What Is Multi-Agent Design
A design where, instead of making one big LLM do everything, multiple agents with divided roles cooperate. Each agent has a different system prompt, tools, memory.
Why Split
- Specialization: one body can't double as code reviewer and sales handler
- Cost: cheap model for simple tasks, frontier for complex judgment
- Parallelism: run multiple investigations concurrently
- Privilege separation: separate the agent reading confidential data from the writing one
- Testability: small roles can be unit-tested
Main Frameworks
LangGraph (LangChain)
Describe agent flows with a state-transition graph (StateGraph). Strong at complex branching/loops/conditional handoff.
- Pro: explicit state management, easy to debug
- Con: somewhat steep learning curve
OpenAI Swarm (Lightweight)
OpenAI's lightweight framework. Designed to "hand off" directly between agents.
- Pro: simple, little code
- Con: hard to write complex flows
