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Jun 12, 2025
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Vibe Coding: When Intuition Meets AI-Assisted Development

Sometimes the best code comes from following your instincts and experimenting freely. Learn how "vibe coding" with AI assistance can accelerate MVP development and help you discover solutions you might never have planned.

Vibe Coding: When Intuition Meets AI-Assisted Development

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There's a special kind of coding that happens when you stop overthinking and start following your instincts. It's what many developers call "vibe coding" - that flow state where you're experimenting, iterating, and discovering solutions through intuition rather than rigid planning. Combined with AI assistance, it becomes a powerful approach for rapid prototyping and MVP development. Here's how I've learned to embrace this more experimental side of development.

Vibe coding isn't about being careless - it's about being experimental. When you combine intuitive exploration with good safety nets (like frequent commits), magic happens.

What Is Vibe Coding?

Vibe coding is that state where you're coding by feel rather than following a strict plan. You have a general direction, but you're open to discoveries along the way. It's particularly powerful when:

  • Building MVPs or prototypes where speed matters more than perfection
  • Exploring new libraries or frameworks
  • Solving problems where the "right" solution isn't immediately obvious
  • Working on creative features where you want to see what emerges
  • Learning new concepts through hands-on experimentation

It's the opposite of architecture-first development. Instead of planning every detail upfront, you start with a rough idea and let the code guide you toward solutions.

Why Vibe Coding Works So Well with AI

AI assistance amplifies vibe coding because it removes many of the traditional barriers to experimentation:

AI Enables

Rapid iteration: Try ideas quickly without getting bogged down in syntax
Fearless exploration: AI can help you understand unfamiliar territory
Pattern discovery: AI suggests approaches you might not have considered
Learning acceleration: Get explanations as you experiment

Traditional Barriers

Syntax uncertainty: Slows down experimentation
Library unfamiliarity: Creates hesitation to try new approaches
Boilerplate overhead: Makes small experiments feel heavy
Knowledge gaps: Stops exploration when you hit unknowns

The Safety Net: Frequent Commits

The key to successful vibe coding is having excellent safety nets. Frequent commits are absolutely essential - they give you the confidence to experiment boldly because you can always roll back.

My Vibe Coding Git Workflow

# Start with a clean state
git status
git add -A && git commit -m "Clean starting point before vibe coding session"

# Make experimental changes with AI assistance
# ... code, prompt, iterate ...

# Commit frequently with descriptive messages
git add -A && git commit -m "Experiment: trying new user auth flow"

# Continue iterating
# ... more changes ...

git add -A && git commit -m "WIP: auth flow working but needs refinement"

# Try a different approach
git add -A && git commit -m "Alternative: simplified auth with middleware"

# If something goes wrong, easy rollback
git log --oneline -10  # See recent commits
git reset --hard HEAD~2  # Go back 2 commits if needed

Commit Message Prefixes I Use

  • Experiment: Trying a new approach, might not work
  • WIP: Work in progress, partially functional
  • Spike: Proof of concept or research
  • Rollback point: Known good state before major changes
  • Discovery: Found something interesting, capturing it

Real Vibe Coding Examples

MVP Feature Development

Recently, I needed to add a "smart notifications" feature to an app. Instead of planning the architecture upfront, I started with a simple prompt:

The Vibe Coding Journey

Start: "Let's build a system that sends smart notifications based on user behavior"
AI suggests: Observer pattern with event listeners
I try it: Quick implementation, commit: "Experiment: observer-based notifications"
Discovery: Too complex for MVP, but learned about Laravel events
Pivot: "What's the simplest way to track user actions and send notifications?"
AI suggests: Middleware + simple queue jobs
Result: Working MVP in 2 hours, commit: "Simple notification system working"

Learning Through Experimentation

Vibe coding is excellent for learning. Here's how I explored Laravel's new features:

// Started with: "Show me how to use Laravel 11's new casts"
// AI showed basic example, I experimented

// Commit: "Experiment: basic custom cast implementation"
class Moneycast implements CastsAttributes
{
    public function get($model, string $key, $value, array $attributes): Money
    {
        return new Money($value);
    }

    public function set($model, string $key, $value, array $attributes): array
    {
        return [$key => $value->cents];
    }
}

// Then: "What about array casts with validation?"
// Commit: "WIP: exploring array casts with validation"

// Then: "How do I handle null values gracefully?"
// Commit: "Discovery: null handling patterns for casts"

// Final working version
// Commit: "Clean: production-ready money cast with null handling"

Vibe Coding Strategies

The Rapid Prototype Loop

1
Start with a vague idea
2
Prompt AI for initial direction
3
Build minimal version
4
Commit & evaluate
5
Iterate or pivot

Effective AI Prompting for Vibe Coding

Great Vibe Coding Prompts

  • • "What's the simplest way to implement [feature] in Laravel?"
  • • "Show me 3 different approaches to [problem], focusing on speed"
  • • "I want to try [concept] - give me a working example to start with"
  • • "This isn't working as expected - what am I missing?"
  • • "How can I make this code more Laravel-like?"

Prompts That Lead Down Rabbit Holes

  • • "Build me a complete [complex system] with all edge cases"
  • • "What's the most advanced way to implement [simple thing]?"
  • • "Create a production-ready [feature] with full documentation"
  • • "Show me every possible optimization for [code]"

When Vibe Coding Goes Wrong

Not every vibe coding session leads to success. Here are the common failure modes I've experienced and how to handle them:

The Rabbit Hole Problem

# When AI takes you down a complex path that doesn't fit your needs

# Recognize the signs:
- Code getting more complex instead of simpler
- Adding dependencies you don't understand
- Solving problems you don't actually have
- Spending more time debugging than building

# Recovery strategy:
git log --oneline -10  # Find your last good commit
git reset --hard abc123  # Go back to before the rabbit hole
git commit -m "Reset: backing out of overengineered solution"

# Try a different prompt:
"What's the absolute simplest way to [solve core problem]?"

The Wrong Context Problem

Sometimes you accidentally give AI the wrong context (like when working in multiple projects). Frequent commits save you here too:

War Story: Mixed Project Context

I was working on two Laravel projects simultaneously. Asked AI to "add user roles to the dashboard" while in the wrong project directory. AI generated code for the wrong database schema and routing structure.

Solution: `git status` showed uncommitted changes. `git stash` → switch to correct project → re-prompt with proper context. Lesson learned: always check `pwd` and `git status` before prompting.

Vibe Coding vs. Structured Development

Vibe coding isn't meant to replace structured development - they're complementary approaches for different situations:

Use Vibe Coding For

• MVP and prototype development
• Learning new technologies
• Creative problem solving
• Exploring "what if" scenarios
• Quick spike solutions
• Personal side projects

Use Structured Approach For

• Production systems
• Team collaboration
• Complex business logic
• Performance-critical code
• Security-sensitive features
• Long-term maintenance

Tools That Enable Great Vibe Coding

Development Environment Setup

# Essential aliases for rapid experimentation
alias gac="git add -A && git commit -m"
alias glog="git log --oneline -10"
alias greset="git reset --hard"
alias gstatus="git status --short"

# Quick Laravel helpers
alias art="php artisan"
alias serve="php artisan serve"
alias migrate="php artisan migrate"
alias fresh="php artisan migrate:fresh --seed"

# Usage examples:
gac "Experiment: trying new caching approach"
art make:controller ExperimentController
gac "WIP: basic controller structure"

AI Tools That Work Great for Vibe Coding

My Vibe Coding Toolkit

  • Cursor: Integrated AI right in the editor for seamless iteration
  • ChatGPT/Claude: For broader architectural discussions and explanations
  • Laravel Tinker: Quick testing of ideas without full implementation
  • Postman/Insomnia: Rapid API testing during development
  • Laravel Telescope: Debugging what's actually happening

Teaching Vibe Coding to Teams

If you want to introduce vibe coding practices to your team, start small and emphasize the safety nets:

Team Vibe Coding Guidelines

Safe Vibe Coding Practices

  • • Always work on feature branches, never directly on main
  • • Commit every 15-30 minutes during vibe coding sessions
  • • Use clear prefixes in commit messages (Experiment:, WIP:, Spike:)
  • • Set time limits for vibe coding sessions (1-2 hours max)
  • • Have a cleanup phase to refactor before merging
  • • Share interesting discoveries with the team

The Learning Accelerator Effect

One of the unexpected benefits of vibe coding with AI is how much you learn. Because you're experimenting constantly and getting explanations along the way, you absorb patterns and techniques much faster than traditional learning methods.

Vibe Coding Learning Benefits

  • Pattern recognition: You see how different approaches work in practice
  • Failure tolerance: Easy rollbacks reduce fear of trying new things
  • Contextual learning: You learn solutions in the context of real problems
  • Rapid feedback: See results immediately rather than studying theory
  • Serendipitous discovery: Find useful techniques you weren't looking for

From Vibe to Production

Not everything you build while vibe coding should go to production, but the good stuff needs a transition path:

The Refinement Process

# After successful vibe coding session
git log --oneline -20  # Review your experimentation journey

# Create a clean feature branch from main
git checkout main
git pull origin main
git checkout -b feature/notification-system-clean

# Cherry-pick the good parts
git cherry-pick abc123  # The working implementation
git cherry-pick def456  # The good refinements

# Clean up and refactor
# - Add proper error handling
# - Write tests
# - Update documentation
# - Remove debug code
# - Apply consistent naming

git commit -m "feat: notification system based on vibe coding spike"

# Create PR with context
# "This feature emerged from experimental development. 
# Core functionality works well, refined for production use."

Embracing the Vibe

Vibe coding has changed how I approach development problems. It's given me permission to experiment freely, to follow interesting tangents, and to discover solutions I never would have planned. The key is balancing that creative exploration with good engineering practices.

The best part? Vibe coding is fun. When you remove the pressure to get everything right the first time and focus on exploration and learning, coding becomes play again. And often, the solutions that emerge from play are more creative and effective than the ones you would have engineered from the start.

🎯 Vibe Coding Principles

Trust your instincts, commit frequently, experiment boldly, and don't be afraid to throw things away. The best discoveries often come from following your curiosity rather than your plan.

Remember: vibe coding is about the journey as much as the destination. Every "failed" experiment teaches you something valuable about the problem space.

Do you have your own vibe coding stories or strategies that work well for your development process? I'd love to hear about your experiences with experimental development and what approaches have led to your most interesting discoveries.

Chris Page

Chris Page

Fractional CTO and Software Engineer with 25+ years of experience. I help startups scale from 0 to 7 figures using AI-assisted development and proven frameworks.

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