The Complete GitHub Copilot Guide: Mastering AI-Powered Development in 2025

GitHub Copilot has evolved from a simple code completion tool into a comprehensive AI development platform that’s transforming how developers write, review, and maintain code. With over 15 million developers already using GitHub Copilot, it’s become the most widely adopted AI coding assistant. This guide covers everything you need to know about Copilot’s features, pricing, and best practices.

What is GitHub Copilot?

GitHub Copilot is an AI-powered “pair programmer” that integrates directly into your development environment. It provides intelligent code suggestions, explanations, and automated coding assistance across multiple programming languages and frameworks. Copilot works in popular IDEs like VS Code, Visual Studio, JetBrains, Eclipse, Xcode, and even command-line tools.

Pricing Plans (Updated May 2025)

GitHub has restructured its pricing to offer more flexibility:

Plan	Price	Code Completions	Chat Requests	Premium Model Access	Key Features
Free	$0	2,000/month	50/month	Limited	Basic completion, chat
Pro	$10/month or $100/year	Unlimited	Unlimited base + 300 premium	GPT-4.1 unlimited + advanced models	Chat, code review, PR summaries
Pro+	$39/month or $390/year	Unlimited	Unlimited base + 1,500 premium	Latest models (GPT-4.5)	Agent mode, priority previews, multiple issue assignment
Enterprise	Custom pricing	Unlimited	Unlimited	All models	Knowledge bases, analytics, enhanced security

Note: Additional premium requests cost $0.04 each for Pro and Pro+ plans.

Core Features

1. Code Completion

The foundation of Copilot is its intelligent autocomplete functionality. As you type, Copilot displays “ghost text” suggestions that you can accept with Tab or Enter.

How to use:

• Simply start coding in any supported IDE with the Copilot extension
• Suggestions appear automatically as you type
• Use Ctrl+Enter (or Cmd+Enter on Mac) to see multiple suggestions
• Hover over ghost text to accept word-by-word

Pro tips:

• Write descriptive comments to guide Copilot’s suggestions
• Use consistent naming conventions for better predictions
• Review suggestions carefully before accepting
• If suggestions aren’t relevant, refine your comments or variable names

Example:

// Function to calculate compound interest
function calculateCompoundInterest(principal, rate, time, frequency) {
  // Copilot will suggest the complete implementation
  return principal * Math.pow(1 + rate / frequency, frequency * time);
}

2. Copilot Chat

Copilot Chat transforms your development workflow with conversational AI assistance. Available in IDEs, GitHub.com, GitHub Mobile, and Windows Terminal.

Key capabilities:

• Code explanations and debugging help
• Test generation and refactoring suggestions
• Architecture discussions and best practices
• Language-specific questions and documentation

Access points:

• IDE: Open the Copilot Chat panel (View > GitHub Copilot Chat)
• GitHub.com: Click the chat bubble icon
• Mobile: Available in the GitHub Mobile app
• Terminal: Use GitHub CLI with Copilot extension

Effective prompting strategies:

✅ Good: "Explain this sorting algorithm and suggest optimizations for large datasets"
✅ Good: "Generate unit tests for this authentication function"
✅ Good: "Refactor this function to use async/await instead of promises"

❌ Avoid: "Fix my code" (too vague)
❌ Avoid: "What does this do?" (without context)

3. Copilot Coding Agent (Public Preview)

The coding agent is an autonomous AI that can make code changes for you by working on GitHub issues and creating pull requests. This feature represents a significant leap toward autonomous development.

How it works:

1. Assign a GitHub issue to “GitHub Copilot” (like assigning to a teammate)
2. Or use @github commands in Copilot Chat
3. The agent analyzes the issue, creates a plan, and implements changes
4. Creates a draft PR with detailed explanations of changes

Best use cases:

• Adding features and fixing bugs
• Extending tests and refactoring code
• Improving documentation
• Medium-complexity tasks in well-tested codebases

Example workflow:

# In Copilot Chat
@github Create a pull request to add input validation to the user registration form

# Or assign an issue directly to GitHub Copilot

Requirements:

• Available for Copilot Pro+ and Enterprise plans
• Must be enabled in account settings (off by default)
• Works best with clear, specific issue descriptions

4. Code Review with AI

Copilot can act as an AI code reviewer, providing feedback and suggesting improvements directly in your IDE or on GitHub pull requests.

Feature	Availability	Action Required	Output
Inline Comments	VS Code, GitHub PR	Select code + request review	Specific suggestions with explanations
Apply Changes	VS Code, GitHub PR	Click “Apply Change” button	One-click fixes
Security Scanning	All platforms	Automatic during review	Vulnerability warnings
Performance Tips	All platforms	Automatic during review	Optimization suggestions

How to use:

• VS Code: Select code and use “Copilot: Request Code Review”
• GitHub PR: Add Copilot as a reviewer on pull requests
• Targeted review: Highlight specific code sections for focused feedback

Supported languages: C/C++, C#, Java, JavaScript, Python, Ruby, Swift, Kotlin, TypeScript, and more.

5. Pull Request Summaries

Copilot can automatically generate comprehensive PR descriptions, saving time and improving documentation.

How to use:

1. Open a pull request (new or existing)
2. Click the Copilot icon (🔥) in the description field
3. Select “Summary”
4. Review and edit the generated content

What it includes:

• Prose summary of changes
• Bullet points of key modifications
• List of affected files and components
• Context about the purpose of changes

6. Copilot in Command Line

The GitHub CLI extension brings Copilot’s intelligence to your terminal.

Command	Purpose	Example Usage	Output
gh copilot explain	Understand shell commands	gh copilot explain "ls -la"	Detailed command explanation
gh copilot suggest	Get command suggestions	gh copilot suggest "find TODO items"	Suggested shell commands

Installation:

# Install GitHub CLI
gh auth login

# Install Copilot CLI extension
gh extension install github/gh-copilot

Practical examples:

$ gh copilot explain "find . -name '*.js' -exec grep -l 'TODO' {} \;"
$ gh copilot suggest "Find all files modified in the last 7 days"
$ gh copilot suggest "Create a backup of the database with timestamp"

7. GitHub Models (Public Preview)

GitHub Models allows you to choose from multiple AI models including Claude 3.7 Sonnet, Gemini 2.5 Pro, OpenAI o1, and others.

Model	Best For	Speed	Cost	Special Features
GPT-4.1 (default)	General development tasks	Medium	Base	Well-balanced for all tasks
GPT-4.5	Complex logic, reasoning	Slow	Premium	Advanced problem solving
Claude 3.7 Sonnet	Code analysis, documentation	Medium	Premium	Excellent at explanations
Gemini 2.0 Flash	Quick tasks, image analysis	Fast	Premium	Vision capabilities
o4-mini	Simple completions	Very Fast	Base	Lightweight, efficient
OpenAI o1	Mathematical reasoning	Slow	Premium	Advanced reasoning chains

Choosing the right model:

• Complex logic/reasoning: GPT-4.5 or Claude 3.7 Sonnet
• Quick completions: o4-mini or Gemini Flash
• Image analysis: Gemini 2.0 Flash
• General use: GPT-4.1 (default)
• Mathematical problems: OpenAI o1

8. Copilot Edits (Multi-file Editing)

Copilot Edits enables AI-powered changes across multiple files from a single prompt.

Mode	Control Level	IDE Support	Best For	User Input Required
Edit Mode	High (you choose files)	VS Code, JetBrains	Targeted changes, refactoring	Specify files to modify
Agent Mode	Low (AI decides)	VS Code, Visual Studio	Complex tasks, architecture changes	Describe the goal

Example workflows:

Edit Mode: "Rename the 'userData' variable to 'userProfile' in this file"
Agent Mode: "Add comprehensive logging throughout the authentication system"

9. Copilot Workspace (Public Preview)

Copilot Workspace is an in-browser development environment specifically designed for pull request workflows.

Key features:

• Add new files directly to the file tree
• Reduced terminal latency
• Side-by-side code editor with AI suggestions
• Built-in build and test capabilities
• Integrated code review and comment handling

Access: Click “Open in Workspace” on any GitHub pull request (invite-only preview)

10. Copilot Spaces

Copilot Spaces create shared, contextual environments where teams can centralize project knowledge for better AI assistance.

What you can add to a Space:

• Entire repositories or specific files
• Documentation and style guides
• Design mockups and screenshots
• Custom instructions and coding standards
• Architecture diagrams and API specs

Benefits:

• AI responses tailored to your project context
• Shared team knowledge base
• Consistent coding standards enforcement
• Faster onboarding for new team members

Creating effective Spaces:

1. Add your main codebase and key documentation
2. Include coding standards and style guides
3. Add architectural decision records (ADRs)
4. Include frequently referenced APIs and libraries
5. Set up custom instructions for your team’s preferences

11. Extensions and Integrations

Copilot Extensions expand functionality by integrating third-party tools into Copilot Chat.

Extension	Purpose	Example Commands	Capabilities
Sentry	Error tracking	“Show 5 most critical errors from last 24h”	Query error data, create issues
Docker	Container management	“List running containers with resource usage”	Container operations, deployment
Kubernetes	Cluster operations	“Show pod status for production namespace”	Troubleshooting, scaling
Azure/AWS	Cloud resources	“List EC2 instances in us-east-1”	Resource management, monitoring

Installation: Find and install extensions from GitHub Marketplace under “GitHub Copilot Extensions”

Usage pattern:

# With Sentry extension installed
"Use Sentry to show the 5 most critical errors from the last 24 hours"

# With Docker extension
"Docker: list all running containers and their resource usage"

12. Custom Instructions

Personalize Copilot’s behavior with custom instructions that apply to all your interactions.

Setting up instructions:

1. Go to Copilot Chat settings
2. Add personal instructions in natural language
3. Include coding preferences, frameworks, and style guidelines

Example instructions:

- Always use TypeScript instead of JavaScript
- Prefer functional programming patterns
- Include comprehensive error handling
- Write tests using Jest and React Testing Library
- Follow the project's ESLint configuration
- Explain complex algorithms with comments

Best Practices and Tips

Writing Effective Prompts

Be specific and contextual:

✅ "Create a React component for user authentication with form validation, error handling, and accessibility features"
❌ "Make a login form"

Use examples and constraints:

✅ "Refactor this function to use the repository pattern, similar to how UserRepository is implemented"
❌ "Make this code better"

Iterate and refine:

1. "Create a user service class"
2. "Add input validation to the user service"
3. "Add error logging to the validation methods"

Security Considerations

• Review all generated code before committing
• Never include sensitive data in prompts
• Validate dependencies suggested by Copilot
• Use organization policies to restrict certain patterns
• Enable security scanning on generated code

Performance Optimization

• Keep files manageable – Very large files may reduce suggestion quality
• Provide clear context with comments and descriptive names
• Use consistent patterns throughout your codebase
• Regularly update extensions for the latest improvements

Team Collaboration

• Share Copilot Spaces with consistent project context
• Establish coding guidelines that Copilot can follow
• Use custom instructions for team standards
• Review AI-generated PRs with the same rigor as human code

Getting Started Checklist

For Individual Developers

1. Choose your plan based on usage needs
2. Install Copilot extensions in your preferred IDE
3. Set up custom instructions for your coding style
4. Try the GitHub CLI extension for terminal productivity
5. Experiment with different models to find what works best

For Teams

1. Enable Copilot for your organization
2. Create shared Copilot Spaces with project context
3. Establish team coding guidelines and custom instructions
4. Set up knowledge bases (Enterprise) with internal documentation
5. Train team members on effective Copilot usage
6. Implement review processes for AI-generated code

For Organizations

1. Evaluate security and compliance requirements
2. Set up organization-wide policies and restrictions
3. Monitor usage analytics and ROI metrics
4. Provide training and best practices documentation
5. Integrate with existing development workflows

Troubleshooting Common Issues

Suggestions Not Appearing

• Check that Copilot extension is enabled and authenticated
• Verify you haven’t exceeded usage limits
• Clear editor cache and restart IDE
• Check network connectivity to Copilot services

Poor Suggestion Quality

• Add more descriptive comments and context
• Use consistent naming conventions
• Break down complex problems into smaller parts
• Try different AI models for different task types

Performance Issues

• Reduce file size if working with very large files
• Close unnecessary files and tabs
• Update to the latest Copilot extension version
• Check IDE performance and available memory

Future of GitHub Copilot

GitHub Copilot continues to evolve rapidly, with the entire software development lifecycle being reimagined through intelligent agents. Upcoming developments include:

• Enhanced autonomous agents for more complex development tasks
• Better integration with cloud platforms and DevOps tools
• Improved context understanding across larger codebases
• Advanced debugging and testing capabilities
• Real-time collaboration features for distributed teams

Conclusion

GitHub Copilot has transformed from a code completion tool into a comprehensive AI development platform. With features ranging from autonomous coding agents to intelligent code review, it’s reshaping how developers approach software development. The key to success with Copilot is understanding when and how to use each feature effectively, always maintaining human oversight and code quality standards.

Whether you’re an individual developer looking to boost productivity or an organization planning to integrate AI into your development workflow, GitHub Copilot offers powerful tools to enhance your coding experience. Start with the free tier to explore the capabilities, then upgrade to Pro or Pro+ as your needs grow.

The future of software development is collaborative—between humans and AI. GitHub Copilot is leading that transformation, making development more efficient, accessible, and enjoyable for developers worldwide.