Taking some of the ideas in here allowed me to champion a $5,500 client. My background is 20 years of large corporation pricing and 30 years of web design. AI - maybe 10 years with apps, tools, and oh yeah PYTHON...so... A Saturday morning, 4 hours, and a complete pricing evolution. 🔥 I recently helped a small industrial parts business move from manual Excel models to a fully autonomous agentic workflow. Using ChatGPT alongside n8n and Claude, I built a system that audits invoices, expenses, and competitor data for an automated Van Westendorp price sensitivity analysis. 😱 The user just chats to a chatGPT chatbot to execute. That’s the power of this stack. Time to put spreadsheets to bed! 🏆 Thank you to all the amazing people on here who post GREAT content!

In this video, I break down exactly how to sign your first AI workflow client in 7 days, with real proof. You’ll hear directly from a member of AIS+, Christian, who signed his first automation client in just 7 days. We walk through the exact process he used, what actually worked, and how you can apply the same steps yourself.

I tried to help everyone. Custom solutions. Custom workflows. Custom timelines. Sounds good in theory. Kills you in reality. Here’s the truth no AI agency wants to admit: You can’t scale “custom everything.” Most AI agencies fail for one reason: They promise to build bespoke automations for every business. What that actually means: - 4–7 days to build ONE automation - Endless revisions - Clients waiting, chasing, hesitating - You drowning in projects And no one wants to wait a week for automation in 2025. So I flipped the model. Instead of custom work, I productized ONE automation. Then I templated it: - Every step - Every integration - Every edge case - Every deployment process The result? Deployment time went from 7 days → under 1 hour. That’s when everything changed. I went from: - Project-to-project chaos - Consistent, predictable, paying clients Saying “no” at the start was hard. But speed compounds. Speed = money. Amazon didn’t win because it had the best products. It won because it removed friction. Imagine if Amazon said: “Fill a 5-page form and wait 10 days to order.” You’d never use it. Instead: 2 clicks. Product at your door. LESS FRICTION = MORE SALES

Hi guys, Right now i am building my first RAG agent, using n8n. I use a combination of pinecone and the simple vector store native to n8n. It works but not in the way i want to. I am getting abit lost in all the videos and tutorials there is. So basically put i have 2 questions. What is the best way to decide how to chunk or vectorise your documents. What can i do to optimise those documents. Extra questions for bonus points: What would be the most efficient way of gettig physical books into my rag agent if there aren't any e-books findable,.