AI Lets Founders Build Solo, but Startup Duos Gain the Edge

Solo founders are now the majority of new startups on Stripe Atlas. In late May 2026, Stripe reported that 63% of companies created through the service in the second quarter had a single founder, a record. Supabase's State of Startups 2026 survey of 2,000 founders points the same way: 61% say AI writes more than half of their code, and among non-technical founders, 54% hand more than three quarters of it to AI.

The technical barrier has clearly fallen. A person with an idea and a coding assistant can ship in weeks what once took an engineering team and a funding round. That, however, is exactly the problem.

When anyone can build, the product is not enough

If one person can build a product in a few weeks, so can a competitor, using the same models and tools. Coding ability no longer protects early movers. Competition is rising accordingly: the France Digitale and Sopra Steria Ventures map counts 1,114 AI startups in France in 2026, up from 750 a year earlier.

The result is dozens of near-identical tools for every use case, impressive demos and products that fail within a week of real use. AI made building easy; it did not make knowing what to build easy. A language model has read much of the internet, but it has never spent a morning in an estate agency, on a building site or in a warehouse. It does not know which figure a customer checks first or which step in a process everyone quietly skips.

The winning pairing: field expertise and technical skill

The author, who is working on a real estate analysis and valuation platform with an industry professional, says the technical side moves fast thanks to AI, while the product's value comes from the expert: what investors actually look at, which sources are reliable, what an estimate must show to be believed.

AI cuts the cost of building but does not remove the need for a technical profile. The role changes: designing systems that hold up in production, deciding what to delegate to AI and what to keep under human control, and turning field knowledge into dependable software.

The argument is that the startups standing out in the coming years will not be those that code fastest, but those that know a trade best, own the data it generates and earn enough trust to run inside customers' daily operations. For domain experts who have long had a software idea, the technical barrier has never been lower, and their field knowledge has never been worth more.