AI / GitHub Copilot CLI Fundamentals Interview Questions
What is the overall workflow for using Copilot CLI on a real development task from start to finish?
Combining all Copilot CLI features into an end-to-end workflow demonstrates how the tool fits into professional development practice.
# ── End-to-end Copilot CLI workflow ────────────────────────────── # 1. Set up the project for Copilot CLI cd my-project copilot # → Trust prompt: "Yes, and remember this folder" /init # → Copilot generates copilot-instructions.md with build/test commands # 2. Discuss the task in Chat mode # [Chat mode is active by default] "I need to add pagination to the GET /api/products endpoint. We use Express + Prisma. How should I approach this?" # → Copilot gives advice; refine as needed # 3. Switch to Plan mode to review steps # Press Shift+Tab once "Implement pagination with limit and offset query params, add Swagger docs, and write Jest unit tests" # → Copilot outlines steps for review - inspect and confirm # 4. Execute with Autopilot mode # Press Shift+Tab again "Go ahead and implement the plan" # → Copilot implements autonomously # 5. Review the changes git diff # If happy: git add -A git commit -m "feat: add pagination to GET /api/products" # 6. Open a pull request /pr "Create a PR for this branch with a summary of what was added" # → Copilot opens PR with AI-generated description # 7. Review session history /chronicle "What did I implement today?"
This workflow demonstrates the full spectrum: Chat (discuss) → Plan (review) → Autopilot (execute) → git review → /pr (publish). Copilot CLI compresses what would previously require multiple context switches (editor, terminal, browser) into a single terminal workflow.
In the recommended Copilot CLI workflow, which mode should you use to review Copilot's proposed steps BEFORE execution?
After Copilot CLI implements changes on your behalf, what should you do before committing?
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