Hi everyone, I’m reaching out to let you know that I’m going to close this community. When I started this group, I was intoxicated by the success of other creators. I wanted to make a lot of money like my competitors and switch from working to teaching because I love it. I thought my huge experience would help me with that—but that was a mistake. During this six-month chase, I realized a lot—mainly that I was focused on the wrong things and had the wrong goals. All these overcrowded communities focus on producing content and getting more members, instead of sharing REAL knowledge. Of course, they share some tips that might seem very good for any non-tech newbie, but professionals in this niche clearly see how far the solutions shared in these communities are from what they actually do daily. Nobody cares about researching technologies and building something reliable and scalable, because it’s very hard and complex work. I’ve been in the no-code niche for five years and know that most no-code agencies focus on MVPs, because 95% of them die after launching. It’s easy money: you build something for a few months, get $15k, and then it dies—nobody will find your bugs, the client will never know that this solution can’t scale beyond 30 users, and you never need to maintain that mess. At the same time, there’s a parallel market for real solutions—usually businesses smart enough to avoid scammy agencies. They collaborate with proven professionals and work with them for years. In this situation, you barely need to make content or share cases, which is why it’s so hard to find such professionals and real information online—they’re busy working. Only a few of them have time to share deep insights. I’m working too—I can’t afford to stop working and just teach because technologies move very fast, and to answer questions, you need to keep gaining new experience, researching new approaches, etc. Otherwise, your knowledge is outdated in just a few months. So I found it very hard to combine content generation and actual work, as both take huge resources to produce high-quality results.

Last time, I shared how we automated hiring 500+ candidates for a client without an HR team. If you missed that post, check it out here. Now, let’s talk about documents—because if you run a business, you know the struggle. This same client receives a constant flow of receipts and invoices via email and manually saves them to Google Drive. The problem? Finding and organizing these files later is a nightmare. They needed a way to automatically process, rename, and categorize them without spending hours sorting through folders. So we built an AI-powered automation that handles everything on autopilot. Here’s how it works: 🛠️ The Setup 1️⃣ Fetching New Files • Every time a new email arrives with an attachment, the system downloads the file and checks if it’s a receipt or invoice. • If it’s something else, we ignore it. 2️⃣ Smart AI Recognition • We process the file using LlamaParse, which allows us to: ✅ Extract tables (common in invoices) ✅ Recognize logos that contain company names ✅ Parse text even from image-based PDFs (which standard N8N nodes can’t handle) 3️⃣ Context-Aware Parsing • Instead of relying on generic AI recognition, we guide the AI with a predefined list of banks and companies the client frequently deals with. • This makes the results far more accurate and stable. 4️⃣ File Renaming & Metadata Tagging • AI extracts key details like date, amount, and entity name based on separate rule sets. • Each parameter is processed separately to increase precision—because main info and entities follow different logic. • Once identified, the file is renamed according to a structured pattern and saved in Google Drive. 5️⃣ Preventing Duplicates • To avoid reprocessing the same document, we add hidden metadata to each file. If a document comes through again, our system detects it and skips processing. 6️⃣ Structured Data Storage • Parsed information is saved in Airtable, where it links to related records—keeping everything structured for future reference.

Hi everyone! 👋 I’ve been exploring Lovable and decided to create a user-friendly interface for my AI agents on N8N. After just 3 hours of work, here’s what I built (see screenshots): 🔹 Chat with N8N and get formatted responses with images. 🔹 Switch between multiple agents in the same conversation. If all agents are yours, they can share chat history for better context. • Example: I asked my YouTube agent to find channels and then had my DB agent save the data in a database (pic. 1). 🔹 Add private agents via webhook (pic. 2). • You’ll need to slightly adjust your agent flow to standardize inputs from different triggers (pic. 3). 🔹 Make agents public so others can use them (pic. 4). • Public agents can’t access others’ data in chat. 🚀 Would you like to see how I built this? Or maybe use it for your own AI agents? Let me know

Hi, Seems simple but couldn't figure it out yet: I want to use the same flow for different inputs (Telegram, webhook, chat, mail). Screenshot below to clarify (I can only refer in AI Agent to one variables node). Please advise, thanks!

Happy Sunday! Got a question . 🙋‍♀️ When you are triggering a workflow with multiple triggers say- webhook, chatinput and when called by another workflow, how do you map or create an expression that will pass in data to the upcoming node- say in a set node that will standardize or work irrespective of which of the triggers you use in triggering the workflow without manually remapping them