AI Automation

AI Automation with n8n

Connect AI models to real workflows using n8n — the open-source automation tool. Learn the HTTP Request and AI Agent nodes, and build automations that run on a schedule or trigger.

n8n and AI: Build Your First Real Automation

A practical walkthrough of wiring an AI model into an n8n workflow — the node structure, the prompt that makes it reliable, and three automations worth building first.

Human in the loop

Human in the loop means inserting a person at decision points in an automated workflow — typically to approve consequential actions or review low-confidence outputs before they take effect.

Weekly Automation Digest

Automated weekly team update via n8n + Slack

RSS-to-Social Repurposer

Auto-posting new articles to social channels

Critique-and-Revise Loops — ChatGPT

A loop is simply feeding a model's own output back to it (or to a second prompt) for review and improvement, repeated until a quality bar is met.

Critique-and-Revise Loops — Claude

A loop is simply feeding a model's own output back to it (or to a second prompt) for review and improvement, repeated until a quality bar is met.

The ReAct Pattern (Reason + Act)

ReAct loops interleave reasoning ("what should I do next?") with actions (calling a tool, searching, running code), then feed the result back in before reasoning again.

Giving Loops Memory

For loops that run over many steps (research agents, multi-turn assistants), summarize prior steps into a short running memory instead of replaying the full history every time — this keeps context small and cheap..

Planner–Worker–Reviewer Teams

The most robust agent architecture is also the simplest: a Planner decomposes the goal into tasks, Workers execute one task each with narrow context, and a Reviewer checks results against acceptance criteria before anything ships.

Loop Budgets and Failure Handling

Production loops need budgets (max iterations, max cost, max time) and explicit failure paths: what happens when the Reviewer fails a result three times? Options: escalate to a human, fall back to a simpler method, or return a partial result flagged as unverified.

Project: Draft–Critique–Revise Content Machine

Deliverable: a working 3-role loop (writer, critic, editor) that produces a publishable piece of content on any topic you give it. Steps: 1.

Connecting an LLM to n8n

n8n connects to AI models either through dedicated nodes (OpenAI, Anthropic community nodes) or a generic HTTP Request node calling any model's API.

Auto Content Repurposing Pipeline

Trigger: new blog post published (RSS or webhook) -> AI node: generate a Twitter/X thread, LinkedIn post, and email blurb from the article -> Route each to the right channel.

AI Email Triage & Auto-Responder

Trigger: new email in inbox -> AI node classifies intent (support, sales, spam, urgent) -> conditional branches route to auto-reply, Slack alert, or human queue..

Error Handling & Idempotency in n8n

Real automations fail: APIs time out, models return malformed JSON, webhooks fire twice.

Human-in-the-Loop Approval Gates

The highest-trust automations pause for approval at the moments that matter: before sending externally, before spending money, before deleting anything.

Project: Your First Production n8n Workflow

Deliverable: one n8n workflow, running on a schedule or trigger, that saves you real time every week. Steps: 1.