In early January, 18‑year‑old Justin Jin launched Giggles — an AI-powered social entertainment app that’s reportedly attracted over 120,000 waitlist sign-ups and generated 150 million impressions — all without a venture capital war chest, a marketing budget, or a traditional engineering team. Instead, he and his team of young co-founders leveraged AI to build an app for Gen Alpha and Gen Z, where users interact through AI-generated content, digital collectibles and gamified social engagements.
A few weeks later, another startup arrived on the scene — Base44, founded by a non-technical creator who used AI to “vibe code” a no-code development platform. Within six months and under ten people, it reached profitability, pulled in 300,000 users and sold to Wix for $80 million in cash, according to TechCrunch. Suddenly, a new archetype emerged: Companies not founded on traditional engineering teams, but shaped by creativity, culture and AI orchestration.
This is the story of the moment. AI is redefining entrepreneurship, allowing people with a vision and cultural understanding — but not necessarily computer-science degrees — to ship platform-level products. But questions are mounting: Can this new model of entrepreneurship scale beyond prototype success without deeper engineering muscle?
The Rise Of Vibe Coding
Two years ago, the phrase “vibe coding” barely existed. Today, it’s everywhere. The term — coined by Andrej Karpathy, former AI lead at Tesla and cofounder of OpenAI — describes writing with AI by simply speaking ideas. “You fully give in to the vibes, embrace exponentials and forget that the code even exists,” Karpathy tweeted in February. It’s shorthand for a new era, where programming is done through a natural language like English.
According to Garry Tan, CEO of Y Combinator, many startups now use AI to generate up to 95% of their codebase — achieving results that once required teams of 50 to 100 engineers with fewer than ten people. Meanwhile, in a recent article for Business Insider, Alistair Barr highlighted how “non‑traditional, AI‑native developers” are turning natural language into apps, fundamentally altering SaaS economics.
This shift is democratizing entrepreneurship. Product managers, artists, even high-schoolers can now ship products faster than ever before, all without technical expertise. But it also comes with some problems. As Nigel Douglas, head of developer relations at Cloudsmith, cautioned in the Financial Times, “If you’re creating an app in your spare time, a “DIY disaster” might just mean an ugly interface. But in a business setting, the wrong tool can do real damage and result in data breaches, service outages, or a compromised software supply chain.”
GitHub CEO Thomas Dohmke echoed this warning at the just-concluded VivaTech in Paris: “A non‑technical founder will find it difficult to build a startup at scale without developers,” adding that tools like vibe coding don’t provide the depth needed to justify serious investment. Even AI-native founders acknowledge the model’s limitations.
“There’s a need to build technical depth. We know that’s important and are expanding engineering operations and bringing on advisors,” said Edwin Wang, co-founder of Giggles. “The future, however, must be a community-governed and decentralized future where there’s a balance between creativity and coding.”
When Creativity Replaces Code: The Giggles Test Case
Giggles is a microcosm of this transformation. Jin, alongside co-founders Edwin Wang and music artist Matthew Hershoff, built a system where users are rewarded for digital expression through game-like interactions — including AI-generated videos, collectible content, and daily quests. The result was a storytelling-centric platform developed without a traditional coding team — a structure that reflects the emerging blueprint behind many Gen Z–led apps.
Jin previously founded Mediababy, which sold for $3.8 million, according to Reuters. That experience, he said, shaped his belief that platforms thrive when they prioritize user expression and fluid engagement over rigid structure.
At Giggles, that belief translated into a product anchored in prompt-driven creativity, gamified feedback loops, and community-led interaction. As Wang noted, the company positions itself not just as an alternative to TikTok, but as a platform tailored for a generation it believes is increasingly disengaged from traditional social formats. And according to Hershoff, “creators aren’t limited to just posting photos and videos. They can vibe code a game, develop an app, create a whole virtual world and post it on Giggles.”
Can AI-First Startups Scale?
For all the momentum behind AI-native startups, there’s a hard truth facing founders like Jin: culture can spark attention, but infrastructure sustains it. Platforms like Giggles, which thrive on virality and creator energy, eventually confront the same foundational question as any company with ambition. Can they scale securely, reliably, repeatedly and with technical discipline?
At this stage, Giggles is less an anomaly and more a litmus test for how AI is transforming digital entrepreneurship. It’s a living experiment in what happens when creativity, not technical expertise, drives product development. But to evolve from prompt-powered outfits into structured business ecosystems, these companies will need more than just vibes. They will need systems, safeguards and engineering depth.
That’s where founders must reckon with the limits of what vibe coding can achieve. Dohmke’s warning at VivaTech isn’t a dismissal of AI’s potential, but a reminder of where the handoff happens. While AI can accelerate the zero-to-one moment, scaling responsibly requires the engineering rigor to turn a clever idea into a truly dependable platform.
Jin and his team appear to recognize that. While Giggles was built without a traditional engineering stack, the company is now investing in its technical foundation. Wang, the platform’s co-founder and lead developer, acknowledges that “scaling creativity still requires coding discipline.” That doesn’t diminish their AI-first origin; it refines it.
The next test for Giggles — and others like it — isn’t whether AI can launch a product. It’s whether that product can become the infrastructure others depend on.
A Hybrid Future For Founders
What might the next decade yield? The trends point at a wave of hybrid founders: People with vivid creative vision and AI fluency who bring in veteran operators and engineers to solidify their product. That’s the emerging blueprint: rapid prototyping, followed by structural discipline.
Industry stalwart Reid Hoffman sees that promise, noting that “bringing AI into your toolkit makes you enormously attractive.” But he and others caution that early AI advantage doesn’t equal long-term lead. As AI-generated code gets better, so too must practices around testing, review, and security.
In the end, the rise of vibe coding is real, but it’s only half the story. Architecture, execution and human judgment are what matters most. While Giggles, Base44 and the rising “AI-native” wave might be writing the prologue, the plot turns on whether these founders can turn vibe into real structure.
“In the end,” Jin told me, “it’s not just about who can build fast. It’s about who can build something that lasts.”
