Author's): Prineet Kaur 👩💻
Originally published in Towards Artificial Intelligence.
ANDjust describe what I want, run, customize, repeat. — A rough paraphrase of how many beginner programmers are currently approaching “vibration coding”
We've all read articles about “vibration coding” lately – a trend where code creation is less about writing every line and more about driving AI tools through intent, feedback, and iteration.
If traditional programming is about precision, vibrational coding is about intention, feedback, and flow. You describe what you want, let the AI generate it, and then you steer, tweak, and strengthen it until it fits.
But what works well, what doesn't, and how should developers implement it responsibly?
Let's explore 🚀
1. What is the buzz around “Vibe Coding”?
At its core, vibration coding means building software by communicating your intentions to an AI system – describing what needs to be built, seeing how it builds, and refining it until it feels right.
Instead of writing every feature from scratch, developers act as curators or guides, using AI tools to support work. The result is faster iteration and expanded creative scope.
This approach doesn't erase engineering skills – it redefines them. You still need to understand architecture, testing and debugging. But the focus shifts from writing syntax to managing behavior.
👉 Vibe encoding does not mean zero encoding. This is AI-powered coding where your role moves from micromanaging details to controlling, correcting, and orchestrating.
2. Immerse yourself in the Vibe coding approach
Vibe coding is based on a simple workflow loop that can be summarized as follows:
- Describe your intentions clearly — “For example, I need a Metrics API that reports daily usage.”
- Let artificial intelligence support your project – immediately provides the initial code skeleton (e.g. folder structure, configuration files and environment configuration)
- Run and watch – Execute it, review logs, identify vulnerabilities.
- Improve through feedback – Customize prompts, ask for tests, or improve logic.
- Validate and integrate – Add tests, polish your nomenclature, and ensure security.
👉 Key insight: you don't just “build the AI to code” – you drive the AI, validate it, cleanse it, and integrate it. Expertise changes.
3. A practical example of Vibe coding in practice
Let's see how vibe coding works in practice for a small project.
Let's look at an example of a small project “Metrics API“
Purpose as a programmer: : Create an endpoint that returns basic account usage metrics (requests per day, errors, latencies).
Step A: Describe the intention (with AI prompts)
An example prompt might be ⤵️
“Build a /metrics/usage Node.js Express route that returns a JSON object with today's request count, error count, and average latency. Include error handling.”
Step B: Run and Observe (Viewing AI Results)
Expect it generated hash*as below ⤵️
(*a basic version of the code that will have the appropriate shape and structure, but will only have minimal or false logic inside)
app.get('/metrics/usage', async (req, res) => {
try {
const usage = await getUsageData(req.user.id);
res.json({
requests_today: usage.requests,
errors: usage.errors,
latency_ms: usage.latency
});
} catch (err) {
res.status(500).json({ error: 'Internal Server Error' });
}
});
It is functional, but you notice the lack of authentication and default settings.
Step C: Iterate (rapid refinement)
Sample prompt ⤵️
“Add a 401 response if no user is logged in, and if no data is available, the default value is zero.”
Sample corrected output after the above:
app.get('/metrics/usage', async (req, res) => {
if (!req.user) return res.status(401).json({ error: 'Unauthorized' });try {
const usage = await getUsageData(req.user.id) || { requests: 0, errors: 0, latency: 0 };
res.json(usage);
} catch (err) {
res.status(500).json({ error: 'Internal Server Error' });
}
});
Step D: Verification and integration (improve security)
Sample prompt ⤵️
“Write a unit test for this endpoint.”
The AI prepares the test and you refine it, check it and incorporate it into your code.
👉 It is the encoding of vibrations in motion — intention, iteration, validation.
4. Now let's talk about the risks of Vibe encoding
Although vibration encoding can accelerate development, it is not always the right approach.
Common pitfalls when coding Vibe
Even with AI in your toolbox, it's easy to fall into bad habits. Here are the pitfalls most developers fall into – and how to avoid them:
- Over-reliance on AI results: The code may seem clean, but it harbors minor bugs or security vulnerabilities. Treat each AI commit like a PR for a junior teammate – review them carefully.
- Fragmented Architecture: Mixing snippets from different prompts without structure leads to messy and incoherent systems. Remember about a clear architecture, not just a set of “cool results”.
- Immediate fatigue: Constantly rewriting prompts instead of improving your design is a waste of time. Focus on clarity, not cleverness.
- More difficult debugging: Unless you wrote the logic yourself, tracking failures can be like digging into someone else's brain. Add logs, tests and comments early.
- Drift code style: AI tools don't always follow your team's coding conventions. Use linters, formatters, and reviews to maintain consistency.
- Surprise Scaling: What works well in a demo may break down on a large scale. As projects evolve, revisit AI-generated sections and refactor with purpose.
- Ethical and licensing blind spots: Some AI results may reproduce licensed code or biased patterns. Always check, clean and get the final implementation.
When not to use Vibe encoding
Vibe encoding is not a silver bullet. There are times when precision, not automation, is needed. Avoid this when working on:
→ Safety-critical systems -Anything related to authentication, encryption, or sensitive data deserves handwritten, peer-reviewed code.
→ Performance-driven paths – Real-time processing, memory optimization, or hardware-level logic still require human-tuned craftsmanship.
→ Legacy systems with delicate dependencies – One wrong abstraction can flow through the stack. Manual controls beat AI shortcuts here.
→ Basic business logic – Modules that your team needs to fully understand and maintain for years should be written intentionally, not prompted.
👉 In such cases traditional, hand-coded, peer-reviewed papers still win.
5. Finally: “How to use atmosphere in Vibe coding”
Here's how to get the most out of vibration encoding without losing control:
- Start small — Use it for scripts, tools and prototypes before core systems.
- Use prompts intentionally — Think of them as mini-specs.
- Add tests earlier — Treat tests as part of the conversation.
- Enforce structure — Apply style guidelines and architecture to your design.
- Evaluate like a team member — AI code still deserves human review.
- Track what works — Write down good tips, reuse them and create an internal manual.
👉 more structure AND the feedback you bring, the better the “climate” becomes.
6. The bigger picture: take it with you 🙌
Vibe coding isn't about replacing developers – it's about empowering developers. It frees you from templates and repetition, allowing you to focus on flow, design and creative problem solving.
While you still need a technical assessment, apply it earlier and faster 🚀
The skill of the future is not just “knowing syntax” – it is the ability to drive intelligent tools to produce reliable results.
👉 Question to think about: “How much do you trust AI in your workflow today? — and where do you still draw the line?”
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Published via Towards AI
