Vibe Coding: Programmers Transition from Writing Code to Directing AI

Vibe Coding: A New Era for Programmers

Recently, a term has gained popularity in Silicon Valley: Vibe Coding. This translates roughly to “atmospheric programming” or “feeling programming”. In simple terms, it means:

You describe the requirements, AI writes the code, and you are responsible for acceptance.

This is not about assistance or code completion; it’s about AI taking over the entire coding process. You only need to tell it, “I want a script that can automatically send emails,” and it will write the code, run it, and even fix bugs.

Sound like science fiction? Not at all; some individuals have already created products in a week that would have previously taken a team a month to complete.

What is Vibe Coding?

The term was introduced this year by Andrej Karpathy, former AI director at Tesla and a founding member of OpenAI. His main point is:

“The way I write code now is by talking to AI. I present my ideas, AI implements them, I test, and I provide feedback. I hardly look at the code anymore; I just observe the results.”

How Does It Work?

Describe the requirement: “Help me create a webpage with a to-do list on the left and a completed list on the right, with drag-and-drop functionality.”
AI generates the code: Tools like Claude, Cursor, and GitHub Copilot directly output the complete code.
Run tests: Check if the results are correct.
Provide feedback: “Change the button color to blue” or “Add a delete confirmation popup.”
AI continues to adjust: Repeat until satisfied.

Throughout this process, you may not write a single line of code yourself.

How Does This Differ from Traditional Programming?

Here’s a comparison:

Dimension	Traditional Software Engineering	Vibe Coding
Core Action	Writing code, debugging, refactoring	Describing requirements, acceptance, feedback
Code Ownership	Programmer has complete control	AI generates, human oversees
Mindset	Machine-oriented (syntax, algorithms, data structures)	Problem-oriented (what users want, business logic)
Skill Focus	Mastery of languages, frameworks, performance optimization	Requirement breakdown, product thinking, acceptance criteria
Development Speed	Measured in days/weeks	Measured in minutes/hours
Code Quality	Depends on programmer’s skill, relatively stable	Depends on AI capability and prompt quality, more variable
Debugging Method	Reading code, setting breakpoints, line-by-line checks	Observing results, providing feedback, letting AI retry
Applicable Scenarios	Large systems, core architecture, performance-sensitive	MVPs, prototypes, utility scripts, internal systems

The difference is clear:

Traditional programming is “I build a car myself,” while Vibe Coding is “I describe what car I want, the factory builds it, I test drive it, and if I’m not satisfied, I make changes.”

How to Get Started with Vibe Coding

If you want to try it out, here’s how:

Tool Selection

Currently, the most popular tools include:

Cursor: Based on VS Code, integrates Claude/GPT, allowing direct interaction to generate code within the editor.
Claude + Browser: Describe requirements on the Claude web version and copy the code to run locally.
GitHub Copilot: Integrated into IDEs, provides real-time code suggestions, suitable for semi-automated modes.
Windsurf / Bolt: Emerging AI programming tools that generate complete projects with one click.
OpenCode: A domestic open-source AI programming assistant that supports multiple model switches (Claude, GPT, DeepSeek, etc.) and is optimized for Chinese scenarios, making it suitable for local developers.

A Real Example

Suppose I want to create a “web-based calculator.”

Traditional Method:

Open the editor and create a new HTML file.
Write the HTML structure, CSS styles, and JavaScript logic.
Handle button clicks, calculation logic, and error boundaries.
Debug various edge cases (division by zero, excessively long numbers, etc.).
Takes about 2-3 hours.

Vibe Coding Method:

Open Cursor and create a new file.
Input: “Help me create an attractive web calculator that supports addition, subtraction, multiplication, and division, with a history record and modern CSS style.”
AI generates complete code (30 seconds).
Run tests, discover an issue: “The history record lacks a clear button.”
AI adds the clear function (10 seconds).
Test again, satisfied, done.
Total time: 5 minutes.

This is not an exaggeration; it’s real.

The Impact of Vibe Coding on Traditional Software Engineering

Many veteran programmers might be skeptical:

“Can this really work? Can AI-generated code go live? Who is responsible if something goes wrong?”

These concerns are valid. Let’s analyze the boundaries and impacts of Vibe Coding objectively.

1. What Scenarios Are Suitable for Vibe Coding?

✅ Very Suitable:

Prototype validation (MVP)
Internal tools, scripts
Personal projects, side jobs
Standardized features (CRUD, forms, display pages)

❌ Currently Unsuitable:

Core financial trading systems
Safety-critical systems like aviation and healthcare
Scenarios requiring extreme performance optimization
Complex architectural designs, distributed systems

2. How Is the Role of Programmers Changing?

It’s not about being replaced; it’s about upgrading.

Previously, a programmer’s core ability was to “translate requirements into code.”

In the future, a programmer’s core ability will be to “break down business problems into instructions that AI can understand and verify the results are correct.”

In other words:

From “coder” to a hybrid of “architect + product manager + tester”
From “writing code” to “designing systems + directing AI + ensuring quality”
From “technical depth” to “technical breadth + business understanding + judgment”

3. The Real Impact on Traditional Software Engineering

I believe there are three levels of impact:

First Level: Disruption of Development Efficiency

Previously, it might take two weeks to go from requirement to launch for a feature. Now, with Vibe Coding, it could be completed in two hours.

What does this mean?

Small teams can accomplish what large teams do.
The cost of trial and error is extremely low, allowing for rapid validation of ideas.
The phrase “one person is a company” is no longer just a slogan.

Second Level: Shift in Skill Requirements

Previously, interviews focused on: can you write a red-black tree, understand memory management, or be familiar with Spring source code?

In the future, interviews may focus on: can you clearly describe requirements, understand business logic, and design acceptance criteria?

The importance of pure technical depth is declining, while the demand for a combination of technical and business skills is rising.

Third Level: Reconstruction of Software Engineering Processes

Traditional process: Requirement review → Technical plan → Coding → Code review → Testing → Launch

Vibe Coding process: Describe requirements → AI generates → Acceptance testing → Launch (or feedback and regenerate)

Code review may become “prompt review”—evaluating not the code, but how well you describe the requirements.

Anxiety for Veteran Programmers and Opportunities for New Programmers

I know many veteran programmers may feel anxious reading this.

“I’ve been writing code for ten years, and now I’m told I don’t have to write anymore?”

Don’t panic. Vibe Coding is not a silver bullet; it has its own issues:

Problem 1: AI Can Make Mistakes, Often Subtly

AI-generated code may run on the surface but could contain security vulnerabilities, performance issues, or unhandled edge cases. Launching without review could lead to serious problems.

Problem 2: AI Struggles with Complex Systems

A simple webpage can be handled by Vibe Coding, but a microservices architecture involving distributed transactions, data consistency, and high concurrency is still beyond AI’s current capabilities.

Problem 3: Maintenance Is a Major Concern

AI-generated code may have inconsistent styles, lack comments, and contain convoluted logic. Three months later, you might not even understand it, let alone maintain it.

Thus, my judgment is:

Vibe Coding will replace some of the “pure execution layer” coding tasks but will not replace the “design layer” and “oversight layer” tasks.

The truly valuable programmers will always be those who:

Can judge whether AI-generated code is correct.
Can design system architectures that guide AI.
Can understand business and translate it into technical solutions.

Three Suggestions for Programmers

1. Learn to “Direct” Rather Than “Do It Yourself”

Treat Vibe Coding as your subordinate. You won’t personally tighten every screw, but you need to understand the blueprint, ensure quality, and point out what’s wrong.

Practicing writing effective prompts is more important than practicing the syntax of a programming language.

2. Deepen Business Understanding, Don’t Just Focus on Technology

AI can help you write code, but it doesn’t understand your company’s business logic, industry rules, or user habits.

Technology can be replaced, but business understanding cannot.

3. Maintain Understanding of Underlying Principles

You may not write code yourself, but you should know how the code runs. Otherwise, if AI provides a solution with obvious performance issues, you won’t be able to spot it.

Vibe Coding doesn’t mean you abandon technology; it means you transition from a technical executor to a technical decision-maker.

Conclusion

Every technological revolution prompts some to shout, “Programmers will be unemployed!”

But history tells us: The more powerful the tools, the more valuable those who know how to use them become.

Vibe Coding is not the end for programmers but a direction for their evolution.

From “code writers” to “problem solvers with code”—that is the essence.

Have you tried Vibe Coding? How was your experience? Feel free to discuss in the comments.