The first time I heard Andrej Karpathy use the term vibe coding, I felt an instant curiosity. Karpathy has shaped some of the most influential AI teams in the world, particularly during his time at Tesla. So when he casually described a style of coding where developers stop obsessing over syntax and instead focus on guiding the AI through intent, it felt like a glimpse into the next era of software creation.
As I explored the idea, it became clear that vibe coding is more than a trend. It represents a meaningful shift in how software is being built in 2025. Instead of developers writing every function or loop manually, humans now describe the outcome, direct the AI, test what is generated, and shape the result through repeated refinement.
This guide breaks down exactly what vibe coding is, how it works, and what it means for the future of work.
What Is Vibe Coding
Vibe coding is a natural-language driven approach to software development.
Instead of writing code line by line, the developer communicates the goal in plain English. The AI model then generates the code that meets this intent.
It replaces the traditional idea of programming with a conversational workflow.
You describe. The AI generates. You test. You refine.
Researchers describe this shift as a change in intent mediation. In the past, developers mediated intent through syntax. Today, we communicate intent directly, almost the way a designer might describe an idea to a colleague.
This does not eliminate the need for developers. Instead, it elevates the role. Developers move from the task of typing code to the larger responsibility of designing systems, evaluating architecture, and ensuring the software behaves as expected.
How Vibe Coding Works: A Detailed Step-by-Step Process
Here is a deeper and more realistic version of the workflow, including what typically happens behind the scenes.
1. You Describe the Goal
You begin by expressing what you want to build. This can be a full application or a small component.
For example:
“Create a simple to-do app with a title, description, due date, and a way to mark tasks as completed.”
This description gives AI a clear intention to work with.
The better the description, the better the result. Developers today are learning that clarity is a form of power.
2. The AI Generates Code
The model translates your instructions into programming languages, libraries, and frameworks.
If you mentioned React, the output will follow React’s structure.
If you asked for a backend with Node.js, the model generates that part.
This is where the speed advantage becomes visible. What used to take hours or days appears in seconds.
3. You Test the Result
You run the generated code and see what works. Sometimes the UI looks exactly right. Other times it needs adjustments. This feedback loop forms the core of vibe coding.
4. You Refine the Instructions
Once you see the output, you refine the request.
You might say:
“Improve the mobile layout. Add a dark theme. Store tasks in local storage so the data persists.”
The AI then modifies or replaces existing code to meet these new expectations.
5. You Iterate Until the App Works as Intended
The process continues until the app feels complete.
This iterative cycle resembles pair programming, except your partner can generate entire components instantly.
The overall development experience feels more fluid and exploratory.
Why Vibe Coding Is Getting So Much Attention
Vibe coding is not popular simply because it is new. It solves real frustrations and opens new opportunities.
Speed Gains Are Significant
Building a working prototype is often five to ten times faster.
Tasks that once required long debugging sessions are now replaced with quick revisions.
Creativity Expands
Since the AI handles the boilerplate, you have more time to think about:
- user experience
- interface layout
- the overall flow of the product
- how the system solves the problem
Many developers say vibe coding feels closer to product design than traditional programming.
Lower Barrier to Entry
People who are not traditional software engineers can now build applications.
Product managers, founders, students, and designers can convert ideas into functional tools.
This democratization is one of the biggest shifts in modern software development.
Fast Feedback Encourages Exploration
Seeing results quickly pushes you to experiment more.
I personally built a newsletter analytics dashboard in two hours, something I had been delaying for weeks.
Startups Are Adopting It Quickly
According to Y Combinator, many startups in the Winter 2025 batch used AI to produce most of their codebase. This is unprecedented and signals how deeply vibe coding is shaping early-stage product development.
The Challenges: What You Must Watch Out For
Despite its benefits, vibe coding is not perfect. The limitations matter because they influence how safely it can be used in real-world environments.
AI Can Generate Messy or Redundant Code
The code may work initially but become difficult to maintain later.
For example, AI might create multiple similar functions or inconsistent structures.
Security Issues Are Still a Concern
Unless reviewed, the output may contain issues such as:
- SQL injection vulnerabilities
- incorrect authentication flows
- exposed API keys
- unsafe dependencies
Security reviews remain essential.
Compliance Requirements Can Slow Adoption
Industries such as healthcare or finance cannot accept generated code without auditability and traceability.
Debugging Can Become Slower
If you did not write the code, it may take time to understand the logic when something breaks.
Overdependence May Harm Core Skills
If developers rely solely on AI for everything, their fundamentals may weaken.
This matters because debugging, optimization, and architectural decisions still require human expertise.
This is why enterprises are building governance frameworks before integrating vibe coding into production systems.
Vibe Coding Compared with Agentic AI
A common misconception is that vibe coding and agentic AI are the same. They serve different purposes.
Vibe Coding
- You stay in control.
- You guide the AI step by step.
- Great for creative builds, prototypes, and interface development.
- Requires active participation and oversight.
Agentic AI
- The AI plans and executes tasks more independently.
- It can break down goals, create sub-tasks, and run processes on its own.
- Useful for automation or repeated workflows.
- Requires strong guardrails to avoid unexpected actions.
A simple mental model:
Vibe coding is like working with a junior developer.
Agentic AI is like delegating work to a highly autonomous assistant.
Best Practices for Getting Reliable Results with Vibe Coding
The quality of the output improves dramatically when you apply the following habits.
Write Clear and Detailed Instructions
Specify libraries, programming languages, design styles, or restrictions.
For example, “Use React with Tailwind and avoid using external UI libraries.”
Test After Every Iteration
Small, frequent checks help you spot problems early.
Review the Code for Logic and Structure
You do not need to read every line, but reviewing high-level structure prevents surprises later.
Commit Code Frequently
Version control makes it easy to compare outputs or revert changes.
Document the Prompts You Used
This helps you understand how the project evolved.
It also provides helpful context during handovers or audits.
Use Automated Tools for Quality Checks
Security scanners, linters, and testing frameworks should remain part of your workflow.
Real-World Examples and What They Teach Us
Kevin Roose
He used vibe coding to build a lunch scheduling app. It worked, but it had bugs. This shows that AI can generate working software but still requires human judgment.
Enterprise Hackathons
Teams are generating prototypes in a matter of days. However, compliance and security teams still require human review before anything reaches production.
Students and Beginners
Studies show beginners rely heavily on automated testing and rarely look at the code. This raises questions about long-term skill reliability.
These examples highlight that while vibe coding increases speed, human oversight remains necessary.
The Future of Vibe Coding
Based on industry movement, three major developments are expected.
Integrated Development Environments
IDEs are beginning to support prompting, code generation, debugging, testing, and deployment in a unified flow.
AI Testers
AI will soon write unit tests, execute them, and explain failures. This will allow faster iteration and higher reliability.
New Roles
We may see job titles such as AI Orchestrator or Prompt Architect.
These roles will require deep understanding of how to communicate with AI systems to create consistent, high-quality software.
How You Should Approach Vibe Coding in Your Career
Vibe coding should not be viewed as a threat.
It should be seen as a competitive advantage.
Developers who adopt it early will be able to build faster, iterate more often, and focus on higher-level thinking.
Here is a simple plan to start.
Start with Small, Low-Risk Projects
Internal tools, dashboards, and hobby apps are perfect for learning.
Learn How to Create Strong Prompts
Prompt clarity has become a core technical skill.
Maintain a Prompt Library
Save the prompts that produce good results so you can reuse or adapt them.
Keep Strengthening Your Fundamentals
Core programming concepts will help you detect mistakes and improve the reliability of AI generated software.
Frequently Asked Questions
Is vibe coding ready for production?
It is ready for prototypes and internal tools.
Production use must include testing, audits, and security reviews.
Can non-developers use vibe coding?
Yes. The barrier to entry is lower, but understanding basic programming concepts improves the outcome significantly.
Will vibe coding replace developers?
It will not replace developers.
It will replace developers who do not adapt to working with AI.
Final Thoughts
Vibe coding represents one of the most significant shifts in software development since the mainstream adoption of cloud computing. It speeds up creation, increases experimentation, and makes software development more accessible to a wider group of people.
However, it also introduces new responsibilities related to security, governance, and long-term maintainability.
The most successful professionals will be those who embrace this technology early, understand its strengths, recognize its weaknesses, and learn how to guide it effectively.
AI literacy is becoming just as important as coding literacy.
The sooner you build comfort with this new workflow, the more prepared you will be for the next stage of the software industry.