What Is Cursor AI and Why Developers Are Switching in 2025

Key Features That Make Cursor AI a Game-Changer for New Developers

Cursor AI is transforming how developers write code in 2025, reducing coding time by up to 40% for many users. This advanced AI-powered code editor builds on Visual Studio Code's familiar interface while adding intelligent code generation, refactoring, and debugging capabilities. Whether you're writing your first lines of code or optimizing complex applications, this guide will help you leverage Cursor AI to write better code faster.

Key Features of Cursor AI

Built on VS Code Foundation

Cursor inherits VS Code's robust functionality while adding AI capabilities. This means your existing VS Code knowledge, extensions, and shortcuts continue to work seamlessly, making the transition painless.

Want to understand which model fits your workflow best? See our detailed comparison of Sonnet 3.7 vs Gemini 2.5 Pro.

Operation Modes

The differences become clearer when examining actual code. Here's how each model approached the game's scoring system:

Ask Mode

In this safer mode, the AI suggests changes but waits for your approval before implementing them. Perfect for:

• Learning new languages or frameworks
• Working in critical sections of code
• Understanding AI reasoning before committing changes

Agent Mode

Allows the AI to work more autonomously, handling repetitive or predictable tasks without constant confirmation. Ideal for:

• Generating boilerplate code
• Implementing standard patterns
• Batch processing similar files

Smart Context Tagging

Bring additional context directly into your coding environment with smart tags:

• @file filename.js - References specific project files
• @web URL - Pulls information from online documentation
• @git commit-hash - References specific code versions
• @doc "API documentation" - Includes documentation content

Development Workflow Best Practices

The quality of your instructions dramatically affects Cursor's output. Follow these techniques to get better results:

Test-First Development

1. Write tests describing desired functionality
2. Ask Cursor to implement code that will pass these tests
3. Refine the implementation with the AI until all tests pass

Strategic Logging

Add comprehensive logging to help both you and the AI understand code execution flow:

javascript

Documentation-Driven Development

Start projects with clear documentation files:

• README.md for project overview
• SETUP.md for installation instructions
• CONTRIBUTING.md for contribution guidelines

Ask Cursor to help maintain these documents as your codebase evolves.

Prompt History Management

Create a prompts.md file in your project to document important AI interactions:

markdown

Simplify Early Development

• Use fewer files in early development phases
• Stick with standard language features before introducing complex libraries
• Add explicit comments to mark intentional code patterns:

javascript

// NOTE: This unusual pattern is intentional due to legacy integration

When Cursor Generates Incorrect Code

1. Switch to Ask mode to explore alternatives
2. Try another AI model that might better understand your domain
3. Use checkpoint restoration to revert problematic changes
4. Rephrase your prompt with more specific constraints

When Responses Are Incomplete

1. Type "continue" to request additional output
2. Break complex requests into smaller steps
3. Provide more context about what you're trying to accomplish

When Performance Slows

1. Close unused files to reduce context window usage
2. Use dedicated workspaces for different projects
3. Upgrade your subscription for larger context windows

If you're coding within Cursor, choosing the right LLM for each phase of development can significantly impact velocity and output quality:

• Deploy faster with Gemini — optimized for code generation and throughput.
• Refine with Sonnet — ideal for cleanup, formatting, and structural edits.

Strategically toggling between models helps you maintain flow state and reduce iteration overhead—especially when building dynamic applications like AI-driven games or tools.

Want a broader platform comparison? Cursor vs Windsurf offers a detailed look at IDE-level trade-offs, agent handling, and developer UX.