Study guide
GitHub Certified: Agentic AI Developer study guide
Read a lesson, then practice the ideas you want to remember.
Lessons
- Agent Observability & Human Intervention Con
- Planning vs. Execution Separation & Plan Out
- Agent SDLC Integration & Task Boundaries
- Instruction, Memory & Tool Access Tuning
- Evaluation Signals & Automated Scanning
- Root-Cause Failure Classification — Free Study Guide 2026
- Authorization Checkpoints & Responsible AI C
- Least-Privilege Permissions & Policy Enforce
- Action Risk Classification & Autonomy Levels
- Core Concepts of Agentic AI in GitHub — Free Study Guide 2026
- GH-600 Exam Facts and Strategy — Free Study Guide 2026
- Durable Artifacts & Context Pruning — Free Study Guide 2026
- Context Drift & State Continuity — Free Study Guide 2026
- Short-Term, Long-Term & External Memory
- Conflict Detection, Handoffs & Lifecycle Man
- Multi-Agent Orchestration Patterns — Free Study Guide 2026
- Parallel Execution & Workspace Isolation
- Tool Scoping in CI/CD & Branch Workflows
- Error Handling, Retries & Escalation Paths
- Function Calling & Tool Selection — Free Study Guide 2026
- MCP Architecture, Transports & Registries