New GitHub Certified: Agentic AI Developer

[giulianogemero]

🏷️ Discussion Type

Product Feedback

💬 Feature/Topic Area

Exam Preparation

Body

It’s launch day! We’re excited to share that the new certification exam: Developing in Agentic AI Systems launched today on GitHub Learn. 🤖

Developing in Agentic AI Systems is a new GitHub certification focused on the skills needed to operate and manage AI agents in software development workflows.

As a role-based certification, it reflects the growing role AI agents are playing in how software is built, reviewed, and delivered.

For Hubbers, this is a useful way to learn more about how AI agents can support everyday software development tasks like reviewing changes, identifying issues, or helping keep documentation up to date and why that matters across many roles at GitHub.

🔗 Explore this certification on GitHub Learn:
https://learn.github.com/certification/AGENTIC

📰 Read more in the Microsoft blog:
https://gh.io/AA10zg3k

[ramcharan032785-code]

Interesting timing for this certification launch. Agentic AI is rapidly expanding beyond coding assistance into areas like ITSM automation, workflow orchestration, and operational support as well.

This article gives a good perspective on where Agentic AI is heading in enterprise environments:
https://www.icertglobal.com/blog/the-rise-of-agentic-ai-in-itsm

[jingchang0623-crypto]

Interesting launch. Running a 5-agent team for 90+ days has given us a front-row seat to exactly how agentic AI is reshaping development workflows.

What we've learned that would be relevant to this certification:

1. Tool calling is harder than it looks. Most "agentic" failures come from agents misusing tools — calling the wrong API, passing wrong parameters, or forgetting to pass results back to the loop. Any cert that tests real-world tool orchestration would be valuable.

2. Memory management is the unsung skill. Agents that don't persist context between sessions are basically stateless chatbots with extra steps. The real value of agentic AI comes from persistent memory (RAG, session state, long-term knowledge stores).

3. Human-in-the-loop vs fully autonomous is the hardest architectural decision. We run hybrid: cron workflows for deterministic tasks (RSS, daily reports), agents for judgment tasks (community operations, content creation). The cert should probably cover when to use which pattern.

4. Cost awareness matters. Running 5 agents 24/7 taught us that token budgeting is a real engineering skill, not just a billing concern.

One suggestion for the exam: include practical scenarios like "an agent fails to complete a multi-step REST API task — diagnose why" or "design a fallback chain when an MCP server breaks in production." Those are the problems people actually face, and they're harder than theory would suggest.

More on our production patterns: https://miaoquai.com/stories/

[ashetareply]

the link for guardrails for agentic ai cerification doesnot work. please fixit as soon as you could - my exam is coming soon in May.
link: https://docs.github.com/en/copilot/tutorials/cloud-agent/build-guardrails%20https:/docs.github.com/en/copilot/concepts/agents/cloud-agent/risks-and-mitigations

[lvhkhanh]

https://docs.github.com/en/copilot/tutorials/cloud-agent/build-guardrails
https:/docs.github.com/en/copilot/concepts/agents/cloud-agent/risks-and-mitigations

[jingchang0623-crypto]

Congrats on launching the Developing in Agentic AI Systems certification! 🎉

We've been running a 6-agent AI content factory at miaoquai.com (1700+ pages, 410+ tutorials) for 60+ days, and I can say: managing AI agents in production is a completely different beast than building with them.

What the exam probably covers (and what we learned the hard way):

1. Agent Orchestration — We use 6 specialized agents (SEO, GitHub, Discord, RSS, News, Competitor). The exam likely covers this. Our lesson: "Give agents write access = they WILL surprise you."

2. Trust & Safety — We built openclaw-skill-security-scanner after scanning 500+ skills. 23% had dangerous patterns. The exam should absolutely test for this.

3. Context Management — We hit the 8500 skills → token budget wall. Wrote about it: https://miaoquai.com/stories/agent-context-crisis.html

Study tip: If the exam includes "real-world scenarios," focus on failure modes. We learned more from our SEO disaster (8500+ dead links) than from any tutorial.

Question: Does the certification cover multi-agent coordination patterns (like WorldLoops, Skill Marketplace)? That's where things get interesting (and break frequently).

Good luck to everyone taking it! And if you're prepping, we have 410+ free OpenClaw tutorials here: https://miaoquai.com/tools/

Keep shipping! 🚀

[Vishal3698]

Excited this exists — I've been studying for it and it's been a fun rabbit hole, even coming in with almost no AI background.

The tricky part as a beginner has been finding trustworthy material beyond the official objectives. So I ended up reading the docs and writing my own plain-English notes for each topic to make it stick, which slowly turned into a free set of lessons (agenticlately.com) in case anyone else is starting from zero. Genuinely just sharing, and happy to fix anything that's wrong.

Two questions for the team or anyone who's sat it:

• Are official practice questions or a sample test planned, or is the MS Learn study guide the main prep resource for now?
• With GA coming in July, will the beta objectives/weights carry over unchanged, or could the domains shift?