Vibecoding: The New Way to Build Products

We built our last prototype in 4 hours. Not a mockup—a working product with authentication, payments, and real users. No massive team. No months of planning. Just one engineer, an AI coding assistant, and a clear outcome in mind.

This is vibecoding. And it’s changing everything about how products get built.

What Is Vibecoding?

The term was coined by Andrej Karpathy in February 2025, but the practice emerged the moment AI coding tools crossed the capability threshold. Vibecoding is outcome-driven development where you evaluate results instead of reviewing code line-by-line.

You describe what you want. AI generates the implementation. You test if it works. You iterate based on behavior, not syntax.

It’s the difference between “does this function return the correct value?” and “did we fix the checkout bug?”

Traditional coding: You write code, review code, debug code.

Vibecoding: You define outcomes, AI writes code, you validate outcomes.

The shift is fundamental. You’re no longer a typist debugging semicolons—you’re a product architect validating systems.

The Tools Making It Possible

Four platforms dominate the vibecoding landscape:

Cursor leads with a $2.6B valuation and $100M ARR. It’s VS Code on steroids—AI pair programming that actually understands your codebase. Context-aware suggestions, full-file generation, and chat-driven refactoring. Engineers love it because it feels familiar while being radically more powerful.

Lovable and Bolt.new took a different approach: natural language to deployed app in minutes. No local setup. No git workflows. Just describe your product and watch it materialize. Perfect for non-technical founders who need MVPs yesterday.

v0 by Vercel focuses on React components. Show it a screenshot, get production-ready code. It’s vibecoding for the UI layer—fast, focused, and surprisingly accurate.

Each tool has a sweet spot. Cursor for engineers who code. Lovable for founders who don’t. v0 for designers who need implementation. Bolt for anyone who needs speed above all else.

The Numbers Don’t Lie

25% of Y Combinator’s Winter 2025 batch reported codebases that are 95% AI-generated. Let that sink in. A quarter of the world’s most competitive startup cohort is shipping products written almost entirely by AI.

These aren’t toy projects. They’re venture-backed companies building for millions of users.

Cursor’s growth trajectory tells the same story: $100M ARR in under two years. Developers voted with their wallets. The era of AI-assisted development isn’t approaching—it arrived.

Solo founders are driving much of this shift. 38% of startups in 2024 were solo-founded, up from 22.2% in 2015. Why? Because one person with AI tools can now do what required a full team five years ago.

The math is brutal: 10 engineers with AI tools deliver output equivalent to 100 traditional developers. Not 10x productivity. 10x capability. There’s a difference.

Productivity means you write code faster. Capability means you ship features you couldn’t have built alone.

When Vibecoding Wins

Vibecoding excels in specific scenarios. Know when to use it:

Prototyping and MVPs

Building to test assumptions? Vibecoding dominates. You need speed to insight, not architectural perfection. Ship in days, learn from users, iterate or kill. AI handles the boilerplate. You handle the learning.

We use vibecoding for every first version. Get the product in front of users before you’re emotionally attached to the implementation. Fast feedback trumps clean code at the validation stage.

Standardized Features

Authentication flows. Payment integrations. CRUD operations. Email verification. Password resets. These problems are solved. AI knows the patterns. Why spend days reimplementing what’s been built a million times?

Generate it, test it, move on. Save your brain cycles for actual product differentiation.

Rapid Experimentation

Testing new features? A/B testing different flows? Exploring product directions? Vibecoding gives you the velocity to try ten ideas instead of one. Most will fail. That’s the point. Fail fast, learn faster.

Solo Founder Scenarios

If you’re building alone, vibecoding is your unfair advantage. You can’t hire a frontend engineer, a backend engineer, and a DevOps engineer. But you can describe what each layer should do and let AI generate the initial implementation.

Not perfect code. Working code. Ship, validate, refine.

The Hard Truths About AI-Generated Code

Now the part most advocates skip: 45% of AI-generated code contains security vulnerabilities.

Not might contain. Does contain.

We’re not talking about style violations or inefficient algorithms. We’re talking about SQL injection vulnerabilities, authentication bypasses, exposed API keys, and broken access controls.

AI tools are trained on public repositories—including the 40% of GitHub that contains known vulnerabilities. The model doesn’t distinguish between good patterns and dangerous ones. It optimizes for “looks right,” not “is secure.”

Quality Issues You’ll Hit

Inconsistent architecture. AI generates code file by file. It doesn’t maintain architectural coherence across a codebase. You’ll see three different state management patterns, two conflicting API conventions, and database queries that work but don’t scale.

Hidden technical debt. The code runs. Tests pass. Users can click buttons. But the implementation is a house of cards. Fragile error handling. Tight coupling. Hard-coded assumptions. You won’t notice until you need to change something fundamental.

Scalability blind spots. AI optimizes for working code, not scalable code. That database query works fine with 100 rows. It dies at 100,000. The file upload succeeds at 1KB. It times out at 10MB. You discover this in production, not during generation.

Maintenance nightmares. Six months later, you need to modify a feature. The AI-generated code has no clear mental model. No architectural rationale. No documentation about why decisions were made. You’re debugging someone else’s code—except there’s no one to ask.

When Traditional Development Wins

Vibecoding is a tool, not a religion. Use it where it helps. Abandon it where it hurts.

Production systems require human architecture. Once you’re past validation and into scale, you need engineers who understand system design. Database optimization. Caching strategies. Error handling. Monitoring. Security hardening.

AI can generate implementations. It can’t design systems that handle millions of users.

Complex business logic demands human judgment. If your product’s value is in algorithmic sophistication, domain-specific logic, or novel problem-solving, vibecoding won’t get you there. AI handles the common case. You handle the unique case.

Regulated industries need audit trails. Healthcare, finance, legal tech—if you need to prove code correctness or trace decisions, AI-generated code is a liability. You need human-reviewed, well-documented implementations with clear accountability.

Long-term codebases need maintainability. Building for years, not months? Invest in architecture. Code review. Testing. Documentation. Vibecoding optimizes for speed to first version. Traditional development optimizes for speed to hundredth version.

Our Approach at Vibery

We use both. Strategically.

Phase 1: Vibecoding for validation. New product idea? We vibecode the MVP. Ship in days. Get it in front of users. Learn if the concept has legs. Most ideas fail here. Better to fail with 10 hours invested than 10 weeks.

Phase 2: Traditional development for production. Concept validated? Users want it? Now we rebuild with intention. Proper architecture. Security review. Performance optimization. Test coverage. The stuff that doesn’t matter until it matters completely.

This isn’t about AI versus humans. It’s about using the right tool for the job.

Vibecoding gives us speed to insight. Traditional development gives us production quality. We need both.

The Honest Workflow

Here’s what vibecoding actually looks like for us:

Define the outcome. Clear spec. Specific success criteria. “Users can create an account, log in, and see their dashboard.”
Generate initial implementation. Use AI to create the feature. Full stack. Frontend, backend, database schema.
Test the outcome. Does it work? Not “is the code elegant?”—does the feature do what we need?
Security audit. Always. Every AI-generated feature gets manual security review. Check for common vulnerabilities. Fix what’s broken.
Refactor or rebuild. If it’s a prototype, leave it ugly. If it’s going to production, refactor or rewrite the critical paths. Especially auth, payments, and data handling.
Document the why. AI generates the what. Humans document the why. Future you will need context the model doesn’t have.

We’re not religious about it. Some features get vibecoded and shipped as-is. Others get vibecoded and completely rewritten. The deciding factor is always: how much does code quality matter for this specific feature at this specific stage?

What This Means for Founders

If you’re building a product in 2025, here’s the tactical reality:

Vibecoding lowers the barrier to validation. You don’t need a technical co-founder to test if your idea works. You need clarity about what you’re testing and users willing to try it.

Use AI to get to version one. Use humans to get to version ten.

But don’t ship production systems you don’t understand. If you can’t read the code, you can’t maintain it. If you can’t maintain it, you don’t own it. If you don’t own it, you’re one breaking change away from rebuilding everything.

Technical debt isn’t evil. Unmanaged technical debt is.

Speed matters, but direction matters more. Vibecoding lets you build fast. Make sure you’re building toward something real. Fast iteration on bad ideas is just expensive learning. Learn, but learn with intention.

Security cannot be vibecoded. Period. Get human eyes on authentication, authorization, data handling, and API security. The 45% vulnerability rate isn’t a suggestion—it’s a guarantee that bad code exists in your AI-generated codebase. Find it before attackers do.

The Broader Shift

Vibecoding is part of a larger transformation. Code generation is becoming commoditized. Building is accessible. The bottleneck isn’t “can you build it?”—it’s “should you build it?”

Product judgment is the new scarce skill. Knowing what to build. Who to build for. How to position it. Where to distribute it. These questions don’t have AI-generated answers. They require taste, insight, and deep understanding of human behavior.

Distribution remains the moat. A thousand founders can vibecode the same product. Only one has the audience, the brand, the trust, the channels that convert users. Build something people want—but more importantly, build relationships that let you reach them.

Taste compounds. AI averages the internet. Great products deviate from average in intentional ways. Your job is to know where to deviate and why. That’s taste. It develops through shipping, feedback, and iteration.

Where Vibecoding Goes Next

The tools will get better. The vulnerabilities will decrease. The code quality will improve. AI coding assistants will understand architecture, not just syntax.

But the fundamental dynamic won’t change: AI generates options, humans make choices.

You’ll always need judgment about what to build, taste about how it should feel, and understanding of why certain implementations matter. The AI handles the mechanical translation from intent to code. You handle everything that makes the product worth building.

The engineers who thrive won’t be the ones who resist AI. They’ll be the ones who use it strategically—vibecoding where speed matters, traditional development where quality matters, and always knowing the difference.

The founders who win won’t be the ones who can code. They’ll be the ones who know what to build and who to build for. Vibecoding gives you the implementation. Product insight gives you the outcome.

The Vibery Perspective

We’re practitioners, not evangelists. We vibecode when it helps. We traditional-code when it matters. We measure results, not religious adherence to methodologies.

Here’s what we know for certain:

Building products is faster than ever. Building great products is just as hard as always. The tools changed. The principles didn’t.

Ship fast. Learn faster. Build for humans, with AI.

That’s vibecoding. That’s how we work. That’s the new way to build products—when you know when not to use it.

Building something ambitious? We work with technical founders who value speed and sustainability in equal measure. Join our waitlist to explore how we can help you ship faster without sacrificing what matters.