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.
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