Overview

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Strong agentic AI engineering starts with judgment: knowing when an agent beats a simple prompt, and how the runtime beneath it works. This course builds that foundation with the GitHub Copilot SDK. You'll evaluate real tasks for agentic automation, stand up an SDK development environment, build a working single-task agent, and trace the SDK's internal runtime to debug with confidence. By the end, you'll be able to: - Evaluate tasks for agentic automation vs. prompt-response approaches - Configure and initialize a Copilot SDK development environment - Build single-task agents using the SDK's agentic loop - Analyze the SDK's JSON-RPC runtime to diagnose issues You'll work hands-on with the GitHub Copilot SDK (Python and Node.js/TypeScript), the GitHub Copilot CLI, VS Code, and Git/GitHub. This course is intended for learners with at least 2 years of programming experience in Python or Node.js/TypeScript, with familiarity with Git workflows, REST APIs, and command-line tools. No prior experience with AI agents or the Copilot SDK is required. This course is designed for: - Software developers and ML engineers who want to build agentic AI applications. - Technical professionals with at least 2 years of programming experience in Python or Node.js/TypeScript. - Developers who are comfortable working with REST APIs, Git workflows, and command-line tools. - Professionals who want to understand when to use agentic AI and begin building agents with the GitHub Copilot SDK. No prior experience with AI agents or the GitHub Copilot SDK is required.

Syllabus

Understanding Agentic AI Systems
- Explore the architectural differences between traditional prompt-response AI systems and agentic AI systems that plan, use tools, and autonomously execute multi-step workflows. You'll learn to evaluate real-world tasks for agentic automation by analyzing the complexity of decisions, external capability requirements, and workflow structure.
Setting Up the Copilot SDK Environment
- Set up a complete GitHub Copilot SDK development environment from scratch. You'll install and configure the Copilot CLI, authenticate with GitHub, and initialize SDK clients, with hands-on practice in Python and Node.js/TypeScript, plus a reference guide covering all six supported languages (.NET, Go, Java, Node.js/TypeScript, Python, Rust).
Building Your First Agent Workflow
- Build your first Copilot SDK (Software Development Kit) workflow around a single analysis task. You will create an SDK session, send a scoped task prompt, ask for a structured response that includes an analysis plan, and parse the result in your application. The emphasis is on designing prompts and application guardrails that make SDK-powered workflows predictable, reviewable, and safe to reuse.
SDK Architecture & Runtime Internals
- Analyze the internal architecture of the Copilot SDK to understand how your application code communicates with the Copilot CLI (Command-Line Interface) server via JSON-RPC. You'll learn to trace messages through the communication stack, diagnose common runtime issues, and interpret error states, skills essential for debugging agent applications in development and production.
GenAI Module: AI-Augmented Agent Design
- Explore how generative AI tools can augment the agent design process itself, from generating evaluation frameworks and architecture diagrams to drafting system prompts and reviewing agent configurations. You'll learn to use AI as a design collaborator while critically evaluating its outputs.
Project Module: Agentic Automation Feasibility Assessment
- Produce a professional feasibility assessment that evaluates multiple enterprise tasks for agentic automation, then validate your top recommendation by building a proof-of-concept agent that demonstrates the agentic loop, meaning iterative planning, tool usage, and execution, in action. This project integrates task evaluation, SDK (Software Development Kit) environment setup, agent-building patterns, and runtime-architecture analysis into one professional project deliverable.