Udemy – Production AI Agents: Reliable Business Workflows

The market is full of courses that stack up 100 labs, 100 agents in 100 days, or five frameworks in a weekend. They are fun, and the reviews say the same thing over and over: not production depth. They show you how to make an agent do something clever once, but never how to make it reliable enough to put in front of a real business, with real money and real customers on the line.

This course lives in that gap. Using one running case study, Cascade Commerce, a mid-market retailer whose splashy multi-agent demo collapsed in production, you will learn the production judgment that decides whether an agent workflow ships or embarrasses you.

• Architecture decisions: single agent versus sequential workflow versus router versus multi-agent versus human oversight, and when not to use an agent at all.
• Business-process modeling: start from the job-to-be-done, and map inputs, outputs, decisions, and the exceptions where demos die.
• Context and handoffs: typed schemas and shared state that stop context leaking between agents.
• Evaluation: golden datasets, rubrics, failure taxonomies, and regression tests for the day you swap the model.
• Observability: traces, tool calls, and cost, built on OpenTelemetry ideas, to catch loops and drift before your users do.
• Governance: tool permissions, approval gates, and audit logs mapped to NIST AI RMF and the OWASP agentic risks.
• Pilot launch: scope, success metrics, rollback, and change management.