Improve GitHub Copilot Chat responses by indexing repositories for semantic code search, allowing better context-based answers to questions about code within a repository.
GitHub Copilot now offers text completion for pull request descriptions. This beta feature helps developers write more effective descriptions by suggesting completions based on context.
This post highlights how the GitHub Copilot Chat VS Code Extension was vulnerable to data exfiltration via prompt injection when analyzing untrusted source code.
This article explains the use of GitHub Copilot, an AI-powered coding companion that suggests edits and refactors to improve code quality and developer productivity. It includes examples of how to use Copilot effectively to modify and refactor code.
Discover how GitHub engineers leverage GitHub Copilot to automate repetitive tasks, stay focused, and even explore new technologies.
The GitHub Blog article "4 ways GitHub engineers use GitHub Copilot" discusses how different GitHub engineers leverage GitHub Copilot to enhance efficiency and productivity in their work. The main use cases highlighted in the article are:
1. Semi-automating repetitive tasks: A GitHub engineer uses GitHub Copilot to automate the process of incrementing ID numbers in protobuf definitions, significantly reducing manual work.
2. Avoiding distractions: A colleague develops a regular expression to capture a Markdown code block and extract the language identifier. By prompting GitHub Copilot with a code comment, the regular expression is generated swiftly and accurately.
3. Structuring data-related notes: A support engineer at GitHub uses GitHub Copilot Chat to structure and compile their notes into Markdown tables, enabling efficient documentation of a complex troubleshooting process.
4. Exploring and learning: A colleague uses GitHub Copilot to develop a program in Rust, a programming language he was not previously familiar with. In just 23 minutes, he successfully created a functional program that converts numerical input into written English equivalents.
The GitHub Blog article "4 ways GitHub engineers use GitHub Copilot" discusses how different GitHub engineers leverage GitHub Copilot to enhance efficiency and productivity in their work. The main use cases highlighted in the article are:
1. Semi-automating repetitive tasks: A GitHub engineer uses GitHub Copilot to automate the process of incrementing ID numbers in protobuf definitions, significantly reducing manual work.
2. Avoiding distractions: A colleague develops a regular expression to capture a Markdown code block and extract the language identifier. By prompting GitHub Copilot with a code comment, the regular expression is generated swiftly and accurately.
3. Structuring data-related notes: A support engineer at GitHub uses GitHub Copilot Chat to structure and compile their notes into Markdown tables, enabling efficient documentation of a complex troubleshooting process.
4. Exploring and learning: A colleague uses GitHub Copilot to develop a program in Rust, a programming language he was not previously familiar with. In just 23 minutes, he successfully created a functional program that converts numerical input into written English equivalents.
