Getting Started With GitHub Copilot: Your First Project

Getting started with GitHub Copilot works best when you choose one place to use it, ask for one small change, and verify the result before accepting it. You do not need to build a whole application on your first attempt. A tool like fenbs can keep the project brief and unfinished work outside the conversation, ready for your next coding session.

What should you do in your first Copilot session?

1. Choose a project you can run locally, with no live customer data or production access needed for the exercise.
2. Pick one observable improvement, such as rejecting a blank task title or explaining an unfamiliar utility function.
3. Ask Copilot to inspect the relevant code and describe a small plan before making changes.
4. Review the proposed edits, run the project’s existing checks, and try the changed behavior yourself.
5. Save what changed, what passed, and what remains uncertain before ending the session.

Choose work whose answer you can recognize. If you are new to programming, an explanation followed by a tiny edit is a better first task than a login system. Write the expected result in plain language: an empty title should show an error, while a normal title should still save.

Run the project once before asking for edits. Existing failures belong in your starting notes, so you do not confuse an old problem with a new suggestion. You want a clear before and after, even when the change is only a few lines.

Where should you use Copilot for this first project?

Use the environment you already understand. An IDE, meaning your code editor and its development tools, is a practical starting point when you want to inspect files and run local checks. GitHub’s IDE quickstart↗ (opens in a new tab) covers the required account access, extension, and sign-in steps for supported editors.

Copilot is also available on GitHub.com, where GitHub’s browser quickstart↗ (opens in a new tab) demonstrates asking questions about repository files. For this exercise, stay with file questions and a small reviewed change rather than adding several unfamiliar workflows at once.

If you prefer a separate workspace or the terminal, read our GitHub Copilot app guide or Copilot CLI guide afterward. Questions about eligibility and account access belong in the Copilot license guide. Keep your first session focused on doing useful work.

What context should you give Copilot before requesting code?

Provide the goal, relevant files, project conventions, and a definition of success. GitHub’s prompt guidance↗ (opens in a new tab) recommends specific requests, useful examples, and relevant context. In practice, a small request with concrete expected behavior gives you something you can check.

Goal: reject task titles that are blank after trimming.
Inspect the task form and its existing validation tests.
Use the current validation pattern and test framework.
Show a short plan before editing. Change only what this needs.
A normal title must still save. Do not add dependencies.
Report the files changed, checks run, and any unresolved questions.

Replace each detail with something true about your repository. Point Copilot toward a nearby example that already follows your conventions. Ask it to identify any missing requirement before coding, especially where the choice affects people using the app.

Do not paste access tokens, private customer records, or an entire unrelated document just to add background. A short description of the rule is usually more useful. Keep the approved brief and current task together in fenbs AI context, so another connected assistant can begin with the same facts.

How do you review the first result without trusting it blindly?

Read the changed lines and compare them with your original requirement. A diff is the view showing what was added and removed. Look for unexpected files, changed dependencies, weaker validation, or tests that disappeared. Ask Copilot to explain anything you cannot follow, then confirm the explanation against the code.

• Check the ordinary case: a valid task title still saves as before.
• Check the new boundary: an empty title and a spaces-only title are both rejected.
• Run the existing relevant tests and the checks your repository requires.
• Confirm that errors are readable and the form remains usable on a phone.
• Separate checks you actually ran from checks Copilot merely suggested.

GitHub’s review guidance↗ (opens in a new tab) covers testing generated code, checking intent, and watching for invented dependencies or skipped tests. Treat the output as a contribution you are responsible for reviewing. A confident explanation does not replace a working result.

If the change fails, narrow the next request to the observed failure. Include the relevant error and the expected behavior. Avoid asking for a complete rewrite unless the evidence shows the approach itself is wrong. You can explore Copilot models later; changing models is not a substitute for a clear requirement.

What should you save before ending the session?

Save a short handoff that another person could act on without reading the conversation. Include the task goal, changed files, actual test results, remaining question, and next action. If nothing was accepted, say so clearly. An attempted solution and a completed task are different states.

For example: blank-title validation is implemented; the targeted tests pass; the mobile error message still needs checking; next, test the form on a narrow screen. This gives the next session a starting point and prevents a second assistant from repeating work that is already finished.

Use Where we left off in fenbs for this checkpoint. Keep reusable project rules separate from temporary status, so a note about today’s test failure does not accidentally become a permanent instruction.

How to keep your first project moving with fenbs?

1. Create a free account, then add a project for your coding exercise.
2. Add the small improvement as a task, including expected behavior and the files worth inspecting.
3. Record decisions you have made, such as using the existing test framework, in Decisions and rules.
4. Use the integration guides to connect Copilot over MCP, a standard way for an AI app to use an outside tool, and ask it to read the project context first.
5. After reviewing the code, record what passed and save progress with the next action.

fenbs keeps the work record; it does not run your application or decide whether code is correct. If you only want a one-time explanation of a short function, your editor conversation may be enough. Start a shared record when there is a real next session to prepare for, and use the AI at work hub to find other practical workflows.