Become a Production AI Agent Engineer

You already left no-code behind and built a multi-tool Python agent with basic state and one code-enforced guardrail in Become an AI Automation Developer. This is the third and final course in the arc — the one where a system that merely worked in your own testing becomes one you could actually hand to a client to run, unsupervised, against real customer data. You'll give an agent real knowledge it was never trained on through RAG, coordinate more than one agent through a supervisor pattern when that's genuinely the right call, build real observability so you can explain why an agent did what it did, evaluate it against a repeatable test suite instead of trusting a demo, and enforce a genuine human-approval workflow for anything risky.

The promise: Leave with a real production-grade AI agent system as your portfolio piece, a freelance-style resume, and a ready-to-send proposal.

What's inside

1. 1. Why this job existsFree preview
2. 2. Memory, state & the planning pattern Locked
3. 3. Controlling the agent loop Locked
4. 4. Give agents real knowledge — RAG with ChromaDB Locked
5. 5. MCP & the tooling stack Locked
6. 6. Build a real project Locked
7. 7. Get AI feedback Locked
8. 8. Add multi-agent coordination Locked
9. 9. Add real observability Locked
10. 10. Add evaluation Locked
11. 11. Create your portfolio Locked
12. 12. Write your resume Locked
13. 13. Write your proposal Locked
14. 14. Apply for jobs Locked