When I first started building in n8n, I thought more nodes meant more power. I’d create massive workflows with 30+ nodes, dozens of connections, and complex logic, just to automate something simple. It looked impressive… until it broke. Most beginners overestimate what a workflow should do. They try to automate everything at once, marketing, leads, messages, reports, all inside one big flow. The result? Confusion, errors, and a mess that’s hard to fix. Here’s the truth: n8n isn’t about building big workflows, it’s about building smart systems. A great workflow is like a minimalist home. Every node has a purpose. Nothing extra. When you try to do too much in one place, you lose clarity and control. Here’s what works better: ✅ Start from the end goal — what do you actually want to achieve? ✅ Break the process into smaller workflows (collect → process → act). ✅ Use Execute Workflow or Webhooks to connect them. ✅ Keep each flow simple enough that anyone can read it in one glance. One of my early clients wanted one huge automation to manage leads from Facebook to CRM to email campaigns. Instead, I split it into three clean workflows, easier to debug, scale, and reuse across other clients. Remember this: A 3-node workflow that runs flawlessly 10,000 times is more powerful than a 100-node one that fails once a week. Keep it simple. Keep it stable. That’s how you master n8n, one clean workflow at a time.

I’m giving away 2 free n8n Cloud Starter Plans (1 year, $240 value each) to 2 lucky members! How to enter: 💬 Drop your favorite meme about AI or Nate Herk in the comments below. 🕒 I’ll pick my 2 favorite memes and announce the winners on Friday morning at 9:00 a.m. CT. Let’s see who’s got the funniest take, time to get creative! Cheers, Nate

40-year-old construction company client. Their document sources made me cry. THE FRANKENSTEIN INPUTS Fax machine from 1997 still receives quotes Email attachments in 12 different formats Photos from job sites with handwritten estimates on napkins Scanned contracts from the 90s Modern PDFs from new suppliers Excel sheets with bizarre macros Built the ugliest n8n workflow ever. 23 nodes of pure chaos. THE MONSTROSITY ARCHITECTURE 5 input nodes: Email, fax server, Dropbox, API webhook, manual upload 7 document detection types: Fax quality, photo, scan, PDF, Excel, Word, other 12 different processing paths based on document characteristics Fax documents get noise reduction plus OCR enhancement Photos get perspective correction plus handwriting OCR Scans get deskew plus quality improvement PDFs get standard extraction Tables get structure preservation Legacy formats get conversion first Validation layer with confidence scoring, human review queue, retry logic Output integration to their ancient ERP system using SOAP API from 2003 Email notification system with color-coded status reports IT'S HIDEOUS BUT PROFITABLE Monthly processing volume: 847 fax documents (yes really) 1,230 email attachments 456 job site photos 2,100+ total documents Results after 8 months: 97.3% processing success rate Saved 3 full-time data entry positions Client fee: $3,800/month API costs: $127/month Profit: $3,673/month THE UGLY TRUTH My prettiest 6-node workflows: Average $900/month My ugliest 23+ node monsters: Average $3,200/month Clean workflows impress developers. Working workflows impress clients. Current ugly workflow revenue: $14,800/month across 4 clients Pretty workflows: $4,200/month across 7 clients The construction client just referred me to 3 competitors. All have similar document chaos. What's your ugliest automation that somehow prints money?

Recent times i'v been encountering with webhooks, and I have these questions about webhooks that can solved by professionals. While designing “autonomous agent network” powered by n8n and webhooks, what real-world problem would you solve? Give me the list if possible? How would you combine webhooks and AI models to create a self-updating knowledge base or a real-time decision-making system?

🚀 OpenAI just dropped AgentKit a new flow builder for automations and AI agents, kind of like what we do in n8n, but fully inside the OpenAI ecosystem. It looks like they’re moving toward visual agent creation, drag, drop, connect, and deploy directly. Do you think this could affect tools like n8n, or just open up more possibilities for integrations and AI workflows? 💬 Curious to hear your thoughts — will you stick with open-source (like n8n) or try OpenAI’s new builder?