A decade ago, the idea that a lone founder could build, launch, and scale a venture-backed company sounded like a Silicon Valley daydream. Today it is edging toward the mainstream. According to Carta’s Founder Ownership Report 2025, 35 percent of the U.S. startups incorporated in 2024 had a single founder. That’s more than double the 17 percent recorded in 2017. Yet, those solo ventures captured only 17 percent of all seed and Series A cheques written that same year, showing both the momentum and the funding gap at play. Fueling that momentum is a step-change in capability. Modern generative-AI systems now write code, design interfaces, draft marketing copy, and even reconcile Stripe receipts. Anthropic CEO Dario Amodei recently predicted that “the first one-employee billion-dollar company” could arrive as soon as 2026. In other words, the solo founder is becoming a new archetype, all thanks to artificial intelligence.
How Startups Used to Begin
Just to paint the picture, in the not-so-distant past, launching a startup meant assembling a founding team with a mix of skills. Technical cofounders to build the product, commercial leads to validate the market, and operators to scale the business. These teams would often spend months developing a minimum viable product. They’d pitch investors, join incubators, and burn through capital before generating meaningful revenue. Much of the early struggle revolved around human bottlenecks. Finding the right people, convincing them to join, and coordinating their work.
There were painful trade-offs, even at the product level. In 2010, Mike Krieger and Kevin Systrom built Instagram with a small team, but even something as simple as adding a photo filter required weeks of engineering time. Resource constraints were about the money and the bandwidth. You had to choose between adding video or refining the feed. You couldn’t do both, at least not quickly. Capital efficiency was tied to headcount. If you wanted to build more, you had to hire more. And that meant raising more money and giving up more equity. The startup journey was a complex relay, and speed was often limited by how fast you could pass the baton between functions.
How AI Changed the Game
When Krieger returned to startup life as Chief Product Officer at Anthropic, he saw a different landscape altogether. Today’s founders aren’t building startups the way he did a decade ago. They’re using AI agents to handle everything from prototyping and customer research to marketing campaigns and infrastructure configuration. And they’re doing it in days, not weeks or months. AI models like Claude 4, powered by Anthropic’s Model Context Protocol, can interface directly with tools like GitHub, Notion, Stripe, Webflow, and Google Analytics. This makes it possible for a single founder to not only write code but also deploy products, manage customer support pipelines, update documentation, and track metrics, all through natural language prompts. In other words, one person can now perform the work of an entire team. At Anthropic, majority of Claude’s internal code is self-written. Krieger says that with Claude, he recently built a prototype in 25 minutes, something that would’ve taken six hours by hand. Across the board, usage of Claude’s code agent has spiked nearly 40%, suggesting a broader trend among solo builders. They’re turning to AI not just as a helper, but as a creative and operational partner. The rise of agentic AI is both a technical milestone and a philosophical one. Yes, AI is a tool, but agentic AI is a collaborator. Almost like an employee.
A New Archetype of Solopreneurs
There is a shift in the archetype of founders that allows one-person startups to succeed at this rate. In the past, technical ability or industry experience often defined early success. Now, the edge may belong to those who can effectively translate customer needs into prompts, workflows, and iterative experiments powered by AI. Think of specific niches like AI companions that wouldn’t be possible without AI, and how some entrepreneurs lean into them by deploying lean, AI-driven products that tap into highly specific user desires. And while solo founders still receive less venture capital on average, that may change as AI reduces the perceived risk of single-person operations. If one founder can build, test, and scale with the support of intelligent agents, the argument for requiring three or four cofounders begins to erode. We’re already seeing it. Startups with three, four, or five cofounders are declining. Equal equity splits are rising. The old rulebook is being revised. And the first wave of solo-AI companies may only be the beginning.
One-Person Unicorns?
If today’s agents can build apps, write code, and simulate business operations, what happens when they can make decisions with even greater autonomy? Anthropic CEO Dario Amodei thinks we may see the first billion-dollar, one-employee startup as early as 2026. It’s a provocative prediction, but perhaps not as far-fetched as it sounds. With standards like MCP becoming widely adopted, AI agents are no longer isolated chatbots. They are integrating into digital workflows at companies like Microsoft, Google, and GitLab, operating across cloud platforms, apps, and systems. The analogy is less like hiring a virtual assistant and more like adding a tireless, multipurpose executive to your team. The implications are massive. As AI agents become more sophisticated, the marginal cost of scaling a company drops. A solo founder could conceivably build a product, serve customers, handle billing, collect analytics, and manage updates without hiring a single full-time employee. The traditional startup stack is being replaced by a founder-and-agent stack.
And while one-person startups are on the rise, and will probably become a dominant percentage of startups in the future, critics like Google CEO Sundar Pichai urge caution, reminding the public that current models are still prone to errors and hallucinations. Analysts like Gartner’s Tom Coshow warn that while AI agents are powerful, they still need to be tightly scoped and monitored. Building complex systems based on probabilistic models introduces risk. AI may write code quickly, but debugging, compliance, and decision-making still require human oversight. That said, even the skeptics acknowledge the momentum. They’re not arguing against the tools.
The future of entrepreneurship may not be a crowded garage filled with caffeine and code, even though that is almost romantic. It might be a quiet apartment, a founder with a laptop, launching his product with well-paced prompts. The tools are here. The model is shifting. And for the right kind of founder, this could be the most empowering era in startup history.
