You Described It. AI Built It. Now What?
You sat down with ChatGPT, Cursor, or Claude and described the app you wanted in plain English. Within hours, you had a working prototype. Screens rendered, buttons clicked, data flowed. It felt like magic — like the future had finally arrived. This is vibe coding, and it was officially named the word of the year 2025.
But here’s what nobody tells you: that beautiful prototype is almost certainly not going to production.
Vibe coding has democratized the ability to create software prototypes at lightning speed. Entrepreneurs, designers, and non-technical founders can now go from idea to working demo in a single afternoon. But there’s a massive, painful gap between “it works on my laptop” and “it’s running reliably in production serving real users.”
Let’s talk about why — and what you can actually do about it.
What Is Vibe Coding and Why Everyone Is Talking About It
Vibe coding is the practice of building software by describing what you want in natural language while an AI model writes the actual code. Instead of learning programming syntax, understanding data structures, or studying software architecture, you simply tell the AI what you need: “Build me a dashboard that shows real-time sales data with charts and a user authentication system.”
The term was coined by Andrej Karpathy (co-founder of OpenAI and former Tesla AI director) in early 2025 and quickly exploded across the tech world. It perfectly captures the experience: you’re not really coding — you’re vibing with an AI, guiding it through conversation.
The Tools Powering the Vibe Coding Revolution
ChatGPT / Claude — conversational AI that generates code from descriptions
Cursor — AI-powered IDE that writes code as you describe features
v0 by Vercel — generates full UI components from text prompts
Bolt / Lovable — full-stack app generators from natural language
GitHub Copilot — AI pair programmer that autocompletes entire functions
The appeal is undeniable. What used to take a development team weeks can now be prototyped in hours. Non-technical founders can validate ideas before hiring engineers. Designers can build functional prototypes instead of static mockups. The barrier to creating software has never been lower.
The Seductive Appeal: From Idea to Prototype in Hours
Let’s be honest — vibe coding feels incredible. There’s a reason it went viral and became the defining tech trend of 2025:
Instant Gratification
You describe a feature, and within seconds you see it rendered on screen. The feedback loop is intoxicating. Traditional development might take days to build what vibe coding produces in minutes.
No Technical Barrier
You don’t need to know React, Python, SQL, or any programming language. You just need to clearly describe what you want. This opens software creation to millions of people who previously couldn’t build anything.
Rapid Iteration
Don’t like the layout? Tell the AI to change it. Need a new feature? Describe it and watch it appear. The speed of iteration is genuinely revolutionary for the prototyping phase.
Impressive Demos
Vibe-coded prototypes look great in demos and pitch decks. Investors see a “working product” and get excited. Friends and family are amazed. The problem is that what they’re seeing is a facade.
Vibe coding is the best thing that ever happened to prototyping — and potentially the worst thing that ever happened to production software quality.
The 5 Critical Failures of Vibe-Coded Projects
After rescuing dozens of vibe-coded projects that hit the wall, I’ve identified five consistent failure patterns that kill these projects before they ever reach real users:
1. Zero Tests, Zero Safety Net
Vibe coding produces code that appears to work, but nobody — including the AI — has verified that it actually handles edge cases, unexpected inputs, or failure scenarios. There are no unit tests, no integration tests, no end-to-end tests. Nothing.
- Any change to one part of the app can silently break another
- You can’t deploy with confidence because you have no way to verify nothing is broken
- Bugs in production are discovered by users, not by your test suite
- Refactoring becomes impossible because you don’t know what you’ll break
2. No Error Handling — The Happy Path Delusion
AI builds for the happy path. Everything works perfectly when the user does exactly what’s expected. But real users do unexpected things: they submit empty forms, they lose internet connection, they click buttons twice, they paste emojis into number fields. Vibe-coded apps crumble under these conditions.
- App crashes with cryptic errors that confuse users
- Data corruption from unvalidated inputs
- No error logging — you don’t even know your app is failing
- Payment processes that silently fail without notifying anyone
3. Security Holes Everywhere
This is the most dangerous failure. AI generates code that works but is fundamentally insecure. API keys hardcoded in frontend code. No input sanitization. SQL injection vulnerabilities. Authentication that can be bypassed. CORS configured to allow everything.
- User data exposed to anyone who inspects the network requests
- API keys visible in client-side JavaScript that anyone can steal
- Database vulnerable to injection attacks that can destroy all data
- Authentication tokens stored insecurely, enabling account hijacking
4. Spaghetti Architecture — The Unmaintainable Mess
When you vibe code, you’re building feature by feature without any architectural plan. The AI doesn’t maintain a mental model of your entire system. Each prompt produces code that works in isolation but creates a tangled mess when combined. Business logic mixed with UI code. Duplicated functions everywhere. No separation of concerns.
- Adding new features becomes exponentially harder over time
- Bug fixes in one area introduce new bugs elsewhere
- No developer (human or AI) can understand the full codebase
- Technical debt accumulates faster than features are added
5. Dependency Hell and Environment Chaos
Vibe-coded projects typically end up with dozens of unnecessary dependencies, conflicting package versions, and configurations that only work on the original developer’s machine. The AI installs packages for quick solutions without considering bundle size, security vulnerabilities, or version conflicts.
- Build fails on any machine except the original development environment
- Security vulnerabilities in outdated or unmaintained packages
- Bundle sizes so large they cripple application performance
- Version conflicts that make updating any dependency a nightmare
Real Patterns I’ve Seen Rescuing Vibe-Coded Projects
These aren’t hypothetical scenarios. These are patterns I encounter every week when clients come to me with their stuck vibe-coded projects:
The “Almost Done” Trap
A founder tells me their app is 90% done and just needs “a few fixes.” When I audit the code, I find that the 10% remaining is actually the hard part: authentication, payment processing, data validation, error handling, deployment. The visible UI was the easy 90%. The invisible infrastructure that makes it production-ready is the critical 90% that’s missing.
The Frankenstein Codebase
The project was built across 50+ ChatGPT conversations over several weeks. Each conversation produced code that worked independently but contradicts the code from other conversations. Different naming conventions, different state management approaches, different API patterns — all stitched together into a monster that barely runs.
The “It Worked Yesterday” Mystery
The app was working perfectly yesterday. Today, nothing works. Nobody changed anything. What happened? An auto-updated dependency introduced a breaking change. Or a free-tier API hit its rate limit. Or the database connection string was hardcoded to a local address. Without proper environment management and pinned dependencies, vibe-coded apps are time bombs.
The Security Wake-Up Call
A client launched their vibe-coded app and within 48 hours received a message from a “security researcher” who had accessed their entire user database. API keys were exposed in the frontend code, the database had no access controls, and user passwords were stored in plain text. The rescue involved rebuilding the entire authentication and data layer from scratch.
When Vibe Coding DOES Work
I’m not anti-vibe-coding. I use AI tools daily in my own development workflow. The key is understanding where vibe coding excels and where it falls apart:
Vibe Coding Shines For:
- Rapid prototyping — Validating an idea’s visual and functional concept before investing in real development
- Internal tools — Simple dashboards and admin panels that only your team will use, where security requirements are lower
- MVPs with known limitations — When you explicitly plan to rebuild before scaling, and stakeholders understand it’s a prototype
- Learning and exploration — Understanding how a technology or approach works before committing to it
- Hackathons and demos — When speed matters more than durability and the code will be thrown away
Vibe Coding Fails For:
- Any application that handles user data or payments
- Products that need to scale beyond a handful of users
- Software that must meet compliance or regulatory requirements
- Applications where downtime or bugs have real consequences
- Anything you plan to maintain and iterate on for months or years
How to Bridge the Gap: From Vibe-Coded Prototype to Production
If you’ve built something with vibe coding and you want to take it to production, here’s the realistic path forward. It’s not about throwing away your prototype — it’s about treating it as what it is: a validated proof of concept that needs professional engineering to become a real product.
Step 1: Honest Assessment
Get a professional code audit. Understand what you actually have versus what you think you have. Most vibe-coded projects need 60-80% of the code rewritten or restructured. This isn’t failure — it’s the normal path from prototype to production.
Step 2: Architecture First
Before touching any code, design a proper architecture. Define data models, API contracts, authentication flows, and error handling strategies. The prototype showed what to build; now you need to plan how to build it properly.
Step 3: Security Foundation
Implement authentication, authorization, input validation, and data encryption from the ground up. This is non-negotiable for any production application. Use battle-tested libraries and frameworks, not AI-improvised solutions.
Step 4: Test Infrastructure
Set up automated testing before writing production code. Unit tests, integration tests, and end-to-end tests give you the confidence to ship and the safety net to iterate. No tests means no reliable deploys.
Step 5: Incremental Migration
Rebuild component by component, using the prototype as a specification. Keep the UI elements that work, replace the underlying logic with production-grade code. Deploy incrementally so you always have a working application.
Step 6: Production Infrastructure
Set up proper CI/CD pipelines, monitoring, logging, error tracking, and automated backups. Production isn’t just running code — it’s running code reliably with visibility into what’s happening.
Don’t Let Your Prototype Die — Get It Production-Ready
You’ve already done the hardest part: you had an idea and validated it with a working prototype. The vibe-coded version proved your concept has legs. Now you need the engineering expertise to make it real.
I specialize in rescuing vibe-coded and AI-generated projects. I’ve taken dozens of prototypes that were “almost done” and turned them into production applications that reliably serve real users.
Ready to Go From Prototype to Production?
I’ll audit your vibe-coded project, give you an honest assessment of what it takes to ship, and build a clear roadmap from where you are to production. No judgment about how it was built — just a clear path forward.
