Solopreneurs as a New Class of Investible Entrepreneur
Kelly Wagman, University of Chicago Computer Science PhD and Tensility intern
Wayne Boulais and Armando Pauker, Managing Directors, Tensility Venture Partners
Recap: The AI Software Engineering Matrix
In our last blog post, we described how AI code generation tools are making it easier to produce software. Using the AI Software Engineering Matrix, we showed how the impact of AI software development changes on two axes: complexity of the software, and technical training of the engineer. Overall, we argued that producing MVPs for early stage startups has gotten significantly easier and startup founders will need to focus on domain expertise, distribution, and data to differentiate. In this blog, we turn to how AI coding tools have enabled a new class of investible entrepreneur: the solopreneur.
Rise of the Investible Solopreneur
The term “solopreneur” is used to describe founders who start companies nearly alone. Since writing software using AI coding tools is dramatically easier today and a deep technical background is no longer required, there has been a rise in solopreneurs. Data from Carta (see Figure 1 below) shows the number of bootstrapped solopreneurs increasing sharply since 2023. In addition, founders are increasingly delaying hiring (see Figure 2 below). Delayed hiring is likely due to the fact that a founder can develop an MVP without hiring an engineer, as well as use AI support for other tasks like marketing and writing sales outreach content.
The profile of a solopreneur is increasingly a domain expert with an idea for improving a system they are already familiar with. Domain experts no longer need a computer science background or a technical cofounder to get started building a company. This domain expertise and deep knowledge of the customer also becomes an important differentiator that enables founders to stay ahead of competitors. Domain experts with a distribution network and sales skills are particularly well poised to take advantage of AI coding tools to build a successful product and scale rapidly.
Two Financing Paths After MVP
Before AI coding tools became available, investing in solopreneurs was not particularly viable because 1) early teams required both business and technical expertise within the team to build and scale a product, and 2) niche markets were not very interesting investment opportunities because the capital needed to build a successful product would be too high for the potential returns. However, AI changes the economics and provides a new opportunity for investment in solopreneurs. The type of financing depends on whether the addressable market is niche or large, as we show in the diagram “Two Financing Paths After MVP” below.
Solopreneurs can build an MVP with limited capital and, if it is going to be successful, the MVP should show signs of rapid growth acceleration soon after launch. After the MVP starts to “go viral” there are two possibilities: the potential market is large or it is niche. If the potential market is large, then the product might enter a traditional venture model where a larger amount of capital is invested in exchange for equity in order to help scale the team and product quickly. If the potential market is niche, the product is capital efficient, and there is cash flow, but a large exit is unlikely, then it presents an interesting investment opportunity through a different model than traditional VC investing. One example might be revenue sharing, where the investors take a cut of the cash flow as the company grows. This investment model has been used to back new content creators since the time of musicians and record labels.
Are Solopreneurs the New Content Creators? Lessons from the Creator Economy
AI coding tools have enabled solo software founders in a similar way that low-cost recording, publishing and social media enabled solo content creators a decade or so ago. Prior to the content creator era, broadcast media production (e.g. TV, newspapers, recorded music) was expensive because it required teams of people for both production and distribution. The confluence of smartphones that have high-quality recording abilities and social media networks significantly brought down the cost of both production and distribution, leading to the rise of solo content creators and the influencer phenomenon. Like content creators, solopreneurs can now develop software at a much lower cost due to AI coding tools. Social media also presents an option for software distribution, although other distribution channels exist such as app stores, trade shows, or other professional networks. It is also possible new distribution channels develop specific to software micro-products and perhaps AI agents. For these reasons, we believe that solopreneurs are the new content creators, and the investing models around them may change drastically in the next few years.
Content creator business models provide insight into possible investing models for solopreneurs. Similar to solopreneurs, successful content creators use domain expertise to distribute content to both niche and large audiences. Content creators leverage their audiences to build high-revenue businesses through paid content, brand partnerships, and selling D2C products (typically physical goods such as beauty products). Creators can join agencies that represent them and help with distribution and brand deals; agencies then typically take a cut of the creator’s revenue. This model evolved from earlier examples such as record labels and publishing houses that would provide artists with an advance as well as production and marketing support and in return take a percentage of revenue generated from the record or book. A similar model might be possible with software, where investors could provide a solopreneur with a small advance and timeline to create a product, support distribution and sales, and then take a percentage of revenue. The details of how this model might work for both investors and solopreneurs is still an open question.
Case Study: Interview Coder
Chungin (Roy) Lee, a 21 year old who formerly attended Columbia University, built a product with classmate Neel Shanmugam called Interview Coder in a week. Interview Coder is a tool that software engineering interview candidates run while on Zoom interview calls to help them answer coding questions. The software takes screenshots of problems and provides real-time solutions but is not detectable by the interviewer. Lee posted on X that after just two months, Interview Coder had reached $228,500 in revenue, mostly from subscriptions, and had 99% margins.
Lee combines domain expertise with effective distribution. He is an expert at doing the kinds of problems traditionally asked in software engineering interviews, having spent 600 hours on the platform LeetCode to get to the top 2%. And he realized the value of distribution: “I’ve just been blowing up the story as much as possible in order to get as much attention and eyes on me, because I really think that that’s the only differentiator between winners and losers, and in a post-AI world,” Lee said in an interview with the Columbia Spectator. He echoed this sentiment on LinkedIn saying that for his current company Cluely, “we only hire influencers and top-tier engineers.” In fact, Cluely is trying to hire 1,000 content creators that they pay per video.
Interview Coder caused significant controversy in the tech industry because it was seen as allowing candidates to cheat, and Lee was ultimately suspended from Columbia. He argues that the way coding interviews are structured is outdated in the AI era and it should be on companies to devise new and more appropriate ways of testing candidates. Lee and Shanmugam now have a startup called Cluely which has three employees and has raised $5.3M in capital. Lee says Cluely reached $1M ARR in 16 days. Our goal with this example is not to endorse Interview Coder, but to show how a very small team can achieve rapid success using AI coding tools to create an MVP that gets to market quickly.
Conclusion
AI coding tools are enabling the rise of solo founders, called solopreneurs, as well as small teams of 2-3 people. As solopreneurs become an increasingly large fraction of early stage startups, we argue in this blog that solopreneurs represent a new class of investible entrepreneurs. We posit that when considering an investment in this class, investors first look for domain expertise (rather than technical skill) and a quick time to market followed by rapidly accelerating growth. Solopreneurs in both large and niche markets have the potential to be successful—large markets follow more traditional venture investing patterns, while niche markets represent the potential for new investing models like revenue sharing. We can learn from models used in the content creator economy, as software solopreneurs begin to resemble content creators.