I vibe coded a 7-figure tool for my startup. Here are the 4 steps I followed — and how I avoided coding slop.
John Hu left a banking career and his MBA program to build Stan. He and his cofounder went on to vibe code Stanley, an AI tool, in just 14 days.
John Hu left a banking career and his MBA program to build Stan. He and his cofounder went on to vibe code Stanley, an AI tool, in just 14 days. This
Read Full Story at Business Insider Mkt →Why This Matters
The rise of "vibe coding"—rapid, iterative development fueled by intuition and AI assistance—challenges traditional notions of startup timelines and technical rigor. This approach signals a shift where speed and adaptability may outweigh the need for exhaustive planning, empowering non-traditional founders to compete in tech’s highest stakes without legacy constraints. It also underscores how AI is democratizing software creation, potentially reshaping the balance between elite engineering talent and accessible innovation.
Background Context
Silicon Valley’s latest wave of AI-driven startups often prioritizes rapid iteration over polished code, but venture-backed teams still face pressure to demonstrate technical depth. Meanwhile, the decline of mid-tier engineering roles in favor of specialized "10x" builders has created a skills gap where foundational knowledge is sometimes sacrificed for output. This backdrop makes "vibe coding" both a symptom of the current tech culture and a strategic workaround for founders navigating an increasingly complex tooling landscape.
What Happens Next
If "vibe coding" gains wider adoption, we may see a bifurcation in software development: one track for high-stakes, mission-critical systems where precision is non-negotiable, and another for experimental or MVP-stage projects where speed trumps perfection. Regulatory scrutiny could also emerge as AI-generated code proliferates, raising questions about liability for bugs or failures. Meanwhile, incumbents like traditional SaaS providers may face pressure to either adopt AI-assisted workflows or defend their slower, more deliberate processes.
Bigger Picture
This story fits into a broader trend where AI is redefining the cost and speed of innovation, blurring the lines between prototype and product. As industries from healthcare to finance experiment with AI-driven tools, the tension between "good enough" solutions and robust, scalable systems will intensify. The success of a tool like Stanley may embolden a new generation of founders to bypass conventional gatekeeping, but it also risks normalizing technical debt in an era where software increasingly underpins global infrastructure.
