There is a new trend taking over software development. It is fast, intuitive, and a little chaotic. It is called “Vibe Coding.”
This approach lets developers build applications by simply describing what they want in plain English, letting an AI agent write the code, and then rolling with it. But is it ready for prime time? And how can you do it safely?
This post breaks down what vibe coding is, where it works best, and how to level up from a quick demo to production-ready code using techniques like spec-driven development.
What is Vibe Coding?
Imagine working on a project in your IDE. On one side, you have your file structure. On the other side, you have an AI assistant (like a Copilot or agentic coding tool) embedded directly in your editor.
Instead of manually typing out every class and function, you simply type a request:
“Create a Java project for a banking API with these specific dependencies.”
The AI thinks about your request, looks at your existing code, and generates the necessary files. It pops up a suggestion: “Add this file?” You click approve. You run a command to test it. Maybe it works, maybe it breaks. If it breaks, you copy the error message back to the AI, and it fixes it on the fly. Boom. The demo is working.
That, in a nutshell, is vibe coding.
It is a specific use case for agentic AI where the “agent” (the code editor) has access to your project and the tools to write and edit files. You are essentially “giving into the vibes,” trusting the AI to figure out the implementation details while you focus on the high-level direction.
The Good: When Vibe Coding Shines
Vibe coding is an incredibly fast and fun way to build. It excels in specific scenarios:
- Scaffolding New Projects: Quickly spinning up a new application with the right structure and dependencies.
- Building Demos and MVPs: Getting a working prototype in front of users as fast as possible.
- Creating Scripts and CLIs: Generating utility scripts or command-line tools without writing every line from scratch.
- Exploring a Codebase: Asking questions like “What is my project structure?” or “How does this function work?”
The Bad: The Risks of Vibing Too Hard
However, if you are building for production, there are significant risks. When you skip reading the generated code, you skip traditional software development safeguards:
- Hallucinations: The AI might make up functions, libraries, or logic that don’t exist.
- Security Vulnerabilities: You might accidentally hardcode API keys or introduce insecure dependencies.
- Lack of Testing: Vibe coding often skips writing the tests that prove the code actually works.
- Technical Debt: Without reviews and documentation, you can end up with a codebase that no one understands.
How to Be a Better Vibe Coder (Without Breaking Things)
So, how can you capture the speed of vibe coding without the chaos? It requires a shift in process. Here are the best practices to take your AI-assisted code from “demo” to “shippable.”
1. Architect First, Code Second (Spec-Driven Development)
Before you ask the AI to write a single line of code, define the blueprint. A great strategy here is spec-driven development.
Instead of just saying “build a banking API,” you first write (or generate) a clear specification or outline. For example:
- “The API will have a
/usersendpoint.” - “It will use JWT for authentication.”
- “It will connect to a PostgreSQL database.”
This gives your coding agent a checklist to follow. You can cross off items as they are implemented, ensuring the AI stays on track and meets the desired outcomes. This is the architectural phase, and it prevents the AI from wandering off into the weeds.
2. Write Tests First (Test-Driven Development)
One of the most deterministic ways to ensure your vibe-coded app works is to write the tests before the code.
Write a test that says “When I call this endpoint, I expect this response.” Then, let the AI coding agent write the code to make that test pass. This creates a feedback loop where the AI can run the tests (using tools in the terminal) and iterate until the checks turn green.
3. Keep Tools and Dependencies Updated
Make sure your coding agent has access to the latest information. Using protocols like the Model Context Protocol (MCP) allows the AI to fetch the newest library documentation or run automated tests without you touching the terminal. This keeps the AI from using outdated or deprecated code.
4. Version Everything
As the AI adds features, you need to track the changes. Use Git rigorously. Commit each successful change. This structure allows you to revert to a previous state if a new feature breaks something, letting you go back and forth as needed.
5. Review with a Second Pair of (AI) Eyes
Reviewing AI-generated code can sometimes take longer than writing it yourself. The basics still apply:
- Lint and Type Check: Ensure the code meets basic quality standards.
- Security Scanning: Scan dependencies for known vulnerabilities. Check for hardcoded secrets.
- Use a Reviewer Agent: Have a separate AI agent review the code written by your vibe coding agent. An outside perspective can spot security risks or logical flaws that the original coder missed.
Vibe coding is powerful. It lowers the barrier to entry and accelerates development like never before. Fortunately, most modern coding agents are already capable of adapting to your project’s practices. They can be prompted to help with architecture, implementation, and even review.
Watch the Video
The video below contains the original explanation from IBM Technology that this post was based on.