Why Multi-Agent?

Single-chain LLM architectures hit a ceiling fast. When your application needs to query structured databases, search unstructured documents, and synthesize answers — a single prompt chain becomes brittle and unpredictable.

Multi-agent systems solve this by decomposing complex tasks into specialized agents, each optimized for a specific capability.

The Architecture

The system I built uses four specialized agents orchestrated by a router:

  • Router Agent — Classifies incoming queries and delegates to the appropriate specialist
  • SQL Agent — Translates natural language to SQL and queries structured supply chain data
  • RAG Agent — Performs hybrid retrieval over unstructured documents using vector + keyword search
  • Summarizer Agent — Aggregates outputs from multiple agents into coherent responses
from langgraph.graph import StateGraph

graph = StateGraph(AgentState)
graph.add_node("router", router_agent)
graph.add_node("sql_agent", sql_agent)
graph.add_node("rag_agent", rag_agent)
graph.add_node("summarizer", summarizer_agent)

Key Lessons

1. State management is everything. LangGraph’s state graph pattern forces you to think about what information flows between agents. This is a feature, not a constraint.

2. Router accuracy determines system quality. If the router misclassifies a query, the downstream agent produces garbage. I spent more time tuning the router prompt than any other component.

3. Fallback chains are essential. When the SQL agent fails (malformed query, empty results), the system needs a graceful degradation path — usually falling back to the RAG agent.

4. Evaluation is hard. Unlike single-model benchmarks, multi-agent systems need end-to-end evaluation that accounts for routing decisions, intermediate outputs, and final synthesis.

What I’d Do Differently

If I were starting over, I’d invest more in structured logging from day one. Debugging a multi-agent system without detailed traces of each agent’s inputs, outputs, and decision points is painful.

I’d also consider using a more explicit orchestration pattern rather than letting the router make all delegation decisions autonomously.