For decades, software followed a predictable pattern. First, identify a large market with a common problem. Next, build a solution that works well enough for most people in that market. Finally, scale it to as many users as possible to justify the enormous investment required to build it in the first place. This approach made perfect sense in a world where software development was prohibitively expensive, requiring teams of skilled programmers, project managers, designers, and testers.

But we're witnessing the dawn of a new era, one where software can be built for a single user. The economics of software creation have fundamentally changed, and with it, our assumptions about what's possible. We are in the age of "Software for One."

The Old Economics: Scale or Die

Traditional software development has been an expensive endeavor. A competent developer in the US commands a six-figure salary. For any reasonably complex application, you'd need a team: frontend developers, backend developers, DevOps engineers, and a product manager to coordinate them all.

This coordination isn't trivial. As Fred Brooks noted in "The Mythical Man-Month," adding more people to a software project often makes it slower, not faster. The communication overhead grows exponentially with team size. A five-person team doesn't merely have five lines of communication, but ten. Scale to twenty people, and you're managing 190 potential communication channels.

With such high fixed costs, software companies needed significant funding and, crucially, a large addressable market to justify the investment. Venture capitalists didn't get excited about niche solutions; they wanted products that could serve millions. The holy grail became "product-market fit," that magical moment when your offering perfectly matched what a large market desperately needed.

Companies obsessed over defining their Ideal Customer Profile (ICP). Who exactly are we building for? What are their pain points? Their buying habits? Their decision-making processes? The quest for the perfect ICP consumed countless whiteboard sessions and strategy meetings.

The User's Compromise

From the user's perspective, this model had clear drawbacks. Software built for the masses inevitably included features irrelevant to many individual users. The professional video editor using Premiere Pro might use just 10% of its features but still had to navigate the complexity of the entire application.

This one-size-fits-most approach created an inherent tension. Make the software too specialized, and your market shrinks. Make it too generic, and users feel frustrated by bloat and irrelevance.

The learning curve became a necessary evil. Every new piece of software required time to master, with interfaces designed as a compromise between power and accessibility. An entire industry of UI/UX design evolved to mitigate this friction, creating conventions and patterns to make software more intuitive. But the fundamental problem remained: mass-market software couldn't perfectly fit individual needs.

The AI Inflection Point

The emergence of powerful AI tools has dramatically altered this equation. What once required a team of specialized developers can now be accomplished by a single person with the right AI tools. The economic barriers to software creation are crumbling.

Consider what's now possible: An entrepreneur can describe a complex application to an AI assistant, receive working code, deploy it with minimal infrastructure knowledge, and maintain it with AI-assisted debugging. Features that once took weeks to implement can materialize in hours.

This isn't just a modest improvement in productivity; it's a paradigm shift. When software development costs drop by an order of magnitude, our fundamental assumptions about what's worth building change completely.

The Rise of Personal Software

In this new environment, "Software for One" becomes not just feasible but desirable. Why use Asana or Trello when you could have a project management tool tailored specifically for your unique workflow? Why adapt to Notion's structure when an AI could create a knowledge management system that matches exactly how your brain organizes information?

The economics make sense now. When building and maintaining custom software costs hundreds of dollars instead of hundreds of thousands, the calculus changes entirely. You don't need a million users to justify development. You just need one very satisfied user: yourself.

This shift parallels what we've seen in content. Mass media gave way to narrowcasting, which gave way to the creator economy. Each evolution moved toward more specialized content for smaller audiences. Software is following the same trajectory, with the logical endpoint being bespoke applications for individuals.

Beyond Mass-Market Mediocrity

The implications are profound. No more forcing your workflow to match how software designers imagined you might work. No more hunting through menus for that one feature you need regularly. No more watching tutorials to learn interfaces designed for someone else's needs.

Instead, imagine software that adapts to you. Your email client could prioritize messages exactly as you would, with an interface showing precisely the information you care about. Your code editor could have custom shortcuts for your common patterns. Your CRM could reflect your unique sales process instead of forcing you into a standardized funnel.

The learning curve flattens when software is built for you alone. The interface can match your mental models instead of forcing you to adopt someone else's. The features can align precisely with your needs without the bloat of serving thousands of other use cases.

The New Software Economy

This doesn't mean the death of mass-market software. Many use cases genuinely benefit from standardization and network effects. But we're entering an era where the default assumption—that software must serve many to justify its existence—no longer holds.

The startup playbook changes dramatically. Finding product-market fit becomes less critical when your "market" is potentially a single person. The pressure to "grow or die" diminishes when profitability doesn't depend on massive scale. A long tail of micro-software businesses becomes viable, serving incredibly specific needs for tiny user bases.

For users, the promise is comforting: technology that truly adapts to humans, rather than humans adapting to technology. Software that feels like it was built just for you because it actually was.

The future of software isn't just personalized; it's singularly yours.