Orchestrating multiple AI agents: coordination, state, failures, and applications
Choosing between sequential vs parallel agents sounds like a performance question, but it's really a dependency question. Get it wrong and you'll either slow down tasks that could parallelize, or corrupt state between agents running simultaneously.
Picture this: you're a developer who just got a LangGraph multi-agent system working in a notebook, then watched it behave completely differently when you added a state reducer. State management in LangGraph is the hard part — here's how to get it right.
CrewAI promises to make multi-agent coordination feel like assembling a team. This crewai tutorial shows you what that means in practice — the parts that work cleanly, the parts that fight you, and when to reach for a different tool.
