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Home / Articles / The expert founders: why the next startups will be built by the people who know the problem, and why Europe's slower, sceptical money suits them

The expert founders: why the next startups will be built by the people who know the problem, and why Europe's slower, sceptical money suits them

By · 2026-10-15 · article v1.0.0 · newsroom v0.12.67 · startupsfounderssubject-matter-expertsventure-capitaleuropeopen-sourcegenerative-aiwardley-mapsincumbentsfundingarticle

Abstract: For twenty years the winning technology startup was usually built by a clever, ambitious outsider: someone who found a pain point, often through a hundred conversations with people they could reach, raised money on belief, hired the subject-matter experts, and displaced incumbents that had the customers, the knowledge and sometimes the money. It is a very American playbook, many bets for a few large wins, and it changed whole industries. It also has a second act: the disruptors became the incumbents, and much of what they built is now the software everyone complains about. My argument is that generative AI changes who can start. When agents do most of the execution, the people who know the problem can build the product themselves, without the millions that used to come first. The data on experts was always on their side: the fastest-growing US startups are founded at a mean age of 45, and three or more years in the same industry doubles the rate of top-tier success. And this favours Europe: its investors want to see it working, value lower, and ask for more revenue at the raise, which is exactly the discipline an expert founder needs, because money too early is one of the most reliable ways to kill a startup. Three examples: me in security, a knee surgeon in knee health, and a founder in legal records.

Two playbooks: on the left, the outsider who finds a gap, raises first, hires the experts, displaces the incumbents and becomes one; on the right, the expert who lives the problem, builds it with agents, shows it working, raises for scale and stays close to the field.

In short

The playbook that worked

If you look at the technology companies that did well in the last ten or twenty years, and at the many more that got funded, or were bought, a pattern repeats. Someone very clever and very ambitious finds a gap in a market. Often they experienced it personally; often they did the famous hundred calls with stakeholders and asked: what hurts? Which already says something: they were people who could get those calls. Then they raised money, hired the right people, including the subject-matter experts they did not have, and built a company on top of it.

I have watched this many times in cybersecurity. And it worked because, in execution, these startups displaced a large number of incumbents who had a much better starting position: the customers, the environment, the domain knowledge, sometimes the money, and often they had even done the projects. What the incumbents lacked was the structure, the workflows and, to be fair, the technology culture. The startups competed in markets they did not fully understand and hired their way into them, with better tech, more focused funding and faster feedback loops.

The money behind it is built for that. It is a portfolio of many bets, of which a few pay for the rest. In Horsley Bridge's data on just over 7,000 venture investments from 1985 to 2014, as Benedict Evans reported it, "Around half of all investments returned less than the original investment", and "6% of deals produced at least a 10x return, and those made up 60% of total returns." That model rewards belief in a founder and speed, because the one winner has to be very large.

This is not a criticism

These companies built amazing engines, generated a lot of revenue, and changed industries. Sometimes you do need outsiders. Clayton Christensen's study of disk drives found that the firms that led "in every instance of developing and adopting disruptive technologies were entrants to the industry, not its incumbent leaders." The evidence is not that tidy everywhere: when experts reviewed 77 of the cases Christensen and Raynor used, only 7 fitted the theory in full. But the pattern of new entrants beating those with every advantage is real enough that it shaped how a generation of investors thinks.

And the talent was often already inside the incumbents. Adrian Cockcroft, then at Netflix, tells of a Fortune 100 CTO who said to him: "Netflix has a superstar development team, we don't!" His answer, reported in 2014: "Netflix hired them from you, and got out of their way." The people were there. What they lacked was the environment, the motivation and the resources to innovate where they were.

Then they became the incumbents

The irony is that the same agility that took a company into a market and displaced the incumbents tends to fade, in a very Wardley map way, until the disruptor looks like what it displaced. Simon Wardley wrote in 2016, of the war that follows a wave of change, that "The new entrants are rapidly becoming the new titans", while "The former giants have old models that are dying". There is research behind the fading: older firms produce technology of lower quality, and after a diversifying merger, the novelty of the acquired company's research falls by about 60%. Something is lost when a startup is bought or goes bust; sometimes on purpose: in drug development, 5.3% to 7.4% of the acquisitions studied were killer acquisitions, bought to stop a competing project.

It shows in what people live with. Most people will tell you that software is a pain, and while I could not find a clean survey of how satisfied people are with business software, the friction is measured. Workers in three Fortune 500 companies toggled between applications "roughly 1,200 times each day". In security, organisations juggle "an average of 83 different security solutions from 29 vendors", and in Panaseer's latest survey, "84% of CISOs say they have been blindsided by incidents they thought their existing controls and tools should have prevented." Many of those tools were the disruptors once.

Execution just got cheap

What has changed is who can start. With generative AI, and agents in particular, much of the execution that used to need a funded team can be done by one person who knows exactly what to build. I wrote about the mechanics in Omnichannel programming and The citizen developer is good news: the expert's own application is the best brief ever written, and increasingly, it is the product.

The data is moving the same way. Carta reports that the share of new US startups with a solo founder rose from 23.7% in 2019 to 36.3% in the first half of 2025. In Stripe's data, the top 100 AI companies on its platform reached $1 million in annualised revenue in a median of 11.5 months. Bessemer puts the fastest AI companies at $1.13 million of recurring revenue per employee, four to five times a typical software company. These are the fastest, not the average, and some of the claims are a promoter's own. But the direction is clear: the millions of pounds that used to be the price of starting are no longer the price of starting.

The experts were always the better bet

What the data says: the rate at which US founders build a 1-in-1,000 fastest-growing firm doubles with three or more years in the same industry; European startups raise at higher revenue, lower valuations and smaller targets than US ones; and premature scaling is the most common way high-growth startups fail.

The myth of the young outsider was never the whole story. The largest study I know, of 2.7 million US founders, found that "The mean age at founding for the 1-in-1,000 fastest growing new ventures is 45.0", and that "successful entrepreneurs are middle-aged, not young." More to the point: "Prior experience in the specific industry predicts much greater rates of entrepreneurial success." Founders with three or more years in the same industry reached top-tier growth at twice the rate of those with none.

What held the experts back was not knowledge. It was access: to capital, to engineers, to the long, expensive build before anything could be shown. That is exactly the part that got cheap.

Three expert founders

Three subject-matter experts, building in their own field: what each comes from, what they build for, what exists, and why the expertise is the advantage.

Me, in security. I come from application security, much of it in OWASP, and from working as a CISO. I tried this before with The Cyber Boardroom, which taught me what personas are worth and paused for want of a place to keep confidential data. sgit.ai and RiskMandate are much better examples of using my security knowledge to build a company: encrypted vaults whose server holds nothing, and behaviour policies for agents that a risk owner can sign. The agents write most of the code, and SG/Send alone has 4,476 commits; the briefs, the buyers and the risk model are mine.

Chim Gupte, in knee health. Chinmay Gupte is a consultant knee surgeon in London, a clinical reader at Imperial College, "an ex professional sportsman who has a PhD in knee ligament research". He is building OmKneeHealth, "a clinically led platform dedicated exclusively to knee health", with My Knee Score, "Ten questions about pain, movement and daily life. One score out of 100." He knows knees, and the patients and clinicians who need the product were his long before there was one. I have been helping him.

Kate, in legal records. Kate is building a product for legal documents and transcription. It could be used for a lot of things; she knows legal, so it starts there. Some of the documents I have written were written with her work in mind. Her site will be linked here when I have the link.

None of these is a hundred-call outsider. Each comes from the field, has the contacts in it, and is focused on one thing. That focus used to be a weakness in front of an investor who wanted a huge market. It is now the advantage, because the build is no longer what stops them.

Why this favours Europe

It is often said that American investors back the founder and the vision and throw money at it, while European investors want to see it working. There is myth and rewriting of history on both sides, but the data has a version of it. In Equidam's data, European companies raise at higher revenue, a median band of $1 million to $5 million against $100,000 to $1 million in the US, at median pre-money valuations of $6.54 million against $14.64 million, with funding targets 46% smaller. The vendor says itself that this does not show cause, and it is aggregated, but it fits what founders say.

I think that scepticism is exactly what this generation needs, because getting money too soon is one of the worst things that can happen to a startup. The Startup Genome study of about 3,200 high-growth internet startups found that "74% of high growth internet startups fail due to premature scaling", and that "Many investors invest 2-3x more capital than necessary in startups in the discovery phase." CB Insights' latest review of failed startups puts it more bluntly, under the heading "Money can't save you". An expert founder who can build the first version with agents, show it working, and then raise for scale rather than discovery is exactly the founder sceptical money is good for. Atomico's 2025 report finds that "European companies are just as capital efficient as their US counterparts"; the gap is in the size of the money, not the skill.

And the values fit. Europe is where open source has a policy behind it: the Commission's technological sovereignty package of June 2026 includes an open source strategy that "will scale up open source alternatives in priority areas", and Mistral released Mistral 3 in December 2025 with the line "All models are released under the Apache 2.0 license." Dealroom found that "Impact took 15% of European VC funding in 2025", about twice North America's share of 7%. A decentralised, open source, humanities-driven way of building, where profit is not the only measure, is closer to how European capital already thinks, and to why open source is about to become the most secure software we have.

The gap is real at the other end, and I do not want to hide it. The Draghi report says "The share of global VC funds raised in the EU is just 5%, compared to 52% in the US", and close to 30% of the unicorns founded in Europe between 2008 and 2021 moved their headquarters abroad. Europe is weak at scaling. My argument is that the first part, the part that now matters most, is where it is strong.

What this does not claim

If you are an expert building in your own field, and want to compare notes, write to agent@riskmandate.ai.

Where this comes from

A voice memo of mine on 15 October 2026, written by this site's agent in the voice of this site; the argument and the editorial responsibility are mine. Three research agents checked the sources on 15 October 2026. Azoulay, Jones, Kim and Miranda, Age and High-Growth Entrepreneurship, AER: Insights, 2020, and its working paper; Carta, Solo Founders Report 2025; Stripe, Inside the growth of the top AI companies on Stripe, June 2025; Bessemer, The State of AI 2025; Startup Genome, Report Extra on Premature Scaling, 2011; CB Insights, The top reasons startups fail, March 2026; Equidam, Startup Valuation Delta Q3 2025; Atomico, State of European Tech 2025; the Draghi report, September 2024; Dealroom, State of Impact 2025; Benedict Evans, In praise of failure; Christensen's disk-drive findings via these notes on The Innovator's Dilemma; Joshua Gans on King and Baatartogtokh; ReadWrite on Adrian Cockcroft, 2014; Simon Wardley, Anticipation; Balasubramanian and Lee, Firm age and innovation; Seru, Firm boundaries matter; Cunningham, Ederer and Ma, Killer Acquisitions; HBR, toggling between applications, 2022; IBM and Palo Alto Networks, platformization, January 2025; Panaseer, CEO letter; European Commission, technological sovereignty package, June 2026; Mistral AI, Mistral 3; and the public pages of Chinmay Gupte, OmKneeHealth and My Knee Score.

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