What is Vibe Coding? Should You Be Concerned or Excited?

Vibe coding refers to the practice of leveraging AI tools to assist in writing code and building applications. It typically involves giving instructions to AI models, which then generate boilerplate code, structure components, and suggest implementations. While this can significantly boost productivity, it doesn't eliminate the need for a solid understanding of core development concepts.

Effective use of AI in development still requires critical thinking, technical knowledge, and the ability to assess and adapt what the AI produces. Knowing what to build, why to use a particular framework, and how to deploy and maintain it are decisions that cannot be offloaded to an AI. The developer remains responsible for guiding architecture, resolving edge cases, and ensuring long-term code quality.

One of the common pitfalls when learning new technologies—AI tools included—is skipping the foundational learning in favour of copying a “perfect” implementation from a tutorial or online resource. While this might seem efficient in the short term, it often results in a lack of real understanding. Without knowing why something is built a certain way, developers are more likely to misuse it and encounter issues they’re ill-equipped to solve.

A better approach when learning something new—whether it’s a framework, a language, or even how to integrate AI into your workflow—is to build a proof of concept. Start small, create something end-to-end, and spend time exploring its limitations and structure. Writing a few thousand lines of code around a single idea helps build the kind of intuition that no tutorial or AI prompt can replace. It’s through these hands-on efforts that you’ll begin to understand how to apply best practices effectively, rather than just repeating them without context.

For beginners, it’s still essential to learn the fundamentals first—understanding programming logic, data structures, and the environment you’re working in. For most, the web stack is a practical starting point, offering broad opportunities across employment, freelance, and startup paths. AI tools can be great companions in this journey but should support learning—not replace it.

For experienced developers, incorporating AI tools is more about amplifying productivity. Much like the shift that came with the adoption of modern frameworks, AI can accelerate the development process by automating routine tasks. However the design decisions and overall software quality still depend on human expertise.

Ultimately, AI in software development acts like a set of power tools—it can help get the job done faster, but the craftsmanship still comes from the developer.

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[Disclosure: This article is a collaborative effort, combining my ideas with the assistance of LLM for enhanced articulation.]