Vibe coding is building software by describing what you want in natural language while an AI code editor generates, runs, and fixes the code. Coined by Andrej Karpathy, it shifts the developer’s job from writing syntax to directing AI, reviewing output, and making architecture decisions—collapsing the distance between idea and working prototype from months to hours.
A practical, jargon-free guide for Indian engineering teams and founders — part of the Learn AI with Reeturaj series on InBharat AI.
I watched a product manager with no coding experience build a working prototype in 90 minutes. Not a wireframe. Not a mockup. A functional web application with a database, API endpoints, and a user interface. Using nothing but plain English prompts and an AI code editor.
Two years ago, I would have called this impossible. Today, it's called vibe coding. And it's about to reshape who builds software in India.
Vibe coding is a development approach where you describe what you want in natural language and AI generates the code. You don't write syntax. You describe intent. "Build me a dashboard that shows daily UPI transaction volumes with filters for merchant category and city." The AI builds it.
The term was coined by Andrej Karpathy—the former Tesla AI director—and it captures something real. When you vibe code, you're having a conversation with an AI coding partner. You describe the vibe of what you want. The AI translates that vibe into implementation. You review, adjust, and iterate through conversation rather than through manual coding.
This isn't autocomplete on steroids. It's a fundamentally different way of interacting with software creation. The developer's job shifts from writing code to directing AI, reviewing outputs, and making architectural decisions.
Tools like Cursor, GitHub Copilot Agent mode, Replit, and Windsurf enable this today. They understand your entire project context, generate multi-file changes, run the code, see the errors, and fix them—all from your natural language descriptions.
India has 2.4 million software developers. But India also has millions of domain experts—in agriculture, healthcare, education, government, logistics—who understand problems deeply but can't code solutions themselves.
Vibe coding bridges this gap. A doctor in Jaipur who understands patient management workflows can now describe an appointment scheduling system and watch it come to life. A school principal in Coimbatore who knows what parents need can describe a parent communication app and build a working prototype.
This doesn't mean these domain experts will build production systems alone. It means they can create prototypes that communicate requirements better than any product specification document. It means they can validate ideas before hiring an engineering team. It means the distance between "I have an idea" and "I can show you what I mean" collapses from months to hours.
For the Indian startup ecosystem, this changes the economics of experimentation. Testing a business idea used to require ₹5-10 lakhs in development costs to build an MVP. With vibe coding, a founder can build a testable prototype over a weekend with zero engineering spend. The bad ideas die faster. The good ideas get validated sooner.
Don't mistake vibe coding for amateur hour. The best professional developers I know are using it to supercharge their workflow.
A senior engineer in Bangalore described his process: "I vibe code the first draft, then I engineer it properly." He uses natural language to generate the initial structure—components, APIs, database schemas—in minutes. Then he reviews every line, refactors for production quality, adds proper error handling, writes tests, and optimizes performance.
This approach cuts his development time by 40-50%. He's not writing less code. He's spending less time on code that follows predictable patterns and more time on the code that requires his specific expertise and judgment.
Another team I know uses vibe coding for rapid prototyping during sprint planning. Instead of estimating how long a feature will take, they build a rough prototype in the planning meeting itself. This makes estimation dramatically more accurate because the team sees the actual complexity, not imagined complexity.
For Indian engineering teams running tight sprints with aggressive deadlines—which describes most Indian startups I know—this acceleration in prototyping and initial implementation is transformative.
I need to be honest about the downsides, because the hype around vibe coding can be dangerous.
Vibe-coded applications without expert review are often fragile. The AI generates code that works for the happy path but breaks on edge cases. For a demo, that's fine. For a production system processing UPI payments for 10 lakh users, it's a disaster waiting to happen.
Security is a genuine concern. Vibe-coded applications may include SQL injection vulnerabilities, insecure authentication flows, or exposed secrets. The AI doesn't think about attackers. It generates functional code, not secure code. Every vibe-coded application needs security review before production deployment.
Debugging vibe-coded applications is hard when developers don't understand what the AI generated. If you can't read the code, you can't fix the code when it breaks at 3 AM. Indian teams should ensure that at least one engineer on every project deeply understands every piece of generated code.
Technical debt accumulates fast with vibe coding. AI generates solutions that work but aren't always well-architected. Without deliberate refactoring, vibe-coded applications become maintenance nightmares.
At InBharat.ai, we've adopted a structured approach to vibe coding that captures the speed benefits while managing the risks.
Vibe code for prototypes and first drafts. Let AI generate the initial implementation quickly. This is where the biggest time savings come from.
Engineer review for production code. Every piece of vibe-coded output goes through the same review process as manually written code. Security scanning, code review, testing—no shortcuts.
Domain experts vibe code requirements. Instead of writing PRDs, our product team describes features through vibe coding. The working prototype replaces pages of specification documents. Engineers then rebuild it properly with production standards.
Continuous learning from AI output. When the AI generates a pattern you haven't seen before, investigate it. Sometimes the AI knows techniques you don't. Sometimes it generates anti-patterns. Either way, you're learning.
Vibe coding isn't replacing software engineering. It's democratizing the first step—turning ideas into working code. The engineering discipline of making that code reliable, secure, and scalable still requires humans.
But it's changing who can take that first step. And in a country of 1.4 billion people with unlimited ideas and limited developers, that change matters enormously.
What is vibe coding? A development approach where you describe intent in plain language and an AI editor (Cursor, Copilot Agent mode, Replit, Windsurf) generates multi-file code, runs it, sees errors, and fixes them. You review and iterate through conversation.
Is vibe coding only for non-developers? No. Senior engineers "vibe code the first draft, then engineer it properly"—generating structure fast, then refactoring, securing, testing, and optimizing. It cuts initial implementation time 40–50%.
What are the risks of vibe coding? Vibe-coded apps are fragile on edge cases, may include SQL injection or exposed secrets, are hard to debug if you can't read the generated code, and accumulate technical debt. Every output needs security review before production.
Why does vibe coding matter for India? India has millions of domain experts—doctors, teachers, farmers—who understand problems but can't code. Vibe coding lets them build working prototypes to validate ideas before hiring engineers, cutting MVP cost from ₹5–10 lakh to a weekend.
Should vibe-coded code go straight to production? No. Vibe code for prototypes and first drafts; apply full engineering review—security scanning, code review, testing—for anything production-bound, especially systems handling UPI payments at scale.
Reeturaj Goswami is the founder of InBharat.ai, building AI built in India, for India. He writes about technology, startups, and scaling in the Indian ecosystem.
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