01Module 07: Multi-Agent SystemsOrchestration, communication, parallelism, and real frameworks - from first principles to production multi-agent systems.02Why Multi-Agent Systems?The fundamental case for multi-agent: parallelization, specialization, and verification - and the honest cost of coordination overhead.03Orchestrator-Subagent PatternThe most reliable multi-agent pattern: one orchestrator plans, subagents execute. Deep dive into task decomposition, assignment strategies, and production-grade implementation.04Agent Communication ProtocolsHow agents pass information: message formats, schemas, synchronous vs async, routing, error propagation, and tracing through multi-agent systems.05Parallel Agent ExecutionRunning agents concurrently with asyncio, worker pools, DAG-based scheduling, rate limiting, and cost/speed tradeoffs in parallel multi-agent systems.06Debate and Critique PatternsHow LLMs critiquing each other improves quality: verifier/critic patterns, multi-agent debate, ensemble approaches, and convergence detection.07OpenAI SwarmOpenAI's experimental multi-agent framework: agents, handoffs, context variables, and the triage pattern. What it gets right and wrong.08AutoGen Deep DiveMicrosoft AutoGen v0.4: async conversational multi-agent systems, actor model architecture, group chat patterns, and MagenticOne.09CrewAICrewAI v0.80+: role-based multi-agent systems with Crew, Agent, Task, Process, and Flow - the most production-friendly multi-agent framework.10LangGraphLangGraph: stateful graph-based multi-agent systems with checkpointing, human-in-the-loop, streaming, and the supervisor pattern - the most powerful and flexible agent framework.
