Vibe Coding: Build Real Apps Without Writing Code

Back in 2018, I paid a freelance developer $2,000 to build an app idea I'd been sketching for months. Three weeks after the first milestone payment, he vanished. No code. No refund. Just an empty Slack channel and a hard lesson about the gap between having ideas and having the technical skills to execute them.

That experience pushed me to learn programming properly, which worked out—I'm now a software engineer who builds AI systems for a living. But I've never forgotten that frustration. The barrier between "I have a great idea" and "I have a working product" was too high for most people, and it felt fundamentally unfair.

Then February 2025 happened. Andrej Karpathy, one of OpenAI's founding members, posted about something he called "Vibe Coding." The concept was simple: instead of learning syntax and debugging semicolons, you just describe what you want in plain English, and AI writes the code for you. I was skeptical at first—I've seen enough "no-code" tools that produced garbage to be wary of bold claims. But after spending a weekend building three functional apps without writing a single line of code, I'm convinced this changes everything.

Here's what I discovered, why it matters, and exactly how you can start building today.

Why Traditional Development Creates Gatekeeping

Before diving into Vibe Coding, let me explain why this matters beyond convenience. Understanding the traditional web app architecture helps you appreciate what these AI tools are actually automating.

Think of a web application like a restaurant. The front end is the dining area—everything the customer sees and interacts with. Buttons, colors, layouts, the menu on your table. It's designed to be pleasant and intuitive.

The back end is the kitchen. Customers never see it, but it's where all the real work happens. When you place an order, the kitchen receives it, prepares the food, and sends it out. In app terms, this is where business logic lives—user authentication, data processing, calculations.

The API is your waiter. It carries requests from the dining room to the kitchen and brings responses back. When you click "submit" on a form, an API takes that data to the back end and returns the result.

The database is the pantry. All your ingredients—user profiles, product inventories, order histories—are stored there for the kitchen to access when needed.

Hosting is the building itself. Your code needs to live somewhere accessible on the internet, with an address people can visit.

Traditional development requires expertise in all these layers. A full-stack developer needs to understand React or Vue for front ends, Node.js or Python for back ends, PostgreSQL or MongoDB for databases, and AWS or Vercel for hosting. Learning each layer takes months. Integrating them takes years of practice.

This is why hiring developers is expensive and why so many ideas never get built. The technical barrier isn't just high—it's deliberately specialized in ways that exclude casual builders.

Vibe Coding tools collapse these layers. You describe what you want, and AI handles front end, back end, API, database, and hosting simultaneously. The restaurant analogy still applies, but now you have an AI architect designing and staffing the entire operation based on your description.

The Vibe Coding Workflow I Actually Use

After testing several AI coding platforms, I settled on Replit as my primary tool. It integrates everything—editor, database, hosting, deployment—in one interface. The free tier is generous enough to build and test MVPs, and the AI agent genuinely understands what you're trying to accomplish.

Here's the workflow that consistently produces functional apps:

Step 1: Create a Product Requirements Document

Before touching any AI tool, I write a structured PRD using ChatGPT. This sounds formal, but it's just a clear description of what you want.

I prompt ChatGPT like this: "I want to build a 2026 Resolutions Tracker. Users should be able to sign up, log in, add resolutions with target dates, mark them complete, and see their progress. The design should feel gamified, maybe pixel-art style. Create a product requirements document for this."

ChatGPT returns something like:

Product Overview: A web-based resolution tracking application with user authentication and progress visualization.

Core Features:

• User registration and login
• CRUD operations for resolutions (create, read, update, delete)
• Progress tracking with percentage completion
• Gamified UI with pixel-art aesthetic
• Deadline reminders

User Flows:

• New user signs up → sees empty resolution board → adds first resolution
• Returning user logs in → sees existing resolutions → updates progress

Technical Requirements:

• Secure authentication system
• Persistent data storage
• Responsive design for mobile and desktop

This PRD becomes the prompt I feed into Replit. The more specific and structured your PRD, the better the AI output. Vague descriptions produce vague apps.

Step 2: Feed the PRD into Replit

I paste the entire PRD into Replit's AI agent interface. The agent starts working immediately—creating file structures, writing backend logic, designing database schemas, and generating front-end components.

What still surprises me is watching it simulate a developer's thought process. It creates an authentication system, then realizes it needs session management, then builds the resolution storage logic, then connects everything with API routes. The live preview updates as it works, so you can see the app taking shape in real time.

Step 3: Iterate Through Conversation

The first output is rarely perfect. Maybe the login button is in a weird position, or the color scheme clashes. This is where Vibe Coding shines—you just describe what's wrong.

"Move the login button to the top right corner." Done.

"Make the background darker, more cyberpunk aesthetic." Done.

"The progress bar isn't calculating correctly when I mark a resolution complete." The AI debugs its own code, identifies the issue, and fixes it.

I spent three hours on my resolution tracker, and most of that time was describing refinements, not waiting for the AI to generate code. By the end, I had a fully functional app with user authentication, persistent data, and a distinctive visual style that looked nothing like generic templates.

Step 4: Publish and Share

Replit handles deployment automatically. Click publish, get a URL, share it with anyone. My resolution tracker is live on the internet right now, handling real users, and I never opened a code editor or configured a server.

Building a 3D Game With One Sentence

To test the limits, I tried something ambitious: building a 3D obstacle course game with a single prompt.

I typed: "Build a 3D obstacle course game with WASD controls, physics, checkpoints, and a timer."

Fifteen minutes later, I had a playable game. A 3D character navigates platforms, avoids obstacles, respawns at checkpoints, and races against the clock. The physics felt responsive. The controls worked exactly as described.

Were there issues? Of course. Some obstacles had collision detection problems. The camera occasionally clipped through geometry. But when I described these problems, the AI fixed them. "The player can walk through the third obstacle—it should be solid." Fixed. "The camera is too close to the character—zoom it out." Fixed.

This isn't replacing professional game developers. Complex games still need human expertise for polish, performance optimization, and creative direction. But for prototypes, internal tools, and minimum viable products, Vibe Coding handles 80% of the work instantly.

The PRD Technique That Dramatically Improves Output

Through experimentation, I found that PRD quality directly correlates with app quality. Here's the framework I use for better results:

Start with the user story. "As a [type of user], I want to [accomplish goal] so that [benefit]." This forces clarity about who you're building for and why.

List features as behaviors, not implementations. Don't say "add a PostgreSQL database." Say "users should be able to save their data and access it later from any device." The AI chooses appropriate implementations.

Describe the emotional experience. "The app should feel fast and responsive" or "the design should feel professional but approachable." These qualitative instructions influence the AI's aesthetic choices.

Specify edge cases. What happens if a user submits an empty form? What if they try to access someone else's data? Explicit edge cases produce more robust applications.

Include real examples. "The navigation should work like Notion's sidebar" or "the loading animation should feel like Linear's." Reference points give the AI concrete targets.

My best apps came from PRDs that took 20-30 minutes to write. That upfront investment saves hours of iteration later.

Where Vibe Coding Fits in My Professional Workflow

I still write code daily. For production systems handling sensitive data, for performance-critical algorithms, for anything requiring deep customization, I'm in VS Code with TypeScript open. Vibe Coding doesn't replace engineering expertise—it extends it.

Here's where I now default to Vibe Coding:

Internal tools. My team needed a dashboard to track content performance across multiple channels. Instead of spending two days building it, I described what we needed in Replit and had a working prototype in an hour. We refined it over a few days, and now it's a daily-use tool.

Client demos. When pitching ideas to clients, I can build functional prototypes during the meeting. "You want the navigation to work differently? Give me five minutes." The client sees a working example instead of wireframes, which dramatically improves communication.

Learning new frameworks. When I want to understand how something works, I describe it to the AI, watch it build, and study the generated code. It's like having a senior developer write examples customized to my learning goals.

MVPs for validation. Before investing weeks in a proper product, I build a Vibe Coded version to test with real users. If the concept fails, I've lost a weekend, not a month.

The Honest Limitations You Should Know

Vibe Coding isn't magic. Here's where it breaks down:

Complex business logic. If your app requires sophisticated algorithms, custom integrations with enterprise systems, or unusual data processing, you'll hit limits quickly. The AI can scaffold these systems, but fine-tuning requires human engineering.

Performance optimization. Generated code works, but it's not always efficient. For apps with heavy traffic or strict performance requirements, you'll need to manually optimize.

Security hardening. The AI implements basic security patterns, but production applications need proper security audits. Don't rely solely on AI-generated authentication for sensitive data.

Scaling. MVP apps might buckle under serious load. The generated architecture isn't always optimized for horizontal scaling.

Maintenance complexity. When bugs appear in code you didn't write and don't fully understand, debugging is harder. You lose some ownership when you outsource development to AI.

These limitations matter for professional production systems. For prototypes, internal tools, and early-stage validation, they're acceptable trade-offs.

Getting Started Today

If you've read this far and want to try Vibe Coding, here's your action plan:

Sign up for Replit's free tier. It's sufficient for testing and building basic apps. Paid plans ($25/month) remove usage limits for more complex projects.

Start with a simple idea. A personal todo list. A habit tracker. A portfolio website. Don't build something complex on your first attempt—learn the workflow with something achievable.

Write your PRD. Use ChatGPT to structure your idea into a clear requirements document. This is the most important step.

Iterate without frustration. Expect errors. Expect crashes. Expect the AI to misunderstand your first few descriptions. Treat every failure as a prompt refinement opportunity.

Study the generated code. Even if you don't plan to code manually, reading AI-generated code builds intuition about how applications work. This knowledge makes your future prompts better.

Publish something. The real learning happens when other people use what you built. Ship something imperfect rather than polishing forever.

The Future Is Natural Language Development

Karpathy's insight about Vibe Coding reflects something bigger happening in software development. The interface between humans and computers is shifting from specialized syntax to natural language. Programming languages were always an intermediate layer—a concession to what machines could understand. As AI interpretation improves, that layer becomes optional.

This doesn't eliminate programmers. It changes what programming means. Instead of translating ideas into syntax, developers focus on architecture, system design, quality assurance, and creative problem-solving. The mechanical transcription work—the part that excluded non-technical people—gets automated.

For creators with ideas but no engineering background, this is liberation. The 2018 version of me, stuck with an idea and no way to build it, could now produce a functional MVP in a weekend. That changes who gets to participate in building software.

For experienced developers like me, it's acceleration. I ship more, prototype faster, and spend mental energy on interesting problems instead of boilerplate code.

Either way, the gap between idea and execution just got dramatically smaller. If you've been waiting for permission to build something, this is it. The tools are free, the learning curve is gentle, and the worst case is spending a few hours on an experiment that doesn't work.

Start building.

Let's Work Together

Looking to build AI systems, automate workflows, or scale your tech infrastructure? I'd love to help.

• Fiverr (custom builds & integrations): fiverr.com/s/EgxYmWD
• Portfolio: mejba.me
• Ramlit Limited (enterprise solutions): ramlit.com
• ColorPark (design & branding): colorpark.io
• xCyberSecurity (security services): xcybersecurity.io