Test / Eksamen: Developing in Agentic AI Systems (GH-600)

Demonstrate deep expertise in deploying, operating, integrating, and governing AI agents in production SDLC workflows, ensuring reliability, safety, and speed with GitHub as the control plane.

You work closely with architects, platform engineers, DevOps engineers, application developers, product managers, and security engineers to develop, deploy, operate, and manage agents that operate within the GitHub platform.

Updated August 2026

You will have 120 minutes to complete this assessment.

Assessed on this exam:

• Domain 1: Prepare agent architecture and SDLC processes (15–20%)
• Domain 2: Implement Tool Use and Environment Interaction (20–25%)
• Domain 3: Manage Memory, State, and Execution (10–15%)
• Domain 4: Perform Evaluation, Error Analysis, and Tuning (15–20%)
• Domain 5: Orchestrate Multi-Agent Coordination (15–20%)
• Domain 6: Implement Guardrails and Accountability (10–15%)

Module 1: Developing in Agentic AI Systems Part 1 of 2

• Foundations of Agentic AI in GitHub
• Designing Agent Architecture and SDLC Integration
• Tooling, MCP, and Agent Execution Environments

Module 2: Developing in agentic AI systems part 2 of 2

• Multi-Agent Systems and Orchestration
• Memory, State, and Evaluation
• Governance, guardrails, and operations

• You should have subject matter expertise in operating, integrating, supervising, and governing AI agents inside production-grade SDLC workflows and development environments, ensuring reliability, safety, and velocity using GitHub as the system of record and control plane.
• You should have experience with the software development lifecycle (SDLC), workflows in GitHub and controls, and code quality, security, and review practices. You should also have experience with coding agents including GitHub Copilot, MCP servers and agent customization such as custom instructions, custom agents, tools, and Copilot setup steps.