Part VI: Agents & Applications
While a single agent equipped with the right tools can accomplish many tasks, the most complex real-world problems benefit from multiple specialized agents working together. Multi-agent systems decompose difficult challenges into subtasks handled by agents with distinct roles, expertise, and capabilities. This mirrors how effective human teams operate: a project manager coordinates, researchers gather information, writers produce content, and reviewers ensure quality.
This module covers the full stack of multi-agent development. It begins with a practical survey of agent frameworks, comparing how LangGraph, CrewAI, AutoGen, and native provider SDKs approach the problem of building agents. It then explores multi-agent architecture patterns including supervisor hierarchies, debate protocols, and pipeline topologies. The module concludes with agentic workflows and pipelines, where you will build production-grade systems with conditional branching, error recovery, checkpointing, and human-in-the-loop oversight.
By the end of this module, you will be able to select the right framework for your use case, design multi-agent architectures that balance autonomy with coordination, and build robust agentic workflows that handle the messy realities of production environments.