Orchestrating multiple AI agents with n8n: a practical guide

Published on September 15, 2026

More teams are choosing n8n to orchestrate AI agent workflows instead of writing all the logic in code.

The essential building blocks

A scheduler to trigger planned tasks.
HTTP/webhook nodes to connect your LLMs (Anthropic, OpenAI, self-hosted models via Ollama).
Persistent memory (Postgres, mem0) so agents keep context between runs.

Clearly separate collection workflows (scraping, RSS, APIs) from decision workflows (LLM calls, arbitration).
Log every tool call so you can debug an agent stuck in a loop.
Plan a kill switch on critical workflows.

This kind of architecture is what powers the automated watch we publish on NextOptimus.