n4nAI

Topic

Multi-Agent Orchestration Patterns

15 posts on multi-agent orchestration patterns — part of ai agents & automation on the n4n AI blog.

AI agents & automationAnalysis

What breaks first when you scale to 10+ agents

Scaling multi-agent systems past ten agents exposes coordination, rate limits, and observability failures first—not model quality.

4 min read
AI agents & automationComparison

Sequential vs parallel multi-agent workflows

A practitioner's comparison of sequential vs parallel multi-agent workflows across cost, latency, ergonomics, and limits, with a verdict by use case.

4 min read
AI agents & automationComparison

Multi-agent orchestration vs single-agent with more tools

Head-to-head engineering comparison of multi-agent vs single-agent with tools across capabilities, cost, latency, ergonomics, ecosystem, and limits, with verdict.

4 min read
AI agents & automationAnalysis

Multi-agent orchestration costs: more agents, more tokens

Practical analysis of multi-agent orchestration cost: why token usage grows nonlinearly with agents, and patterns to keep spend under control.

5 min read
AI agents & automationHow-to

How to route tasks between specialized agents

Learn how to implement task routing between agents in a multi-agent system with a practical LLM-based router, runnable Python code, and verification steps.

3 min read
AI agents & automationHow-to

How to prevent multi-agent systems from looping forever

Practical steps to detect and stop a multi-agent infinite loop in production orchestration, with code for timeouts, counters, and cycle detection.

3 min read
AI agents & automationHow-to

How to monitor multi-agent systems in production

Practical steps to monitor multi-agent systems in production: distributed tracing, structured events, LLM metrics, and loop detection for reliable agent fleets.

3 min read
AI agents & automationHow-to

How to handle shared state across multiple agents

Practical patterns for managing shared state multi-agent systems: define a contract, use Redis for atomic updates, and verify with integration tests.

4 min read
AI agents & automationAnalysis

How multi-agent systems handle disagreement between agents

Analyzes practical patterns for multi-agent disagreement resolution, from voting to debate protocols, with code and tradeoffs for production systems.

3 min read
AI agents & automationGuide

Debate and voting patterns in multi-agent orchestration

A practical guide to implementing the multi-agent debate pattern: orchestration flows, voting mechanics, code samples, and tradeoffs for production systems.

3 min read
AI agents & automationDefinition

Blackboard architecture for multi-agent orchestration

Blackboard architecture multi-agent defined: a shared-memory coordination pattern for LLM agents, with components, example code, and common misconceptions.

5 min read
AI agents & automationGuide

Orchestrator-worker pattern for multi-agent systems

A practical guide to the orchestrator-worker multi-agent pattern: design steps, code sketches, failure modes, and tradeoffs for production LLM systems.

4 min read
AI agents & automationHow-to

How to design a supervisor agent for multi-agent systems

Practical steps for supervisor agent design in multi-agent systems: define contracts, manage state, delegate with schemas, add fallback, verify.

4 min read
AI agents & automationListicle

Five multi-agent orchestration patterns explained

Engineer-focused explainer of five multi-agent orchestration patterns with runnable code: supervisor, hierarchical, blackboard, pipeline, and debate.

4 min read
AI agents & automationComparison

Centralized vs decentralized multi-agent orchestration

A practitioner's comparison of centralized vs decentralized orchestration for multi-agent systems, covering cost, latency, ergonomics, and failure modes.

4 min read