How to Actually “Vibe” with AI

In the last blog we learned what is vibe coding!

If vibe coding is the new paradigm, then prompting is its secret.

Many people think prompting is just about asking nicely. In reality, it’s a sophisticated skill that can make or break your entire development process.

The Pre-Prompt Preparation

• Choose Your Tools Wisely: Smart vibe coders don’t just pick any AI-integrated IDE. They evaluate options like Cursor, VS Code, and Replit based on AI integration quality, speed, and cost-per-token. The tool you choose shapes how effectively you can communicate with AI.
• Customize Your System Instructions: The pros use templates like .cursorrules from GitHub and create personalized instruction files (like Claude.md) that specify their preferred languages, frameworks, and libraries. This isn't just configuration, it's teaching your AI to speak your project's language.
• Strategic Model Selection: Different models excel at different tasks. Experienced developers switch between Claude 3.5 Sonnet and GPT-4o based on output speed, quality needs, and token costs. They experiment and compare to find the sweet spot for each project phase.

The Prompting Strategies That Actually Work

Context Management is Everything

• Fresh contexts for new features: Open new chat threads when switching focus areas
• Clear the slate: Close tabs and reset context when moving to new development phases
• Reference specific elements: Use actual function names, variables, and APIs for precision

Structure Your Instructions

• Use numbered lists for complex multi-step instructions
• State outcomes AND constraints explicitly
• Provide concrete examples (paste expected JSON responses, UI mockups, error messages)
• Reference previous outputs to give corrective feedback

Scope Control Prevents Hallucinations

• Focus on one phase at a time rather than asking for everything at once
• Set explicit constraints like “don’t integrate Stripe yet, just make a design with dummy data”
• Use external documentation by copying URLs and instructing “use these docs”

Granularity Spectrum

• High-Level Directives: “Make the chat interface more like ChatGPT.” → Let the AI interpret the overall direction
• Mixed-Objective Prompts: “Move the date below and use a very small font, don’t use bold font, narrow the space between conversations.” → Combine specific actions with subjective descriptors
• Precise Technical Instructions: “Create an API for a new conversation with these exact JSON fields…” → Leave no room for interpretation

The Magic of Imprecise Precision

Here’s where vibe coding gets interesting: you can be deliberately vague about aesthetics while being laser-focused on functionality.

What works:

• “Expand the space significantly” (let AI interpret “significantly”)
• “Use a modern theme with good color contrast” (trust AI’s design sense)
• “Make it feel more professional” (leverage AI’s understanding of design principles)

What doesn’t work:

• Vague functional requirements
• Unclear data structures
• Ambiguous user flows

Why Everyone’s Going Crazy for Vibe Coding

Finally, Anyone Can Build Cool Stuff

You know that friend who always says, “I have this amazing app idea, but I can’t code”? Well, those days are over. Vibe coding is breaking down the walls that kept regular people out of software creation.

You don’t need to memorize hundreds of commands or spend months learning Python syntax. Got a brilliant idea for a productivity app? A quirky website? A simple tool that would make your life easier? You can actually build it now, even if you’ve never written a line of code. The skills that matter now are the ones you already possess, such as explaining your ideas clearly, providing constructive feedback, and knowing what you want.

The Speed Will Blow Your Mind

Remember when building even a basic website took weeks? Vibe coding turns ideas into working prototypes faster than you can finish your morning coffee.

This speed isn’t just convenient — it’s addictive. When you can see your ideas come to life almost instantly, it keeps you motivated and creative. You’re not stuck for hours debugging semicolons or wrestling with error messages. Instead, you’re constantly refining, improving, and adding new features.

The Human Side of Creation “Software for One”

People are finally building tools for their own weird, specific problems. You know those tiny annoyances in your daily routine that no big company would ever solve? Well, now you can fix them yourself.

We’re moving away from “let’s build an app for millions of users” to “let’s build something that solves my exact problem.” And when everyone can do that, suddenly we have thousands of creative solutions to problems we didn’t even know existed.

What People Are Actually Building?

1. The Gaming Startup That Shocked Everyone. A small team wanted to create a tank battle game. In the old days, this would mean months of coding, a big team, and probably running out of money before launch. Instead, they spent a few days describing their game to AI through Cursor, and boom — playable tank battles. The whole thing took days, not months.

2. Learning to Code Without the Tears: There’s this educational platform where students don’t memorize syntax or struggle through boring exercises. They just describe what they want to build, and the AI makes it happen while explaining how it works. It’s like having a patient tutor who never gets frustrated and can show you exactly what you’re trying to understand.

3. Small Business Automation That Actually Works: A startup built an app where non-technical business owners can create their automations. Need to organize inventory? Streamline customer responses? Just describe what you need, and the app builds it. No hiring developers, no months of back-and-forth, just solutions that work.

4. Health Apps Built by Health Enthusiasts: Young founders are creating wellness apps without needing to understand complex algorithms. They describe what health metrics they want to track, and the AI builds tools that can spot trends and provide insights. Suddenly, health tech isn’t just for big companies with massive R&D budgets.

5. Artists Who Code Without Coding Musicians are building apps that generate tracks based on mood descriptions. Visual artists are creating tools that make digital art from simple prompts. The technical barrier between creative vision and digital creation is basically gone.

The Real Challenges of Vibe Coding (And How to Handle Them)

Let’s be honest, vibe coding isn’t perfect. While it’s revolutionizing how we build software, it comes with its own set of headaches that every developer needs to know about.

A) The Dependency Trap

It’s easy to get addicted to AI assistance and stop flexing your core coding muscles. When you rely on AI for everything, your problem-solving skills can get rusty. What happens when you face a complex challenge that AI can’t handle, or when you need to debug something the AI created but doesn’t understand?

The Reality Check: You might find yourself panicking when you have to write code from scratch or solve problems without your AI sidekick.

B) Quality Control Nightmares

AI-generated code often looks perfect on the surface but hides nasty surprises. Subtle bugs, inefficient algorithms, and security vulnerabilities can slip through if you’re not careful.

What should you do? You are still the final judge of code quality. The AI might give you working code, but “working” doesn’t always mean “good.”

C) The Generic Solution Problem

When your project has unique requirements or domain-specific logic, AI suggestions can be frustratingly generic. You end up spending more time rewriting AI-generated code than it would have taken to write it yourself.

The Reality Check: For highly specialized or custom solutions, vibe coding might actually slow you down instead of speeding you up.

D) Privacy and Security Concerns

Your code might contain sensitive business logic, proprietary algorithms, or confidential data. When you feed this to third-party AI models, you’re potentially exposing valuable intellectual property.

You must be extremely cautious about the code you share with AI services, especially in corporate or sensitive environments.

E) The Communication Challenge

Sometimes you know exactly what you want, but can’t explain it clearly to the AI. This is especially tough with visual elements, complex user interactions, or abstract concepts.

Developers struggle to describe diagram layouts or animation sequences in words. How do you explain the “feel” of a user interface or the subtle behavior you want from a feature?

F) AI Capability Confusion

Different AI models have different strengths and weaknesses, but figuring out which one to use for which task takes experience. You might waste time using the wrong tool for the job.

Claude might be great for one type of problem, while GPT-4 excels at another. Learning these nuances takes time and experimentation.

G) Tool-Specific Frustrations

Each AI-powered development tool has its own quirks and limitations. Learning to navigate these interfaces and understand their unique behaviors adds another layer of complexity.

Common Issues:

· Not knowing how to revert AI-generated changes

· Struggling with unfamiliar interface elements

· Dealing with AI responses that don’t integrate cleanly into your workflow

How to Navigate These Challenges

1. Stay Sharp: Keep practicing core coding skills even when using AI assistance. Set aside time for manual coding to maintain your problem-solving abilities.
2. Review Everything: Never trust AI-generated code blindly. Always review, test, and understand what the AI created.
3. Know Your Tools: Learn the strengths and limitations of different AI models and development tools. Experiment to find what works best for different types of tasks.
4. Protect Your Code: Be cautious about sharing sensitive code with AI services. Consider using local AI models or sanitizing code before sharing.
5. Practice Clear Communication: Work on explaining your ideas clearly and precisely. The better you communicate with AI, the better results you’ll get.

References

• What is Vibe Coding — GeeksforGeeks
• Vibe coding — Wikipedia
• Vibe coding: programming through conversation with artificial intelligence