Agent Frameworks
Orchestrate teams of specialized AI agents working together.
Single agents have limits. Complex tasks — research, analysis, content production, customer support — benefit from multiple specialized agents collaborating: one that searches the web, one that writes, one that fact-checks, one that formats. Agent frameworks like AutoGen, CrewAI, and the Vercel AI SDK provide the infrastructure for building these multi-agent systems.
Microsoft AutoGen enables conversational multi-agent systems where agents talk to each other to solve problems. CrewAI takes a role-playing approach — you define agents with specific roles, goals, and tools, then assemble them into a crew. The Vercel AI SDK bridges the gap between agent backends and streaming frontend interfaces. Each has its strengths.
In this track, I compare frameworks honestly (not just show you the happy path), build a multi-agent stock analysis system with CrewAI, build a hierarchical AutoGen marketing team, and explain when to use each framework. By the end, you'll be able to design multi-agent architectures that actually work.
📚 Learning Path
- AutoGen conversational swarms
- CrewAI role-based agent teams
- Hierarchical vs peer-to-peer coordination
- Build: Stock Analysis Crew
- Build: Marketing Swarm with AutoGen