WHAT’S CATCHING MY EYE THIS WEEK

 After spending hours testing various vibe coding platforms during my live stream, I've uncovered some fascinating insights about this controversial development approach. Here's what you need to know! ☕

The Two Faces of Vibe Coding

Remember when learning to code was the essential skill everyone talked about? Well, things are changing fast. In a recent video, Replit CEO Amjad Masad—formerly a massive proponent of traditional coding education—completely flipped his position.

His new stance? "I would say learn how to think, break down problems, learn how to communicate clearly...but no, it would be a waste of time to learn how to code."

This radical shift represents a growing sentiment that AI-generated code is becoming so powerful that understanding the mechanics of programming languages might become secondary to problem-solving skills.

But here's my hot take after extensive testing: Two things can be true at once. Vibe coding is genuinely transformative, AND knowing coding fundamentals remains crucial. Here's why that matters for anyone building products in 2025:

• Vibe coding excels at initial prototyping and MVPs

• When products scale or bugs emerge, debugging requires more profound technical knowledge

• Senior engineers can leverage AI to accomplish 10x more than previously possible

I tested this theory with two platforms live: Replit and Cursor. Let me break down what I found.

Replit's Cloud-Based Approach to Vibe Coding

Replit has gone all-in on vibe coding, even creating a formal "Vibe Coding 101" course with Andrew Ng. Their cloud-based platform offers these key advantages:

• Code entirely from your browser (even on mobile!)

• Automatic deployment to the Web

• No local setup is required (perfect for beginners)

During my live test, I attempted to create a Complex-inspired website. While the platform smoothly handled the basic structure, it struggled with more sophisticated styling elements—a limitation I've consistently seen with AI code generation.

Cursor's Desktop Power for Serious Development

For about six months, I've used Cursor (built on VS Code) for my local development workflow. The difference is striking:

• More precise code generation

• Better debugging capabilities

• Seamless integration with existing codebases

During the live stream, I demonstrated building a React app that uses Hugging Face's image classification API. Though we hit a few snags, the result was impressive—a functional grid of images with AI-generated descriptions, all built through conversational prompts.

The key insight? Vibe coding works best when you understand enough code to course-correct when the AI inevitably makes mistakes.

AI-Generated Code: Fortune's Warning

The technical debt crisis is real. Fortune recently highlighted that while "vibe coding lets 10 engineers do the work of 100," it comes with hidden costs. Developer Olson warns, "AI makes it easier to ship code, but that doesn't guarantee better outcomes."

I've witnessed this firsthand: AI-generated code often lacks structure, documentation, and best practices—setting teams up for maintenance nightmares down the road.

Mastering The Vibe Coding Workflow In 2025

What if you could harness the speed of AI code generation while avoiding its pitfalls? After months of experimentation, I've developed a framework that perfectly balances efficiency and sustainability.

Why This Matters For You:

Vibe coding isn't just a passing trend—it's fundamentally changing how developers work. A recent DEVCLASS article highlighted game developer Pieter Levels, who built a multiplayer game with Cursor and Grok 3 that reached $1 million ARR in just 17 days. But the aftermath? Another developer spent "a one-month sprint to recover from tech debt caused by said vibe coding."

The Stats Don't Lie:

• AI-generated code can create MVPs 5-10x faster than traditional development

• 65% of developers report spending significant time refactoring AI outputs

• Technical debt from unstructured AI code can increase maintenance costs by up to 3x

🔧 My Balanced Vibe Coding Framework

1. Setup Your Plumbing First: Instead of letting AI build your entire codebase, establish your own project structure, environment, and core architecture first. This ensures you maintain control over your application's foundational elements.

2. Use AI for Feature Development, Not Architecture Vibe coding works best when you're clear on WHAT you want to build but need help with HOW to make it. For example, during my livestream, I showed how I created a Hugging Face image recognition component in minutes by providing precise requirements.

3. Review and Refactor Immediately. Don't just accept what the AI generates. Develop the habit of immediately reviewing and refactoring the code. As I demonstrated live, adding my Hugging Face API key and understanding how to troubleshoot connection issues was essential to making the demo work.

4. Version Control Everything One of the best practices from Medium's analysis suggests pairing vibe coding with proper Git workflows. Commit AI outputs as separate branches and review them before merging with your main codebase.

5. Implement Regular Code Audits. Schedule weekly reviews of your AI-generated code to identify technical debt early. Tools like Replit's AI agent can help flag potential issues before they compound.

💎 Pro Tips You Won’t Hear Elsewhere:

• Prompt Engineering for Code Quality: I've developed specific prompts prioritizing maintainable code. For example, try adding "Write this with modularity and documentation in mind" to your prompts.

• Hybrid Approach: The most successful teams don't choose between vibe coding and traditional development—they blend both. Use AI for boilerplate and repetitive tasks, and save your brain power for architecture and business logic.

• Educational Opportunity: Use Vibe coding as a learning tool. When AI generates something you don't understand, research why it made those choices.

Quick-Start Action Plan:

1. Start with small, isolated features when first trying vibe coding

2. Build a library of effective prompts that work well for your coding style

3. Establish a review process specifically for AI-generated code

4. Focus on building coding fundamentals alongside AI skills