Use an LLM as a tutor and drafting partner: give it a small, specific task in the context of the relevant repository or file, then review and test its suggestion before committing it. GitHub’s basic workflow—create a repository, work on a branch, save a commit, and open a pull request—gives you a way to keep changes separate and reviewable.
Know the GitHub pieces before you ask for help
A repository is where a project’s files and history live. A branch gives you a separate line of work so you can make changes without editing the main branch directly. A commit records a set of changes, and a pull request proposes those changes for review.
GitHub’s Hello World tutorial walks through creating a repository, creating a branch, editing files, committing changes, and opening a pull request. GitHub says the exercise does not require coding, command-line, or Git installation experience.
Ask for a bounded, understandable change
A vague request such as “make my app better” gives an LLM too much room to guess. State what you want, identify where the work belongs, and describe concrete requirements. For a larger goal, ask for one step at a time. GitHub’s prompt-engineering guidance recommends clear, specific prompts, relevant context, and breaking complex work into smaller tasks.
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A prompt pattern for learning
For example, if you are learning JavaScript, you could ask:
I’m learning JavaScript. In
script.js, explain how the current list is rendered. Then suggest the smallest change to display an empty-state message when there are no items. Explain each change, list any assumptions, and tell me how I can verify it.
This prompt identifies the file, asks for an explanation before a change, sets a limit on the scope, and requests a way to check the result. It is a useful starting point, not a guarantee that the explanation or proposed code is correct.
Give the assistant the right project context
When possible, ask your question where the relevant information is available. Name the file, function, or behavior you mean; you can also ground a question in selected lines, a pull request, or a failed workflow. “Why is this broken?” leaves the assistant to guess. “In script.js, explain what happens when the list is empty” gives it a narrower place to start.
GitHub Copilot Chat can use repository files and symbols as context, according to GitHub’s Copilot Chat documentation. The available context and controls depend on the Copilot surface you are using; if the answer seems to miss project details, name the file or include the relevant code in your prompt.
Use a branch-to-pull-request workflow
- Start with a repository and a small goal. Choose a project you can understand and one change you can describe in a sentence.
- Create a branch before editing. In the repository, use GitHub’s branch control to create a branch from the current branch. Work on that branch so the proposed change stays separate while you develop it.
- Ask for an explanation or a small draft. Specify the file or function, the desired behavior, constraints, and what you want explained. Ask follow-up questions when an answer is unclear instead of expanding the task immediately.
- Inspect the proposed changes. Review the diff—the comparison showing what was added, removed, or changed. Ask the assistant to explain unfamiliar lines, but do not accept a change you cannot explain in your own words.
- Run the project’s checks, if available. Use the build, tests, or validation steps the project provides. Compare the result with the behavior you asked for; a plausible explanation from an LLM is not a test.
- Commit the change and open a pull request. Write a commit message that describes the change. Then open a pull request to propose the branch’s changes for review.
GitHub’s best practices for using Copilot tell users to understand suggested code before implementing it and warn that Copilot can make mistakes. Treat the assistant’s output as a proposal: your review and the project’s checks are what help establish whether it fits.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Save recurring project guidance in the repository
If you repeatedly need to explain the same conventions or validation steps, put that context into repository instructions. GitHub documents repository-wide Copilot instructions in .github/copilot-instructions.md; it also documents path-specific instructions and AGENTS.md for agent instructions. Useful guidance can cover how to understand the project and how to build, test, and validate changes.
Instruction files are not universal switches: support and behavior vary by Copilot surface. Check GitHub’s repository custom instructions documentation and instructions documentation for the relevant feature and interface before relying on a file to apply.
Best Value
Ask it to teach, not just produce
For a learning project, you can ask Copilot to act as a tutor: explain concepts, describe trade-offs, and help you work through a change instead of simply supplying a solution. GitHub describes this as an instruction approach, not a guarantee that the assistant will always follow it. Keep checking whether you understand the result.
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