Multi-Agent Systems in Production

Multi-agent systems promise autonomous problem-solving, but production deployments require careful orchestration, guardrails, and observability.

Table of Contents

• Agent Architecture Patterns
• Tool Use and Memory
• Human-in-the-Loop
• Failure Modes
• Summary

Agent Architecture Patterns

• Supervisor: one agent delegates to specialists
• Debate: agents argue opposing views, judge selects
• Pipeline: sequential handoffs with validation gates

Tool Use and Memory

agent = Agent(
    tools=[search, calculator, code_executor],
    memory=ConversationBuffer(window=10),
    max_iterations=5,
)

Limit tool calls and iterations to prevent runaway loops.

Human-in-the-Loop

Require approval for destructive actions: database writes, external API calls, financial transactions.

Failure Modes

• Infinite loops between agents
• Hallucinated tool outputs propagated unchecked
• Cost explosions from unbounded agent chains

Summary

Start with single-agent + tools. Add multi-agent complexity only when a clear orchestration benefit exists.