Windsurf AI Tutorial for Beginners

Key Concepts

AI-powered code editor, Windsurf, Cascade panel, AI models (Claude 3.5 Sonnet, Gemini 2.5 Pro, GPT-4.0), full-stack application development, React, Node.js, Express, Tailwind CSS, domain name availability checker, whois API, prompt engineering, context management, code deployment, Netlify, MCP (Model-as-Control-Program) servers.

Windsurf Overview

Windsurf is an AI-powered code editor designed to accelerate coding, suitable for both beginners and experienced developers working on projects of any size. It functions as a desktop application, differentiating it from browser-based AI coding tools. While a free tier exists, it's primarily for trial purposes, with the pro plan offering a more cost-effective solution for AI-assisted coding.

Core Features

• File Explorer: A standard file system navigator for accessing and managing project files.
• Code Viewer: The central panel for viewing and editing code files, with tabbed navigation for multiple files.
• Cascade Panel: The primary AI interface, similar to ChatGPT but integrated with the entire codebase. It can answer questions, create files, modify existing code, and insert changes directly.
• Terminal: A command-line interface accessible within Windsurf for running commands, installing software, and starting programs. Commands can also be executed directly from the Cascade chat window.
• Preview: A built-in browser to preview the website directly within the coding tool. Specific elements can be selected to provide context to Windsurf when making changes.

Building a Full-Stack Application

The video demonstrates building a full-stack domain name availability checker using Windsurf.

Project Setup

1. Project Initialization: An empty folder is opened in Windsurf.
2. Technology Selection: Using the Cascade panel in chat mode with Gemini 2.5 Pro, the AI is prompted to suggest technologies for building a domain name availability checker with a React frontend and Node.js backend.
3. Project Structure: The AI suggests using Create React App or Vite for the UI and Node.js with Express for the backend.
4. Code Generation: The AI, in write mode, is instructed to create a project with a UI folder (containing a Vite React project) and a server folder (for the Node.js backend). The whois package is specified for domain checking.
5. Dependency Installation: The AI provides commands to install necessary dependencies using npm install within both the server and UI folders.
6. Running the Application: The AI suggests running npm run dev to start both the UI and server.

UI Enhancement with Tailwind CSS

1. New Chat for Feature Focus: A new chat is started in Cascade to focus on UI improvements, as limiting context improves AI performance.
2. Tailwind Integration: The AI (using Claude 3.5 Sonnet) is instructed to use Tailwind CSS to improve the UI's appearance. Windsurf automatically identifies and modifies the app.jsx file.
3. Dependency Installation: The AI suggests running npm install -D tailwindcss postcss autoprefixer, but encounters an error related to Tailwind version 4.
4. Contextual Documentation: The Tailwind CSS documentation is tagged in the chat to provide the AI with additional context for proper installation.
5. Version Rollback: Due to continued errors with Tailwind version 4, the changes are reverted to a previous checkpoint, and the AI is instructed to use Tailwind version 3 instead.
6. UI Verification: After switching to Tailwind v3, the UI is previewed, and the domain name availability checker is tested.

Server-Side Error Handling

1. Log Analysis: Logs from the server are selected and added to the chat to provide context for error handling.
2. Resilience Improvement: The AI is instructed to improve the server code to be more resilient to timeout errors and other potential issues.
3. Code Review: The AI's code changes are reviewed using Windsurf's highlighting feature (red for removed code, yellow/green for added code).
4. Testing: The updated application is tested to ensure improved error handling.

Adding AI-Powered Domain Name Suggestions

1. New Chat with Web Context: A new chat is started, and the @web tag is used to enable web searches, allowing the AI to access the latest Gemini API.
2. Feature Request: The AI is instructed to add a feature that uses the Gemini 2.5 API to generate domain name suggestions based on a business idea input.
3. API Key Management: The AI instructs the user to add their Gemini API key to a .env file. Windsurf respects the .gitignore file, preventing sensitive information from being sent to Windsurf servers.
4. Windsurf Rules File: The video briefly mentions the windsurf rules file, which allows users to define instructions that Windsurf will follow for every request.
5. Error Handling: An error occurs when generating domain name suggestions. The server code is copied and pasted into the chat for the AI to fix.
6. Model Name Correction: The AI identifies an incorrect model name in the code and suggests a correction. The Gemini 2.5 Pro preview model is used.
7. UI Enhancement: Windsurf Tab is used to quickly modify the code responsible for adding suggestions to the domain search, allowing multiple suggestions to be added at once.

Application Deployment

1. Static Frontend Deployment: Windsurf can directly deploy static frontends using Netlify.
2. Deployment Process: The AI is instructed to deploy the application. Windsurf creates a netlify.toml file to specify deployment configurations.
3. Live Deployment: The application is deployed to a *.wwindsurf.build subdomain and is accessible immediately.

Conclusion

Windsurf is a powerful AI-assisted code editor that streamlines the development process through features like the Cascade panel, AI model integration, context management, and direct code deployment. The video demonstrates how to build a full-stack application, enhance the UI, improve error handling, and add AI-powered features using Windsurf's capabilities. While the AI may not always produce perfect code on the first attempt, Windsurf's features like version rollback and contextual documentation enable efficient debugging and iteration. The ability to deploy static frontends directly from the editor further simplifies the development workflow.