Training: Developing in Agentic AI Systems (GH-600)

Why take the Developing in Agentic AI Systems (GH-600) training

Coding agents moved from prototype to production pipeline in a matter of months. On GitHub, an agent opens a pull request, runs a test suite, fixes a defect, bumps a dependency. The question is no longer whether these agents write code, but how to frame their work so it stays traceable, reviewable and safe. Released by GitHub on 7 August 2026, GH-600 answers that need directly: designing agentic systems that rely on the platform native mechanisms rather than on improvised scripts.

GitHub as the control plane for agents

One idea runs through the official plan: GitHub is both the system of record for code and the control plane for agents. Repositories, branches, pull requests, status checks, CODEOWNERS and protected environments already form a proven framework for human work. The training shows how to apply that same framework to agent-generated work through the contributor model: an agent is a contributor like any other, whose contributions go through review, tests and merge rules. This approach avoids the most common trap, an agent writing to the repository through a parallel path outside any control.

Tooling, MCP and execution environments

An agent is only as useful as the tools it can reach. The Model Context Protocol module details MCP servers, registries and allow lists that decide what an agent may call. You work on execution context, its boundaries and the associated protections, in particular secret handling and token scoping. This is where many teams get it wrong: granting an agent too much reach is the same as granting an API token too much reach, with the same consequences.

Multi-agent orchestration with GitHub Actions

The day then moves to systems built from several agents: splitting responsibilities, orchestrating sequences with GitHub Actions workflows, isolating execution by branch and permission, handling concurrency, detecting conflicts and arbitrating them with GitHub-native mechanisms. The memory and state section completes the picture: memory strategies, context drift, continuity across tools and environments, evaluation signals and quality gates that show whether an agent improves or degrades across iterations.

Governance, guardrails and least privilege

The final module addresses governance: risk-based autonomy boundaries, human-in-the-loop workflows at sensitive steps, agent capabilities restricted by least privilege, actions that are observable, traceable and auditable. For a Swiss company subject to the revised Data Protection Act or to strong sector requirements, such as Geneva finance or healthcare, that traceability is not a nicety: it is the condition for allowing agents anywhere near production code. Knowing who decided what, on which basis and with which human validation becomes part of the compliance file.

The GitHub Certified: Agentic AI Developer certification

GH-600 prepares you for the GH-600 exam, which leads to the GitHub Certified: Agentic AI Developer certification. The official plan holds six modules delivered in a single day, which implies a fast pace and real prior comfort with Git, pull requests and GitHub Copilot. The day covers the exam scope; preparation then continues with practice on your own repositories, the surest way to anchor orchestration and guardrail concepts.

Where GH-600 sits among the ITTA GitHub trainings

The ITTA catalogue holds two neighbouring courses. The GitHub Copilot training (GH-300) covers a developer daily use of the assistant: suggestions, chat, test generation, refactoring. The GitHub Advanced Security training (GH-500) covers code scanning, secret detection and software supply chain security. GH-600 sits above both: it is not about using an assistant, but about designing a system where several agents work within a governed framework. GH-300 is a sound entry point, while GH-500 provides the security reflex that makes the final module guardrails far more concrete.

What the training adds over self-study

GitHub documentation on agents evolves quickly and reads easily. What it does not give you is the judgement call: which responsibility to hand to an agent, where to place human validation, how to isolate two agents touching the same repository, when to stop an agent stuck in a loop. A day with a certified instructor in Geneva or Lausanne lets you test those choices against real cases and avoid the anti-patterns the official plan flags from the very first module. Questions raised by other participants, often from teams of comparable size, are worth as much as the syllabus itself.

After the training

The natural next step is to pick a low-risk repository and deploy a first agent with a deliberately narrow scope: dependency updates, flaky test fixes, documentation generation. You then measure the evaluation signals seen in class before widening the scope. Documenting autonomy boundaries inside the repository itself, as rules and configuration files, keeps the framework alive after the person who built it moves on.

FAQ Developing in Agentic AI Systems (GH-600)

Do I need programming experience for GH-600?

Yes. The course targets developers and DevOps engineers who already practise Git, pull requests and GitHub Actions. It does not revisit platform fundamentals.

How does it differ from the GitHub Copilot training (GH-300)?

GH-300 covers a developer daily use of the assistant. GH-600 covers the design, orchestration and governance of agent systems acting directly on the repository.

Is one day enough for six modules?

That is the official GitHub format. The pace is dense and assumes the stated prerequisites: without hands-on GitHub Actions experience, the orchestration part becomes hard to follow.

Does the course cover the Model Context Protocol?

Yes, the third module is dedicated to it: MCP servers, registries, allow lists, execution context and related protections.

How does the GH-600 exam work?

The exam is taken separately, with GitHub. The training covers the official plan and you remain free to schedule the exam whenever it suits you.

Should I take GH-500 before GH-600?

Not necessarily. GitHub Advanced Security (GH-500) remains a useful complement for teams that will have to justify the guardrails placed around their agents.