---
title: "Multi-Agent Orchestration Patterns That Work in Production"
description: "Choose among manager-worker, parallel fan-out, handoff, and evaluator loops without building an uncontrolled agent swarm."
language: en
canonical: https://navinresearch.com/blog/agents/multi-agent-orchestration-patterns.md
topics: ["multi-agent orchestration", "manager worker agents", "agent handoffs"]
---

# Multi-Agent Orchestration Patterns That Work in Production

Choose among manager-worker, parallel fan-out, handoff, and evaluator loops without building an uncontrolled agent swarm.

**Short answer:** Prefer explicit orchestration. A manager-worker pattern suits decomposable tasks, parallel fan-out suits independent research, handoffs suit distinct permissions, and evaluator loops suit outputs that can be checked. Each pattern needs bounded turns and a typed result.

## Implementation steps

1. Classify the task as sequential, parallel, specialist-routed, or iteratively verifiable.
2. Define the state passed between agents; pass artifacts and decisions, not entire transcripts by default.
3. Set per-agent time, tool, and token budgets.
4. Merge results with deterministic code before asking a model to resolve only genuine conflicts.

## Validation checklist

- Replay the same task and inspect variance in routing and final quality.
- Inject a failed worker and confirm graceful degradation.
- Trace who produced each claim and which tool evidence supports it.

## Common mistakes

- All-to-all chat topologies.
- A reviewer that merely restates the draft.
- No global cancellation or deadline propagation.

## Practical decision

Ship the smallest design that passes the checks above. Record the model, prompt, tool, dataset, and runtime versions used in testing so later changes can be compared rather than guessed. Recheck the linked documentation before relying on provider-specific limits, model names, prices, or preview features; those details change more quickly than the engineering principles in this note.

## Official sources

- [Anthropic, How we built our multi-agent research system](https://www.anthropic.com/engineering/multi-agent-research-system)
- [OpenAI, New tools for building agents](https://openai.com/index/new-tools-for-building-agents/)

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Reviewed: 2026-08-24. This concise engineering note is educational, not a claim that Navin Research created or independently verified the cited provider technology.