How to Build Your First Production AI Agent with n8n

Short summary

A practical guide to building production AI agents in n8n using a five-piece architecture: trigger, retrieval, reasoning, tool calls, and a human-in-the-loop checkpoint. The author argues that skipping the checkpoint turns an agent into an unsupervised script, and that collapsing everything into one giant prompt makes debugging impossible. A lead-qualification example illustrates how each piece maps to real workflow nodes.

• •Production agents need five pieces: trigger, retrieval, reasoning, tool calls, human-in-the-loop checkpoint
• •Skipping the checkpoint or using one giant prompt makes agents fragile and hard to debug
• •Same architecture applies in code-first frameworks like LangGraph or CrewAI

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