1. Open Relevant Files: Having your relevant files open in your IDE provides GitHub Copilot with context. When you have additional files open, it helps inform the suggestions that are returned. This additional context allows Copilot to provide more relevant and useful code suggestions¹.

2. Understand Context: GitHub Copilot is designed to make predictions based on the context provided. The more contextually rich your input or prompt is, the better the prediction or output will be. While using the code completion feature, Copilot can infer context from the code you’re working on. However, you can further enhance this by providing additional context in your prompts. Unlike ChatGPT, where you need to provide all the data in the prompt window, Copilot can leverage the context from your open files in the editor¹.

3. Learn How to Prompt Effectively: Effective prompts are crucial for a successful experience with any large language model. Experiment with different prompt styles and learn how to structure your requests to get the best results from Copilot².

4. Customize the Copilot Experience: Explore the settings and customize Copilot to your preferences. You can adjust its behavior, enable or disable specific features, and fine-tune its responses to align with your coding style².

5. Remember the Limitations: While Copilot is powerful, it’s essential to recognize its limitations. It’s not perfect, and sometimes it may generate incorrect or suboptimal code. Be prepared to review and modify the suggestions it provides².

Feel free to explore these tips and make the most of GitHub Copilot in your coding workflow! 😊 If you’d like more information, you can also check out the official GitHub Copilot documentation¹. Is there anything else I can assist you with? 🚀