GitHub Copilot offers several AI-powered coding features that help you speed up development and streamline your workflow. In this post, we’ll break down five key features—explaining how and when to use each one.
Inline Code Completion via Comment 📝
Use natural language comments to prompt Copilot for inline code generation. It’s like leaving yourself a “to-do” note that gets automatically turned into code.
How to Use
- Write a descriptive comment in your code (e.g., // Create a function that validates email addresses).
- Start typing below the comment and watch Copilot suggest code based on your description.
- Press Tab to accept or modify the suggestion as needed.
Real Life Use Cases
- Quickly scaffolding a new function to handle form validations.
- Generating standard CRUD operations for a REST API.
- Creating helper functions for common tasks like formatting dates. > Use this feature when you need to quickly generate boilerplate code from a clear description 🚀
Code Prompt Dialog (Ctrl + I) ⌨️
Opens a dedicated prompt (using Ctrl+I or Command+I) where you can type detailed instructions for generating code.
How to Use
- Hit Ctrl+I (or Command+I on macOS) to open the prompt dialog.
- Type a clear, concise description (e.g., “Generate a function to filter out invalid URLs”).
- Review multiple suggestions shown in the dialog and select the best one.
Real Life Use Cases
- Quickly prototyping a new feature snippet without interrupting your flow.
- Generating alternative implementations for a specific task.
- Rapidly iterating through different code approaches. > Use this where you should use this feature when you require a fast, on-demand code snippet without breaking your coding flow.⏱️
Note:
- Fast and minimizes interruptions.
- Presents multiple suggestions so you can choose the best one.
Copilot Chat with Reasoning/Thinking 🧠
Provides code suggestions along with detailed explanations and reasoning—like having a mentor explain every step.
How to Use
- Open the Copilot Chat window via your IDE’s menu or shortcut.
- Ask a detailed question (e.g., “Explain how this pagination function works and suggest improvements”).
- Choose AI model that provide reasoning/thinking
- Read the generated code and the accompanying step-by-step explanation.
Real Life Use Cases
- Debugging complex functions where understanding the logic is key.
- Learning new algorithms or design patterns.
- Onboarding team members with clear, step-by-step code explanations. > Use this where you should use this feature when you need in-depth explanations and insights for complex code logic or debugging challenges.🔍
Notes :
- Great for learning and deep dives.
- Provides context and best practice insights.
Copilot Chat without Reasoning Models ⚡
Delivers concise code suggestions without extra commentary—fast and straight to the point.
How to Use
- In the Copilot Chat window, specify “Just the code, please.”
- Accept the direct code suggestion if it meets your requirements.
Real Life Use Cases
- Rapid prototyping when you only need a code snippet.
- Situations where you already understand the logic and just need the implementation.
- Quick bug fixes or minor updates. > Use this where you should use this feature when you just need a concise, ready-to-use code snippet without extra commentary.🚀
Notes:
- Quick and clutter-free.
- Ideal for experienced developers who want minimal guidance.
Copilot Chat with Edit File 🖥️
Merges interactive chat with direct file editing, allowing you to ask questions and immediately apply changes to your code.
How to Use
- Open Copilot Chat in edit mode (using the dedicated “Edit File” option).
- Provide context by selecting the file or code section to update.
- Engage in a multi-turn conversation to refine the edits; review diffs and apply the updates.
Real Life Use Cases
- Refactoring a large component or module.
- Integrating a new feature that spans multiple parts of a file.
- Collaborative code reviews with direct file modifications. > Use this where you should use this feature when you want to seamlessly apply iterative changes to your file through an interactive chat session. 🛠️
Notes:
- Streamlines your workflow by combining chat and editing.
- Keeps all changes in one place for easy review.
- Risk of unintended changes if suggestions aren’t carefully reviewed.
- Requires extra caution during file-wide edits.
Copilot Agent 🤖
An advanced mode where Copilot acts as an autonomous agent, managing multi-file edits and handling complex tasks with minimal input.
How to Use
- Activate Agent Mode in your IDE (usually via a specific command or setting).
- Provide a high-level task (e.g., “Update all API endpoints to use the new version”).
- Review the aggregated changes across multiple files and approve or reject them.
Real Life Use Cases
- Large-scale refactoring or modernization of a codebase.
- Coordinated updates across many files (e.g., renaming variables or updating import statements).
- Automating project-wide repetitive changes like applying security patches. > Use this where you should use this feature when you need to perform extensive, multi-file code updates or refactoring with minimal manual effort. 🔥
Notes:
- Automates complex, multi-file tasks, saving significant time.
- Integrates context from across the project for consistent updates.
- Higher risk of unintended changes—requires thorough review.
- Steeper learning curve; best suited for advanced users.
Final Thoughts 💡
Choosing the right GitHub Copilot feature depends on your specific task and the level of guidance you need. Use inline code completion for clear, simple tasks; opt for the prompt dialog for fast, targeted suggestions; and choose Copilot Chat (with or without reasoning) based on whether you need detailed insights or just a quick snippet. For file-wide or multi-file changes, leverage the edit file mode or the autonomous Copilot Agent.
Happy coding and comment the AI tools you using for code generation and completion with use cases 🎉
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