Vibe coding is the practice of building software by describing what you want in natural language and letting AI generate the code. It's changing how apps are built—here's what you need to know.
Vibe coding (n.): A software development approach where developers describe their intent in natural language and AI generates functional code. The developer focuses on the "vibe" or vision of what they want, while AI handles implementation details.
Term popularized by Andrej Karpathy (2025). Also known as: prompt-driven development, AI-assisted coding, conversational programming.
73% of vibe-coded apps have security vulnerabilities before review. AI optimizes for working code, not secure code. Here are the most common issues:
The good news: these issues are fixable. Scan your app before deployment to catch them.
Vibe coding is powerful, but it needs a security checkpoint. Scan your AI-generated app to find and fix vulnerabilities before they become problems.
Scan Your App FreeVibe coding is a development approach where you describe what you want in natural language and AI generates the code. The term was coined by Andrej Karpathy to describe coding by 'vibes'—expressing intent through prompts rather than writing code directly. Tools like Lovable, Cursor, and Copilot enable vibe coding.
The term 'vibe coding' was popularized by Andrej Karpathy (former Tesla AI Director and OpenAI researcher) in early 2025. He described it as a new paradigm where developers focus on expressing what they want rather than how to implement it.
Not quite. No-code uses visual builders with pre-built components. Vibe coding generates actual code from natural language prompts—you get real source code you can modify, deploy anywhere, and own completely. It's closer to traditional coding but with AI as your pair programmer.
Yes, but with caveats. AI-generated code can be production-ready, but it often has security vulnerabilities. 73% of vibe-coded apps have security issues before review. You can absolutely ship to production, but scan and secure the code first.
Not by default. AI prioritizes functional code over secure code. Common issues include missing database security, exposed API keys, and weak authentication. However, these are fixable—scan your app, apply security best practices, and review AI-generated code before deploying.
Not necessarily for simple apps. However, understanding code helps you review AI output, debug issues, and make modifications. For production apps handling real user data, some technical knowledge is valuable for security review.
Last updated: January 16, 2026