Vibe Coding: Beyond the Joke – A Serious Tool for Rapid Prototyping

As developers, we tend to treat “vibe coding” as a joke. The phrase brings to mind a frantic back-and-forth with an AI model, deploying whatever it generates, and never once opening the source code folder. I’ve made the jokes myself, and I’ve tried the workflow enough times to know exactly why it feels ridiculous.

But if you push past that absurdity and look closely, something interesting happens. Vibe coding—when used intentionally—becomes a powerful way to explore new ideas and to move from a hunch to a functioning prototype with surprising speed.

The Principle Behind the Absurdity

At its core, vibe coding is built on a simple principle: optimize for outcomes, not implementation. You describe what you want, the LLM produces code, and you judge the result solely by whether it behaves correctly. If it doesn’t, you adjust your description, run again, and continue refining.

This way of working feels deeply counterintuitive to experienced developers. We know how much real software depends on architecture, conventions, maintainability, and a mental model of the system that an LLM simply cannot hold. Letting an AI rewrite half your project without even looking at the diff is obviously a terrible idea for anything beyond early experimentation.

And that’s the point: vibe coding is not about production. It’s about freeing yourself from the upfront cost of building the scaffolding required to test a concept. It is the software equivalent of sketching, not sculpting.

The “Code Drafter” Mindset

To use vibe coding effectively, you have to change your relationship with the AI. Instead of imagining it as a engineer who might replace parts of your work, treat it as a drafting instrument—a tool that can rapidly materialize ideas in a rough, exploratory form.

It’s similar to how artists use generative tools. No artist expects an AI-generated illustration to be the final centerpiece of a major film, yet these tools are invaluable for exploring ideas, building visual directions, and breaking through conceptual walls. The roughness is a feature, not a flaw: it gives you something to react to.

Vibe coding plays that role in software. It lets you explore the shape of an API, test a framework concept, or lay out the bones of a new architecture without getting bogged down in boilerplate or complex implementation details. You can decide whether an idea feels promising long before you’ve sunk hours into engineering it properly.

The Emergence of Agentic Tools

Where vibe coding becomes even more compelling is with the arrival of agentic development tools such as the Gemini CLI or Opencode. Instead of being a static code generator, the agent runs in a loop that begins to resemble real human problem-solving.

These tools don’t just produce code; they examine your project structure, propose modifications, run commands, read errors, re-interpret situations, and adjust their actions accordingly. The workflow starts to feel less like prompting and more like giving a direction to a collaborator who then takes initiative.

The underlying mechanism is a repeated cycle of observing, reasoning, acting, and correcting. The agent inspects files, thinks about what they imply, decides which edits or commands to apply, and evaluates the result of those actions. That loop continues until the task converges. It is primitive compared to human reasoning, but recognizably patterned after the same cognitive steps.

In practice, working with a CLI agent can feel like supervising an intern who is extremely fast, somewhat literal, and capable of trying many variations without fatigue. You give a goal; the agent figures out the micro-steps. Your job becomes steering rather than typing.

This transforms vibe coding. What traditionally required you—the developer—to run the experiment–observe–adjust loop now becomes something the agent can partially internalize. You move up a level of abstraction, from “write this code for me” to “make this behavior happen,” and the agent handles the details.

A Concrete Example: Prototyping a Dart Framework

This approach recently proved invaluable when I explored whether a Svelte-like template syntax could be used to generate Dart code for a full-stack framework—something the Dart ecosystem currently lacks (Jaspr is cool, but too different from existing patterns in my opinion).

Traditionally, I would have spent days writing a parser, scaffolding the file structure, and building enough logic to see whether the idea felt right in practice. Instead, I used Opencode with Gemini 3 Pro and described the framework from the perspective of the developer experience I wanted. The model generated a functioning template parser on the first attempt. I tested it, refined the API, and evolved the idea through an iterative conversational process.

By the end of the afternoon, I had a working prototype—something concrete enough that I could evaluate the ergonomics of the whole approach. The result is now available as aloisdeniel/silhouette on GitHub if you're curious. Without vibe coding, I doubt I would have even considered exploring the idea.

Why This Matters

Vibe coding is easy to dismiss because it violates so many of our instincts as engineers. Yet its value lies precisely in its disregard for polish and best practices. It lowers the barrier to exploration. It lets you test more ideas than you otherwise could. It encourages curiosity by making it inexpensive.

You don’t need to use it for production code. But if you let yourself experiment with the absurd, you might discover ideas, tools, or directions that would have remained untested otherwise. The workflows that feel strange today may become the foundations of tomorrow’s development practices.