Artificial intelligence is not just speeding up coding. It may be widening access to software creation itself. That is the central argument in a recent essay by Elena Verna, who says a new era of small, niche software businesses is emerging as the cost and complexity of building products falls.
Verna describes this shift as the rise of “Mom-and-Pop SaaS,” a category of software products built by people outside the traditional tech elite. In her view, the biggest change is not that developers can work faster, but that teachers, real estate agents, accountants, coaches, consultants, and other domain experts can now turn their own knowledge into software.
For years, building software usually required specialized technical talent, often concentrated in major tech hubs and backed by venture capital. That made many ideas uneconomical, especially in small markets or narrow professions. Verna argues that AI is breaking that equation by making software creation cheaper and more accessible.
The essay frames the trend as an economic participation story rather than a pure productivity story. Verna compares it with earlier platform shifts that expanded the number of people able to participate in an industry. She points to Shopify as helping create millions of merchants, Airbnb as opening space for new hosts and properties, YouTube as enabling niche creators, and Substack as supporting independent media businesses.
Her broader point is that lower costs do not simply replace existing players. They can also expand markets by making new kinds of businesses viable. She invokes Jevons Paradox, the idea that when a technology makes something more efficient, overall use can rise rather than fall.
That logic, she argues, should apply to software. If building becomes much cheaper, more people will create more tools for more specific problems, from local clubs and photographers to recruiters, property managers, and niche professional communities.
Verna cites data from Lovable, the AI software platform where she says the company studied its users. According to the figures she shared, 80% of builders on the platform come from non-technical backgrounds, while 55% have more than 11 years of professional experience.
She argues that this suggests domain expertise may become more important than technical expertise. In the older model, a subject matter expert described a workflow to a developer, who then translated that knowledge into software. Verna says that translation step often introduced friction and imperfect products. With AI tools, she says, the person who understands the problem may increasingly be able to build the solution directly.
The essay also says the products people are making are not just experiments. Verna reports that 80% of builders intend to monetize what they are creating, and 35% are already generating revenue. The most common products include websites, landing pages, internal operations tools, consumer apps, and dashboards or analytics products.
A major theme of the piece is that not every software company needs to become a venture-backed giant. Verna argues that AI could make it easier for small businesses and solo operators to build profitable products without chasing the scale expected in traditional SaaS investing.
She says there is a large middle ground between hobby projects and massive startups, where small, specialized software businesses can serve a clearly defined audience and still make a good living. In that model, a local business does not need to become a global brand to succeed.
The essay also raises concerns about who gets included in this new wave of software building. Verna says only 14% of the builders in the Lovable study identified as women, and she argues more participation from different groups is needed because the people who build software influence which problems get addressed.
Her conclusion is that AI is making software creation accessible to a much broader population. If that trend continues, the next wave of software may come less from venture-funded startups and more from people with deep experience in specific industries, communities, and workflows.