There’s a seismic shift underway in software, and it’s not where most people are looking.
When we talk about the AI revolution, the conversation usually centers on product functionality: smarter apps, better personalization, and new user experiences. But the deeper, and arguably more disruptive, change is happening beneath the surface. This isn’t just about what software does; it’s about how it gets made.
We’re entering an era where AI native software development will define the new bar for speed, efficiency, and leverage. This isn’t a theory or a prediction—it’s already happening. At Next47, we believe that embracing this model is no longer optional. It’s a prerequisite for survival.
The Solo Founder Fantasy Is Becoming Reality
Sam Altman recently speculated that a single person might one day build a billion-dollar company with the help of AI. While the idea of a lone founder scaling a global software business remains extreme in the short term, what’s undeniable is that small, highly leveraged teams are already producing results that once required armies of engineers and years of development.
We’re seeing the rise of bionic software teams—small groups (or individuals) supercharged by AI copilots, dev tooling, and infra automation—delivering ERP-scale capabilities in a fraction of the time. These teams aren’t using AI as an add-on; they’re building with AI at the foundation.
That’s a game-changer for early-stage startups. But it’s also a massive threat to incumbents.
A New Definition of Capital Efficiency
Capital efficiency used to mean being frugal with headcount or burn. Now, it’s about whether your engineering output and company execution reflect an AI native operating model. If you’re not incorporating AI across your development stack and core functions, you’re lagging.
The implications are broad and brutal. Software vendors that aren’t re-architecting their approach around AI will soon find themselves obsolete. And it won’t take long.
If your competitors can ship 10x faster, iterate 10x cheaper, and deliver functionality with 1/10th the team size, you’re fighting a losing battle.
The Vulnerability of the Incumbents
Nowhere is this more evident than in enterprise software. ERP vendors like Oracle and Salesforce have long relied on their breadth and depth of functionality as enduring moats. But what happens when a team of five can replicate that functionality in 6 months with AI acceleration?
Historically, new entrants chipped away at the edges of enterprise software with narrow, vertical solutions. Going forward, we’ll see startups launching with broad product offerings that rival (or surpass) incumbents right out of the gate.
This isn’t just faster software development. It’s faster strategic development. It changes how companies differentiate, evolve, and defend their market positions.
What It Means to Be AI Native
So, what does it mean to actually be AI native in your development?
It means leveraging the latest in AI-powered tools like Microsoft Copilot, Cursor, or Windsurf to enhance everything from code generation to system design to testing. It means your engineering team isn’t just tolerating these tools—they’re believers. You want developers who see AI not as a curiosity, but as a core enabler. If you’re trying to convert non-believers into an AI-native mindset, you’re already behind.
Sundar Pichai, CEO of Google, has stated that AI is now responsible for generating more than 25% of all new code at Google. This code is then reviewed and accepted by human engineers before being used. This represents a significant shift in Google’s development process, with AI now playing a fundamental role in its business. Current and potential founders must take note.
Being AI native also extends beyond software development. It touches DevOps, IT infrastructure, QA, customer support, and even go-to-market. AI must be woven into your company’s operational fabric.
And perhaps most importantly, the long-term differentiation of your business won’t be just in the codebase. It will lie in proprietary data, unique UX, and the interfaces you build that make your AI outputs more usable, more trustworthy, and more integrated into customer workflows.
Conclusion
While this trend is undeniable today, we’re still early in the curve. The pace of change will only accelerate from here. Model quality is improving. Tooling is maturing. Founders are getting savvier. And capital is flowing toward those who embrace the new paradigm.
We’re on the cusp of a dramatic reordering of the software world. The winners will be those who understand that AI isn’t just a feature—it’s a foundation. The losers will be those who cling to legacy stacks and outdated ways of building.
If you’re building a software company today, become AI native in everything you do. If you’re an incumbent, start rethinking your roadmap and your organizational structure now, not next quarter. And if you’re an investor, look for the teams who are doing more with less, who treat AI like gravity, and who see this moment not as a threat, but as the biggest opportunity in decades.
Because the future isn’t just faster. It’s different. And it’s already here.
