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Part 1: Setup & Context Engineering

← Overview


In this section, you'll set up your development environment and teach GitHub Copilot about your codebase.

🎮 Play the Bingo Mixer game — See what you'll be building!


🔧 Initial Setup

Step 1: Create Your Repository (Required)

  1. Open github.com/microsoft/vscode-agent-lab-soc-ops
  2. Click Use this templateCreate a new repository
    • Name: my-bingo-mixer
    • Visibility: Public
  3. ✅ Your own Bingo Mixer repo is ready!

Step 2: Enable GitHub Pages

  1. Go to your repo's SettingsPages
  2. Under "Build and deployment", change Deploy from a branch to GitHub Actions
  3. ✅ Any commit will now publish to: https://{username}.github.io/{repo-name}

Step 3: Choose How You'll Develop

Option A: Clone locally in VS Code

  1. Open VS Code
  2. Run command: Git: CloneClone from GitHub
  3. Select your new repository
  4. Install recommended extensions (notification or Extensions: Show Recommended Extensions)

Option B: Create a Codespace for your repo

  1. Open your repository on GitHub
  2. Click CodeCodespacesCreate codespace on main
  3. ✅ Codespace starts with your repo and devcontainer.

Step 4: Run the Setup Agent

In the Chat panel:

/setup

On the first terminal tool, enable Auto-Approve.

Let the agent figure out any required installation steps.

Success: App is running and open in browser!

Keep this workshop/ guide open (📌 Pin).


📚 Understanding Context Engineering

Context engineering is how you teach AI about your specific codebase. This makes Copilot's suggestions more accurate and relevant.

Task 1: Auto-generated Instructions

Instructions guide all agentic codebase interactions, making them more efficient and reliable. Add them early, but make sure to keep them maintained and succinct.

Steps:

  1. Run prompt: /init with Autopilot enabled
    • While agent analyzes the codebase, optionally start next task
  2. Open a new chat for the next task, as init can take a while and we can review later.
  3. Review results — is it not too long and overly detailed
    1. Optional follow-up: "Compress down and add a mandatory development [ ] checklist (lint, build, test) to the top"
  4. Apply and commit

Result: All future requests will have a basic map of the workspace.


Task 2: Dogfooding & Custom Skills

Steps:

  1. Prompt: "Test the app like a critical dogfooder, giving critical feedback on how fun it is"
  2. Watch how the agent launches the built-in browser, interacts with the app, and writes a report
  3. /create-skill for dogfooding — or: "Save this as a dogfooding skill"

Result: The agent used the browser to actually play the app and produced a critical report. You then saved that testing approach as a reusable dogfooding skill.

💡 Context engineering insight: The agent needs hands-on context — running the app, seeing the UI, clicking through flows — to truly understand how it works and validate functionality. Code alone isn't enough; interacting with the running product closes the gap between reading code and understanding the user experience.


Task 3: Customization Modal

Tour the repo customizations to understand how context engineering works in practice.

Steps:

  1. Open the Customization panel, Command: Chat: Open Customizations (Preview)
  2. Browse the repo customizations — instructions, skills, and agents
  3. Look at the frontend design skill and Tailwind 4 instructions

💡 Think about: What conventions or patterns from your own projects could become instructions or skills?


✅ Part 1 Complete!

You've learned how to:

  • Set up your development environment
  • Generate and refine workspace instructions
  • Dogfood your app with the agent's built-in browser
  • Create and save custom skills
  • Tour repo customizations (instructions, skills, agents)