Learning Path
GitHub Agentic AI Developer (GH-600) Exam Prep
A first-attempt prep path for the GitHub Certified: Agentic AI Developer exam (GH-600). Every module maps to the official skills measured: SDLC integration, tool use and MCP, memory and state, evaluation, multi-agent coordination, and guardrails.
GH-600 Course Overview & Exam Map
What the GitHub Certified: Agentic AI Developer (GH-600) exam actually tests, how it is scored, and how this 10-module path gets you to a first-attempt pass.
Agentic AI in the SDLC
What separates an agent from an assistant, the plan-reason-act loop, and where autonomous agents fit into a real software development lifecycle — the mental model GH-600 tests in every domain.
GitHub as the Control Plane: Copilot Agents & MCP
The concrete GitHub machinery GH-600 assumes you know: the Copilot coding agent, custom instructions and custom agents, MCP servers, and how branch protections keep autonomous work safe.
Domain 1: Agent Architecture & SDLC Processes
Integrating agents into the SDLC, separating planning from execution, and configuring observability and control for autonomous agents — Domain 1 (15–20%) of GH-600, with worked scenarios and practice questions.
Domain 2: Tool Use & Environment Interaction
Selecting and configuring agent tools, MCP servers and allow lists, integrating agents into dev environments and CI, and safe execution with error handling, retries, rollbacks, and escalation — the heaviest GH-600 domain (20–25%).
Domain 3: Memory, State & Execution
Short-term vs. long-term vs. external memory, persisting agent state as durable artifacts, detecting and correcting context drift, and keeping state consistent across tools — Domain 3 (10–15%) of GH-600.
Domain 4: Evaluation, Error Analysis & Tuning
Defining success criteria and evaluation signals, root-causing agent failures from logs and traces, and tuning instructions, memory, and tool access based on results — Domain 4 (15–20%) of GH-600.
Domain 5: Multi-Agent Coordination
Orchestration patterns, agent isolation and conflict resolution, observability across agents, detecting degraded multi-agent behavior, and managing the agent lifecycle — Domain 5 (15–20%) of GH-600.
Domain 6: Guardrails & Accountability
Classifying actions by risk to assign autonomy levels, human-in-the-loop for high-judgment actions, blocking policy-violating actions, least-privilege scoping, and authorization for irreversible changes — Domain 6 (10–15%) of GH-600.
Exam-Day First-Attempt Playbook
A two-week study plan, a question-reading strategy, the decision heuristics that resolve most GH-600 questions, a full mixed practice set with explanations, and exam-day logistics — everything to pass GH-600 on the first attempt.