Vibe Coding Tutorial for Beginners

Vibe Coding is a brand-new programming paradigm: instead of writing code line by line, you describe what you want in natural language; AI writes the code, and we are responsible for reviewing and steering the direction.

Vibe Coding Tutorial Reference:https://www.example.com/vibe-coding/vibe-coding-tutorial.html

What is Vibe Coding

Vibe CodingThe term was first coined by Andrej Karpathy, former AI Director at Tesla and co-founder of OpenAI, in February 2025.

He summarized this brand-new programming approach in one sentence:

「I just vibe. I don't even touch the keyboard sometimes. I just talk to the AI, it writes the code, I review it, and we iterate.」

In other words: you just describe your "vibe", AI writes the code, you review it, and then iterate back and forth.

Simply put, Vibe Coding is: you tell the AI in plain language what feature you want, and the AI writes the code for you. No need to worry about syntax details, no need to memorize API parameters, no need to manually debug every error — the AI handles all of that.

Our role shifts from "the person who writes code" to "the person who describes requirements" — or rather, from programmer to product manager + architect.

Vibe Coding isn't about letting AI replace your thinking; it's about letting AI handle low-value repetitive work, allowing you to focus on the more creative parts: understanding problems, designing architecture, and verifying results.

Vibe Coding vs Traditional Programming

Understanding the differences between Vibe Coding and traditional programming approaches helps you use it better.

Dimension	Traditional Programming	Vibe Coding
Input Method	Writing code line by line manually	Describing requirements in natural language
Focus	Syntax, APIs, implementation details	Requirements, architecture, verification
Debugging Method	Manual breakpoint/log debugging	Throwing error messages to AI and letting it fix them
Speed	Depends on typing speed and proficiency	Depends on the clarity of requirement descriptions
Applicable Scenarios	All programming tasks	Prototype development, CRUD, scripting tools, UI pages
Core Skills	Programming language proficiency	Requirement decomposition + result verification ability

Why Vibe Coding is Possible Now

Vibe Coding became possible in 2025 because several key conditions matured.

The Leap in Large Model Coding Capabilities

Models like GPT-5.5, Claude 5, and Gemini have significantly improved accuracy in code generation.

They can not only write syntactically correct code, but also understand project context, follow best practices, and handle edge cases.

More importantly, they can handle extremely long contexts — reading an entire project at once and understanding your codebase structure.

The Explosion of AI Programming Tools

Tools like Cursor, Claude Code, GitHub Copilot, and Windsurf have deeply integrated AI capabilities into the development workflow.

These tools can not only complete code, but also directly modify files, run terminal commands, and search the codebase — working like a real developer.

The Emergence of Agent Mode

Tools in Agent mode can autonomously execute multi-step tasks: reading files, writing code, running tests, and fixing errors based on test results.

You only need to give an initial instruction, and the Agent will loop and iterate on its own until the task is complete.

Introduction to Mainstream Tools

The following are the most mainstream Vibe Coding tools currently available, each with its own focus.

Tool	Type	Core Features	Suitable Scenarios
Qoder	Agent IDE	Deep codebase understanding, Quest automated tasks, multi-Agent, Repo Wiki, CLI/IDE dual mode	Medium-to-large projects, long-term project maintenance
Trae	AI-native IDE	Conversation-driven development, automatic code generation and modification	Vibe Coding, rapid new project scaffolding
Cursor	AI editor	Project-level understanding, multi-file modification, Agent mode	Full-stack development, large projects
Claude Code	CLI Agent	Execute complex tasks in the terminal, automatically modify projects	Backend, automated development
GitHub Copilot	AI coding assistant	Intelligent completion, chat, Agent	Everyday development assistance
Windsurf	AI editor	Cascade workflow, automatic multi-file modification	Rapid development, small-to-medium projects
OpenAI Codex	AI coding Agent	Understand tasks and execute the complete development workflow	Automated development
Bolt.new	Online AI development platform	Generate a complete application from one sentence	MVP, prototype validation
v0 by Vercel	UI generation tool	Automatically generate React pages	Page design, component development
Replit AI	Online IDE	Cloud development + AI collaboration	Teaching, rapid testing
Lovable	AI application generator	Generate SaaS directly from a description	Startups, product validation
Firebase Studio	AI application platform	AI + backend service integration	App / Web development

If you are new to Vibe Coding, you can start with a domesticQoderorTraeStart; it operates similarly to VS Code, has the gentlest learning curve, and won't change the editor environment you're familiar with.

Quick Start

Below, usingClaude Code (terminal CLI)as an example, we'll demonstrate a typical Vibe Coding workflow.

For the complete Claude Code tutorial, see:https://www.example.com/claude-code/claude-code-tutorial.html

First Project: Hello, Vibe World!

Goal:In 5 minutes, use pure natural language to let Claude Code help you create a personal business card webpage.

Step 1: Create a project folder

mkdir my-card && cd my-card
claude

Step 2: Describe what you want to Claude

In the Claude Code interface, enter:

帮我创建一个个人名片网页，要求：
- 显示我的名字（张三）和职业（前端开发者）
- 有一个简短的个人简介区域
- 列出3个技能标签（React、Python、设计）
- 设计风格：简洁现代，深色背景，有轻微的渐变效果
- 单个 HTML 文件，不需要外部依赖

Step 3: Watch Claude work

You will see Claude Code automatically:

分析你的需求
创建 index.html 文件
写入完整的 HTML、CSS 和少量 JavaScript

Step 4: View the result

open index.html   # macOS
# 或
xdg-open index.html   # Linux

Step 5: Iterate and modify

If you're not satisfied, continue the conversation:

把背景色改成深蓝色渐变，字体换成更现代的 sans-serif，
技能标签加上悬停动画效果

Claude Code will directly modify the files without you touching any code.

Vibe Coding Core Workflow

The core workflow of Vibe Coding can be summarized in four steps: Describe, Review, Iterate, Deliver.

Complete Workflow Diagram

描述需求
    ↓
AI 生成代码
    ↓
你审查 Diff
    ↓
  ┌─ 不满意 → 描述修改意见 → AI 重新生成
  │
  └─ 满意 → 运行测试
              ↓
            ┌─ 测试失败 → 把报错贴给 AI → 修复
            │
            └─ 测试通过 → 提交代码

Step 1: Describe Requirements

Tell Claude Code what you want in natural language.

There's no need to write code or mention technical details. Just clearly state "what to do".

A simple example of a requirement description:

帮我创建一个 Python Flask 项目，有一个 /api/tasks 接口，
支持 GET 获取任务列表和 POST 创建新任务，
任务数据用 JSON 文件存储。

After receiving it, Claude Code will plan the file structure, generate code, install dependencies, and run tests on its own.

Step 2: Review the Diff

After generating code, Claude Code will display all changes (Diff) for you to review.

This is the most important step in Vibe Coding——you must understand what the AI changed.

When reviewing, focus on:

Check item	What to look at specifically
Logical correctness	Whether conditional logic is reasonable and edge cases are handled
Security	Whether there are security vulnerabilities such as SQL injection and XSS
Data flow	Whether data input, processing, and output meet expectations
Naming conventions	Whether variable names and function names are clear and easy to understand
Redundant code	Whether there is unnecessary duplication or unused imports

Reviewing is not about nitpicking, but ensuring you understand what every line of code does. If you don't understand a piece of code, just ask Claude Code: "What does this code mean? Why was it written this way?"

Step 3: Iterate and Modify

After identifying issues during review, describe the changes you want in natural language.

Examples of common iteration commands:

把 JSON 文件存储改成 SQLite，用 SQLAlchemy 做 ORM。

给 POST 接口加个验证：title 必填，不能为空字符串。

报错了，看一下：
Traceback (most recent call last):
  File "app.py", line 42, in create_task
    db.session.add(task)
AttributeError: 'NoneType' object has no attribute 'session'

After each iteration, Claude Code will regenerate the code and show the Diff, and you review again until you are satisfied.

Step 4: Deliver

Once all features meet expectations and tests pass, commit the code.

Claude Code will help you write the commit message and commit it:

$ git log --oneline
a1b2c3d feat: add task CRUD API with SQLite storage

Hands-on Demo: Building a Todo App from Scratch with Claude Code

Below, we use a complete practical case to demonstrate the entire Vibe Coding workflow.

We will use Claude Code to build a Todo app from scratch, including a frontend page and backend API.

Project Goal

Feature	Description
Add task	Enter the task title and add it to the list
Complete task	Click the checkbox to mark the task as completed
Delete task	Delete unnecessary tasks
Filter	Filter by All / In Progress / Completed
Persistence	Data is saved to SQLite and is not lost on refresh

Step 1: Initialize the Project

Create the project directory in the terminal and start Claude Code:

$ mkdir vibe-todo && cd vibe-todo
$ claude

Then describe your requirements to Claude Code:

帮我创建一个 Todo 应用，要求：
1. 后端用 Python Flask + SQLAlchemy + SQLite
2. 前端用纯 HTML/CSS/JS，风格简约现代
3. 支持添加、完成、删除、筛选任务
4. 所有 API 返回 JSON，前端用 fetch 调用
5. 代码注释用中文

Step 2: What Claude Code Did

After receiving the requirements, Claude Code automatically completed the following steps:

First, it created the project structure:

vibe-todo/
├── app.py              # Flask 主应用
├── models.py           # 数据库模型
├── requirements.txt    # 依赖清单
├── static/
│   ├── style.css       # 样式文件
│   └── script.js       # 前端逻辑
└── templates/
    └── index.html      # 页面模板

Then it generated the backend code. Here are the core contents of app.py:

Example

# File path: app.py
# Flask main application, defining API routes and page entry

from flask import Flask, render_template, request, jsonify
from models import db, Task

app = Flask(__name__)
# Configure SQLite database path
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///todo.db'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
# Initialize database extensions
db.init_app(app)

# Automatically create table structure on application startup
with app.app_context():
db.create_all()

@app.route('/')
def index():
"""Return the main page"""
return render_template('index.html')

@app.route('/api/tasks', methods=['GET'])
def get_tasks():
"""Get all task lists, support filtering by status"""
# Get the filter condition from the query parameter, defaulting to 'all'
status = request.args.get('status', 'all')
# Filter tasks based on status
if status == 'completed':
tasks = Task.query.filter_by(completed=True).all()
elif status == 'active':
tasks = Task.query.filter_by(completed=False).all()
else:
tasks = Task.query.all()
# Convert task objects to a list of dictionaries for easy JSON serialization
return jsonify([t.to_dict() for t in tasks])

@app.route('/api/tasks', methods=['POST'])
def create_task():
"""Create a new task"""
data = request.get_json()
# Validate the required field 'title'
title = data.get('title', '').strip()
if not title:
return jsonify({'error': 'The task title cannot be empty'}), 400
# Create a task object and save it to the database
task = Task(title=title)
db.session.add(task)
db.session.commit()
return jsonify(task.to_dict()), 201

@app.route('/api/tasks/<int:task_id>', methods=['PUT'])
def update_task(task_id):
"""Update task status (complete/incomplete)"""
task = Task.query.get_or_404(task_id)
data = request.get_json()
# If the request contains the 'completed' field, update the status
if 'completed' in data:
task.completed = data['completed']
db.session.commit()
return jsonify(task.to_dict())

@app.route('/api/tasks/<int:task_id>', methods=['DELETE'])
def delete_task(task_id):
"""Delete a specified task"""
task = Task.query.get_or_404(task_id)
db.session.delete(task)
db.session.commit()
return jsonify({'message': 'Deleted successfully'}), 200

if __name__ == '__main__':
app.run(debug=True)

There is also the database model models.py:

Example

# File path: models.py
# Database model definitions, using SQLAlchemy ORM

from flask_sqlalchemy import SQLAlchemy
from datetime import datetime

# Create database instance, initialized later in app.py
db = SQLAlchemy()

class Task(db.Model):
"""Task model, corresponding to the tasks table in the database"""
__tablename__ = 'tasks'

# Primary key, auto-increment integer
id = db.Column(db.Integer, primary_key=True)
# Task title, required, cannot be empty
title = db.Column(db.String(200), nullable=False)
# Completion status, defaults to False
completed = db.Column(db.Boolean, default=False)
# Creation time, automatically recorded
created_at = db.Column(db.DateTime, default=datetime.utcnow)

def to_dict(self):
"""Convert task object to dictionary for easy JSON serialization"""
return {
'id': self.id,
'title': self.title,
'completed': self.completed,
'created_at': self.created_at.isoformat()
}

Step 3: Review the Code

After Claude Code shows the Diff, you review it line by line.

You might find some issues and suggest changes.

For example, you notice the API routes don't have a unified prefix, and suggest a change:

把所有 API 路由加上 /api/v1 前缀，方便以后版本管理。

Claude Code will automatically update all routes, and after your review it's approved.

Step 4: Run Tests

After the review passes, ask Claude Code to start the application and test it:

$ python app.py
 * Running on http://127.0.0.1:5000

Open a browser and visit http://127.0.0.1:5000 to see the complete Todo app interface.

Test the add task feature:

$ curl -X POST http://127.0.0.1:5000/api/v1/tasks \
  -H "Content-Type: application/json" \
  -d '{"title": "学习 Vibe Coding"}'

Returned result:

{
  "completed": false,
  "created_at": "2026-06-24T10:30:00",
  "id": 1,
  "title": "学习 Vibe Coding"
}

Step 5: Commit the Code

After all features are verified, commit the code:

$ git add .
$ git commit -m "feat: 完成 Todo 应用基础功能"

Throughout this hands-on process, you didn't write a single line of code manually. What you did was: describe requirements, review Diff, describe changes, run tests, and commit code. This is the core experience of Vibe Coding.

Tips for Writing Good Prompts

The effectiveness of Vibe Coding largely depends on how you describe the requirements.

Good prompts can enable AI to generate code close to expectations in one go, reducing the number of iterations.

The Four-Element Model

A high-quality prompt should include four elements:

Element	Description	Example
What to do	Clearly describe the functionality to be implemented	"Create a user registration API"
What to use	Specify the tech stack and tools	"Use Flask + SQLAlchemy + SQLite"
How to constrain	Provide constraints and boundaries	"Email is required and needs format validation"
Expected format	Describe output preferences	"Code comments in Chinese, add docstring to every function"

Good Prompts vs Bad Prompts

Bad prompt	Good prompts
Help me create a login feature.	Help me implement a login endpoint using Flask that receives email and password, encrypts the password with bcrypt, and returns a token using JWT, with a token validity of 24 hours. Return specific error messages on login failure.
This button is too ugly.	Change this submit button to have 8px rounded corners, blue background #2563eb, white text, darken the color by 10% on hover, and add a 0.2s transition animation.
There's an error, help me fix it.	When running python app.py, I get an error: AttributeError: 'NoneType' object has no attribute 'session'. It looks like a database initialization issue. Help me troubleshoot and fix it.

Core principle of prompts: the more specific, the better the results. Vague requirements only produce vague code.

Common Misconceptions and Cautions

Misconception 1: AI Can Replace All Programming Knowledge

Vibe Coding lowers the programming barrier, but does not eliminate it.

We still need to understand basic concepts: variables, functions, APIs, databases, HTTP, async, etc. Otherwise, we can't judge whether AI-generated code is correct, nor can we describe requirements effectively.

Misconception 2: Describing All Features at Once

Don't copy the entire product PRD document to AI, expecting it to generate perfect code in one go.

AI's attention has a limit; the more requirements, the more errors.

A more effective approach is: core feature → validate → add feature → validate → continue iterating.

Misconception 3: Not Reading AI-Generated Code

Some developers merge AI-generated code directly without review, which is very dangerous.

AI may introduce security vulnerabilities, performance issues, or completely unreasonable architecture.

We at least need to quickly review the key logic to ensure there are no obvious issues.

Notes

Don't write sensitive information (API keys, database passwords) directly in the conversation — first use environment variable placeholders in code, then fill them in manually.
Commit to Git after every key change, making it easy to roll back when problems arise.
AI-generated code may not conform to your team's coding standards, so manual adjustments are needed.
For code that requires high reliability (payments, authentication, data processing), be sure to manually review it after AI generation.

Scenarios Suitable for Vibe Coding

Vibe Coding is not a silver bullet; knowing which scenarios fit it can help you allocate your energy better.

Scenario	Suitability	Description
Prototype/MVP development	Extremely high	Quickly validate ideas, get a usable demo in a few hours
CRUD APIs	Extremely high	Clear repetitive patterns, AI completion quality is high
Frontend pages/components	Very high	HTML/CSS/React components, AI is very good at these
Scripts/automation tools	Very high	One-off scripts, data processing, file operations
Unit test writing	Very high	Generate test cases based on function signatures
Complex algorithm implementation	Medium	Requires clear algorithm description, and correctness needs manual verification
Low-level system optimization	Relatively low	Involves memory layout, cache lines, hardware characteristics; AI is prone to subtle errors
Code with high security requirements	Caution	Encryption, authentication, payment code; AI-generated output must be reviewed by experts

Other extensions

Agent Tools

Python Implementing Intelligent Agents

Vibe Coding Tutorial for Beginners

What is Vibe Coding

Vibe Coding vs Traditional Programming

Why Vibe Coding is Possible Now

The Leap in Large Model Coding Capabilities

The Explosion of AI Programming Tools

The Emergence of Agent Mode

Introduction to Mainstream Tools

Quick Start

First Project: Hello, Vibe World!

Vibe Coding Core Workflow

Complete Workflow Diagram

Step 1: Describe Requirements

Step 2: Review the Diff

Step 3: Iterate and Modify

Step 4: Deliver

Hands-on Demo: Building a Todo App from Scratch with Claude Code

Project Goal

Step 1: Initialize the Project

Step 2: What Claude Code Did

Example

Example

Step 3: Review the Code

Step 4: Run Tests

Step 5: Commit the Code

Tips for Writing Good Prompts

The Four-Element Model

Good Prompts vs Bad Prompts

Common Misconceptions and Cautions

Misconception 1: AI Can Replace All Programming Knowledge

Misconception 2: Describing All Features at Once

Misconception 3: Not Reading AI-Generated Code

Notes

Scenarios Suitable for Vibe Coding