Client: "We have 50,000 mixed documents in one folder. Need them sorted by type. Budget: Whatever it takes." THE DIGITAL HOARDER SITUATION - 15 years of accumulated documents - Insurance claims, medical records, contracts, invoices, receipts - No naming convention - No folder structure - Previous attempts failed: "Too complex for interns" THE CHAOS CLASSIFICATION n8n WORKFLOW (12 nodes) Document ingestion (Nodes 1-2): - Batch folder processing - File format detection and validation Content analysis (Nodes 3-6): - Full document text extraction - Keyword density analysis - Layout pattern recognition - Financial data detection Classification engine (Nodes 7-9): - Machine learning document categorization - Confidence scoring per category - Multi-label classification (document can be multiple types) Organization system (Nodes 10-12): - Automated folder creation - File naming standardization - Duplicate detection and handling - Processing log and reporting BUILD AND DEPLOYMENT Development time: 6 hours Testing with sample chaos: 4 hours Full deployment: 2 hours Client training: 1 hour THE SORTING RESULTS 50,000 documents processed in 8 hours: - Medical records: 12,400 documents - Insurance claims: 8,700 documents - Contracts: 6,200 documents - Invoices: 9,800 documents - Receipts: 7,300 documents - Miscellaneous: 5,600 documents Classification accuracy: 94.7% Manual review needed: 2,650 documents (5.3%) Client satisfaction: "Life-changing" THE RECURRING OPPORTUNITY Monthly document volume: 2,000+ new mixed documents Ongoing sorting service: $2,100/month Processing time: 30 minutes monthly Profit margin: 96% THE TEMPLATE EXPANSION "Document Chaos Classifier" deployed for: - Law firms with discovery document dumps - Accounting firms with client record archives - Real estate companies with property files - Medical practices with patient record conversions Deployment variations: - Legal: Contract vs discovery vs correspondence - Accounting: Receipts vs invoices vs tax documents

Most people try to grow income by working harder — but the real growth happens when you build smarter systems. If you’re earning around $1K/mo and want to scale faster, here’s what the top 1% are doing differently 👇 1️⃣ **Automate Income Activities** – Use tools like n8n, Zapier, or Make to remove repetitive work. 2️⃣ **Package Expertise** – Turn your process or service into a digital product or AI-powered offer. 3️⃣ **Build Distribution** – Use LinkedIn, Skool, or Instagram automation to reach new leads daily. 4️⃣ **Leverage Compounding Tools** – Integrate Notion AI, ChatGPT, and HubSpot for clarity + consistency. 5️⃣ **Focus on ROI Work** – Spend 80% of your time on systems that grow, not maintain. 💡 *Scaling to $10K isn’t luck — it’s alignment between value, automation, and strategy.* 👉 What’s your biggest bottleneck right now: leads, systems, or clarity?

In this video, I compare OpenAI’s new AgentKit to n8n to see how they stack up against each other. We’ll go over what each platform is, how they work, and what makes them unique. I’ll walk you through how to access and set up AgentKit, explore its features, and then put both tools head-to-head across different categories. I also score each one so you can clearly see their strengths and weaknesses. Most importantly, I’ll help you figure out when you should use one over the other, because the truth is, they’re built for different purposes and appeal to different types of builders. Whether you’re just getting started or already deep into automation, this video is a full, easy-to-follow guide to help you choose the right tool for your next project.

In this video I'm going to be teaching you how I'd make money with AI in 2026, if I had to start over from scratch. This will be the most actionable video you've ever seen about making money with AI. I'll breakdown everything, and fitting it all into this easy to learn 24 minute guide. Hope you enjoy!