the Thiel Foundation and went to pitch Thiel over breakfast. The presentation was a single page, illustrating a hypothetical of what the fellowship’s $100,000 grants would have returned had they been investments. Thiel committed $4 million on the spot.

They wrote 300 emails to family offices and individual investors, and closed Fund I at $20 million with 30 limited partners in roughly eight months. The very first check 1517 ever wrote was a $1,000 micro-grant, sent to a teenager in a Boston cafe.

On October 31, 2017, the 500th anniversary of Luther’s theses, Gibson nailed a list of anti-education theses to the doors of university administration buildings. The fund published The New 95, declarations that included “Life in the U.S. begins with a 13-year mandatory minimum sentence: K-12” and “Higher education has become America’s national religion, complete with heaven and hell, salvation and damnation”.

The investment thesis was simple, they would back founders without undergraduate degrees at the earliest possible stage. First checks of $50,000 to $1 million into companies that had raised less than $1.5 million, targeting 7 to 10 percent ownership. Agnostic to sector (software, hardware, deep tech, biotech) but insistent on the founder profile. Starting around 2018, the firm expanded to include “renegade scientists” who had abandoned academia to focus on frontier technology like rockets, fusion, quantum computing.

The firm has since grown through four vintages: Fund I at $20 million in 2015, Fund II at $24 million around 2020, Fund III at $80 million in early 2022, and a Fund IV currently in fundraising. The team has expanded to around 14 people, including partners Zak Slayback, who left the University of Pennsylvania in 2014, and Nick Arnett, who never attended university at all and founded a nonprofit at 18. The firm also deploys “operatives”, field agents embedded in cities like Los Angeles and Austin who find talent in communities of young makers before anyone else knows to look.

The Pillars of Fund I (So Far)

1517 Fund I holds 34 unique investments. Four of them have driven most of the returns so far, and each tells a different story about what it means to be the first believer.

Loom

“Danielle and Michael were our biggest early believers. They met with us weekly, gave us feedback, and wired us money before the deal docs were done as our pre-seed lead so that we wouldn’t run out of money 48hrs later. Can’t honestly say Loom would be a company if it hadn’t been for their belief.”

Joe Thomas, Cofounder and CEO of Loom

Co-founders Joe Thomas, Shahed Khan, and Vinay Hiremath started a usability testing tool called Opentest in 2015. After six months of failed launches and no traction, running on borrowed money and maxed-out credit cards, the three were nearly out of runway. In a last-ditch move in June 2016, they repurposed Opentest’s screen-recording feature into a standalone Chrome extension called Openvid and launched it on Product Hunt. Within 24 hours they had 3,000 signups, more than the previous six months combined. The product became Loom, an async video messaging tool that lets anyone record their screen and face, then share the result as a link. Hiremath, a college dropout from Illinois who had moved to Palo Alto to work as an engineer, was 1517’s kind of founder. The firm led the pre-seed round, becoming Loom’s earliest institutional backer.

The pandemic turned Loom from a useful tool into essential infrastructure for remote work. The user base exploded from 4 million to over 14 million in two years. Sequoia, Kleiner Perkins, Andreessen Horowitz, Coatue, and Slack all invested. A 2021 round valued the company at $1.53 billion. On October 12, 2023, Atlassian announced it would acquire Loom for approximately $975 million in nearly all cash, its largest acquisition ever, with 25 million users and 200,000 paying customers at the time of the deal.

Lambda

“1517 believed in me first.”

Stephen Balaban, Founder and CEO of Lambda

1517 was an early seed investor in Lambda, founded in 2012 by Stephen and Michael Balaban, participating when the company was valued at roughly $4 million. Lambda pivoted from deep learning workstations to become a leading GPU cloud and AI infrastructure provider, positioning itself as an Nvidia-aligned alternative to hyperscale cloud providers. By 2024, revenue had reached approximately $425 million with 70% year-over-year growth, serving 10,000+ customers including AI labs, Fortune 500 companies, and government agencies.

A $1.5 billion Series E in November 2025 valued Lambda at $5.9 billion, with Nvidia investing directly alongside TWG Global, ARK Invest, and G Squared. It is 1517’s largest outcome and is widely expected to IPO in 2026. For Fund I, an early seed check at a roughly $4 million valuation that grew to $5.9 billion represents a potential return exceeding 1000x.

Deepgram

“Voice is the dark matter of enterprise data. I have a PhD in particle physics and worked two miles underground architecting systems to detect dark matter with deep neural networks. And I left particle physics to tackle what feels like a bigger and more tangible problem.”

Scott Stephenson, Founder of Deepgram

Scott Stephenson earned a PhD in particle physics from the University of Michigan, where his research involved building dark matter detectors two miles underground in China as part of the PandaX experiment. While working in the lab, he and his colleagues built a device to record audio around the clock as a log of their experiments, then realized the deep learning models they were using to analyze subatomic particle waveforms could be repurposed to analyze audio waveforms. When they looked for an API that could search through hundreds of hours of recordings, nothing adequate existed. Stephenson left his post-doctoral position in 2015 to found Deepgram, betting that end-to-end deep learning could outperform the legacy heuristic models Google and Amazon relied on for speech recognition.

1517 participated in a small 2017 round that placed Deepgram in Fund I’s portfolio, a tiny bet on a physicist building proprietary AI infrastructure for speech at a time when “voice AI” was not yet a recognized venture category. Nvidia and In-Q-Tel (the CIA’s venture arm) invested in the Series A. Tiger Global led the Series B. In the voice AI explosion of 2024 and 2025, enterprises rushed to deploy AI-powered voice agents, and much of the underlying technology ran on Deepgram APIs. In January 2026 the company raised $130 million at a $1.3 billion valuation, its second unicorn milestone for Fund I alongside Lambda. Stephenson was not a teenage dropout but a credentialed scientist who abandoned a prestigious academic career because he saw a problem the academy couldn’t solve at the speed the world needed.

Luminar Technologies

Austin Russell, a 2013 Thiel Fellow who dropped out of Stanford at 17, founded Luminar Technologies to build LiDAR sensors for autonomous vehicles. 1517 invested early. Luminar went public via SPAC in December 2020, opening at a market capitalization exceeding $7 billion and peaking at approximately $11 billion in early 2021. Russell briefly became one of the world’s youngest self-made billionaires at 25.

Unfortunately, this particular story does not have a happy ending. The stock lost over 99% of its value from its peak. Volvo terminated its supply agreement in November 2025, and Luminar filed Chapter 11 bankruptcy on December 15, 2025. MicroVision won the auction at just $33 million.

While 1517 Fund I is now 11 years old, it includes many success stories that are still in the process of playing out: Atom Computing in quantum computing; nTopology in advanced manufacturing design; FOSSA in open-source compliance; Xona Space Systems building a precision GPS alternative; CalWave Power Technologies in wave energy; and Kura, making AR glasses.

Across four funds, 1517 has made roughly 110 investments. More on those, later.

Beating the Benchmarks

The performance figures explain why 1517 has been able to raise progressively larger funds despite holding such a provocative thesis and avoiding the “obvious” deals.

Fund I’s internal rate of return is 38.86%. The Cambridge Associates benchmark for the top 5% of 2015-vintage venture funds is 34.99% (as of 2025). The total value to paid-in (TVPI) multiple of 9.65 times is roughly three to four times higher than even 90th-percentile funds from comparable vintages.

The most striking figure in today’s liquidity-starved environment is the distributed-to-paid-in (DPI) ratio of 4.41x. Their Limited partners have already received, in actual cash, more than four times the capital they committed, with substantial unrealized value remaining (roughly another 5.24x). Industry research consistently shows that even top-quartile venture funds often struggle to distribute 2x cash to their investors, while time to full liquidity is stretching from 16-20 years. These results, in roughly a decade, are excellent.

The secret to 1517’s success is that there were virtually no other institutional investors in the room. The so-called “tier-1” firms don’t send partners to coffee shops to talk to teenagers, as Gibson and Strachman have. As their portfolio companies have grown, those small initial checks produced have multiples that are very difficult for larger funds to achieve in more competitive deals for more “legible” investments.

And, more importantly, Gibson and Strachman gave these founders a chance when the industry as a whole would not. Without the early belief of true adventure capitalists, they may never have found their way to building a company, or they might have ended up pivoting to a worse version of their idea which could fundraise more easily.

Manifesting Science Fiction

“Younger and younger people are working on harder and harder problems and getting to the frontier of knowledge. The best is definitely yet to come.”

Danielle Strachman, GP at 1517

1517’s portfolio is growing with founders who combine the dropout audacity of the Thiel Fellowship with the frontier-science ambition of the renegade scientists.

In each of the examples below, 1517 invested in the founders ahead of anyone else, facilitating their path into programs like the Thiel Fellowship or their connection to later investors.

Positron AI

Thomas Sohmers, a 2013 Thiel Fellow, dropped out of high school at 17 to found chip startup REX Computing. He went on to serve as Principal Hardware Architect at Lambda (a 1517 portfolio company), then Director of Technology Strategy at Groq, before co-founding Positron AI in 2023 with Chief Scientist Edward Kmett. They recruited Lambda’s former COO Mitesh Agrawal as CEO. Their product, Atlas, is a U.S.-manufactured inference system delivering roughly 3x more tokens per watt than Nvidia GPUs.

1517 has participated in every round. In under two years Positron crossed a billion dollars in valuation, with strategic backing from the Qatar Investment Authority and Arm. Customers include Cloudflare, and the next-generation Titan system, built on Positron’s custom Asimov silicon and designed to run 16-trillion-parameter models, targets tape-out in late 2026.

Mach Industries

Ethan Thornton started building weapons prototypes in a high school workshop, dropped out of MIT at 19, became a Thiel Fellow on the recommendation of Strachman and GIbson, and founded Mach Industries in 2023 to build a vertically integrated industrial base for unmanned warfare. The product line includes Viper, a jet-powered VTOL strike aircraft reportedly 300x cheaper than traditional UAVs; Glide, a high-altitude precision glider; and Stratos, an extreme-altitude sensing satellite. Mach was selected by the Army Applications Laboratory to develop a vertical takeoff cruise missile, and has opened a 115,000-square-foot factory in Huntington Beach, the first node in a planned network of distributed manufacturing facilities.

1517 was the first money in, followed by Champion Hill Ventures. Sequoia then wrote its first-ever defense check into the seed round. Bedrock, Khosla Ventures, and Sequoia have since pushed total funding to roughly $185 million at a $470 million valuation.

Rainmaker

Augustus Doricko, a UC Berkeley physics dropout and 2024 Thiel Fellow (again on the recommendation of Gibson and Strachman, founded Rainmaker in 2023 to modernize cloud seeding, a technique invented in 1946 but historically imprecise and hard to verify. Rainmaker deploys autonomous drone fleets guided by numerical weather modeling and radar validation to seed specific clouds with measurable results. Now 25, Doricko leads 120 employees and holds contracts with the Utah Department of Natural Resources, Colorado, and Santa Barbara County. His biggest test is underway, generating snow over Utah’s Bear River Basin to help rescue the shrinking Great Salt Lake, which has lost over 800 square miles of surface area in four decades.

Following their initial check, 1517 invested in the seed round alongside Garry Tan and Balaji Srinivasan. Chris Sacca’s Lowercarbon Capital led the Series A, with Naval Ravikant also participating, bringing total funding to $31.3 million.

Trilobio

Roya Amini-Naieni led synthetic biology competition teams in high school, founded a biohacker space at Harvey Mudd College, and received a $100,000 grant from Alexis Ohanian’s 776 Foundation, all before co-founding Trilobio in 2021 with Maximilian Schommer. They developed modular robots called Trilobots paired with Trilobio OS, a no-code platform that lets scientists enter experimental protocols as naturally as writing a lab notebook, then walk away while the machines execute every step. An estimated 77% of biologists cannot reproduce their own or others’ research. Trilobots are designed so any protocol run on one system replicates exactly in any Trilobio-enabled lab worldwide.

Following 1517’s investment, Initialized Capital led the oversubscribed seed round in May 2025, with Argon Ventures and Lowercarbon Capital participating. The company is early-stage, but sits at the convergence of AI-driven drug discovery, the synthetic biology boom, and a growing recognition that lab infrastructure has not kept pace with computational tools.

There’s no venture industry trend to connect Positron, Mach, Rainmaker, and Trilobio. Instead, they all fit an enduring thesis on founder quality, proven across 15 years. Each was started by someone in their late teens or early twenties. Each founder chose to learn by taking action, rather than by seeking credentials. Each is working on problems that sound like science fiction (advanced silicon, autonomous weapons factories, drone-piloted rainfall, robotic biology labs) yet each has attracted serious institutional capital (Sequoia, Khosla, Lowercarbon, Initialized) within months of 1517’s early check.

1517’s strategy has remained consistent across the decade: arrive first, invest early, let the market catch up.

The Anti-Establishment Educational Institution

“At some point in the last fifty years, our culture flipped. Dedication to the truth became the counterculture. The establishment became denial. For us as a venture capital fund, the truth became profitable.”

Michael Gibson, GP at 1517

The fund describes itself as “technically a venture capital fund, but we like to think of ourselves as an anti-establishment educational institution.” This is more than branding.

The Medici Grant program, named after the Renaissance family’s patronage of art and science, distributes $1,000 no-strings-attached grants to teenagers, college students, and dropouts working on passion projects. Applicants submit a five-minute Loom video. No equity is taken, no intellectual property claimed, no reporting required. More than 3,000 of these micro-grants have been issued. Phoebe Yao received one and went on to raise $4.5 million for her company Pareto.

The Invisible College program, named after the 1640s precursor to the Royal Society, provides $50,000 investments to independent young scientists and founders to run experiments that might become products. At least one founder must lack a college degree.

The community events trace back to the original Under 20 Summit that Strachman created at the Thiel Fellowship, the first of which was held at Mission High School in San Francisco on July 14, 2012, with more than 150 attendees. The Escape from Captivity summit in July 2022 marked the 10th anniversary. The firm runs teen founder coffee hours, city meetups, something called the Santarchy Ball, and a 1517 Flux Cohort launched in 2024.

All of this serves the central insight that Gibson and Strachman carried out of the Thiel Fellowship: traditional credentials (GPAs, test scores, Ivy League pedigrees) are poor predictors of entrepreneurial success. Character, obsessive curiosity, and what Strachman calls “dog on a leash energy” matter far more. The broken credentialing system misprices talent, and a mispriced market is exactly where a small, contrarian fund can generate alpha.

The Medici Family of Venture Capital

1517 is an unusual firm, built on an enduring philosophical conviction rather than a cyclical market thesis.

Gibson and Strachman spent five years inside the Thiel Fellowship watching young people without credentials build billion-dollar companies when the establishment insisted it couldn’t be done. They turned that observation into a fund, named it after history’s most famous challenge to institutional paper authority, and have proceeded to generate returns that place them among the top-performing firms of any vintage year.

Investing at the earliest possible stage in founders the rest of the industry routinely ignores (teenagers, dropouts, people without the credentials that signal “safe bet” to conventional VCs) 1517 accesses a talent pool with virtually no competition. Indeed, every investor who passes on a young dropout because they lack pedigree or experience is leaving money on the table.

1517’s performance suggests the pile of money left on that particular table was, and still is, very large.

As Strachman once put it, with the cheerful extremism of someone who has been vindicated by outperformance:

“In the future, I want to be funding 11-year-olds. The world won’t be ready, but I will be.”

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“We find for the overall sample, that the mean company-level return from IPO exits is 209.5 percent and the median return is 108.8 percent. By comparison, the mean return for M&A exits is 99.5 percent and the median return is −32.1 percent. The substantially lower returns for M&A exits are consistent with the concerns expressed by industry observers and prior academic work which has viewed IPOs as the primary vehicle of VC wealth creation.”

The Decline in Venture-backed IPOs: Implications for Capital Recovery (2013), by Susan Chaplinsky and Swasti Gupta-Mukherjee

Historically, public markets have been the primary customer of venture capital, offering a well-capitalised destination for the most successful venture-backed companies.

Unfortunately, that relationship is breaking down.

Exits by IPO are near historical lows, and post-IPO performance for venture-backed exits is often dismal. Combined with the influx of new (and generally less finance-literate) managers over the same period, there’s a real risk the industry might forget that handing great companies off to public market investors (for a large profit) is really pinnacle of the strategy.

All great companies eventually go public.

So, does venture capital still produce great companies?

In this article, we’ll look at the fundamentals for venture-backed IPOs, and how that relationship might be mended, via four main questions:

• Why do companies go public?

• When do companies go public?

• What stops companies going public?

• Does size matter pre-IPO? i.e. is it better to stay private for longer?

Why Do Companies Go Public?

Cost of Capital

Investors often talk about the range of challenges faced by public companies: stock price volatility, short sellers, compliance and reporting requirements… None of it sounds particularly fun for a young company that enjoys the flexibility offered by private markets.

However, as companies mature, they inevitably run into a problem with the “cost of capital”. That is, the amount of dilution they must accept to raise money, or the terms associated with any debt. Private markets have the highest cost of capital, because of the risk inherent in their opacity. For larger companies with greater capital requirements, this quickly becomes problematic.

Public companies, on the other hand, have a low cost of capital. While the standards for a public company are relatively high, and the transparency can feel uncomfortable, it means investors and lenders can better understand company health which translates into more appropriate terms.

The tipping point, where going public begins to make sense, is when most of the risk (which private market investors like, but public markets do not) has been removed from a company. Usually this implies growth is decelerating while economics are improving, as the business becomes more stable. There’s a misconception that this makes public markets unsuitable for innovative companies, or that you must be (near) profitable to IPO. Neither is true.

“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. Finally, we show that firms’ borrowing costs conditional on their risk drop after going public.”

Access to Capital and the IPO Decision: An Analysis of US Private Firms (2024), by Andres Almazan, Nathan Swem, Sheridan Titman and Gregory Weitzner

Importantly, the lower cost of capital and the “burdensome” reporting requirements are directly connected. You cannot have one without the other, and this is actually an ideal configuration. The opacity and illiquidity of private markets give companies room to experiment without being punished for short-term failure. The transparency, scale and liquidity of public markets, on the other hand, offer a more efficient and meritocratic environment for companies that are larger and more mature.

For example, SpaceX is in the process of gearing up for an imminent IPO. It’s able to do so because a sufficient amount of risk has been removed from the business, and it needs to do so because raising from private markets has become a constraint.

“There’s a lot more capital available in the public markets than private. It might be 100x, but it’s way more than 10x. [...] Speed is important. I just repeatedly tackle the limiting factor. Whatever the limiting factor is on speed I’m going to tackle that. If capital is the limiting factor then I’ll solve for capital. If it’s not, then I’ll solve for something else.”

Elon Musk, Founder of SpaceX

Finally, this has obvious implications for those who frame giant private rounds as “effectively an IPO without going public”. This is clearly not the case, as even when they raise tens of billions, private companies do not undergo anything like the same level of scrutiny. Their incentives are quite different, as private markets continue to emphasise risk-taking behavior to drive growth, and thus the outcomes are different also.

“The very act of dumping hundreds of millions of dollars into an immature private company can also have perverse effects on a company’s operating discipline. The only way to use the proceeds of such a large round is to take on massive operating losses. Historically, as a company neared an IPO level of revenues (say $50-$100mm), investors would expect convergence toward profitability. As these late-stage private companies digest these large fund raises, they are pushing profitability further and further into the future, as well as the proof that their business model actually works.”

Investors Beware: Today’s $100M+ Late-stage Private Rounds Are Very Different from an IPO, by Bill Gurley

Acquisitions

Another reason to go public is the desire to consolidate a leading position in a particular category through strategic acquisitions. Indeed, a survey of CFOs at recently-public companies in the post-dotcom era found that access to capital to drive acquisitions was the largest driver of IPO activity, reflecting the heavily competitive environment at the time.

Going through an IPO enables accelerated acquisitions via two means: firstly, through the capital raised in the IPO itself. Secondly, by converting to liquid stock the acquiring company suddenly has a much more attractive “currency” for stock-based transactions. It’s relatively common for acquisitions to include stock (about 30% of cases), particularly in ‘acquihire’ instances where the acquiring company wants to motivate talent with a stake in the acquiring company.

“We analyze post-IPO acquisition activity of IPO firms and find that there is a high incidence of newly public companies participating in mergers and acquisitions. We document substantial acquisition activity for IPO firms starting as early as their first year after the IPO. Our most striking result is that over the first five years following the IPO, newly public firms spend more money on acquisitions of other companies or assets than they do on research and development or capital expenditures, or the two combined. This suggests that newly public firms grow more through M&A than through internal investment in R&D and CAPEX.”

Going Public to Acquire: The Acquisition Motive for IPOs (2006), by Ugur Celikyurt, Merih Sevilir and Anil Shivdasani

This seems likely to grow in importance, as public companies are more often acquiring startups for access to new technologies and knowledge-driven innovation, such as the recent spate of “reverse acqui-hires” in the LLMs category.

“Firms in highly technological industries, faced with pressure to innovate and looking to expand, are increasingly acquiring startups with little interest in other assets beyond their human capital resources.”

Startup Firm Acquisitions as a Human Resource Strategy for Innovation: The Acqhire Phenomenon (2013), by Jaclyn Selby and Kyle J Mayer

Liquidity

Last but not least, the inevitable need to provide liquidity for shareholders.

With acquisitions being the main alternative to going public, there are a number critical reasons why an IPO is usually the preferred path to liquidity.

Firstly, in an acquisition, it is implicit that the founder loses control of the company to the acquirer. If the company represents their life’s work, this will be unattractive relative to an IPO where they will retain control and can steward it through the next chapter in public markets.

Secondly, there is typically greater information asymmetry between a private company and public market investors than there will be between a private company and a strategic buyer. This means, from the limited perspective of share price, and assuming normal market conditions, a company should be able to get liquidity at a more attractive share price in public markets than through acquisition. Acquirers also tend to have more pricing power, as there will be a small pool of interested buyers, producing a less competitive process relative to the efficiency of public markets.

“In our analysis of IPOs, we have taken the stance that pre-IPO owners’ prime objective is to establish a liquid market for their shares, as a means of maximizing the market value of their wealth. The owners attempt to accomplish this objective by optimally manipulating critical variables including and especially share retention, underpricing, and a lockup restriction.”

Pursuing Value Through Liquidity: Share Retention, Lockup, and Underpricing in IPOs (2003), by Steven Xiaofan Zheng, Joseph P. Ogden and Frank C. Jen

In recent years the pressure to reach a liquid endgame has diminished slightly, as secondary transactions have become more common. In the first three quarters of 2025, the total secondaries volume hit $94.9B, compared to $104.7B from IPOs and $107.1B from acquisitions, according to data from Pitchbook.

However, questions remain:

• How many of these transactions are at steep discounts to the last marked price of the companies or portfolios involved?

• How much of the total value is concentrated in employee-secondaries for the most obvious companies, like Stripe, SpaceX, Anthropic, OpenAI etc?

• How much of the demand is for companies with an imminent IPO, as is true for 8 out of the top 10 on Setter’s ranking of secondary market demand?

• Generally, do current volumes persist in a recovered market where great companies may begin exiting sooner, and GPs have fewer bad assets to offload?

Indeed, the rise of secondaries (particularly PE activity) is often connected to troubled times in venture capital, with patterns repeating across historical cycles.

“Of course, economic turbulence is not positive and investments could suffer in this environment. However, the performance of PE during these past recessionary periods demonstrates the opportunity that fund managers have to capitalise on declining valuations and distressed opportunities that often emerge during downturns.”

The secret behind private equity’s strength during the dot-com crash and the great recession, by Blazej Kupec and Jason Feder

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When Do Companies Go Public?

In a basic sense, the timing of an IPO is typically the point on a spectrum at which the risk is no longer appropriately priced by private markets. Where the business is sufficiently and obviously strong enough that it would see a net benefit from the transparency imposed by public markets.

However, there are two other influences on when a company might decide to go public, one internal and one external.

Productivity Shocks

“In our model, two firms, with differing productivity levels, compete in an industry with a significant probability of a positive productivity shock. Going public, though costly, not only allows a firm to raise external capital cheaply, but also enables it to grab market share from its private competitors.”

IPO Waves, Product Market Competition, and the Going Public Decision: Theory and Evidence (2012), by Thomas J. Chemmanur and Jie He

A “productivity shock” can be considered as a major step-up in capability in a particular technology, unlocking real economic value. It significantly improves the offering of the company, with meaningful consequences for revenue and profitability, providing a springboard into public markets.

For example, OpenAI’s release of GPT-3.5 in 2022 was a major turning point for technology, but it did not constitute a productivity shock. At that point, LLM chatbots were a fun toy with obvious future potential but little immediate utility.

Since then, we’ve seen a number of AI-related productivity shocks.

• Arguably, DeepSeek’s R1 model, released in January 2025, was the first hint at a productivity shock, by significantly driving down the cost of inference with fairly sophisticated models.

• The next (minor) productivity shock was the release of “Nano Banana” by Google, in August 2025. For the first time, image models were accessible and accurate, creeping into the domain of professional photography (e.g. product photos, fashion catalogue images, headshots).

• With coding agents it’s harder to pick a specific moment; the ability to write code with an LLM has been improving steadily since day one. Recent releases like Claude 4.6 Opus and GPT-5.3 Codex may be looked back on as the tipping point at which much artisanal programming (particularly for front-end) became obsolete.

Today, both Anthropic and OpenAI are both rapidly tapping new veins of potential productivity, with Excel agents, financial agents, legal agents, and more. As both companies reportedly aim to go public within the year, it’s clear they are both looking for (and likely on the verge of) some new productivity shock.

IPO Windows

You will often hear private market investors discuss the need for an “IPO window”, but it’s never entirely clear what that means.

Under the interpretation that an IPO window is a period during which public markets seem healthy, that describes most of the last three years, and yet IPO activity has been relatively subdued. A more honest interpretation is that an IPO window is simply a time in which there are many IPOs, which isn’t really helpful; a private market investor calling for more IPOs is like a baker calling for more bread.

Here’s the slightly uglier truth: an IPO window is appealing because it’s easier for lower quality companies to go out with a herd. Few want to be the first out, but plenty will pile into a broad surge (like the ~1000 companies that exited in Q4 1999–Q1 2000 and Q2–Q3 2021) where going public becomes easier.

“The IPO market has significant time variations over time and IPOs issued during the high-volume period are more likely to have worse performance on average than those issued during other periods.”

Essays On Ipo Cycles And Windows Of Opportunity (2021), by Meng Chen

If you’re the CEO of an outstanding company, in great financial health, you can IPO virtually whenever you like and the market will reward you with less competition for attention. However, if you’re not actually doing that well, and your timeline may be accelerated with pressure to create liquidity, you can squeeze out in a crowd if you play into the right narrative. A greater number of recent IPOs lowers the information cost of going public as there’s much more to benchmark against. You’re less likely to attract detailed scrutiny, as investors simply have too much volume to carefully analyse every opportunity in what is likely a less rational market already. .

Indeed, hot IPO markets (IPO windows) are often triggered by a few excellent companies going public, followed by a swelling stream of exits of decreasing quality. As this becomes obvious over the following months, with more time to absorb the actual performance of these companies, the market will freeze and liquidity will diminish.

What Stops Companies Going Public?

Extreme Idiosyncracy

As described above, private markets price-in large amounts of risk, because of the intrinsic opacity and information asymmetry. Early in a startup’s life, that’s a reasonable cost of doing business. Later on, as the company matures and produces more predictable financial performance, it becomes the burden which makes private capital feel expensive.

However, some companies remain intrinsically risky for a long time, by the very nature of their activity. A good example is SpaceX. Up until recently, with the proving of Starship and the growing profitability of Starlink, SpaceX seemed like an extremely risky company and so required private investors to keep the business going.

However, examples of sustained idiosyncratic risk more than 10 years into the life of a company are extremely rare. Today’s frontier companies, Anthropic, OpenAI and Cohere, are considering IPOs on much shorter timeframes as their idiosyncratic risk is much lower (it’s broadly accepted that AI is a huge opportunity), even if their systematic risk (exposure to a speculative bubble) is much higher.

Financial Health

“The roles have reversed. In the dotcom bubble there wasn’t much VC money, and companies went public to get the stupid money at crazy prices. Now you get the crazy prices privately, and if you go to the public market you have a reality check.”

Martin Shkreli, Founder of Gödel Systems

Once upon a time, venture-backed companies would go public somewhere between 5 and 8 years. The central question of venture capital was whether or not a startup could scale into a large, mature business with positive cash flow and sustainable competitive advantages to offer an attractive proposition to public markets.

As private markets have seen greater deregulation over the last 50 years (most notably via NSMIA, in 1996), venture capital has become bloated with the growing capital inflows. On one hand, this is a huge positive for entrepreneurship (more money!), but on the other hand it has warped incentives and outcomes significantly.

Today, venture-backed companies go public somewhere between 12 and 14 years, in large part because large growth rounds give VCs somewhere to put all of this capital. See, for example, the Series L of Databricks in December 2025. Generally speaking, private market investors want growth regardless of risk, and with less concern for economics. Exposure to these incentives over long periods of time risks creating brittle businesses with high growth and lofty valuations and an unusual amount of risk.

Indeed, the brand of “founder friendliness” that has developed alongside this new funding environment has explicitly encouraged founders to embrace more risk in order to drive growth.

“The VCs get the founders to pursue high-risk strategies like blitzscaling, underwater expansion, regulatory entrepreneurship, and venture predation. In compensation for the risk they bear, the founders receive private benefits. They can cash out in secondary sales, indulge in a little self-dealing, avoid public criticism and lawsuits, and benefit from a soft landing.”

Risk-Seeking Governance (2023), by Brian J. Broughman and Matthew Wansley

The outcome is essentially that valuation growth is held-back in private markets, under much looser conditions, producing businesses which are much more valuable on paper but perhaps don’t really have the fundamental strength that a public market investor would expect. Thus, the IPO process can feel like an incredible hurdle, and many supposedly “IPO ready” unicorns from the last decade will simply never make it.

For those that make it out, they might do so at a lower price than their last private round, or they may see returns slip fairly quickly. Or both.

Preference Stacks

Finally, the other main issue which discourages IPOs is the ubiquitous use of preferred stock in venture capital transactions.

Over the lifetime of a company, each institutional funding round is likely to have at least a 1x preference, meaning that those investors are entitled to at least a 1x return on their capital in the event of a liquidity event. This downside protection doesn’t move the needle with successful exits, where there’s enough for everyone, but it becomes crucial if the value of a company slips.

In an IPO, it’s typical for all share classes to be converted to common stock. All preferences are wiped out, and thus downside protection evaporates. For growth investors who contributed huge sums of capital to an IPO, this becomes a major headache if the company slips significantly from the marked price.

In some cases, investors will include terms which provide downside protection in the event of an IPO, such as guaranteed return or IPO veto provisions. Similar to preferred stock, these clauses structurally shift value towards protected investors, away from common stock holders. Here, it is the founders and employees who may feel discouraged to go public until the company is in better shape, as their shares are effectively underwater.

“The postmoney valuation metric overvalues all unicorns in our sample, but the degree of overvaluation varies dramatically. The average unicorn in our sample is overvalued by 50%. There is a large variation in the degree of overvaluation: while the 10 least overvalued companies are overvalued on average only by 13%, the ten most overvalued companies are on average overvalued by 170%.”

Squaring Venture Capital Valuations with Reality (2017), by Will Gornall and Ilya A. Strebulaev

The Scale Factor

It’s certainly true that going public became more expensive in the post-dotcom era, as regulation drove up compliance costs. The most significant update to requirements, Sarbanes-Oxley, was designed to mitigate the risk of fraud by companies like Enron, and many other bad apples that snuck out in the dotcom IPO window.

However, while the increased cost has raised the minimum threshhold (companies must be able to afford the process), it does not make the case that bigger is necessarily better. The shift to fewer, larger IPOs has largely been attributed to the expansion of private markets, artifically and cyclically suppressing the cost of capital.

It’s easy to look at post-IPO performance data and draw the conclusion that IPOs of companies with more revenue will have deliver stronger returns.

As a result, many VCs talk about the challenge of delayed exits in terms of the volume of revenue a company must achieve in order to go public. This is an unfortunate misread, rooted in venture capital’s obsession with revenue as a proxy for success.

Public markets want quality businesses, which means solid growth, healthy margins, large markets and strong competitive positioning. Scale of revenue has a loose correlation with “quality” but it is far from causal. Bigger is not necessarily better.

“According to this analysis, the larger you are, the better your metrics on essentially every dimension. This is not a surprise for one simple reason: selection bias.

Companies with billions of dollars of ARR implicitly have leadership positions in large markets supported by durable growth and strong unit economics that have allowed them to ‘grow out of’ the smaller buckets (and quite quickly). Smaller companies are less valuable due to business quality, not due to scale. If you’re a smaller company and not growing fast, you might get ‘stuck’ in the lower buckets.

Based on the chart above, it might be reasonable to assume that there is a ‘size premium’ for larger SaaS companies. Is that really the case? The short answer is no, not really. The chart below is a regression of revenue multiple vs. ARR scale. There is little correlation between scale and valuation multiple in the public markets: R-squared = 0.11. We’ve removed Adobe and Salesforce from the chart for the sake of visibility, but even when including those, the correlation is still only R-squared = 0.02. That said, the trend line is up and to the right – a symptom of the selection bias mentioned in the prior paragraph.”

2024: When to IPO in the Age of Uncertainty, by Alex Clayton and Cathy Choi

Unfortunately, with scale as their only measure of success, many venture capitalists believe that companies must simply be larger to be more attractive. Thus, they end up compounding the problem by focusing even more aggressively on that one dimension, to the detriment of others.

This hints at the truth of venture capital’s exit problem, which is not that the bar to go public has risen, but rather that venture-backed companies are fundamentally weaker.

Projecting this “growth at all costs” revenue obsession onto public markets has had a number of toxic consequences:

• Delayed exits

• Public market stagnation

• Slipping post-IPO performance

• Rising rates of fraud.

• Bias toward rapid scalability, at a cost to innovation

Indeed, the final point is probably the most concerning.

In overemphasising the importance of scale, venture capital has prioritised business models and technologies that are rapidly scalable — most obviously characterised by the 2010s era of SaaS. In a decade where the cost of capital was remarkably low, due to low interest rates, there was remarkably little technological progress.

This has obvious connections with the problem of financialsiation.

“The VC business model favors innovations that promise large returns in a medium time frame with minimal risk. Such criteria necessarily deprioritize large swaths of socially valuable innovations with longer, riskier development timelines.”

Enhancing the Innovative Capacity of Venture Capital, by Peter Lee

IPOs Are the North Star for Venture Capital

Ultimately, venture capitalists need to remember that their fundamental goal is to generate returns, not to generate faster markups on larger pools of capital, even if their own LPs might appear confused by that at times. In this context, more companies heading for public markets sooner, and in better health, is the best outcome for everyone. Particularly for investors that may hold onto (some of) the public stock to enjoy the growth enabled by public market capital.

Similarly, we need to shift the debate away from exits as an end to the story for innovation, which clearly isn’t true. Many of the most obviously innovative companies (Amazon, NVIDIA, Meta, Apple) had early IPOs and obviously built incredible success stories in public markets.

"I’ve been very outspoken about staying private as long as possible. I don’t think it’s that necessary to do that. [Going public] is actually a valuable process. Having gone through a terrible first year as it made our company a lot stronger. You have to know everything about your company. It took us to the next level and we run our company much better now."

Mark Zuckerberg, Founder and CEO of Meta

Today’s anxiety about market dips seems fairly trivial compared to the post-dotcom crashes experienced by companies like NVIDIA and Amazon, which likely played a part in the incredible discipline that those companies operate with today.

If there is a moral goal to venture capital, beyond generating returns, it is to support the growth of innovation and economic prosperity. A huge amount of that happens in public markets, and the desire to claw that growth back into private markets is short-sighted. It’s not an environment that is conducive to long-term company health.

All great companies go public, and it is venture capital’s responsibility to provide a fertile environment for great companies at the earliest stages.

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“We keep our heads down and obsess over how we can help entrepreneurs build great businesses. We are consumed with generating great returns for our limited partners. We are the blue collar VCs that keep showing up every morning to get after it.”

Erik Rannala, Mucker Capital

When Erik Rannala and William Hsu opened their small Santa Monica office in 2011, venture capital’s center of gravity sat squarely in the ten-mile strip between Sand Hill Road and South of Market. The serious money lived in the Bay Area, and the serious founders moved there to get it. Los Angeles, for all its technical talent and cultural influence, was an afterthought.

Rannala and Hsu disagreed, and they named their firm after the people who proved that great things come from unglamorous work. Thomas Edison called his laboratory team “muckers” - collaborative inventors who got their hands dirty. That name became a statement about their firm, and the work they intended to do for entrepreneurs.

Their first institutional fund, a roughly $12 million vehicle raised in 2013, would go on to return more than $280 million from a single investment: Honey, the coupon-finding browser extension that PayPal acquired for $4 billion in 2020. That 23x return on the entire fund from one deal placed Mucker among the most successful micro-funds in venture capital history and validated an idea the establishment had been slow to accept: that world-class companies can be built anywhere, if the investors are willing to do the work.

Overall, our napkin math indicates Mucker Fund I returned somewhere between 43 and 53x cash on cash; i.e. at least $3m (net of carry) to an investor from a $100k cheque. This is the rarefied air of the 99.9th percentile.

This is the story of how they built it, and what the results reveal about where alpha actually lives in early-stage venture capital.

The Operators

“When you know that your investors have walked the operating road at a company, and then apply those operating principles of starting a business in their venture fund, it adds a different type of filter. I feel more comfortable taking the advice I get from the team and applying it in real-time.”

Allan Jones, Founder of Bambee

William Hsu spent years at eBay and AT&T, building and scaling products inside large organizations where shipping was the only metric that mattered. Erik Rannala worked at TripAdvisor during its high-growth years and later at Harrison Metal, where he studied the mechanics of early-stage investing from the inside. Both had seen how the best companies are actually built: not through decks and term sheets, but through the daily grind of product iteration, customer acquisition, hiring, and firefighting.

They believed a basic asymmetry existed in the market. Southern California had Caltech, UCLA, and USC producing world-class engineers. It had a deep bench of technical talent. And it had a fraction of the venture dollars per capita that the Bay Area commanded. Founders in Los Angeles were building real companies, but the institutional capital wasn’t showing up, or when it did, it demanded they relocate to San Francisco.

Rannala and Hsu saw this as a pricing error. The talent was there, and the ideas were there. What was missing was an investor who would stay local, get involved early, and do the unsexy operational work that helps create strong businesses.

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The Lab

“In addition to their nose for new opportunities, Erik and Will were capable of being hands-on, operationally oriented investors who could help portfolio companies solve problems, achieve product-market fit, and stimulate growth. This was most apparent in MuckerLab, the firm’s accelerator program for pre-seed opportunities, which it established as a precursor to an institutional fund. In many cases, the companies working with MuckerLab were only a founding team and an idea, relying on Mucker for initial funding, office space, and coaching as the companies worked to build or expand on an early product.”

TIFF Private Equity Team

Before the fund, there was MuckerLab.

Launched in 2011, the accelerator was Mucker’s proof of concept. For $100,000 to $175,000, Mucker took 10 to 15% equity in pre-seed startups and gave them office space in Santa Monica, access to a network of more than 300 mentors and specialists, and something harder to quantify: daily operational coaching from two partners who had actually built products and managed teams. The main objective was to help companies find product-market fit.

There were no pedigree filters, no insistence on Stanford degrees or well-known co-investors. Mucker evaluated founders on the quality of their thinking and the defensibility of their market, not on accolades from the past. In this sense, the accelerator was a deliberate inversion of the Valley model, where pattern-matching on credentials had become a substitute for good judgment.

The accelerator also served as a low-cost laboratory for the partners’ investment thesis. Every cohort generated data on which kinds of founders and markets produced results in Southern California. By the time Rannala and Hsu went out to raise institutional capital, they had something more persuasive than just a pitch deck.

The $12 Million Bet

The first institutional fund began raising in March 2013. It closed at roughly $12 million, with TIFF Investment Management serving as the anchor LP, committing 25% of the total.

At that scale, the economics were not exactly comfortable. The management fee on a $12 million fund does not support a comfortable lifestyle in Los Angeles, let alone two partners. Rannala and Hsu’s livelihoods depended entirely on carry, which meant they depended entirely on returns. For LPs and founders, however, that alignment is a feature rather than a bug.

The strategy was explicit in avoiding exposure to the froth of Silicon Valley. The fund targeted seed and pre-seed companies building defensible internet software and services in undercapitalized ecosystems, Los Angeles first among them. Investments ranged from accelerator checks to Series A rounds. The portfolio would be a few dozen companies, each treated as a long-term partnership, with Mucker providing hands-on support in product development, customer acquisition, business development, recruiting, and fundraising.

It was concentrated, conviction-driven investing in which the partners’ time was the most valuable asset they deployed.

The Sweetest Exit in Venture Capital

“Back in the early days of starting Honey, we needed funding, but what we needed even more was a thought partner to help us really understand and perfect our product-market fit. Mucker provided both the capital and the expertise.”

Ryan Hudson & George Ruan, Co-founders of Honey

In December 2015, a company called Honey Science Corporation entered MuckerLab. The product was a browser extension that automatically found and applied coupon codes at online checkout. It was a simple idea in a crowded e-commerce landscape, and it was exactly the kind of opportunity that most funds on Sand Hill Road would have scrolled past.

Mucker became the first institutional investor.

Honey scaled to 17 million monthly active users and roughly $200 million in annual revenue, raising about $49 million in total funding along the way. In January 2020, PayPal acquired the company for $4 billion.

For Mucker Fund I, that single exit returned more than $280 million - 23x the entire fund from one deal. For TIFF, whose look-through exposure to Honey across fund commitments and direct co-investments totalled approximately $1 million, the payout was $60 million; a 60x return on their total investment.

Honey’s outcome did more than generate spectacular numbers. It proved that a two-person firm in Santa Monica, writing small checks into companies the establishment had never heard of, could produce the kind of outlier return that defines a generation of venture capital.

Importantly, it validated the thesis that Rannala and Hsu had been quietly building since 2011: great companies can emerge from non-traditional hubs, and the investors who find them are the ones willing to show up before anyone else does.

Beyond the Headlines

Honey was the blockbuster, but Fund I’s portfolio extended well beyond a single exit. Across Mucker’s early investments, 97% of portfolio companies secured outside follow-on funding, reflecting the accelerator’s ability to turn raw startups into appealing prospects for later-stage investors. The broader roster included consumer, enterprise, and fintech plays that together raised billions in subsequent capital.

ServiceTitan

Founded in 2012, ServiceTitan built business management software for home services companies: plumbers, electricians, HVAC technicians, the trades that keep the physical world running but were still managing their operations on paper and spreadsheets. Mucker invested early. The company achieved unicorn status with a valuation exceeding $9.5 billion and raised billions in funding, becoming one of the defining enterprise SaaS companies to emerge from the Los Angeles ecosystem. In December 2024, ServiceTitan completed its IPO on the NASDAQ under the ticker TTAN, pricing shares at $71 and debuting with a market cap of approximately $8.9 billion.

Emailage

Emailage built fraud prevention technology that used email address metadata and machine learning to assess transactional risk. Mucker was among the early investors. The company raised roughly $55 million before LexisNexis Risk Solutions, a subsidiary of RELX, acquired it for a reported $480 million in early 2020. The deal closed weeks after PayPal’s acquisition of Honey, making the first quarter of 2020 a remarkable period for Mucker’s Fund I.

Retention Science

Retention Science, founded in 2012 in Santa Monica, was an early MuckerLab company that applied machine learning to a problem most e-commerce businesses were ignoring: keeping existing customers rather than spending more to acquire new ones. In April 2020, Retention Science was acquired by Newfold Digital Holdings Group (formerly Endurance International Group), adding it to the roster of Mucker portfolio exits that closed in early 2020 alongside both Honey and Emailage.

Besides the standout successes of Honey, ServiceTitan, Emailage, and Retention Science, Mucker Capital’s Fund I boasted several other notable exits that underscored its early prowess in seed-stage investing. These include Wallaby Financial, acquired by Bankrate in 2015 for its credit card optimization tech; Chromatik, bought by TakeLessons in 2016 to enhance music education platforms; Penango, snapped up by Google in 2014 for secure browsing tools; Blayze, also acquired by Google in 2014 for video coaching software; TaskRabbit, sold to IKEA in 2017 in a deal valued around $100 million; and Surf Air, which went public via SPAC merger in 2023 as Surf Air Mobility, focusing on sustainable aviation.

Taken together, the early funds demonstrated that Mucker’s approach (geographic contrarianism, operational depth, disciplined check sizes) could produce exceptional outcomes across a range of categories.

Compounding the Lesson

Fund I’s performance gave Mucker the credibility to grow without abandoning its model, and their second fund provided further validation. By 2016, the firm raised the $45 million Mucker III, which Hsu considered, with characteristic self-awareness, as similar to a Series A for the firm itself. Later vehicles, including a 2017 vintage, brought total cash raised to more than $150 million by 2023.

“Today, we are inside the tornado. The entrepreneur and venture capital market in LA has hit the hockey stick, and I no longer worry about whether we are going to be around 12 months from now. We’ve shifted our focus to scaling our business, just like a real company.”

William Hsu, Founding Partner at Mucker Capital

The accelerator model has remained the core. The fund size might have grown, but the approach has remained to find founders in undercapitalized markets, get in at the earliest stage, provide real operational support, and let the returns compound over time.

The co-investment structure has also proven durable. Mucker offered LPs preferred terms on follow-on rounds, giving them direct exposure to breakout companies like Honey. This amplified LP returns, mitigated J-curve risk, and built the kind of trust that leads to re-ups in subsequent funds. TIFF’s 60x return on its Honey exposure was a demonstration of how the co-investment model, applied with discipline, can transform a small fund’s economics for everyone involved. It is an actionable solution to the Reserves Paradox.

The Blue-Collar Blueprint

“They returned almost 5x the fund in the form of carry to themselves, which is life changing money for Erik and Will, and yet they are amongst the hardest-working GPs we have”

Michael Kim, founder and Managing Partner of Cendana Capital

Mucker’s story contains a set of lessons for emerging managers that are easy to state, but exceptionally difficult to execute.

1. An accelerator can serve as a low-cost laboratory for an investment thesis. MuckerLab allowed Rannala and Hsu to build a track record and generate deal flow before raising institutional capital. The accelerator was the proof of concept.

2. Small fund economics enforce a kind of discipline that larger funds cannot replicate. At $12 million, there is no room for a fee-driven lifestyle. The managers must generate real returns, which concentrates their attention on the only thing that matters: finding alpha.

3. Geography can be an edge. Mucker’s focus on Los Angeles was contrarian in 2011. It meant less competition for deals, lower entry prices, and access to a founder pool that mainstream VCs were ignoring. The bet has since been vindicated as LA emerged as one of the country’s most productive startup ecosystems.

4. Operational expertise can be a moat. Rannala and Hsu did not offer portfolio companies vague “value-add.” They sat in the room and helped build products, acquire customers, recruit engineers, and prepare fundraising materials. That hands-on work is why 97% of Mucker’s portfolio companies went on to raise further outside capital.

5. The relationship between GP and LP is itself an investment. The co-investment structure, the alignment through small fund size, the willingness to let performance speak for itself. These are not incidental features of Mucker’s model.

The Magic of “Mucking In”

Thomas Edison did not invent the light bulb alone. He built a team of muckers, people who worked in the laboratory alongside him, testing filaments and wiring circuits, doing the unglamorous daily work that turned ideas into products.

Erik Rannala and William Hsu chose the name deliberately, because they were not trying to get ahead by being the smartest investors on Sand Hill Road. They were trying to be the most useful investors in a market that the “smart money” had overlooked. They started with an accelerator in Santa Monica, raised $12 million from investors who believed in alignment over scale, and built a portfolio that returned 23x from a single deal while producing unicorns, IPOs, and dozens of successful exits across the rest.

The thesis was never complicated. Find the founders. Do the work. Stay close. Let the returns take care of themselves.

And it worked. Oh boy, did it work.

Build the next Mucker Capital with Odin

“Speculators may do no harm as bubbles on a steady stream of enterprise. But the position is serious when enterprise becomes the bubble on a whirlpool of speculation. When the capital development of a country becomes a by-product of the activities of a casino, the job is likely to be ill-done.”

John Maynard Keynes, The General Theory of Employment, Interest, and Money (1936)

Meme stocks. Crypto. Leveraged bets. Prediction markets. VCs white-knuckling $2B Seed rounds.

Savings at an all-time low, debt at an all-time high.

More than ever, capital feels impatient. Creating wealth has become a game of taking big shots with long odds, hoping to get lucky.

Gambling has infiltrated every part of the economy, top to bottom; institutional and individual. It has shaped how younger generations behave, and the direction of technology investment.

Welcome to Casino Culture.

The Roots of Financialisation

To understand Casino Culture, you must first understand how we arrived here. That’s primarily via a process known as “financialisation”, which describes the gradual dislocation of capitalism from productive activities within the economy.

In practice, financialisation means economic rewards shift to capital owners, away from those responsible for production. It is the opposite of industrialisation, during which investments in manufacturing and infrastructure increase, shifting economic rewards from capital owners to production.

The cycling between these two forces, in response to major technological revolutions, is a central topic of Technological Revolutions and Financial Capital by Carlota Perez. In the early stages of a market boom (the “installation period”) there is a heavy focus on financing capital requirements along with a layer of raw speculation. At some point, the market corrects (the bubble bursting) and the market enters a new productive phase (the “deployment period”) where the new technology is rolled out across the economy, broadly driving prosperity.

In a healthy economy, a full cycle seems to occur every 40–60 years or so, and these are broadly positive for driving human progress. However, the West is at around 50 years of unmitigated growth in financial services and industrial stagnation.

From a policy perspective, financialisation has been enabled by deregulation of the financial markets (e.g. The Nixon Shock, GLBA and NSMIA in the US), and money printing disguised as smart fiscal policy (“quantitative easing”). As a result, companies have been incentivised to seek success through financial engineering. Shareholders focus on metrics that proxy performance in the financial market, rather than economically productive activities.

Consider the recent decade of low interest rates, a period that could have seen unprecedented growth in manufacturing and infrastructure. Instead, financialisation manifested a generation of “asset-light” businesses, built to efficiently convert the abundant capital into inflated valuations and shareholder returns. Capital collected in pools, rather than flowing out to productive activities.

Going back to its roots, financialisation began with mercantilism and bullionism between the 16th and 18th centuries. At a time when international trade was usually paid for in precious metals, politics ended up favouring the gross accumulation of precious metals as the indicator of success, rather than a more active and productive trade economy. This shift, and the associated “zero-sum” thinking, underpin many of today’s economic woes.

“The great affair, we always find, is to get money... It would be too ridiculous to go about seriously to prove that wealth does not consist in money, or in gold and silver; but in what money purchases, and is valuable only for purchasing.”

Adam Smith, The Wealth of Nations (1776)

Profits Without Prosperity

The preference for accumulation is reflected in how public companies pursue market capitalisation as the metric of success. For example, the growing trend of distributing earnings via dividends, or spending cash on stock buybacks (repurchasing shares to reduce supply, inflating earnings per share (EPS) and stock price), rather than investing capital in productive activities like R&D or capital expenditure. Essentially, rather than engage in productive activities that generate more value, companies will manipulate reality via metrics and ratios to inflate their market cap.

While this activity makes sense to a certain extent, driving value for shareholders, it risks producing “hollow” companies with inflated valuations that ultimately erode the productivity of the wider economy.

“For U.S. manufacturers, the ratio of dividends paid to the amount invested in capital equipment increased from the low 20 percent range in the late 1970s and early 1980s, to around 40 percent to 50 percent in the early 1990s, to above 60 percent in the 2000s In other words, rather than reinvesting in capital, market pressures have forced companies to keep share prices high by paying greater dividends (or by undertaking share buybacks).”

The Greater Stagnation: The Decline in Capital Investment is the Real Threat to U.S. Economic Growth, by Luke A. Stewart and Robert D. Atkinson (2013)

We Had Robots, Once

Across the 2010s, outsourcing production allowed iRobot to shed fixed assets (factories) and inventory risk from its balance sheet, boosting return on net assets (RONA) and return on equity (ROE) by reducing the capital denominator. At the same time, cutting R&D expenses increased free cash flow, which was redirected into share buybacks rather than new product innovation. This inflated the company’s earnings per share (EPS), creating a feedback loop that drove up the stock price and shareholder compensation.

In the process, iRobot was repositioning itself as a “smart home” technology company with more attractive valuation multiples (P/E, P/B ratio, etc), rather than a less exciting “appliance” company. This led to hiring large numbers of software developers, while selling off the defence and security arm of the company along with its US manufacturing base. In the years that followed, staying ahead of the competition relied increasingly on sales and marketing spend, rather than sustaining technical moats.

This is the story of a cutting-edge DARPA-funded MIT robotics spinout (responsible for everything from defusing IEDs in Afghanistan to search and rescue efforts after 9/11) being transformed into a distributor of commodity robotic vacuum cleaners, manufactured overseas. Ultimately, and inevitably, the business faltered when the company lost control of its own product, allowing its monopoly to be eroded by more innovative alternatives.

iRobot offers one example of the wider systemic problem associated with financialisation. As such, much of the apparent economic growth of the last few decades has looked good on paper, despite a feeble reality marked by long periods of stagnation. The benefit has been overstated in financial reporting (see Goodhart’s Law), without having a proportional impact on general prosperity and opportunity for individuals.

Debt to the Centre

“When one has too much student debt or if housing is too unaffordable, then one will have negative capital for a long time and/or find it very hard to start accumulating capital in the form of real estate; and if one has no stake in the capitalist system, then one may well turn against it.”

Peter Thiel, Email to Mark Zuckerberg (2020)

From the individual’s perspective, financialisation limits opportunity to participate in wealth creation, as the economic upside is concentrated in the hands of capital owners. If companies are pushed to reduce R&D, capital expenditures and domestic workforce to optimise financial metrics, they become top-heavy. As this spreads through the economy, it suppresses wages and deepens inequalities.

In an industrial economy, money is simply the liquid unit of value which makes the system more efficient. It’s a tool with which you may do important things, not important itself. Money has value because it allows you to have a nice house, a good car, and a pleasant lifestyle. Your primarily economic role is the production and consumption of goods or services, driving (and benefiting from) the “invisible hand” of prosperity.

“Money has the same relationship to real wealth, that is to actual goods and services, that words have to the physical world. And as words are not the physical world, money is not wealth; it’s only an accounting of available economic energy.”

Alan Watts, Writer and Philosopher (1968)

In a financialised economy, the unequal distribution of opportunity is subsidised with financial products. You’ll take a mortgage to buy a house you can’t really afford. You’ll lease a car and put vacations on your credit card. Day-trading stocks or buying crypto makes it feel manageable; there’s a chance you’ll earn your way out of the permanent underclass. Your primary economic role is debt to the centre, and the system is designed to hold you there.

“Banks are using increasingly sophisticated models to predict which customers will borrow more if their limit is raised. For many, that means an automatic increase they never asked for and may not fully understand. These decisions are shaping household debt across the country in ways most borrowers don’t see.”

Dr Agnes Kovacs, Senior Lecturer in Economic at King’s Business School

The Gambling Gene

“Buying a lottery ticket is the only time in our lives we can hold a tangible dream of getting the good stuff that you already have and take for granted.”

Morgan Housel, The Psychology of Money (2020)

In periods of economic stress, financialisation has evolved to exploit our tendency to overweight long odds of extreme rewards, which economists Daniel Kahneman and Amos Tversky described as Prospect Theory:

“People underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty. This tendency, called the certainty effect, contributes to risk aversion in choices involving sure gains and to risk seeking in choices involving sure losses.”

For example, if you are chasing wealth, you’re more likely to use debt to buy lottery tickets, because we are cognitively wired to prioritise the extreme (and unlikely) reward more than the small (and certain) cost. On the other hand, a person who is already wealthy will prioritise avoiding loss, and is therefore less likely to buy lottery tickets they can easily afford.

The result, as financialisation deepened over the last fifteen years, has been a significant shift in behavior from saving into debt and gambling. US Sports betting revenue rose from $0.4 billion in 2018 to $13.8 billion in 2024, while credit card debt rose from $870 billion to $1.14 trillion across the same period.

This behavior masks much of the poor health of the economy, as purchases made with debt still appear as consumption of a good, and gambling as the consumption of a service.

As this attitude spreads across the economy, there’s an increase in the rate of gamblification. Whether it’s sports betting, meme stocks, altcoins, gamified brokerages, or ripping through video game loot boxes and Pokemon packs, social media is full of people desperately pursuing wealth by rolling the dice.

Perhaps even more worrying is the scale of audience this activity generates, reaching another level of abstraction from real wealth where viewers live vicariously through the performer. This content is bringing a new generation of young adults into an environment where gambling is entirely normalised, if not celebrated.

“Although loot box related activities significantly predicted frequency of participation in monetary gambling activities (opening free loot boxes, paying for loot boxes, and selling items from loot boxes) and perceived normative pressure (selling items from loot boxes), other activities are of greater importance. More specifically, all tested monetary gambling outcomes could be significantly predicted by the viewing of gambling streams - or videos that include gambling behavior.”

More than loot boxes: the role of video game streams and gambling-like elements in the gaming-gambling connection among adolescents, by Eva Grosemans, Rozane De Cock, Lowie Bradt and Bieke Zaman

Of course, the house always wins. Whether it’s harvesting order flow data, collecting fees, or just the negative expected value of gambling, existing capital owners come out ahead of individuals who have to meet liquidity demands on less predictable, shorter-term horizons.

Finance Eats Innovation

Since 2011, Silicon Valley’s thesis has been “software eats the world”. Perhaps more accurately it should have been “finance eats the world”. Despite a reputation for contrarianism and independence, venture capital unfortunately exhibits all of the flaws associated with financialisation with the associated preference for accumulation.

In the era of low interest rates, software offered VCs a vehicle to convert venture dollars into inflated asset values and fee income. Negative-margin businesses were scaled at a huge loss, only to be marked-up on multiples to justify further investment. Capital chased capital in an inflationary cycle, as the “best” deals became those that were the most likely to attract more investment. Similar to share buybacks, this created brittle market leaders with inflated valuations.

This particular era of financial engineering died out with the low-interest-rate environment in 2022, and the subsequent correction washed out much of the “paper” accumulation. The market remains in the tail-end of the hangover, with the collapse of liquidity felt in weaker fundraising across all subsequent vintages (albeit primarily by peripheral hubs and “outsider” managers).

Still, the problem persists. Managers aren’t immune to Prospect Theory, and the parallel with “buying lottery tickets” and today’s investment activity is clear: as incumbents capture the centre via accumulation, the general response is to greatly overpay for any deal that might produce an extreme outcome. “Power law” now shapes entry more than it explains exits, as investors rush toward the endgame.

Worse still are the investments which exploit the behaviors entrenched by such a long period of financialisation. You can gamble on your bills, you can bet against insiders on prediction markets, or try your hand in the poorly-regulated crypto casinos. Thus, the desperation of late-stage financialisation brings us financialisation squared; investors seeking scalable models that print markups based on exploiting the economic stagnation created by financialisation.

Ultimately, this is a choice which investors will be held accountable for. Investors can coast on the tail-end of financialisation, and the products which enable it, all the way to the bitter end. Or, they can be part of the correction, backing the companies that help to deliver long-term prosperity through industrialisation.

The Obstacle is the Way

Despite adverse incentives (slower growth, lower multiples) and subscale activity, sectors like industrial manufacturing are on a steady march upward.

It’s not clear whether this signals a cycle back to industrialisation, or whether there’s just a growing recognition that the status-quo is not sustainable. Indeed, as more capital concentrates into fewer investors, flowing through to fewer companies, there is implicitly a growing number of investors and builders who do not feel like they have a stake in the current system.

Something, eventually, will break.

“This time however, things are different. With the current ICT revolution, we seem to be stuck in the installation period or in what I call the ‘turning point’, which is the mid-way time of recessions and uncertainty, revolts and populism that reveals the pain inflicted on society by the initial ‘creative destruction’ process. It is precisely when the system is in danger and is being questioned and attacked that politicians finally understand they must set up a win-win game between business and society.”

A long delayed golden age: Or why has the ICT ‘installation period’ lasted so long? by Carlota Perez

As Perez describes, the turning point has typically been spurred by government action. While the current US administration has made some progress with industrial policy, there has been a continued drift toward deregulation. As a result, this could be the first time an industrial economy has quietly emerged in parallel to a financial economy, with the two in competition for capital and talent.

Make no mistake, industrialisation is the harder path, as managers face skepticism from their LP base and less immediately lucrative markups. Long-term, however, these “hard tech” and “deep tech” companies offer enduring moats and compounding value that can outperform the hotter sectors. More importantly, they do so by solving real problems with a direct and positive impact on prosperity.

“Reindustrialisation” is the call of technologists who recognise the tragedy of a lost future.

It’s a new uranium enrichment plant amidst a nuclear renaissance, a marine robotics startup solving critical food supply chain issues, or a specialist AI lab focused on the blue ocean opportunity of drug discovery in a world with AlphaFold.

None of these ideas benefit from financialisation. They do not easily fit around the metrics and ratios that have enabled money printing in private markets. Instead, they will make the economy genuinely productive again.

The Age of Industrialists

“The relationship between the creation of money and credit and the creation of wealth (actual goods and services) is often confused yet it is the biggest driver of economic cycles.”

Ray Dalio, Founder of Bridgewater Associates

Financialisation became the lazy default in a post-prosperity era of stability; a mechanism for extraction and driver of stagnation. Ultimately, it’s self-serving, zero-sum, and increasingly vulnerable to systemic shocks that wash away accumulation and all hope of recovery.

Hopefully, capital is ready to embrace “hard problems” once again. This part of the cycle is characterised by great industrialists, particularly those who operate out on the frontier. Critically, they are idealists with a vision that supersedes the shallow incentives of finance. They’ll put enduring competitive strength ahead of fragile capital moats, and legacy over short-term status games. Finance will bend to their needs, rather than vice-versa.

Meanwhile, the return of Adam Smith’s “invisible hand” will not be kind to those who keep trying to juice the metrics of investor-friendly slop.

(Thanks to those that provided feedback on the early drafts, including Yifat Aran, Alex LaBossiere, Laurel Kilgour and Aaron Slodov.)

Build and invest in the Age of Industrialists with Odin

We are living through the most important transition in human history. I don’t say that lightly. I’ve spent the last eighteen months thinking deeply about the Current Thing, talking to the smartest people working on the Current Thing, and I’ve come to a conclusion that I think more people need to hear:

The Current Thing changes everything.

I know what you’re thinking. You’ve heard this before. You heard it about the Previous Thing, and the Thing Before That. You heard it about social, about mobile, about cloud, about crypto, about the metaverse, about whatever it was we were all excited about in 2021. I was there too. I remember.

But here’s what people get wrong. Those were necessary precursors to the Current Thing.

Every Previous Thing was the universe slowly teaching capital markets how to recognize the moment when it actually arrives. And it has arrived. I feel it in my body. I think you feel it too.

Let me be more precise.

The Current Thing is not a technology. It is not a sector. It is not a market. The Current Thing is a civilizational inflection point. It is the hinge upon which the next century will turn. Historians will look back at this exact eighteen-month window and they will say: that is when the future was allocated.

Not built. Allocated. There is a difference, and it matters.

I’ve been talking to founders. Hundreds of them. Maybe a thousand. I’ve lost count, which I think is the point. What I’m hearing is that the Current Thing unlocks capabilities that were, until recently, the domain of science fiction. Founders describe it with a kind of reverence, a quiet awe. Several have cried. I have cried. We looked at each other, crying, and we understood that something very important was happening, not just to technology but to the species.

Some of these founders will fail. Most of them will fail. Almost all of them will fail. That is the cost of building the future and it is a cost that someone, ideally with a 2-and-20 structure, must be willing to bear.

I want to talk about the skeptics for a moment.

There are people, smart people that I respect. People who went to good schools and have good families and presumably feel love. Some of these people look at the Current Thing and say: “I’m not sure this is as transformative as you’re suggesting.” Or: “The unit economics don’t seem to work.” Or: “This is structurally identical to the last three bubbles.”

I used to engage with these criticisms. I used to take them seriously and respond to them point by point. I don’t anymore.

Here’s why.

When you are standing at the edge of the most important transformation in human history, and someone tugs your sleeve and says “excuse me, I have a spreadsheet”. That person is afraid. And I have compassion for that. Fear is natural. Fear is human. But fear is not an investment thesis.

What I have is an investment thesis.

Let me tell you what I believe.

I believe that the Current Thing will generate more value in the next decade than the last five Previous Things combined. I believe that the companies being built right now, today, in this specific vintage, will become the foundational infrastructure of the twenty-first century. I believe that the founders I am backing are not just entrepreneurs but protagonists of history, and that my role, our role, as their capital partners, is not merely financial but moral.

We are not investors. We are stewards of inevitability.

And inevitability, as you know, commands a premium.

Some people have asked me whether there’s a valuation concern. Whether paying 200x revenue for a company with eighteen months of runway and a product that is, in the most technical sense, a wrapper around someone else’s API, constitutes “prudent capital allocation.”

I want to reframe this question.

What is the value of the electric light? What is the value of the printing press? What is the value of fire? What if you had the opportunity to invest in fire? Not the application of fire, not a fire startup, but fire itself, the underlying platform. Would you ask about the revenue multiple?

You would not. You would simply wire the money.

That is what we are doing. We are wiring the money. Into fire.

I want to be transparent about something. Our new fund is larger than our previous fund. Significantly larger. Some have suggested that this is because management fees scale with fund size, and that raising a $2 billion fund generates $40 million per year in fees regardless of performance, and that this creates a structural incentive to raise ever-larger funds irrespective of deployment opportunities.

To those people I would say: you are describing the mechanics correctly but missing the music.

Yes. The fund is larger. Because the moment is larger. Because the Current Thing demands capital at a scale that previous things did not. We are not raising more money because we want more fees. We are raising more money because the future is expensive and someone has to pay for it and it should probably be pension funds.

There is a phrase I keep coming back to. I think about it in the morning when I wake up and at night before I sleep and during the day when I am pricing term sheets. The phrase is this:

We are building the infrastructure of human progress.

When I say this to LPs, some of them nod. Others write very large checks. The ones who write the largest checks nod while writing them, and I think that is the purest form of conviction I have ever witnessed.

Let me address the elephant in the room.

Some of the companies in our previous fund, the ones built around the Previous Thing, have not performed well. A few have shut down. Several have pivoted to the Current Thing, which I actually think demonstrates extraordinary founder resilience and also conveniently means we don’t have to mark them down yet.

But here is what I want you to understand: the Previous Thing was always a stepping stone to the Current Thing. We said this at the time. I am almost certain we said this at the time. And if we didn’t say it explicitly, it was implied by the font choices in our deck, which were very forward-looking.

The point is: everything we have ever done has been leading to this moment. Every fund, every check, every fee, every carry calculation. All of it was preparation. We were not wrong about the Previous Thing. We were simply early. And being early, in venture capital, is the same as being visionary, which is the same as being right, eventually, in a way that is difficult to measure but easy to feel.

I want to close with something personal.

Last week I was at a dinner. A small dinner. Twelve people, all of whom are building the Current Thing or funding the Current Thing or advising the people who are funding the Current Thing. The wine was very good. The conversation was better. At one point, someone said something that I will never forget. They said:

“If we don’t do this, who will?”

I looked around the table, at the partners and the founders and the operators and the one person whose role no one could quite explain but who seemed important, and I realized: we are it. We are the ones who have to deploy this capital. Not because we want to. Not because it enriches us personally, although it does, considerably. But because the Current Thing requires it. Because history is watching. Because our LPs are watching. Because the management fee won’t generate itself.

This is our moment.

This is the Current Thing, and I support it.

And I think you should too.

Use Odin to invest in the Current Thing

Or maybe use Odin to invest in whatever you actually think is a good idea, not what everyone else thinks is a good idea. The choice is yours.

“The single best opportunity in venture capital today is investing in operators’ funds that are small in size, have differentiated access, and exercise independent judgement. I’d bet this cohort of managers will outperform 90%+ of traditional VC’s with billions in AUM.”

- Ankur Nagpal, Founder of Carry

You might assume that venture capitalists broadly improve their performance over time, alongside growing experience, brand and network. Each of these factors, in theory, allow investors to make better investment decisions based on a higher quality pool of opportunities, and produce stronger returns.

While this is true for some, it doesn’t appear to be a general rule. In fact, venture capital has notoriously weak “persistence”; the performance of one fund isn’t necessarily predictive of success with a subsequent fund.

The silver lining is that emerging managers (funds 1-3) have remained an attractive part of the market, with above-average performance and LP-friendly terms. Thus, LPs benefit from access to great firms before allocation becomes competitive, and the market enjoys the healthy competition created by new entrants.

Despite this, the emerging manager opportunity remains overlooked and underfunded, as LPs have retreated to the safety of “established” brands.

The Urgent Demand for New Ideas

“The biggest risk in early-stage investing is likely the ongoing difficulty for emerging managers to raise new funds. While multistage managers may boost their activity, and AI will keep channeling more money into VC, emerging managers invest in many companies both inside and, importantly, outside major capital hubs.”

- PitchBook 2026 US Venture Capital Outlook

It’s no secret that the last few years has been brutal for smaller firms, and particularly for those without a meaningful track record to show prospective LPs. Data from PitchBook shows first-time funds in the US raising a total of $7B in 2024, and $6.6B in 2025, compared to $15B raised by Andreessen Horowitz alone.

Indeed, according to analysis by Sapphire Partners, 2025 is the first year since the dotcom bubble burst that there has been a net decrease in the number of active VC firms.

Active firms are categorised as those that have made a single equity investment in the previous four years (in order to give time for SAFEs to convert to equity rounds). It seems virtually certain that this will fall further next year, in line with the continued decline in funds being raised in recent years.

The venture capital industry is dependent on a steady stream of new firms entering the market, both to ensure a competitive environment with options for LPs, but also because emerging managers tend to offer differentiated investing and an appetite for the newer and more idiosyncratic ideas that are the fuel of the innovation economy.

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Quantifying Outperformance

What’s notable about emerging manager performance is not that it significantly beats the market average (the difference is fairly marginal) but rather how consistently the outperformance occurs across datasets from institutional LPs and market data aggregators.

“In our simulation, between 2010 and 2019, if a dollar was contributed to only funds run by an emerging manager, LPs had a better chance of getting a higher return.”

- Pitchbook

Pitchbook’s examination of four different strategies (buyout, real estate, private debt, venture capital) found that emerging manager performance was generally attractive, particularly in venture capital. Unsurprisingly, they found that this outperformance was combined with a wider dispersion (worse underperformance, greater outperformance), as untested managers deliver broadly improved median and top quartile performance with greater volatility.

“In our experience investing across approximately 180 partnerships, emerging managers have outperformed relative to their established counterparts.”

- Greenspring Associates

Data on 180+ partnerships from Greenspring Associates, a venture capital firm with an LP strategy, also found outperformance in their emerging manager portfolio. The difference was small (+0.87% in net IRR), but again contrasts the expectation that more established managers ought to outperform.

Indeed, Greenspring Associates warn specifically about “the decay of brand”, with the reputation of a firm being tied to the past - echoing the common investing maxim, “past performance is not indicative of future results”.

(Greenspring Associates defines emerging managers as firms with one or two funds, rather than the common definition of one to three funds.)

“Top returns are not confined to a few dozen companies. As Figure 3 shows, new and developing fund managers consistently rank as some of the best performers.”

- Cambridge Associates

Cambridge Associates data reinforces the case for allocation to emerging managers. Their research examines the top outcomes each year (rather than median or top quartile IRR) and the percentage of total value generation.

One key finding: the idea of concentration of returns in a small group of VC funds is a myth. It belongs to the pre-dotcom era. There are more meaningful exits nowadays, and there has been an increase in the number of firms involved in those exits vs. the 90s.

“For the last 10 years, 40%–70% of total gains were claimed by new and emerging managers, a clear signal to investors to maintain more constant exposure to this cohort”

- Cambridge Associates

(Cambridge Associates uses the definition of “new and developing/emerging” managers as firms with one to four funds, rather than the common definition of one to three funds.)

“On an absolute return basis, Fund Is significantly outperform later funds. While performance tends to degrade over time, Funds II and III continue to deliver strong absolute returns. These trends hold true with respect to relative performance. The likelihood of outperforming the median is highest for Fund Is and gradually declines thereafter.”

- Stepstone Group

Analysis from Stepstone Group recognises similar outperformance amongst emerging managers, and attributes it in part to stronger alignment between LPs and GPs. Often, newer managers have not yet accumulated significant personal wealth and remain highly economically and professionally invested in the success of their early funds.

“Emerging managers outperform established peers on average. The IRR advantage is 7.2 percentage points, and the total value creation gap is 0.34x. These differences are statistically robust and economically significant.”

- Colibri Institute

Analysis from Colibri Institute confirms prior analysis, with emerging managers delivering significantly better median returns than their established peers.

In addition to the incentives driven by compensation, Colibri also highlights structural considerations such as the fact that emerging managers tend to write much smaller checks and build broader portfolios.

Why Emerging Managers Outperform

The data is compelling, but what explains it? There are a number of reasons why emerging managers might outperform their established peers:

Scale

Emerging managers are likely to raise small funds ($10M-30M), rather than incumbents who leverage their track record to raise larger funds ($100M+). Fundamentally, it is easier to deliver larger multiples on smaller amounts of capital, giving these emerging managers a mathematical advantage.

Compensation

Another consequence of fund size is the balance of compensation incentives. While larger funds may drive more fee based motivation (focusing on the guaranteed 2% management fees), smaller funds are more incentivised by the 20% carry (focusing on the profit share from successful investments). This creates stronger alignment with finding good exits and efficient returns, rather than scaling and accelerating capital deployment.

Proximity

Emerging managers often raise a fund to address a particular opportunity they have identified, perhaps based on professional experience or angel investments, indicating some ‘edge’ over the market. Established investors, on the other hand, have moved further away from their background or original theses and often develop ‘strategy drift’.

Focus

Established firms, with larger teams and more staff in adjacent functions, simply have more to worry about. Emerging managers (particularly solo GPs and small partnerships with a solid backoffice solution) may be more focused on investing. This is comparable to the advantage that startups have over incumbents, making the most of their size to be nimble and responsive.

Value

It’s often assumed (outside of “spintout GPs” from larger firms) that emerging managers don’t have the network to access “hot” deals, so LPs are happy for them to pursue experimental strategies and novel theses. By targeting less competitive parts of the venture market, emerging managers end up making investments with stronger economics. They avoid the trap of “Money chasing deals” (their proximity to a specific opportunity space also helps here).

Weathering Colder Markets

“We observed the widest gap between median IRRs in the 2010-2014 group (4.5%). During this period, the private market gradually emerged and recovered from a financial meltdown. During and shortly after the GFC, there was a pullback in LP commitments to venture. [...] Our simulation results suggest that emerging managers that secured LP commitments during this harsh fundraising climate outperformed by investing in nascent, high-quality startups with fund structures that ensured the winners had a disproportionate amount of impact on the overall fund return.”

- Pitchbook Analyst Note: Establishing a Case for Emerging Managers

Another point in favour of emerging managers is the extent to which their performance is less correlated to the wider fundraising market and macroeconomic concerns. The target of their investment, early-stage companies building specialised solutions, aren’t large enough to be impacted by market fluctuations or more challenging exit conditions.

Indeed, the analysis from Pitchbook suggests that emerging managers offer an effective hedge against systematic risks in venture capital. This aligns with research that shows that “centrally located” firms (i.e. well networked incumbents) see a temporary performance edge in hot markets where gaining access to competitive deals is potentially more valuable. However, in cooler markets this “central location” becomes a negative, as consensus related deals are at risk of collapsing in value when this systematic risk blows up.

Options on Outperformance

Overall, there’s a substantial amount of data supporting the potential of emerging manager performance, and they serve a clear strategic role in LPs’ allocation strategy.

First, by providing a hedge against market-related headwinds that tend to have more influence on larger firms. Backing early-stage firms solves part of this problem, but truly unenmeshed emerging managers are the main source of alpha in venture capital.

Second, for the same reason that VCs like to invest early, you are effectively buying a call option on future potential. If you skip the first fund, and the performance is impressive, you’ll have a much harder time getting access to the second fund.

It’s also clearly critical, for anyone in venture capital, that the “base” is well funded. Emerging managers exist primarily to make sure that capital is distributed to opportunities across all industries and markets.

The coverage they provide, combined with an appetite for idiosyncrasy, helps create a fertile environment for innovation, for the testing and refinement of ideas, for the development of new platforms and - in some cases - new industries. Without this, the whole downstream funding ecosystem will compete over a smaller pool of opportunity, and humanity will be worse off.

Emerging manager or LP? Get in touch

That is all changing.

Venture is borrowing hard from the private equity playbook. “AI rollups” of services-heavy businesses with complex human-in-the-loop workflows - law, accounting, financial services, medical services - are in vogue.

They have been the talk of town for the last 12 months in particular.

The core idea is pretty simple. You find services businesses with repetitive workflows, buy a bunch of them and automate everything with AI. This makes them more efficient & improves customer experience. Ergo, you make lots of money.

A number of prominent VC firms - General Catalyst, Thrive, Lightspeed and 8VC in particular - are pouring billions into this space.

General Catalyst have been pioneers of the AI rollup strategy, having cofounded or invested early in at least 10 companies.

Thrive have a $1B dedicated vehicle called Thrive Holdings just to roll up services businesses. They announced a partnership with OpenAI in December last year under which OpenAI researchers will work closely Thrive Holdings engineers to build custom models and products for the services businesses they’re acquiring. OpenAI will also gain deep insight into better ways to develop their agents as part of the partnership.

Firms in the space are taking various strategies - sometimes partnering with founders who build the tech holding for the services acquisitions, sometimes creating the holding themselves. It’s a fascinating hybrid of the VC & PE playbooks.

In today’s guest post, Alex Prokofjev, the founder of RollUpEurope - the world’s largest community for Acquisition Entrepreneurs - will briefly cover :

1. The Thesis: What AI rollups are - and why they should work in theory

2. Execution: The 3 types of rollup, the metrics they target, and the skillsets required to run each one

3. Investing: How to spot early winners among wannabe AI rollups

Let’s dig in. Over to Alex.

For the majority of my 20-year career, small-time M&A was decidedly uncool.

Now all of a sudden, everyone is chasing $0.5M EBITDA technical services contractors and accountancies.

The usual buyers - lower middle market PE and search funds - are competing for deal flow with Silicon Valley’s brightest minds.

Is this just another instance of the “AI” buzzword attracting capital, or is there more to it? What are “AI rollups”- and which ones should you be backing (if any)?

You’ve come to the right place to figure this out. Since 2023, at RollupEurope we have published 100+ deep-dives on serial acquirers of just about everything, everywhere. Software, car washes, coffee shops, anaesthesiology practices, e-commerce brands.

We’ve developed a deep understanding of the “DNA” of successful buy and build strategies. Whilst AI rollups have their nuances, I believe many of the patterns are the same, and we can learn a lot from the successes of others.

1. The thesis: what are AI rollups - and why should they work in theory?

Not long ago, I posed this very question to two thought leaders in the AI rollup space: from Shore Capital (back then at OpenOcean) and Sahil Patwa from Unbound. Cyrus’ and Sahil’s answers informed my article Missed out on crypto, tempted by AI rollups?

You can dig into the details there, but TL;DR:

• AI rollups are technology holding companies that grow by acquiring distribution through M&A (rather than through sales). In theory, in the markets they target, it is cheaper and faster to grow this way - rather than to sell tech to incumbents that are often SMBs

• AI rollups work best in stable, regulated industries where customer relationships are sticky and switching costs are high

• The two-step playbook goes like this.

  • One, find industries with
    a) high quality revenue (recurring, high cash generation) and
    b) high volumes of repetitive, labor-intensive workflows.

  • Two, automate these workflows with AI, in order to unlock genuine productivity gains for human employees (more customers served per FTE etc.).

For me, the distinction between “AI enabled” rollups and the traditional kind lies in the extent to which the operating models of the acquired businesses are disrupted.

If you’re ripping up the tech stack, re-educating (or firing) the workforce etc. - then chances are you’re running the AI playbook to justify the mayhem.

Some examples of this from a few different industries:

• Property management:

  • Buena 🇩🇪 - raised $58m from and GV announced July 2025

• Lettings agencies:

  • Dwelly 🇬🇧 - recently closed series B led by

• Marketing agencies:

  • 2X 🇺🇸 - Insight Partners led a growth round announced March 2025

• Accountancies:

  • Crete 🇺🇸 (backed by Thrive) is planning to spend $500m on acquisitions in the coming years.

  • Integral 🇩🇪 - raised €12m from General Catalyst & Cherry Ventures

  • Bhub 🇧🇷 - raised $55m from Valor Capital, Hedosophia and others

• Wealth Management:

  • Savvy 🇺🇸 - recently raised a $72m series B from Industry Ventures, Thrive

  • Clove 🇬🇧 - from Paddle founder Christian Owens & Trouve cofounder Alex Loizu, launched with $14m in pre-seed funding from Accel, Kindred and Air Street

• Call Centres:

  • Crescendo 🇺🇸 - secured a $50m series C from General Catalyst

There are many more, from the above industries and others.
You can access the full list here - kudos to Sahil for maintaining it!

What makes AI rollups, in theory, a smart approach for these industries?

1. The incumbents have a poor understanding of technology;

2. They’re extremely fragmented markets, and;

3. There is a large volume of fairly repetitive “human in the loop” workflows that LLMs - in theory - can eat.

However, make no mistake, an AI rollup is not a normal startup. Executing on the AI rollup playbook requires a unique set of people and skills.

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2. Execution: the 3 types of rollup, the metrics they target, and the skillsets required to run each one

When I worked for a ride hailing platform, the most impressive individuals I came across were city launchers.

These people were like paratroopers. They would land behind the proverbial enemy lines, mount surprise assaults, plant the flag and, after 100 days or so, fly off to the next operation.

In the rollup world, dealmakers are city launchers. They develop the equity story. They raise money. They source and close deals. And then exit.

They tend to come from investment backgrounds and excel at Type 1 - aggregators.

• Focus on a single industry - think dental practices or HVAC

• Acquire multiple businesses fast

• Have a clear and relatively short (3-5 years) exit strategy

For example, Simago built and exited a $600 million radiology rollup in less than three years, while the founders were still in their early 30s.

Charles-Henry Beglin, the man who built Simago, strongly believes that the founding team (he doesn’t believe in solo founders) must include at least one person with a PE or Corporate Development background.

Why? Two reasons:

1. At its most basic, rollup success = scale = number of acquisitions. Synergies between acquired businesses are secondary to scale.

2. If you target a successful exit in 3 years’ time, you need to understand potential buyers’ investment processes from day one.

Type 1 aggregators target Multiple on Invested Capital (MOIC) in the 3-5x range over a 5-year horizon. This is not enough to get VCs excited, but there are plenty of investors interested!

Type 2 Rollups are the so-called “permanent equity” compounders:

• Buy businesses to hold them indefinitely (or at least over the very long term)

• Reinvest profits into more M&A whilst minimising dilution

• Deliberately avoid industry concentration; prioritise asset quality instead.

In this category you will find enduring compounders like Berkshire Hathaway, Constellation Software, Roper, Danaher, and Lifco. Their portfolios are filled with mission-critical, highly resilient, cash-flow-rich companies.

Type 2 aggregators do not interfere with day to day management. They introduce the acquired businesses to proven playbooks (“operating systems”), but otherwise just let them keep building. These knowledge-based operating systems govern everything from decision making to working capital management. Think Danaher Business System.

Type 2 aggregators swear by Return on Invested Capital, or ROIC - how effectively a company generates profits from its total capital (debt + equity). They like efficient, profitable businesses with clear moats (the term “economic moat” is in fact often attributed to Buffett) that can compound over long time horizons.

Importantly, for Type 2 founders, disciplined capital allocation and operational excellence > deal-making experience. The goal is not speed or volume, it is quality.

Now, let’s look at Type 3: AI rollups. Very different from the above!

As Dan Lifshifts, a co-founder of Dwelly, a General Catalyst backed British lettings rollup, said at our recent conference:

“In order to succeed, you need to reengineer entire workflows. To do this efficiently, you have no choice but to completely scrap the existing systems… Fundamentally how we create value is taking this customer base, putting it on our tech platform, and running the business the way we believe it should run”.

If you break this down into daily workflows, a successful AI rollup must excel at three things:

1. Sector Expertise
   Know their industry well enough to identify what can be automated and where to create value

2. Dealmaking
   Find good companies and acquire them quickly, on favourable terms

3. Radical Change Management
   Completely rebuild operations on their tech platform, and maintain service quality throughout this transformation so customers don’t leave.

Unlike Type 1 or Type 2 rollups, there isn’t a catch-call KPI for AI rollups. They look for efficiency gains across the board. Some examples from a General Catalyst report on the topic: gross / EBITDA margin uplift; reduced customer response / service times; and team productivity.

Essentially, you need the skill set of both Type 1 and Type 2 rollups, plus a shit-hot software & operations team that can completely redesign the operating model of every company you acquire.

Sounds intense! How many people do you know that can do all three?

3. Investing: how to spot winners among AI rollups

The investment case for AI rollups is compelling. There are millions of small businesses with stable revenue and margins, and repeatable workflows that can be optimised with the help of the latest technology.

Where things tend to break down is in the execution. People forget that companies are run by human beings. They have unique cultures that are often very resistant to outside forces.

Do not underestimate the operational burden and risk of re-engineering day-to-day processes across multiple acquired companies whilst buying, buying, buying!

My advice is threefold.

1. No Solo Founders - team must have all the key skills

You’re highly unlikely to find everything you need in one person You need to look for founding teams that tick all the below boxes:

1. Great at acquiring at pace

2. Great at operational transformation

3. Have AI capabilities in-house

4. Have an industry edge

2. It has to be a good investment for more than the immediately obvious reasons.

There are a number of characteristics of target companies and industries to think about here:

1. Low competition for acquisitions will help keep prices low and drive better returns. Ability to acquire at relatively low P/E multiples is a very significant success factor in rollup strategies generally. If every lower mid market private equity firm is also competing for deals and an AI rollup company ends up overpaying for acquisitions, even great operational improvements won't generate strong returns. Thrasio is an interesting VC-backed case study in this exact problem from the 2020 Amazon brand rollup craze. They raised $3.4B in equity and debt, acquired over 200 brands and eventually went bankrupt prior to a planned IPO.

2. Strong existing evidence gross / EBITDA margin can be improved with AI - it is all well and good talking about this, but can they prove it?

3. Relatively young employees OR customers at acquired companies, meaning willingness to change and adopt new tech is likely to be higher

4. Regulatory moats - industries with licensing requirements, compliance complexity, or local regulations create natural barriers to entry that make the rollup more defensible.

5. Fragmentation depth - it's not enough that a market is fragmented; you need to know there are enough targets to build meaningful scale. A market with a couple of hundred potential acquisitions hits a ceiling fast. Thousands of potential targets gives much more runway.

3. Avoid obvious red flags

Thirdly, after researching 100+ serial acquirers, I will leave you with a couple of things that that are likely to cause trouble (tbh, these apply to all types of rollups, not only AI ones):

• Founders of software companies that lack PMF - it’s unlikely that pivoting to an AI rollup strategy is going to magically produce that PMF. AI rollups are a way to accelerate GTM for software that already has PMF;

• Founders with little interest in the actual workings of industry XYZ. In particular, avoid folks who invest all their time into developing new revenue streams - instead of upgrading existing operations (see e.g. Teamshares / fintech). You want teams that are obsessed with process optimisation for their chosen industry, not trying to turn the business into something else.

Good luck - happy investing!

Best of the Internet

Welcome to the Roaring Twenties

It’s been a pretty insane week in tech.

The singularity beginning as a bunch of AIs shitposting on an AI version of reddit was not on my bingo card to be honest.

I can’t really begin to summarise it, but this tweet does a good job.

Enough internet for me - I’m going to the park with the kids!

Take care out there.

PR

PS - as always just reply to this email or check out our website if you need SPVs (UK or Delaware) or a better, more digital fund admin.

“In today’s market, you’re either a lifecycle capital partner to founders, or you’re a niche operator originating unique opportunities for those who can be. To originate deal flow, one needs some combo of unique networks, top tier reputation in a niche, or uncommon levels of investment rigor for the company stage.”

, GP at Also Capital

Outperformance Begins With Origination

While there is a lot of talk about “winning deals” in hot markets, the real success in venture capital typically comes from investments in unusual or overlooked sectors. You’ve got to find outliers. This is especially true for emerging managers, who lack the network, brand or AUM to compete head-to-head with other firms.

The challenge, of course, is figuring out how to find good opportunities before they become competitive. This is the art of “origination”; identifying new opportunities that are invisible or illegible to other firms, and avoiding getting into a bidding war.

“The consensus in recent literature is clear: proactive deal origination is pivotal for achieving superior outcomes in venture capital investments.”

Optimizing Venture Capital Deal Origination - Marie Claudette Garella

Importantly, “origination” differs from “picking” in that it refers to the pool of opportunities you create, rather than the ones you choose. Research demonstrates that proactive origination (as opposed to the passive harvesting of in-network dealflow) has significant influence on performance:

“Private equity and venture capital funds that employ a proactive origination strategy have consistently higher returns, driven by both greater quantity and higher relevance of incoming investment opportunities.”

Where Are the Deals? Private Equity and Venture Capital Funds’ Best Practices in Sourcing New Investments - David Teten & Chris Farmer

There's a mathematical explanation for this: the success rate of investments is essentially a combination of pool quality and picking skill. Pool quality acts as a ceiling or constraint - you can't pick winners that don't exist in your pool.

Thus, a small improvement in pool quality yields greater returns than a much larger improvement in picking skill, as picking skill compounds on pool quality to produce alpha.

Put another way, your ability to pick well only matters if there are good options to pick from.

The x-axis represents the effort/improvement you make (e.g., +5%, +10%). The y-axis represents the quality of your final portfolio (the percentage of winners you end up holding).

Notice how the solid line (Pool Quality) shoots up rapidly, while the dashed line (Picking Skill) grows much more slowly.

• A mere 1.5% improvement in the quality of the pool raises your portfolio’s success rate to roughly 9%.

• A massive 10% improvement in your picking skill only raises your portfolio’s success rate to roughly 7%.

You would need to become drastically better at picking stocks to match the benefit of simply finding a slightly better list of stocks to start with.

As Charlie Songhurst put it, in this episode of Invest Like the Best:

Trying to be smarter than other people is very hard and it doesn’t work very often. Trying to have an insight that you get because you sit in a different information flow just seems exponentially easier.

This phenomenon is grounded in Bayes’ Theorem and the concept of the Base Rate.

Despite this, the competitive concepts of “picking” and “winning” absorb a huge amount of attention in VC. Everyone is keen to beat their chests about deals they “picked” or “won”.

Origination, meanwhile, is relatively overlooked. Short-sighted venture capital firms will throw their cold-inbound flow to a junior associate, or focus on attending events which are primarily attended by other investors instead of finding new opportunities in new places.

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Go-to-Market for Venture Capital

There’s endless advice aimed at helping founders grapple with go-to-market strategy; novel solutions require creative ways to identify and convert target customers. It goes without saying that this is a critical skill for entrepreneurs.

But what about investors?

The equivalent of go-to-market for venture capital is origination: identifying the type of founder a firm is looking to back (encompassing everything from founder attributes to stage, region and industry), and understanding where can they be found in the greatest concentration.

The exact answer is unique to a firm’s strategy, but it usually falls into one of two broad categories:

1. Networking via in-person events & targeted outbound

2. Brand-building and cold-inbound

Essentially, the founders that firm can go out and find, and the founders it can attract into the funnel. In a sales context, these might be described as “hunting” and “trapping”. There’s also “farming”, which (in the venture capital context) would be nurturing existing portfolio companies to tap into their networks, secure the subsequent rounds of repeat founders, and generate referrals.

Typically, small firms tend to specialise in finding founders, as they don’t have the same media footprint or brand strength for a large deal funnel. Larger firms, on the other hand, can leverage their scale to attract more founders into the funnel simply through notoriety and the signal associated with their brand. Both also tend to focus on nurturing their community of portfolio companies, albeit with different approaches: small firms focused on specialised support, while larger firms build comprehensive platform teams.

In this article, we’re mostly focusing on the strategy of smaller firms and the need to build proactive origination strategies rather than the brute-force strategies of larger firms.

Searching for Signal

While venture capitalists spend a lot of time talking about the founders they invest in, and the traits they tend to see in those founders, they spend relatively little time on the specifics of how they find those people in the first place.

For the purpose of illustration, here are two example strategies:

Find People, Not Companies

You don’t need to worry about competing for deals or finding promising startups if you’ve built a community of brilliant young future-founders. This might involve running events with universities and schools, or extra-curricular activities for young people interested in technology or entrepreneurship.

An excellent example of this is the Thiel Fellowship, which offered qualifying candidates (younger than 22, no degree) $100,000 over two years to pursue their ambition. The result was an unprecedented rate of success, with 13.79% of the fellows going on to create unicorn companies — including Figma, Ethereum and Plaid.

This is an insane hit rate when you compare it to other elite institutions. It’s almost an order of magnitude better than the runner up, Y Combinator:

Of course, the Thiel Fellowship is not a venture capital firm, and the structure and incentives aren’t the same. It is also hard to replicate “the Prophet’s” unique wisdom & eye for talent.

However, these principles have continued in 1517 Fund, a firm created by Michael Gibson and who previously managed the fellowship. In addition to events for young adults, 1517 Fund also runs a grant program called Medici, offering $1,000 to bright young minds with big ideas.

“It’s really a relationship over time. So a lot of times when we’re writing a check, we’ve already known the founder sometimes for months or sometimes for years. We might meet them through our grant program that we run. And then they might come back later and say ‘Hey, I’m starting to build something in the startup realm’. And we’re like, oh, we’ve seen this person execute before. We’ve seen how they work with other people. They’ve sent us quarterly updates on what they’re up to.”

- Danielle Strachman, GP at 1517 Fund

Identifying genuine human potential might be the most deeply qualitative and tricky part of a venture capitalist’s role, but if you can crack the code it appears to provide a significant edge. In the case of 1517 Fund, and the Thiel Fellowship, that edge may be related to Michael and Danielle’s background in philosophy and education.

Find Ideas, Not Companies

Another way you can avoid having to compete for access is by identifying the future opportunities ahead of everyone else. Indeed, with hindsight many of the technology shifts that ended up producing immense value in venture-backed startups were the subject of discussion in academic circles or hacker communities far in advance.

A good example of this strategy is the research-oriented firm, Compound. By guzzling a firehose of academic work, and learning to distinguish noise from signal, Compound has been ahead of the curve on a number of trends — including voice models (Deeepgram, 2016), autonomous driving (Wayve, 2017) and world models (Runway, 2018).

“[Ulkar Aghayeva] wrote a piece called [Waking up science’s sleeping beauties], and the idea is very similar to something that we talk about, which is that major scientific breakthroughs sit out in the world for a long time. [...] And so a simple thing I tell people who get interested in trying to do more thesis-oriented research is like, if you find a paper that you think is really interesting, you should set citation alerts and get an email anytime anyone cites that paper. You will get to see as more and more people start citing it. [...] That will tell you a bunch of people who are ostensibly smarter than you are starting to care about a thing and are spending material amounts of time writing and talking about that thing. And so I think we have a bunch of signals like that in the same way that a lot of great VCs, you know, believe they have signals on how to tell if a founder is amazing.”

- , Managing Partner at Compound

That’s not to say that Compound isn’t focused on founders, just that their path to finding founders is very different. Instead of following great founders towards the interesting places to build, Compound looks to understand those interesting places first and then meet the founders there.

Right Place, Right Time

Both of the strategies outlined above share a recognition of the importance of timing. Research tells us that success in VC is significantly connected to being in the right place, at the right time due to the cyclical nature of technology investment.

For example, had you raised a fund for internet companies in 1995, or SaaS in 2010, you’d have been likely to outperform based on the nascent opportunity. On the other hand, funds raised in 1998 or 2018 generally had a much harder time, and significantly worse returns. They arrived to find a flood of capital, and the current carried them over the cliff.

Implicitly, the best thing you can do is to optimise your origination strategy around being in the right place, at the right time. You can do that by following the journey of talented young technologists, like 1517 Fund, or you can do it by following the science, like Compound. Both offer a compelling approach to identifying genuine opportunity ahead of market momentum.

To repeat an earlier point, these are just two examples of a particular belief executed in a particular manner. The opportunity to formulate a strategy matching your own thesis and market is vast. There’s a huge amount of alpha left on the table by venture capital firms that stick to the typical playbook - there are many, many more unusual ways to run origination than these two examples.

Origination Tools

In addition to bespoke strategies that involve finding founders out in the wild, there’s a growing list of tools that venture capitalists can use to find opportunities. Historical examples include Crunchbase or F6S, where investors can search through a database of opportunities, filtering by features like industry, stage or location. Of course, this biases towards slightly older companies, and it also means your edge becomes how you filter a pool that everyone else can access.

Newer AI powered tools also claim to help venture capitalists find deals. It’s worth noting the three likely outcomes of these tools:

• Least likely - they make it easier to find great investments. They tend to magnify investor attention and push prices up in a way that will erode any advantage created by the tool; also known as “alpha decay”.

• More likely - they make it easier to filter the total pool of companies (and/or people) on the platform, which allows investors to find opportunities that fit a narrow thesis more easily. In this case, these tools will help generate alpha.

• Most likely - they land somewhere in the middle, and end up without much measurable influence on venture capital outcomes. At the early stage, the greatest outliers will still be more easily identified by investors with a unique thesis, reflected in how they approach origination.

Curating Cold Inbound

While the volume of cold inbound (pitches submitted without any existing relationship) is unlikely to be a problem for emerging managers, it may become a burden if the firm has a well-known founder or a particular investment catalyses a lot of interest in the firm. Certainly, with time and with success, the firm’s inbox (and those of the partners) will require an increasing level of attention.

“VCs are obsessed with the idea of gaining ‘proprietary dealflow,’ yet reject some of the most easily implementable methods to expand and diversify dealflow pipelines. They argue that cold inbound is definitionally non-proprietary because everyone sees non-networked companies. That’s clearly not the case since most funds don’t accept cold inbound and therefore don’t “see” anything in that domain. Most importantly, their argument fails to conceptualize inbound dealflow sourcing and filtering processes as themselves powerful fund differentiators and branding opportunities.”

- “Ban Warm Introductions” -

As mentioned earlier, a common mistake is to throw the problem at junior team members who haven’t been properly trained. Instead of looking for potential outliers, they are more likely to seek simple patterns and prioritise hot industries and well-credentialled founders. Often, in trying to select deals that are likely to get partner approval (seen as “success” in screening) they will over-index on recent deals the firm has made.

Recognising value in an inbox of pitches is neither easy nor fun, but there’s a lot to be said for partners pitching in and doing the work. They will most efficiently be able to pick out opportunities, applying what they have (hopefully) learned about managing the various biases involved in investment decisions. Much may be learned from Y Combinator’s screening process, which limits the information that partners consume to a single one-pager, expediting the process and focusing their attention on meaningful factors.

Once you have a well-designed approach to finding alpha in your inbox, by systematically improving the signal-to-noise ratio, you can consider options that scale the exposure of your firm to founders in your thesis. Ideally, the value you get from cold inbound always scales with the volume of interest.

Constraints Breed Creativity

In theory, the highest-performing venture capital investor would see the entire market and be able to select the best opportunities within it. Unfortunately, “picking” is significantly overstated as a persistent skill in venture capital, and it’s only possible to see a small fraction of the available deals at any time.

Thus, origination is the art of setting productive constraints on your firm. How can you focus your attention in a way that improves the aggregate quality of opportunities while also preserving outliers? Essentially, you must optimise for quality without accidentally overweighting moderately-risky companies with middling potential.

As portfolio construction recognises the inability of venture capitalists to pick winners consistently, origination recognises that they would drown in a sea of unfiltered opportunity. Designing processes and systems that enable more consistent outcomes (and learning from mistakes) is the key to surviving in a world where only 10% of firms make it to a fourth fund.

DG

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Get Rid of the Golden Snitch

He’s kind of got a point when you think about it.

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Good morning!

Please give a warm welcome to Dan Gray, who joins Odin as Research Lead!

Dan has spent years deep in the weeds of academic literature on venture capital & private equity, and we share a passion for and belief in the massive economic value that emerging fund managers can bring to society, especially radical managers with radical ideas about how the world could look very different. You can follow Dan on Twitter and LinkedIn - well worth it!

This is the first post in a new series of guides we are producing for emerging fund managers, covering everything from sourcing through to fund structuring. Today we’ll dive into the thorny topic of reserves. Let’s get going.

“In the beginning the majority of our fund was for initial investments, and now the majority of our fund is some level of reserve for follow-on. I don’t know if we’re good at it. I could say to a founder right now that I think there are few firms as good as First Round to be your partner for the first 24-36 months. The hunt for massive product:market fit, building culture, building a team, figuring out pricing and positioning… all that stuff, that’s our power alley. I don’t know if we would be the best partner for founders at the later stage, and maybe we’re just a dumb provider of capital.”

- Josh Kopelman, Founder of First Round

Are Reserves a Good Use of Capital?

In simple terms, a “reserves strategy” represents the capital that a firm will hold back in a fund to make follow-on investments in the future rounds of portfolio companies.

In the common wisdom of venture capital, there are two competing narratives about the use of reserves:

1. Reserves are a crucial way to improve performance by doubling down on your winners. They offer an opportunity to build or preserve ownership in the best companies, generating more alpha from asymmetric insider knowledge.

2. Reserves are a scam. Subsequent rounds are typically a significant step-up in price without a meaningful change in the risk profile of the company. Good piece from on this in October last year.

This is further confused by the fact that analysis seems to suggest that reserve strategies rarely make sense, and yet remain common practice.

“While reserves can occasionally boost returns, they can, and more frequently do, bring down fund multiples. They also (dare I say) sometimes create potential conflicts of interest with LPs. This is why LPs want to understand how a GP thinks about using reserves.”

- Sapphire Ventures

So, how should an emerging manager think about reserves in the present and future of their firm? We’ll run through all of the considerations.

A Magnifier of Performance

Reserves function as a form of concentration, which is the opposing force to diversification:

• Concentration = owning a larger % of a smaller pool of companies, so more upside is captured in the event of an exit.

• Diversification = owning a smaller % of a larger pool of companies, so your portfolio is (a) more tolerant of failure and (b) statistically more likely to hit outliers.

Balancing these forces is a fundamental question for any investment strategy, and all elements (fund size, target stage, typical round size, failure rate, future dilution) play a part in informing the correct approach to risk and reward.

Research helps to illustrate the general trade-off for investors here:

“Increasing concentration has a pronounced positive impact on performance for outperforming funds; the opposite is true for underperforming funds. Most importantly, higher levels of concentration generally hurt the poorly performing funds more than it helps the outperforming funds.”

- Fund Concentration: A Magnifier of Manager Skill

Essentially, if you believe you can reliably predict good and bad investments in your portfolio based on a few years of observation, reserves can help compound those good decisions, by increasing your concentration in your winners. However, most of the time it’s likely to add unwelcome risk.

Implicitly, this means reserves become more obviously beneficial for later stage investing, where failure rates are generally lower and companies produce more metrics that are more predictive of trajectory. Older firms with a longer track record (and better internal processes to track investments) also have an easier time getting value out of reserves.

For emerging managers who are typically investing in the earliest stages, it’s important to recognise the trade-offs in a dedicated reserves strategy. It should not be treated as the default approach.

To break this down, we can take a closer look at the simulated portfolio data from Sapphire Ventures, illustrating how difficult it is improve fund performance by adding reserves:

• Reserves @ 2x: If the follow-on capital only generates a 2x Gross return, its contribution to the fund is a sad 1.5x Net TVPI. This is “dead weight” that drags the total fund performance down from 4.0x to 2.7x. The GP has effectively diluted their own track record by raising more money than they could efficiently deploy.

• Reserves @ 3x - 4x: Even with solid outcomes where reserves triple or quadruple in value, the marginal efficiency (2.2x – 2.9x Net) remains well below the 4.0x benchmark. The fund is getting bigger, but its performance metrics are getting worse.

• Reserves @ 5x: Even if the GP executes brilliantly, and generates a 5x Gross Return on follow-ons, the net impact of that capital is only 3.5x Net TVPI. Because this is still lower than the 4.0x seed benchmark, even this “home run” scenario lowers the fund’s overall average.

As an inexperienced manager investing at the most unpredictable stage, are you willing to bet that you’re going to pick ~25 amazing companies right off the bat, and follow on into all the right ones? Or would you rather double your probability of finding the next generational outcomes like Spotify, Revolut or Elevenlabs?

The Cost of Reserves

Another basic consideration for reserves is simply whether a GP can raise enough capital to cover follow-on activity. A common rule-of-thumb is a 1:1 ratio of initial capital to reserves, implying doubling fund size, which further rules out many capital-constrained emerging managers.

The value you can extract from a reserves strategy is directly dependent on the quality of your initial investments. The more initial investments you can make, the more likely you are to find great companies. This is the tension of reserves: the utility relies on your ability to find great companies, which is easier with a larger portfolio. However setting aside capital for reserves implies a smaller portfolio.

Indeed, underdiversification is already an area of concern for early-stage venture capital, making it difficult to justify fund expansion that amplifies risk further.

“This model seems to show that the larger your portfolio, the better you’re likely to do. Why should that be so? With a power law distribution of returns, success is all about hitting that rare outlier. Other things being equal, the more chances you have, the greater the chance of a big hit.”

- Steve Crossan, Founder of Dayhoff Labs, venture/operating partner at multiple funds

An important additional caveat: generally speaking (unless you are very careful about maintaining the same pool of LPs) you will not be able to use a later fund to invest in later rounds of a particular portfolio company. LPs will not want to provide financial support to an investment where they only capture a fraction of the upside.

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The conclusion appears to be that reserves are not likely to be a good strategy for new managers. However, that doesn’t mean it’s not worth thinking about for the future.

Is your long-term goal to build a collaborative Seed-focused firm that would benefit from greater diversification and the commensurate network effects (e.g. First Round with ~70 companies per fund, or Boost VC with >100 companies per fund)?

Or, are you building a traditional early-stage firm that aims for greater concentration and a more active role in fewer portfolio companies (e.g. Lowercase capital with 10-15 companies per fund, or Hummingbird VC with <20 companies per fund)?

This question will help decide if reserves should become a priority later on.

Alongside this fundamental question, reserves have a number of second-order consequences which are important to consider:

1. Signalling

2. Portfolio support

3. Incentive alignment

4. Sunk-cost fallacy

Let’s run through them.

Important Considerations for a Reserves Strategy

Signalling

One of the ‘soft sciences’ of venture capital, signalling refers to how the activity of an investor might inform the decision of other investors looking at the same company.

For example, if a large multi-stage firm leads the Seed round of a startup, but then doesn’t participate in the Series A, this is interpreted as a negative signal. Their decision not to invest is seen as a consequence of having insider information.

“If a VC invests in your seed round and does not participate in a future round the next round investor will think to himself, “well, if Big VC Co. invested in the seed round they have more inside knowledge than I do. If they’re not willing to fund the next round then something must be wrong with this company.” This is true and does happen.”

- Mark Suster, Upfront Ventures

This may in turn make the life of that company even more difficult, further ensuring a negative outcome. For some VCs this is a good enough reason to avoid a formal reserves policy, and the related signalling risk.

However, the signal strength of a VC firm develops over time, alongside their reputation, so the associated risk is actually minimal for emerging managers. The market isn’t likely to read much into a missed follow-on opportunity.

Later on, the risk is eliminated entirely if you hardly ever do follow-ons, or if (like USV) you never pass on a follow-on opportunity. In these cases there is no real signal to the market about your belief in other portfolio companies.

“Our pass rate is zero. Never happened. Not once in the history of USV. In many cases, we should have, but we did not. We have passed on late stage rounds where our participation was not required and the round was oversubscribed, but when our participation has been necessary, we have always done it.”

- Fred Wilson, USV

Support

Startups are virtually never straightforward success stories. Many of the best companies had struggles with fundraising early in their lives, and will have benefitted from their initial investors having capital to support them through later rounds.

“There is surprisingly little correlation between how hot a company is at Demo Day and how well they end up doing. Coinbase struggled to raise money after YC but ended up doing the best in their batch.”

- Paul Graham, Y Combinator

While a diversified Seed fund may not worry about filling this supporting role, it’s likely that another firm with a more concentrated strategy might. This becomes particularly important in periods of market turbulence, where other sources of funding may dry up.

The implication here is that a comprehensive reserves strategy is not simply for backing “obvious winners” with momentum, but for doubling-down on your own conviction, especially when the going gets tough. The more trouble a company has, the lower their subsequent valuation, the more important protecting yourself from dilution may become.

Incentive Misalignment

Efficient returns are best achieved by smaller funds. GPs, however, are incentivised to prioritise their management fee income, which means raising larger funds. Thus bolting on a reserves strategy often benefits the manager more than the LP, as the additional capital acts as a drag on the overall portfolio performance.

Again, this is well-illustrated in the simulated data from Sapphire Ventures:

• In the “Reserves @ 2x” scenario, the fund’s Net TVPI falls from a solid 4.0x to a mediocre 2.7x. Paradoxically, the GP’s carry increases by $11M, rewarding them for managing a larger, less efficient fund.

• Even in the best-case “Reserves @ 5x” scenario, the fund’s net multiple (3.8x) fails to recover to the original “No Reserves” benchmark (4.0x), proving how difficult it is to maintain efficiency at scale.

While dedicated reserves remain fairly common, it’s worth keeping in mind that LPs are increasingly wary. Are you raising more capital as part of a carefully considered strategy, or is it an excuse to pad out your fund?

Sunk-cost Fallacy

There’s an obvious danger of “sunk-cost fallacy” playing a role in the execution of a reserve strategy. While investors should try and be as laser-focused as they can on objective metrics and personal conviction, it can be hard to overcome biases like market momentum and relationships.

Research tells us that the more time a VC has spent with a particular portfolio company, the more likely they are to invest in follow-on rounds. Similarly, the more capital they have contributed to previous rounds, the more likely they are to participate in future.

“Based on a dataset of 30,602 investment decisions about US-based portfolio companies from 2009 to 2019, we find that both the amount of capital previously invested and the intensity of monitoring significantly increase the probability of continued investment, underscoring the sunk cost fallacy’s role in venture capital.”

- The sunk cost fallacy in venture capital staging: Decision-making dynamics for follow-on investment rounds

It is therefore important, where the follow-on process is selective, that each new round of a portfolio company be considered independent of any prior financing or existing relationship.

The Barbell of Reserve Allocation

“The Seed Fund” - Informal follow-on

For firms focused on the earliest stages, and especially emerging managers, a defined reserves strategy doesn’t make sense for the reasons outlined above. However, that doesn’t necessarily mean you cannot participate.

In rare instances where you have extremely high conviction and believe it’s worth making an exception (e.g. for helping get a round over the line) you can usually get a little wiggle room with your LPs for investments outside of the usual scope. This may just be LPs allowing you the latitude, or sometimes GPs might build an ‘out of thesis’ allocation (10-20%) into their LPA, allowing for investments beyond the main stage, industry and market targets.

While it can be tempting (particularly under the threat of signalling risks) to simply never do follow-ons, it’s unwise to tie your own hands in an industry that is built on exceptions. Especially when it may help shape your learning for a more sophisticated strategy later on.

“The Legacy Firm” - Always follow-on

For more established firms, with a track-record of good judgement which allows for larger fund sizes, the best model to consider might be that of USV. Acknowledging that it’s impossible to know who your winning investments are early on, and that renowned VC firms carry more signal, they simply choose to back all of their portfolio companies to the bitter end (and it seems to work for them).

For as long as their initial investments are well judged, this strategy is likely to help firms graduate from solid-performers (~4-5x) into all-time greats (>7x). However, in a world where only 6% of venture funds are delivering more than 5x returns, managers should be honest about whether the additional risk is worthwhile.

Other Ways to Follow-On

While reserves are the primary vehicle for follow-on capital, there are a few other approaches which may be attractive.

SPV Capital

Firstly, there’s the approach used by many small firms such as Everywhere Ventures, RareBreed Ventures and Hustle Fund, where the fund exists for initial investments, and follow-on allocation is opened up via an SPV. This allows a venture firm to support their portfolio companies with follow-on capital without putting their fund performance at any direct risk. It also gives more active LPs the opportunity to get more direct exposure to companies that they particularly like.

This is going to make the most sense for Family Offices and HNWIs who may value the deal flow. It will tend to be hit-or-miss for a Fund of Funds (for some co-investments of this nature are actually a dedicated part of their strategy), and be unappealing to larger institutions who usually don’t want the admin burden. This aligns well with the typical LP-base of an emerging manager.

Opportunity Funds

Secondly, there’s the strategy usually employed by larger firms, which is to raise specific “opportunity funds” which allow for concentration in their later-stage winners. These funds may be “stapled” to their early-stage funds (so an LP in one must also invest in the other) in order to ensure LP continuity. This allows for meaningful participation in larger, late-stage rounds.

The capital requirements of this strategy also lean towards the larger institutional LPs which tend to back these larger firms, making this a distant consideration for most emerging managers.

Conclusion: Start Small and Experiment

The most common question from emerging managers is “How much should I allocate to reserves?”, and the best answer is probably “As much as you believe you can make a good return on.”

The value of reserves is so dependent on when, where and how you invest. This makes it impossible to outline a generic set of best practices. Certainly, there should be no assumption of reserves as a default strategy.

Fortunately, you can run limited experiments, like an entrepreneur. In your first fund, you might never make a follow-on investment if the right opportunity doesn’t appear, or you might make a handful (capital/LP flexibility allowing). Carefully monitor the outcome of those decisions, and consider the opportunity cost of any allocated capital.

If those experiments seem to pay off, you might want to consider a formal allocation for follow-ons in your next fund. Expand the experiment, get more data. You may eventually end up with >50% of the fund in reserves, like First Round Capital. However, as Josh Kopelman implies, you might never really be certain it’s the best use of that capital. The only way to tell is to carefully track performance over time.

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Launch your fund with Odin

We let anyone, anywhere launch and run a private investment firm online, and work with over 10,000 VCs, angels and founders globally.

2025 was a big year for Odin. We:

• Processed more investment than in the previous 4 years combined.

• Hit $500m in assets under administration, with individual deals as small as $30k and as large as $18.5m.

• Completed KYC and AML checks on 5,517 individuals & companies

• Processed 488 deals (run rate closer to 600 / annum now) and over 6,500 individual investments.

We now administer over 1,500 investment vehicles globally, primarily in venture capital but also in private equity & real estate, made up of over 12,000 individual LP investments, from as little as $1,000 to as large as $10m.

But what’s the point of any of this? Why do it?

If you’re not doubling down on a career in either public service or the private markets in 2026, I believe you’re missing out on a once in a century opportunity.

In fact, I think the future of everything you hold dear might well depend on it.

Let’s dig into why.

Western Capitalism is a pretty good invention.
I like it.

The combination of

• A robust “operating system”, with a focus on the rule of law, sound financial & social policy, individual freedoms;

• Capital (modern money, securities and physical assets like machines and warehouses)

has been the primary engine for every single thing that has fundamentally reshaped our species’ trajectory over the last 300 or so years.

Whether you are an investment banker, a musician, a biotechnologist or a schoolteacher, the life you lead and the work you do would not exist were it not for capitalism.

Capitalism allows humanity to manipulate the rules of time & space to shape our environment to our will. By coordinating a fundamentally selfish species at scale, capitalism lets us build things our caveman ancestors - genetically and intellectually indistinguishable from modern humans - could never have imagined in their wildest dreams.

Some examples of this:

The Transcontinental Railroad (1860s):

• By granting land and issuing government bonds to private companies to build the railroads, the U.S. government coordinated the labour of thousands to stitch the American continent together. Building the railroads turned a 4-6 month long journey into one that took just one week - an order of magnitude improvement.

• OK, we can get places a bit faster - big deal. But the downstream consequences of this change were much, much bigger than you may realise.

• Suddenly we were able to move not just humans but big, heavy things across incredible distances (without slaves - shoutout to the Ancient Egyptians). This changed the way we were able to shape the landscape, and in turn our reality.

• It is no coincidence that soon after the railroads came industrial agriculture, mass manufacturing, electricity, the telephone, the motor car, kitchen appliances, mass information (and with it mass literacy). These things are all direct downstream consequence of the railroads.

• The acceleration of mechanisation meant that child labor became less necessary, and over time women were (partially) liberated from their household / carer role. The suffragette movement gained more momentum in the 50 or so years after the railroads were built than the 50 thousand years before it.

Fast forward to today. There are many more examples of capitalism’s ability to create technologies that change what it means to be a human being. A modern semiconductor manufacturing plant (a “fab”) is perhaps my favourite. It is arguably the single most complex and capital-intensive thing humanity has ever built.

• A single leading-edge fab (like those built by TSMC or Intel) now costs upwards of $20 billion to $30 billion.

• This capital is used to coordinate a global supply chain of extreme precision - specialised chemicals from Japan, ultra-pure lenses from Germany, and “extreme ultraviolet” (EUV) lithography machines from the Netherlands (each costing $200M - $400m. ASML’s core product is the most expensive mass-produced machine tool in history).

• Without this massive concentration of capital, the compute required for everything from video calls with your parents on the other side of the planet to this AI-generated video of Trump singing Childish Gambino’s “This is America” would not exist (make of that what you will).

• Capital here is being used to “force” the laws of physics at the atomic scale - the thinnest chips we are making are now just three atoms thick, and we’re running into quantum interference with the way they work.

In essence, semiconductors have further compressed space and time. They allow us to be anywhere instantly.

They also now allow us to scale our own intelligence, helping us to solve hard problems that even humans cannot.

But continued progress is not guaranteed

The machinery that got humanity here faces existential threats. The barbarians are at the gates.

1. There is a nasty confluence of political, cultural and economic division that is making everyone quite pessimistic about the future. Put another way, the vibe in the West right now isn’t great.

2. Our institutions are decaying. You simply cannot get shit done. You can’t build anything, and the state can’t seem to get its act together to fix this problem. Same story in Britain, France, Germany, USA, etc.

   

3. Meanwhile, in China, an authoritarian-techno-capitalist-communist superpower is outcompeting everyone and building an actual robot army. We risk a situation where we are all watched over by machines of not so loving grace.

   

4. Finally, there is also a significant risk that as machines do more and more of the work historically done by human labour, the delicate relationship between labour & capital that has sustained human progress for the last ~300 years collapses.
   People who own productive AI assets get wealthier and wealthier, and they don’t need to employ humans to make money. Everyone else fights in the dirt for scraps.
   In this case, regardless of whether it’s China or some Western power in the driving seat, we end up with some sort of AI-powered neofeudal dystopia.
   Both Sam Altman (in 2021) and Philip Trammel (a few weeks ago, via ) have written interesting pieces about this. Of course there are gaps in the argument - “If people don’t have salaries, who buys all the stuff the AI makes?” - but regardless, shit’s about to get real.

In short, the stakes couldn’t be higher.

This is also an opportunity.

The future depends more on where talented Westerners put their time than at any moment since WW2

If you want to fight for the values and the world you hold dear, you have two options:

1. Go into politics or public service (work on the operating system)

2. Build a startup or investment firm (work on the application layer)

If you’re thinking about option 1, I salute you. You’re trying to do the hardest and most valuable thing.

If you’re thinking about option 2, I’d like to talk to you.

How Odin can help

Our product lets anyone, anywhere launch and operate a private investment firm online. We work with fund managers and angel syndicates in London, New York, SF, Dubai, Helsinki, Singapore, Sydney and Hong Kong. They can run their VC fund or handle their angel deals from their phone. We take care of the admin, they coordinate capital.

We are firm believers that many of the best capital allocators - the founders, fund managers and investors seeing round corners and leveraging capital to shape the world to their will in new and incredible ways - do not have “traditional” backgrounds.

They may have spent a long time doing something weird or niche, and for this reason they see the world differently. This is what gives them their edge - to paraphrase Big Daddy Thiel, they understand a fundamental truth about the world that others do not.

Often, at least until they build a track record, these are not the people that mainstream VCs or LPs get excited about working with.

They have audacious visions for the future - often great ideas that look like bad ideas - and a willingness to invest their time and money in turning these ideas into a reality.

People like

• Warrick - probably the best VC you’ve never heard of, an investor in everything from Great British defencetech to emerging markets neobanks. A man who goes to war for his porfolio founders and gives it his all to help them grow faster;

• Chris - one of the the biggest backers of Rodolfo and Hannah - who are aiming to make computer chips 4,000x more energy efficient with a radical new paradigm - reversible computing;

• Harvey - who is pulling CO2 out of the air and turning it into carbon-neutral rocket fuel;

• And many more - too many to count!

We do something unsexy - the plumbing, the paperwork, the KYC and AML, the payment processing, the legal structuring of investment vehicles, the tax documents and reporting - but this is what allows our customers to coordinate capital to solve humanity’s hardest problems as fast as possible.

The early results for our customers have been…promising. Big visions produce big results (when they work).

We’ve processed over 50 liquidity events. Our most successful investor is sitting on a ~500x markup on an investment they made only 2.5 years ago. Many more are sitting on markups or cash exits of anywhere from 3x - 250x their money.

No, this time you really should hop on a call

In 2026, we want to speak to you if you’re:

1. A new or established fund manager looking for a service provider to handle your SPVs and/or fund admin. You’ll like working with Odin if you like digital-first, self-serve products that just work, but also want to be able to pick up the phone to a human being to solve trickier admin problems (more info).

2. A deal by deal investor (merchant bank, angel syndicate, secondaries broker, multi family office) looking for similar service (more info).

3. A founder looking for a seamless way to raise capital from tens or hundreds of smaller angel investors and bundle them all into a single entity on your cap table, simplifying both your fundraise and ongoing governance (more info).

You’ll be joining a community of over 1,500 founders, deal sponsors and fund managers like you - maniacs on a mission looking to solve hard problems quickly.

We’ll continue to scale geographically and work with both smaller angel syndicates and institutional partners.

We’re ramping hiring in both our engineering and commercial teams (see live roles here), and laser focused on shipping great products our customers need much faster than in previous years.

We will also publicly launch our E2E fund administration offering (currently beta testing), which will be compatible with multiple legal structures and regulatory jurisdictions.

We’ll keep doing the admin - so you can build the future.

We’re counting on seeing you at the Last Chance Saloon

Build & Invest with Odin

PS - We’ll be publishing more regularly this year - I’m very excited to be bringing on board a regular partner on our content. More on that in our next post!

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Fuck it, why not, everyone’s doing it now

Harsh, but he has a point

Perspective is everything

Motivational speech to round things off

Chat soon!
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Today another opinion piece from Dan Gray (@credistick) on the long stagnation of Venture Capital, followed by some comments from me.

“In the early days of Valar, a lot of VCs passed on us because they didn’t believe we could raise the money.” - Isaiah Taylor, founder of Valar Atomics

Yes, VCs will pass on a company out of fear that other VCs will pass on it.

This is institutionalised insecurity. Venture capital emerged from opportunity of frontier technologies; huge idiosyncratic risk, huge upside potential. Power law meets portfolio strategy.

Today it is dominated by low-agency herd animals that have traded that opportunity away for easier personal enrichment and job security. Instead of independent judgement, and the implicit accountability, they outsource to the collective via market signals that manifest in everything from round pricing to discourse online.

This exposes venture capital to major systematic risk, unmanageable via portfolio design, exacerbating the boom-and-bust nature that leg-sweeps the market every few years.

That’s a taste of how problematic this behavior is. It gets much worse.

The influence of “signals” fundamentally erodes the quality of decisions and the competence of investors.

This basic economic principle is described by Keynes in “The General Theory of Employment, Interest and Money”, and Abhijit V. Banerjee, in “A Simple Model of Herd Behavior”.

tl;dr — At some point, if signals are a significant driver of activity, and incentives aren’t well designed, the market becomes a snake eating its own tail. All that matters is a mindlessly recursive consensus.

Thus began the financialisation of venture capital; the point at which the opportunity mutated from chasing great investments to chasing pools of LP capital with “venture banks” as the brokers.

This is why from 2010 to 2022, a period of generational abundance, venture capital produced increasingly bloated B2B SaaS companies and monkey JPGs. Technological stagnation.

Capital that could have gone to reindustrialisation, to energy or biotech, was instead recycled through fragile ARR-printing machines into bigtech profits.

Farming markups to raise more capital to farm more markups — progress be damned.

This is all a direct result of the incentives. Indeed, these incentives are powerful enough to manifest as market capture:

Implicitly, the VC media playbook that has emerged over the last decade allows firms to develop influence over signal-driven activity (they become kingmakers).

Explicitly, research looking at VC activity indicates that firms who refuse to play along are strategically frozen out of capital networks.

Evidence of this behavior is everywhere. Most investors have never known anything else.

The following sentiments are all gateways for this financialisation and the associated market capture:

• Venture capital is a relationship business

• Access is all that matters

• The best deals are competitive

• Entry price doesn’t matter

• Consensus is good, actually

Indeed, many established practices (like pricing on ARR multiples) are symptomatic of this problem, reflecting a goal of exploiting badly designed incentives (concentrating capital and power) rather than chasing outlier outcomes.

Venture capital will continue to fail entrepreneurs, innovation and LPs (especially in times of abundance) until these incentives are addressed. There are exceptions, such as the early believers in Isaiah Taylor, but those exceptions should not make the industry complacent about glaring structural flaws and obvious failure.

Frustration with this issue led me to write “Why venture capital should be consensus-averse”, at around the same time Valar Atomics was getting started.

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A thought-provoking piece. Valar Atomics have their share of critics in the nuclear community, but the point remains - it is frustrating to see how much capital we are shovelling unproductively into non-problems.

Dan is not alone in calling out this issue - many of the world’s top VC investors have said something similar in different ways.

• Chamath Palihapitaya (Social Capital) calls it the “VC Ponzi Scheme” - the conspiracy to blindly throw capital at hot deals in the hopes of bidding up valuations, rather than thinking about what fundamental new value the business actually creates. The question becomes not “is this an amazing company” but rather “can this company raise more money”. The real winner in all of this is the Magnificent 7, who receive ~40% of every venture dollar (through ads and cloud spend).

• Roelef Botha (Sequoia) calls the current state of affairs “return free risk”. In essence, over the last 20-30 years, there have only been only 20 or so companies a year that are worth $1B or more in realised exits. With more cash plowing into VC, there isn’t a noticeable change. About $250B a year goes into VC now. If you assume 12% net IRR (worse than the nasdaq over last 15 or so years (16%)), that’s about a trillion dollars a year coming out. Assuming investors own 2/3 of these companies that’s 1.5T in exit value per annum. That means even if you take a big IPO like Figma (40B), you need ~40 of those a year! Or more like 100 average-sized unicorn exits every year. That’s simply not going to happen.

• Peter Thiel (Founders Fund) has an entire manifesto on this problem, called “What Happened to the future?”. My favourite quote:

  “VC has ceased to be the funder of the future, and instead has become a funder of features, widgets, irrelevances.”

I am unsure how this can be fixed, but for the sake of our progress as a species, it needs to be. Our view at Odin is that it starts by supporting dealmakers, fund managers and companies doing things differently.

Breaking the mould in VC? Do it with Odin.

Speak to Odin’s Sales Team

Today a guest post from Dan Gray (@credistick), followed by some commentary from yours truly.

There are two types of VC:

1) busy complaining / thinks VC is about access

2) busy investing / knows VC is about outliers

The phenomenon experienced by the first group is called “money chasing deals”, and has been the subject of study going back to the 90s.

“First, the analysis shows that inflows into venture capital funds have had a substantial impact on the pricing of private equity investments. [...] Consistent with predictions, the impact of venture capital inflows on prices was greatest in states with the most venture capital activity and segments with the greatest growth in venture inflows.

Second, we show that the relation between increased fundraising and prices does not appear to be due to greater perceived investment prospects.”

Source: “Money Chasing Deals?: The Impact of Fund Inflows on Private Equity Valuations”

VCs find a vertical they like and it starts to get “hot”.
The herd piles in - bigger rounds, monster markups, overnight “successes”. All without any material impact on the underlying value of the companies.

It’s a recurrent structural problem in VC and leads to boom and bust cycles that, more often than not, incinerate a whole lot of cash and leave us with very little to show for it.

This is most obvious in hindsight. The bubble burst in 2000, but the impact was felt on vintages as far back as 1997. By the 1998 vintage, performance had already fallen off a cliff.

Excellence in investing requires bravery.

• Were you brave enough to hold Amazon when its stock crashed 90% during the bust?

• Or brave enough to back a non-consensus dotcom bet like Google? When they launched in 1998, search was considered by many to be a solved, stagnant category.

• Perhaps you were brave enough to avoid the sector altogether? The following giants were all started in that same period. Many would likely have taken/ your money at a very competitive valuation:
  - BYD (1995), batteries [at the time] - ~$107bn turnover 2024
  - Lululemon (1998), clothing - $9.1B turnover 2024
  - Intuitive Surgical (1995), medical devices - $8.35B turnover 2024
  - BioMarin Pharmaceutical (1997), biotech - ~$2.85bn turnover 2024
  - Seagen / Seattle Genetics (1997), biotech - ~$2.3bn turnover 2024

Unfortunately, in the heat of the moment, none of those options aligned with the incentives created by eager LPs, arriving late to the party with sacks of cash.

The same steps play out every time, as the supply of capital increases:

more capital → higher prices → greater expectations → multiple expansion → overcapitalisation → market crash

All without any implicit increase in quality or potential of the underlying investments.

A very simple way to avoid this trap is for VCs to develop a better understanding of valuation (not “pricing”), so they may recognise when the market transitions to truly irrational behavior. This is easy for the non-consensus investor, since price increases are mostly limited to consensus categories. Unfortunately, the majority of capital is not typically deployed by these investors.

The waste of a bubble is often further amplified when, for political or macroeconomic reasons, the supply of capital is greater, and the apparent supply of other opportunities is lower:

“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.”

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

An obvious recent example of this is the enthusiasm for Web3 in 2021, driven by a perfect storm of ZIRP, Covid boredom and technological stagnation.

Thus, one of the tragic paradoxes of venture capital:

- When capital is most abundant, it is usually being put to work by opportunists - money chasing deals. Very little value is created.

- When capital is most restricted, it is usually put to work by competent investors. Lots of value is created.

Ideally, and obviously, you’d want the capital abundance in the hands of the competent investors, but that’s just not how venture capital has been structured.

What does this mean for us today?

Things certainly look a bit spicy, don’t they?

We can discuss when the bubble might burst, if it’s a good bubble or a bad bubble, etc.
I don’t think this is particularly useful or novel.

A more interesting question to ask is “how might this play out over the next 10-15 years, and what does it imply for us today?”

Personally, I sit in the same camp as Nicolas Colin, Andrew Cote and Jerry Neumann.

As Jerry puts it, “AI will not make you rich”.

When Apple launched their first computer, nobody gave a shit about computers. Even 7 years later the hype was only getting going.

In contrast, the entire world is talking incessantly about generative AI, and has been since ChatGPT launched. Everyone sees and understands its potential.

More importantly, the incumbents have cottoned on quickly to the opportunity and are capitalising on it - i.e. they’ve beaten the Innovator’s Dilemma.

This isn’t the sort of highly uncertain arena that VCs tend to make real money in.

In fact, the argument goes, Gen AI is the opposite of a revolutionary technology.

We are eking the final efficiencies out of the tail-end of computing’s great technological cycle, which was kicked off by the invention of the transistor in the 50s and the microprocessor in the 70s. It boomed with the internet in the 90s, and there were still great returns via SaaS and mobile apps from 2000 to today.

But information technology is now a well-understood area of the economy. Uncertainty and risk are low. The big winners of the information era dominate the global economy completely; the Magnificent Seven represent ~35% of the value of the S&P 500. This game is won.

It is, therefore, not in a place where speculative capital has nearly as much opportunity to make outsized returns.

This is a predictable pattern that previous technological booms have followed, as famously highlighted by Carlota Perez (every VC thinkboi’s favourite writer):

This macro cycle typically plays out over 50 -70 years.

First, a revolutionary technology gets early adoption in niche circles. Over a period of 20 - 40 years, speculative investment by risk-on investors follows, driving widespread deployment of the technology. This eventually leads to overinvestment and ultimately, a big collapse, after which the technology continues to spread and make its impact felt, but eventually matures into a commodity.

Each collapse - marking the shift from extraordinary returns to more average ones, more in line with the rest of the capital markets - lays the foundation for the next wave of innovation. What was once cutting-edge becomes part of the commoditised, background infrastructure that enables the next great technological “irruption”.

For example:

• Industrial Revolution → Steam Engine & Railways

• Steam Engine & Railways → Steel, heavy manufacturing and electricity

• Steel, heavy manufacturing & electricity → Oil, the automobile, mass-production, telecomms

• Oil, the automobile, mass-production & telecomms → Information Technology

“If I had asked people what they wanted, they would have said faster horses”

Think about who invented the transistor in the first place - it was created at Bell Labs in 1947. Bell Labs was the moonshot lab of a telecoms monopoly - winners of the previous cycle. It was also only possible for the computer to revolutionise the world because we already had mass production, plastics and telecomms.

Similarly, Henry Ford started his career at Edison Illuminating Company of Detroit (winners in electricity). After his promotion to Chief Engineer in 1893, he had enough time and money to devote attention to his experiments on gasoline engines. These experiments culminated in 1896 with the completion of a self-propelled automobile, which he named the Ford Quadricycle.

But is Gen AI like the Ford Quadricycle, or is it more like “faster horses”?

Let’s think about it.

Gen AI’s best use cases are
1. Writing, and
2. Producing audio, images & video

This allows you to do two things well:
1. Make more software, and
2. Make more content.
It actually does both of these things quite badly right now, but it’s getting much better over time.

Gen AI therefore represents the commoditisation of software and online media, the two “highest leverage” technologies of the last 40 years. It doesn’t give us anything fundamentally new so much as it gives us “more of the same”.

It is very hard to make money in commoditised markets.

Scale, brand and control of distribution are your only real moats.

In Neumann’s view, therefore, most of the value that generative AI creates as a technology will likely be captured by:

1. Incumbents (the Magnificent 7)
   These are the only firms with the capital and access to data at scale to compete at the model level. They’ll swallow up most of the model startups - there will be a lot of consolidation. They also own the consumer distribution channels for model access AND for all the new content people are making.

2. “Knowledge economy” services companies that are “content heavy” and can morph into gen-AI powered software businesses, offering the same service much better AND cheaper.
   Think professional services like management consulting, healthcare, education, law, financial services, marketing, etc. Startups in these spaces will be able to disrupt and consolidate fragmented, often low NPS industries that software hasn’t eaten yet - industries that account for a third or more of global GDP.

3. Consumers - “who should see a wider variety of knowledge-intensive goods at reasonable prices, and wider and more affordable access to services like medical care, education, and advice.”

All of this is not to say that many investors are not going to make money in AI. You can make a huge amount of money in bubbles simply by trading the bubble, for example - we are seeing a lot of secondary activity in the likes of OpenAI, xAI, Anthropic, etc. at the moment, and people are doing well. But this is trading, not investing, and it’s risky in illiquid markets.

There are also many interesting bets in bucket 2 - the “AI rollup” thesis is a bet on this trend - companies like Lawhive (legal services, backed by Balderton, GV, Episode 1), Dwelly (property management, General Catalyst), Buena (property management - GV, 20VC), Crete Professionals Alliance (accounting, Thrive), Savvy Wealth (financial services, Thrive), etc. But it’s closer to private equity structurally than VC.

My point is more that the next Elon Musk, Henry Ford, JD Rockefeller or Thomas Edison probably isn’t building a company like this. They almost certainly don’t describe themselves as an “AI founder”. They might use AI, but it’s not their focus.

What they will build is not certain. But to be revolutionary, it has to truly change the trajectory of human history and drive our progress as a species, the same way the automobile, refined petrochemicals and electricity did.

Maybe they’re in biotech, maybe they’re in energy, maybe they’re in material science - who the hell knows.

One thing is for certain; they’re a weirdo in a garage, and most people don’t know about them… yet.

Want to invest in weirdos? Launch your investment firm with Odin.

Speak to Odin’s Sales Team

P.S. thought you’d enjoy this video

Note: a shorter version of this article appeared Friday in Sifted. If you’ve already read it, feel free to skip to the “Best of the Internet” section at the bottom for some thoughts and laughs.

It has never been harder to raise money as a solo GP.

With the IPO market closed and returns for more recent fund vintages looking very poor, investors have fled to “safety”. In 2024 just nine US firms (including names you will probably recognise, like a16z, General Catalyst, Thrive, Tiger Global and Kleiner Perkins) secured well over half of all new capital raised in the US.

Emerging managers raised about 20% of all capital in VC last year - compare this to a peak of ~50% in 2017 (Pitchbook (1), (2))

In Europe, the number of VCs announcing new, first-time fund closings plummeted to 34 in 2024; down ~50% in two years, from 42 in 2023, and 66 in 2022, according to Sifted.

This bifurcation of fortunes is not unique to venture. According to McKinsey, the largest vehicles on record were raised in buyout, real estate, infrastructure, and private debt in 2023, but smaller and newer funds struggled. Fewer than 1,700 funds of less than $1 billion were closed in 2023 across all private markets assets - the lowest number since 2012. New manager formation also fell to its lowest levels since 2012, with just 651 new firms launched.

The environment out there is brutal.

The median time to final close across the entire Venture Capital industry currently sits at 15 months (down from 9.3 months in late 2021), and that data includes established managers.

One solo GP I spoke to recently spent 2 full years raising their $12.5m fund 1, with four separate closes. They interacted with ~1,200 prospective LPs and 58 people eventually invested - about a 5% conversion rate. Their lawyer, who focuses on micro-funds, said only ~15% of her clients even make it to final close.

But it doesn’t need to be that way.

In fact, in my opinion, most solo GPs should just never raise a fund at all.

It is also possible to build a successful career investing purely on a deal-by-deal (DBD) basis. You can do this as a side-hustle, or even full-time as you scale.

An aside for the less VC-savvy:
In DBD investing, a “lead” investor (eg. an emerging fund manager) builds a founder relationship and presents the opportunity to invest in a company to their network of LPs (investors). Each LP then decides themselves whether they want to invest in the company, on the basis of their own due diligence. An SPV (a “special purpose vehicle”) is used to pool the investors’ money and take care of legal arrangements like governance of the investment, deal fees and carried interest. It’s a bit like a fund set up for one investment. Many angel syndicates invest this way and, increasingly, larger VC and PE firms are also taking this approach.

Last year at Odin we helped over 3,000 investors (primarily angels, high net worths and family offices) deploy capital into hundreds of SPVs led by emerging managers, backing both later-stage companies like SpaceX, Groq, OpenAI and Anduril, and very early-stage startups in incredibly exciting sectors like AI chips (Vaire), clean energy (Rivan), biological computing (Apoha) and much more. Often these investments were alongside the “tier 1” firms named above.

Many of the best paid and best performing solo GPs on our platform invest exclusively this way. They don’t plan to raise a fund any time soon — and their approach is, in my opinion, smarter and more flexible:

1. They build a large portfolio at pre-seed, seed and Series A. They charge deal carry to investors, with no or minimal cash fees.

2. To pay the bills, they work a job that gives them excellent deal access and network anyway (the two key things VCs claim as their USPs). For example, they might:

   1. Have an operator role at a Series A plus company that's performing well;

   2. Do corporate finance work (fundraising for other funds, capital intros to their portfolio breakouts and other later-stage businesses via their network of Series B plus investors, family offices, etc.);

   3. Work at a family office.

The benefits of deal-by-deal investing

Sticking to investing DBD has a host of advantages:

1. You can charge deal carry on investments, rather than fund carry.
   If you’re confident you’ll perform, your unit economics on exits actually look much, much better — we're talking up to 5x more cash out in exit events on a typical 20 deal VC portfolio (see data from a sample portfolio below on this, and this blog post for more info).

   

   Despite the obvious structural disadvantage and potential for incentive misalignment from their perspective, LPs are often happier with a deal by deal arrangement, at least initially. There are two reasons for this:

   1. They don’t usually pay management fees on DBD SPVs. Remember, most VCs get paid well to lose money. LPs are often stuck paying the salaries of poorly performing managers in their portfolio for 10+ years. Investing DBD allows them to test the water without risking all their capital at once.

   2. They like picking deals. Simple as that.
      This is basic human psychology. Although the odds are stacked against us, many of us like to think we can beat the market. Choosing between opportunities presented to me is fun. Other investment sectors show very similar psychology: despite the fact you should probably just buy a couple of ETFs and sit on them, you’ve probably bought some individual public stocks in the past. If you’re an emerging manager, you’re likely to be dealing with non-institutional LPs, from smaller angels all the way up to UHNWIs and family offices. They might not have the time to go find opportunities themselves (that’s your job), but they’ll enjoy picking from your deals.

2. You build better direct relationships for value-add between LPs and companies.
   If you’re smart and thoughtful, you can turn the preference for deal picking into a competitive advantage. We’ve recently started working with a VC firm launched by two successful, exited founders. They invest from their own holding in every company. Some LPs in their network have bought in at the level of this holding (making it, effectively, a “fund” of sorts). But they also structure an SPV for every investment, and bring in specific, value-add LPs to the SPV. They then work to build close, trusting relationships between these LPs and the founders of the company early on, so that the LPs can genuinely help the company with intros for things like sales and hiring. We see this all the time. In fact, some of the stronger angel syndicates in our network are able to outcompete funds for deal access at pre-seed and seed, because their LPs are so value-add. This is particularly the case in very niche sectors with dense professional networks, like cyber security and biotechnology.

3. You can write more flexible cheque sizes, and get access to better deals.
   If you’re not after a specific ownership percentage and not seen as a competitor to other funds, it’s easier to squeeze onto the cap table in competitive deals. We structured an SPV for Clay VC as part of their investment in the ElevenLabs pre-seed that was only £70k. That’s a tiny SPV and meant they were able to squeeze onto the cap table. It has already delivered over £4m in cash (the IRR was over 1,200%), and the SPV still holds 30% of their original equity in the company (which has tripled in value again since the initial liquidity event).
   Later-stage funds are noticing this trend. We are also now working with a growth-stage firm with over $3B in AUM, who are launching a DBD strategy for late Seed - Series B companies. This strategy allows them to flexibly build optionality and relationships for investments from their growth fund, and their non-institutional LPs enjoy doing it (which strengthens the LP relationship too). For them, it’s a bit like a scout program on steroids, with 15 or 20 value-add LPs in every SPV.

4. You can invest outside of a strict fund mandate. This can be very impactful in a dynamic, rapidly changing market. Imagine you raised a fund to invest in crypto/Web3 in 2021. It’s hard to pivot. Change is only going to happen faster in the coming years. DBD keeps you nimble and able to take advantage of opportunities as they arise. That growth fund mentioned in (3) above thought about raising an earlier stage fund, but felt that in the current environment DBD made more sense, and the speed of change driven by AI was a key factor in their decision making.

Even if you do later hope to raise a fund, DBD helps you to fine-tune your fundraising skills (remember raising money is basically sales), build LP trust, grow your co-investor network and build out your track record on a part-time basis. This makes raising a fund in the future much, much easier.

We saw some incredible exits last year, the best delivering 70x cash on cash returns in 18 months (that ElevenLabs deal led by Clay) and 10x in 6 months (Praktika AI, led by Namat Bahram). Both emerging managers who led these DBD investments are now well subscribed for their first funds.

Want to set up an SPV and make a DBD investment?
Get in touch with Odin

New to this? Want to learn more about launching an angel syndicate? Sign up for our 3-part masterclass, in partnership with AngelSchool (video also shared by email so you can learn async)

The downsides of deal-by-deal investing

There are, of course, disadvantages to this approach:

1. The best investments often look like bad investments initially, so they’re hard to raise money for DBD.
   Excellent performance in venture (as is the case in all investing) is about being non-consensus and right (see Paul Graham’s famous post “Black Swan Farming”). You have to see opportunity where others do not. For emerging managers, it’s hard to raise money DBD for non-consensus investments (Clay’s undersubscribed ElevenLabs pre-seed SPV is actually a good example - they didn’t even manage to fill their allocation!).

2. It can be slow and time-consuming.
   At the worst of times, raising DBD is like herding cats - chasing people urgently for wire transfers to help the founder get the round closed on time. This can also make it trickier getting into competitive rounds, since you can’t deploy as quickly as funds. At Odin we have built tooling to help smooth over this specific problem, but it still doesn’t give you the decision-making control that a fund does.

3. It can be more faff (and $) for LPs.
   For LPs, DBD means more admin (more wire transfers, signatures, etc.) and potentially higher fees overall (due to deal carry - see this article for a detailed explanation of the economics of DBD vs fund carry). If they really back you, over the long-term LPs are better off giving you committed capital and paying management fees, but benefitting from fund-level carry, which drives better alignment of their interests and yours;

4. It can put founders off.
   For startups, a commitment from a fund is much more of a certainty than a commitment from a syndicate (which might fail to raise as much capital as they had hoped). As above, funds can also move faster. They’ll also tend to make fewer, higher-conviction bets, and they’re more likely to follow their money in future rounds. This can make funds more attractive as investors.

Beyond the pros and cons above, I simply don’t think running a VC firm is for most people.

Not only is raising money incredibly tough, each fund is a 10+ year commitment, and comes with significant fiduciary responsibility. On Fund 1, it usually isn't glamorous, and it certainly doesn't pay well.

Doing another job is often more fun, and a better financial decision.

Deal by deal is the right way to test the water - and it may well pay better long-term too.

Best of the internet

About damn time

Beauty will save the world. Glad brutalism and glass monstrosities are in the past. Patrick Collison gets it…

Jolly good show gents

The Lessons of History

It’s well worth reading. Short too. This Spotify audio version is only 5 1/2 hours long and has interviews with Will Durant between each chapter. I enjoyed it.

Don’t listen to the naysayers

Everything can be fun

That’s all for today. Take care and have a lovely Sunday!

PR

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Good morning!

Today I’m announcing our launch of modular institutional investment vehicles, or as I like to call them, Asset Management Legos (please don’t sue me Lego).

If the thought of reading about this sounds about as enjoyable as running barefoot down a corridor full of Legos, fear not. You can skip straight to the “Best of the Internet” section at the bottom for some politics, memes and cultural commentary.

Today we’re launching a brand new product - Modular Institutional SPVs

They’re aimed at larger VCs and private equity firms.

With Modular Institutional SPVs, you get all of the below in one place, together with Odin’s best-in-class technology and customer service:

• Legal Structure: use one of our off the shelf structures (English Limited Partnership, BVI Limited Company), or use your own legals. Our structures work for any asset - companies, real estate, wine, crypto, etc.

• Multi-currency bank account, with interest rates of 4%-5%

• Investor onboarding, KYC & AML

• Regulated management company and Appointed Representative arrangement

• Multiple closes, including calculation of equalisation interest

• Maintaining entity accounts & statutory records

• International tax compliance filings (FATCA, CRS, etc.)

• Ongoing monitoring (KYC)

• Audit

• Registered address

• Annual compliance monitoring and review

What’s more, since it’s modular, you can pick and choose which parts you want from us vs. someone else! Want to use your own legal structure? Just slot it in. Want to use a different banking partner? We can integrate with them.

Here’s the structure chart for our English Limited Partnership (ELP).

This particular “Lego block” works for managers anywhere, and the regulated manager of the vehicle does not need to be in the UK.

We’re launching with the ELP and a BVI (offshore) Limited Company as our first off the shelf legal structures. Other jurisdictions will be fast follows.

If you’re a VC or PE investor and you’re interested in setting up an SPV or running your fund with best in class technology and top-quality customer service, get in touch.

I want to deploy capital like it's 2024

Why this product?

Our mission is simple: allow more people to vote with their money on what the world looks like.

To get there, it is necessary to tackle the root problem - the plumbing that the private markets run on. You see, it sucks:

1. Fund managers hate their fund admins. Almost universally. As an industry, it has a serious customer service problem.

2. 90%+ of fund admin has barely changed since the 90s. A lot of back and forth over email, lots of duplication of work, lots of spreadhseets, lots of data errors. We can definitely improve this with software. LLMs are going to be a massive unlock too.

3. Customisation & flexibility are important. Whilst a lot of the core workflows are the same (onboarding, KYC/AML, tax), specific user needs can vary a lot from customer to customer. Larger asset managers that we speak to feel that current digital providers tend to try to sell you a “one size fits all” solution, when really you’d like flexibility. Things like LP familiarity with a jurisdiction, tax treatment of the local jurisdiction, handling reporting a specific way, accounting, tax-efficient treatment of carried interest and more become much more important tradeoffs (worth paying extra for) when you’re doing bigger deals. You want a digital provider who can do it all.

Our vision for what can be built on top of this plumbing - a way for people to discover and invest in private deals and funds seamlessly (think Blackrock for the private markets) - is only realisable if these problems are addressed.

The “dirty work”, so to speak, needs to be done really, really well.

This is the first of several products we are building that target institutional asset managers.

We’re excited for the next step in the journey!

Best of the Internet

Foundations - why Britain is stagnating

Excellent piece from Ben Southwood, Sam Bowman and Samuel Hughes on the reasons for the UK’s stagnation. The tl;dr is that Planning Permission (specifically the Town and Country Planning Act, introduced by Clement Attlee), dated infrastructure and rising energy costs are massively hindering Britain’s potential. The upshot is that reform is actually not that difficult if the right people make some big decisions.

Here are some choice datapoints that will blow your mind

• Tram projects in Britain are two and a half times more expensive than French projects on a per mile basis.

• At £396 million, each mile of HS2 will cost more than four times more than each mile of the Naples to Bari high speed line. It will be more than eight times more expensive per mile than France’s high speed link between Tours and Bordeaux.

• Britain’s last nuclear power plant was built between 1987 and 1995. Its next one, Hinkley Point C, is between four and six times more costly per megawatt of capacity than South Korean nuclear power plants, and four times as expensive as those that South Korea’s KEPCO has agreed to build in Czechia.

• The planning documentation for the Lower Thames Crossing, a proposed tunnel under the Thames connecting Kent and Essex, runs to 360,000 pages, and the application process alone has cost £297 million. That is more than twice as much as it cost in Norway to actually build the longest road tunnel in the world.
  The planning document, if the pages are laid end to end, is far, far longer than the tunnel will be.

Planning is the root issue. You can’t build anything any more, so people can’t live affordably close to where they can be most economically productive, and companies can’t invest in new opportunities that create growth.

What I really like about this piece of research is that the changes necessary will, I imagine, appeal fairly equally to young Tory and Labour voters.

If we do not reform planning, houses in the UK will remain stupidly expensive, and GDP per capital will remain unnecessarily sluggish.

The UK’s economists almost unanimously agree it’s the country’s biggest problem.

Feeding the world

I thought maybe this was Nikola Tesla - it isn’t.
He is a big part of the reason you’re here today though (click the image to read on).

And did those feet, in ancient time

Great thread on some of the norms, habits and systems that make England what it is.

Renting an old man in Japan

You can literally buy anything these days can’t you. Surprisingly wholesome.

Asking Russians what they know about Americans

Mostly pretty accurate in fairness

Harry McLovin

That’s all for today. Don’t forget to get in touch if you’re in VC/PE and want to run your back office with the best in the game.

See you soon!

PR

It’s been a tricky couple of months! In mid-August, the UK regulator asked us to pause operations in order to make some changes to our platform.

I am delighted to say that after a tough slog and a lot of back & forth with lawyers, as of last Monday we are back up and running!

I won’t bore you with the details, but in short we now operate our angel syndicate deals via a couple of fantastic partners, Talbot Capital and Thompson Taraz, who have the prerequisite regulatory permissions:

This new structure makes us the only tech-first deal syndication platform in the UK that is fully regulated for arranging investments with retail investors and holding client money.

It also unlocks a number of exciting new opportunities - for example, investors can now pledge capital for multiple deals up-front, making the process of running your syndicate with regular investors waaay simpler and lower friction!

We are very grateful to everyone for their support and patience over the last few weeks. We’ve got a lot of exciting new products in the pipeline, for fund managers in particular. We couldn’t be happier to be back focusing on our mission to allow more people to vote with their money on what the future looks like.

If you’re interested in setting up an angel syndicate or running your fund with best in class technology, don’t hesitate to get in touch.

Otherwise, here’s what feels like an appropriate song.

We’ve already contacted our affected customers, but wanted to share the below with our community so that people have clarity and we can assuage your concerns. In short - we’ve been advised to pause onboarding of new customers by the FCA (UK financial regulator) until we make some changes to our operating model. We are complying with this advice.

We’ve got a plan in place and we’ll be back soon. It’s unfortunate, but we have to do what is right. Here are the details.

What’s happened?

• We have recently had a dialogue with the FCA regarding our operating model and how we comply with regulation.

• We have, of course, had consistent third party legal advice since inception, and assurances that we are compliant.

• However, recently, the FCA advised us that Odin requires a specific regulatory permission (arranging deals with retail investors) that we do not have.
  Neither, to our knowledge, do our primary competitors in the UK (whilst they may have slightly different operating models and regulatory advice).
  Note that a “retail investor” is anyone who is not a professional investor under FCA regulation - even if they are sophisticated / high net worth. 

• Let’s be clear on our product - we offer administrative software & services to sophisticated & high net worth angel investors, VCs and founders who would often be doing these deals with or without us - eg. via lawyers and email. We’re basically tying together a number of previously independent products and services: legal, document signature, spreadsheets, email communications, payments and a few other other workflows. We put them in one place and make it all work seamlessly with technology.

• There are a number of exemptions from regulation that, our lawyers advised, we were able to benefit from. However, the FCA has taken a different view.

• As a result of the FCA’s decision, we have had to introduce a temporary pause on new investments for a short period of time while we change our regulatory permissions and operating model to better comply with their requests.

• Since we’ve already been engaged in this dialogue for some time, we have a plan in place. We’re aiming to be back in 2 - 6 weeks with full service.

• Fintech is tricky. This sort of thing happens a lot. Most UK fintechs have had to make difficult decisions quickly following FCA requests at various times in their history. Plus, without being directly regulated, you do not have the ability to communicate with the FCA most of the time. This meant that even though we had legal advice from 2 firms, we could never be certain whether the FCA was ok with our operating model.

• The positive here is that we have clarity on their recommendations so that, moving forward, we hopefully never have this issue again!

We will share more information on timelines for relaunch soon - right now we’re focused on executing on our plan and minimising customer impact.

What does this mean for Odin’s customers, practically?

Until they hear from us, they cannot launch any new deals on Odin. For anyone with a deal live that’s partially funded, we’re closing it out free of charge and offering a free rolling close once we are back online. Alternatively we are refunding them. Full customer FAQs are available here.

It shouldn’t be a big outage, and thankfully it’s during summer, which is a quieter time for venture - fewer of our customers have been affected than may have otherwise been the case.

Is Odin safe? Are people’s investments safe? 

We have significant capital reserves and runway even with no revenue and no layoffs for 8 months or more, which is ample time for us to implement a solution. We have also been prepared for any worst case scenarios since day 1, although we think the risk here is minimal. It is normal for startups to experience challenges of this nature, and we think it’ll be a relatively quick fix.

Note: Any capital we hold in our designated accounts on behalf of investors / investee companies is segregated and not affected - this is not our money.

What’s next?

For now, we just need to get this out of the way.
It’s a bump in the road, and we will get it sorted. 

We have had a large number of supportive messages from the community, and we’re very grateful for everyone’s offers of help! We’ve also had some upset customers and we want to say - we hear you, and we understand why you’re annoyed. We’re going to fix this as fast as possible. If you need to make alternative arrangements then please do so.

It’s a tough break, but we have to do what is right and proper, and act with integrity in the long-term interests of our customers, our shareholders, our relationship with the regulator and, of course, the entire UK / EU startup ecosystem.

We love building for you all, and we’re still only just getting started.

For the next few weeks we’ll be heads down focused on shipping improvements to the product, so that when we’re back online, it’s better than ever.

Hopefully that’s very soon.

Don't Whine...Don't complain. Work harder
Joan Didion

Thanks for reading. Please feel free to share with other founders & investors, and reach out if you’ve got questions.

And have a great summer!

Paddy, Mary & team