I Tried Vibe Coding to Build an App — Real Insights for 2025

I Tried Building an App with Vibe Coding — Here’s What Really Happened

The AI coding revolution is here, and vibe coding is the hottest trend dividing developers. After a full week of experimenting—building a real-world productivity app without writing a single line of code myself—I discovered both the incredible potential and serious limitations of this approach. Here’s the full story.

What Is Vibe Coding?

Vibe coding is a new paradigm in software development, coined by OpenAI co-founder Andrej Karpathy in February 2025. Instead of writing traditional code, you describe your app in natural language and let AI generate the implementation. The key principle: accept AI suggestions without meticulously reviewing every line of code.

Vibe coding isn’t just AI autocomplete—it flips the development process upside down, prioritizing outcomes over understanding the underlying code.

Key Principles of Vibe Coding:

• Describe features conversationally: “Create a task manager with due date reminders.”
• Accept AI-generated solutions without manual coding.
• Focus on rapid iteration and working prototypes rather than perfect architecture.

How Vibe Coding Works in Practice

During my experiment, I used multiple AI coding platforms to build a productivity app. Here’s what stood out:

1. Natural Language First: Features were described in plain English. No functions, no variables—just a conversation with the AI.
2. Error-Driven Development: Bugs were fixed by feeding error messages back to AI—no debugging marathons required.
3. Rapid Iteration: Features like “add dark mode” or “collapse sidebar” were implemented instantly instead of hours of edits.

Where Vibe Coding Shines

Vibe coding excels at rapid prototyping and standard app features:

• Boilerplate Automation: Authentication, database connections, and APIs set up in minutes.
• Cross-Platform Consistency: Code automatically adheres to responsive design and accessibility standards.
• Speedy Prototyping: Ideas go from concept to working prototype almost instantly.

Real-world examples show the power: one developer created a $1 million ARR game in 17 days, while 75% of Replit users reportedly never write a single line of code themselves.

The Limitations You Need to Know

Vibe coding has serious challenges that can’t be ignored.

1. Security Vulnerabilities

AI-generated code often contains SQL injections, insecure authentication flows, and unsafe file handling. Developers without security expertise might not catch these, creating major production risks.

2. Architectural Chaos

While AI can generate features quickly, it struggles with system-level design. Inconsistent naming, messy logic, and poor documentation make scaling and maintenance difficult.

3. Debugging Nightmares

Complex bugs are nearly impossible to trace. AI-generated logic is often non-linear and obscure, requiring reverse-engineering someone else’s AI decisions.

4. Performance and Scalability Issues

AI prioritizes “working” over “efficient.” Queries, algorithms, and resource usage can be suboptimal, leading to poor performance under load.

5. Integration Challenges

Vibe coding struggles with niche APIs, legacy systems, and custom business logic, which can lead to costly trial-and-error cycles.

Success Stories vs. Failures

Successes: Rapidly built PDF converters, SaaS tools, and game prototypes. Some founders iterate quickly by feeding errors back to AI until the product works.

Failures: Complex apps often hit walls in debugging, optimization, and integrations, sometimes taking longer than traditional coding.

The Economics of Vibe Coding

While vibe coding reduces initial development time, hidden costs include:

• AI API expenses (e.g., $50+ per weekend)
• Technical debt from poorly structured code
• Security audits costing thousands of dollars
• Performance optimization requiring rewrites

Verdict: Vibe Coding Is a Tool, Not a Replacement

Vibe coding is revolutionary for MVPs and standard apps, but it’s not a replacement for skilled developers.

Best use cases:

• MVPs or proof-of-concept apps
• Standard CRUD applications
• Rapid prototyping for user validation

Avoid using it for:

• Production apps with sensitive data
• Performance-critical systems
• Complex business logic or niche integrations

Top developers treat vibe coding as a first-draft generator, then refine architecture, security, and performance manually.

The Future of Development

Vibe coding signals the future of AI-assisted software development. The most successful approach combines AI’s rapid prototyping power with human expertise in architecture, security, and optimization.

“You need to be a good software engineer to make vibe coding effective,” one developer notes. AI amplifies your skills—it doesn’t replace them.

By understanding both the hype and the pitfalls, you can harness vibe coding to accelerate development without sacrificing quality.