Learning AI Agents in Practice, Part 4

Covers the practical aspects of multi-agent systems, from designing single and multi-agent systems to building collaborative architectures and enabling asynchronous communication. Learn how to use LangGraph workflows and message-broker-based parallel communication to divide complex business domains and coordinate tasks. You’ll also develop the skills to objectively evaluate and manage agent performance by building LLM-based automated scoring systems using evaluation metrics such as precision and recall, along with TDD-based quality gates.