Don't Want to Vibe Code Yourself? What Users Really Want Is Better Software

A Single Statement Ignites the AI Programming Route Debate

Five months after AI programming tools swept the globe, prominent American policy commentator Matthew Yglesias posted a thought-provoking take on social media: "Five months in and I think I've decided — I don't want to Vibe Code myself. What I want is for professionally managed software companies to use AI coding assistants to produce more, better, and cheaper software products, and then sell them to me."

This brief statement precisely struck a blind spot overlooked in the current AI programming narrative: Who should be the biggest beneficiary of AI programming — programmers, everyday users, or software companies?

The Vibe Coding Craze and the Reality Gap

From late 2024 to early 2025, the concept of "Vibe Coding" rapidly gained traction. Coined by Andrej Karpathy, the term describes an entirely new approach to programming — users simply describe their requirements in natural language, and AI automatically generates the code. Developers don't even need to read the code line by line; they just "go with the feeling" to push projects forward.

Social media was suddenly flooded with stories of people "building an app in three hours with zero coding experience using AI." Vibe Coding seemed to proclaim: Everyone can be a developer, and the barrier to software development is approaching zero.

But Yglesias's perspective represents the true sentiments of another massive group — the vast majority of people have no desire to become developers. What they've always wanted is not "the ability to write their own software" but rather better, more affordable software products.

Two Paths: Democratization vs. Professional Enhancement

The AI programming space currently features two distinctly different development paths:

Path One: Democratization of programming. Represented by tools like Cursor, Replit Agent, and Bolt, this approach enables non-technical users to build applications through natural language. It emphasizes "everyone can code" and aims to bridge the gap between technical and non-technical populations.

Path Two: Professional productivity multiplication. Represented by GitHub Copilot, Devin, and Amazon CodeWhisperer, this approach helps professional development teams dramatically boost productivity. It doesn't alter the fundamental structure of the software industry but enables professional teams to deliver higher-quality products at lower costs.

Yglesias clearly sides with the second path. His logic is straightforward: software development is far more than writing code — it involves architectural design, security assurance, ongoing maintenance, user experience optimization, and a host of other professional disciplines. There is an enormous quality gap between an application cobbled together with Vibe Coding and a product refined by a professional team.

The Overlooked 'Consumer Perspective'

The tech industry has long been accustomed to discussing the value of AI programming from the "producer's perspective" — how much developer efficiency has improved, how accurate code generation has become, and how many non-technical people have learned to code.

But Yglesias reminds us of a fundamental economic principle: The ultimate value of technological progress should be reflected in improved quality and lower prices of end products.

If AI programming tools can reduce a SaaS company's development costs by 40%, the ideal outcome is not for users to cobble together a crude substitute themselves, but for that company to:

• Offer services at lower subscription prices
• Iterate and fix bugs faster
• Develop features that were previously too costly to implement
• Serve niche user segments that were previously ignored because the market was too small

This is how AI programming technology truly benefits the masses.

Deeper Implications for the Industry

This discussion reveals a key tension in the commercialization of AI programming. Currently, many AI coding tool companies focus their marketing on the "everyone can code" narrative. While this certainly helps expand user bases and boost fundraising valuations, it may be missing the larger market opportunity.

In reality, the enterprise AI coding assistant market is far larger than the individual Vibe Coding market. According to McKinsey estimates, AI-assisted programming could unlock hundreds of billions of dollars in annual productivity value for the global software industry. Releasing this value depends primarily on professional software teams deeply integrating AI tools, not on scattered attempts by individual users.

Moreover, the Vibe Coding model faces a series of real-world challenges: uncontrollable code quality, security vulnerability risks, long-term maintenance difficulties, and data privacy concerns. For personal projects or prototype validation, these issues may be acceptable. But for production-grade software intended for long-term use, professional development remains irreplaceable.

Looking Ahead: The Value of AI Programming Will Ultimately Return to the Product Itself

Yglesias's view is not a rejection of AI programming tools' value. Quite the opposite — he holds even higher expectations for AI programming: not enabling ordinary people to barely produce code that runs, but empowering professional teams to create truly outstanding software products.

With the rise of the Agentic Engineering paradigm, AI is evolving from "code completion" to "autonomous development." In the future, the biggest winners in AI programming may not be individual users who learned Vibe Coding, but software companies that are first to deeply integrate AI into their R&D workflows — and ultimately, the billions of consumers who enjoy better products as a result.

The value of technology must ultimately be delivered to users through products. This is perhaps the most important piece of common sense worth remembering amid the AI programming boom.