[V+ AI Perspective] From Idea to Monetization: The Technical Challenges and Opportunities of Vibe Coding
- Chin-Yuan Yang
- Jul 15
- 3 min read
Updated: Jul 30
As the AI wave continues to reshape the landscape of software development and product design, a new term has begun to surface—Vibe Coding. It blends intuition, tools, and inspiration to help creators turn ideas into products faster than ever before. But amid this revolution, some fundamentals remain unchanged.
The Unchanging Foundations of Technology
Despite the rapid evolution of tools, core fields like programming, software engineering, and programming languages remain the solid foundation of the development world. Most programming knowledge still applies, no matter how advanced the tools become. And let’s face it—not everyone wants to learn how to code, let alone dive into complex engineering.
As a result, development tools are diverging into two worlds:
On one side are traditional programming tools favored by professional developers who value flexibility, performance, and scalability. On the other side are low-code/no-code platforms preferred by hobbyists or non-technical users. These tools promise “code-free creation,” allowing beginners to build projects more comfortably—even at the cost of higher complexity behind the scenes.
![[V+ AI 觀察站] 從想法到變現:Vibe Coding的技術挑戰與機會](https://static.wixstatic.com/media/11062b_9456e610ba474c50b4ad5cd8f475d623~mv2_d_5760_3840_s_4_2.jpg/v1/fill/w_980,h_653,al_c,q_85,usm_0.66_1.00_0.01,enc_avif,quality_auto/11062b_9456e610ba474c50b4ad5cd8f475d623~mv2_d_5760_3840_s_4_2.jpg)
Opportunities and Challenges Brought by AI
AI is further blurring the lines between these two worlds. Professional developers can now leverage AI to boost their coding efficiency, while non-coders can use low-code/no-code tools to create products they previously couldn’t build on their own. In a sense, it seems like everyone can become a creator now.
However, even the most powerful tools can’t eliminate the gap between software development and actual productization. Going from prototype to commercialization still requires solid technical knowledge. Deployment, maintenance, and scaling challenges can’t be solved just by dragging and dropping components. Many prototypes that seem promising at first end up being detours—especially when your goal is to build a stable, value-generating system.
The Evolution of Teamwork and Collaboration
From an organizational perspective, AI doesn’t mean the end of traditional roles. The reason companies have front-end developers, back-end engineers, UI designers, and product managers (PMs) is because each of these domains demands deep expertise.
While AI can assist with content generation, the nature of how teams collaborate won’t be completely overturned.
What’s more likely is that each role will expand its boundaries. For example, PMs may need to use AI tools to rapidly prototype products to reduce communication friction and accelerate decision-making. UI/UX designers might need to deepen their technical understanding to create designs that align better with implementation constraints.

Holding on to Core Values
AI can empower every role—but it cannot replace foundational skills, deep user empathy, or the responsibility to deliver real business value.
No matter how smart your tools are, they can’t substitute for attention to detail, a grasp of first principles, or a commitment to outcomes. Users won’t care whether your product was built by AI or by humans. To them, a product is just a product—and it either solves their problem or it doesn’t.
Ultimately, products exist to serve human needs. Tools just help us get there faster and more effectively.
Conclusion: Embrace Change, Hold on to What Matters
What’s changing: tools are more powerful, barriers to entry are lower, and more people want to create.
What’s not changing: the value of deep expertise and the complexity of turning ideas into working, scalable products.
Software engineering may seem like an “old” discipline, but it exists for a reason—it carries decades of hard-earned wisdom and real-world lessons.
AI opens new doors to creativity. But these are starting points—not finish lines. The real challenge is still building products that run smoothly, scale well, and generate lasting business value.
In this era of endless possibilities, we must embrace change—but also stay grounded in the values that truly stand the test of time.
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