GH-600 vs GH-300: Which GitHub AI Certification Should You Take?

Take GH-300 if your AI work is Copilot in the IDE: suggestions, chat, prompts, and the governance of a Copilot rollout. Take GH-600 if you assign work to autonomous agents that plan, open branches and create pull requests, because that exam is about operating agents safely: MCP servers, memory, orchestration and guardrails. They are GitHub's two AI certifications, both hosted on Microsoft Learn, and they overlap far less than their names suggest. GH-300 is generally available; GH-600 is still labeled beta on its official certification page as of July 2026, with 120 minutes on the clock versus GH-300's unstated duration, and delayed scoring while the beta runs.

Here is the decision laid out properly, using facts verified from the official study guides rather than course-seller summaries.

What each exam certifies

GH-300: GitHub Copilot leads to the GitHub Copilot certification. Its six domains cover using Copilot's features across the IDE and CLI, prompt engineering, how Copilot handles data (input processing, proxy filtering, post-processing), responsible AI, and the administration side: organization-wide policies, content exclusions, audit logs. Roughly half the exam is governance rather than coding, which is what surprises daily Copilot users.

GH-600: Developing in Agentic AI Systems leads to GitHub Certified: Agentic AI Developer. Its six domains cover agent architecture and SDLC integration, tool use and MCP configuration, memory and state management, evaluation and error analysis, multi-agent orchestration, and guardrails with autonomy levels. It is not a prompt-writing exam; it is an operations exam for a world where the coder is sometimes a fleet of agents.

The word-count test: what the outlines are actually about

We count terms in every official skills-measured outline we cover, because density predicts question territory better than marketing copy does. Put the two AI exams side by side and the difference is stark.

Read that as a map: GH-300 is a product exam about one AI assistant and its enterprise controls. GH-600 barely names any product at all; it examines patterns, which is why its material (context drift, escalation paths, agent isolation, human-in-the-loop) transfers beyond GitHub's own tooling.

The practical differences that decide it

Which one is the better career bet in 2026?

Short version: GH-300 is the safer, more legible line on a resume today; GH-600 is the higher-upside, earlier-adopter play. Copilot has years of enterprise adoption behind it, so the person who can answer a security team's rollout questions has a well-understood role. Agentic development is younger, but it is where engineering workflows are visibly heading: teams now delegate whole tasks to agents, wire them into CI, and browse marketplaces of ready-made AI agents for functions they used to staff. The operational discipline GH-600 examines, who approves what, how state is shared, how conflicts between parallel agents get resolved, is precisely the skill shortage in that shift. Holding the credential while it is still novel is the whole point of sitting a beta.

If your work already includes both, take GH-600 first while the beta pricing and the novelty premium last, then add GH-300 when the Copilot rollout questions land on your desk.

How to prepare for each

For GH-300: the trap is prep freshness. The current outline names Agent Mode, Copilot Edits, MCP, Sub-Agents, Spaces and Spark verbatim; banks written in 2024 predate most of that list. Build questions from the current study guide and your own notes with the GitHub Copilot certification practice test generator, and drill the governance half hardest: policies, exclusions, audit logs, data flow.

For GH-600: the trap is that no calibration exists: no official mock, no vetted banks. The study guide is the only authoritative source, so work it domain by domain with the GitHub agentic AI certification practice test generator, generating a fresh set per domain until the outline's vocabulary is something you can define cold. Then simulate the sit: a long mixed set, 120 minutes, all six domains.

If you are earlier in the track than either exam, start with the order in our GitHub certification path guide; there are no prerequisites, but the Foundations and Actions material reappears inside both AI exams' scenarios.

What is actually on each exam, domain by domain

GH-300's six domains: use GitHub Copilot features (25 to 30 percent, the biggest), use Copilot responsibly (15 to 20), data and architecture (10 to 15), prompt engineering and context crafting (10 to 15), developer productivity (10 to 15), and privacy, content exclusions and safeguards (10 to 15). The named-feature list is what ages fastest: Agent Mode, Copilot Edits, MCP, Sub-Agents, Copilot CLI, Spaces and Spark all appear verbatim on the current outline.

GH-600's six domains: implement tool use and environment interaction (20 to 25 percent, the biggest, and where MCP servers, registries and allow lists live), prepare agent architecture and SDLC processes (15 to 20), perform evaluation, error analysis and tuning (15 to 20), orchestrate multi-agent coordination (15 to 20), manage memory, state and execution (10 to 15), and implement guardrails and accountability (10 to 15). Notice how flat both blueprints are: neither exam lets you pass on one strong domain, which is why domain-by-domain drilling beats cramming your favorite topic on both.

Should anyone take both?

Yes, one profile: the engineer who owns AI tooling for a team. In practice that person fields two different question streams, how do we govern Copilot for two hundred developers (GH-300 material: policies, exclusions, audit logs) and how do we let agents ship code without breaking things (GH-600 material: autonomy levels, approvals, rollback paths). Holding both maps exactly onto that job. For everyone else, one deliberate pick beats two rushed ones; the exams reward depth of real usage, not collection.

Frequently asked questions

Can I take GH-600 without GH-300?

Yes. There are no prerequisites anywhere in GitHub's certification family. The two exams share surprisingly little material, so skipping GH-300 does not leave a gap in GH-600 prep. What GH-600 does assume is real experience running agents: its scenarios reward people who have watched an agent drift off-task or clobber a branch, not people who memorized definitions.

Is GH-600 harder than GH-300?

They are hard in different ways. GH-300 is broad and product-specific; its difficulty is knowing the admin and privacy material that daily use never teaches. GH-600 is newer, has no official mock to calibrate against, and gives you 120 minutes with possible interactive components; its difficulty is that the material is young enough that most candidates have never had to name the patterns they use. Experienced agent users tend to find GH-600's content familiar but its vocabulary exacting.

Do both certifications cost the same?

Microsoft's pricing feed lists GitHub exams under one GH family code at $99 US, with no per-exam entries for either GH-300 or GH-600. Beta exams like GH-600 are often discounted at registration, so check the fee when you book rather than trusting third-party figures.