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4d •
🚀New Video: How I'd Learn n8n if I had to Start Over in 2026
If I had to start over and learn n8n from scratch today, this is the exact path I’d follow. The skills to focus on, the mistakes to avoid, and the fastest way to go from beginner to building real workflows that clients actually pay for. This is one of my most valuable videos yet, so I hope you guys enjoy!
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6d •
🚀New Video: n8n 2.0 is Here (What You Need to Know)
I just walked through everything new in n8n version 2.0. This update brings a refreshed UI, smoother animations, and a few behavior changes that make building automations feel more intuitive. In the video, I highlight the biggest improvements, show how they affect your workflows, and share what you should expect as you transition to the new version. If you want a quick overview of what’s changing and why it matters, this breakdown will get you up to speed.
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🏆 Weekly Wins Recap | Dec 6 – Dec 12
From five-figure months to first clients and real-world AI builds - this week inside AIS+ showed what happens when people stop waiting and start executing. Here are this week’s highlights inside AIS+ 👇 👉 @Sef El is collecting $25K this month from client invoices - built solo, step by step, through consistency and patience. 👉 Jan Goergen-Makinson launched his first voice agent, “Kora,” handling appointments using Retell - a big leap into real client-facing AI. 👉 Prakhar Dubey built his first client workflow for a UK-based NGO supporting SEND children - turning learning into meaningful impact. 👉 @Eduard Friesen broke into the All-Time Top 10 leaderboard and landed his first paid client - momentum stacking fast. 👉 @Abel Alvarado shipped an AI Social Media Intern - from research to auto-image generation and multi-platform posting, all automated. 🎥 Super Win Spotlight of the Week: Nick Mohler | Partnerships Through Community Nick didn’t join AIS+ just for tools - he showed up, participated, and shared openly. That single decision led to meeting a business partner, multiple collaborations, and new client opportunities - all through community connection. 🎥 Watch his quick story 👇 Nick’s journey is proof that when you put yourself out there, the right connections find you. ✨ Want to see more wins like these every week? Join the builders inside AI Automation Society Plus - where consistency, community, and action turn learning into real results 🚀
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Built Document Review Queue That Catches 100% Of Extraction Errors 🔥
Automated extraction is powerful. But wrong data in QuickBooks or CRM is worse. Needed confidence-based review queue catching low-quality extractions before problems. Built smart review system. Only reviews uncertain extractions. 100% accuracy maintained with minimal human time. THE APPROACH: Not all extracted data has equal certainty. Some 99% confident. Others 60% uncertain. Route based on confidence. High → auto-process. Low → human review. THE QUEUE WORKFLOW: Switch checks confidence per field (not just overall) Critical fields (amount, date, invoice number) need 95%+ Supporting fields (notes, descriptions) need 85%+ ANY critical field below threshold → Review queue Airtable record: document preview + extracted data side-by-side Slack notification when queue has items Reviewer corrects if needed, approves Webhook continues processing THE CRITICAL INSIGHT: Don't review entire documents. Review specific uncertain fields. Invoice with 99% confident amount but 60% confident date? Only review date. Accept amount. REAL EXAMPLE: 500 invoices monthly. 94% overall accuracy. But 30 invoices have errors. Without field-level routing: Review all 500 (forever) or auto-process all (30 errors reach system). With field-level routing: System flags 45 with uncertain fields. Review 45 takes 60 minutes monthly. Zero errors reach destination. THE REVIEW INTERFACE: Document preview embedded Extracted data in clean format Confidence scores highlighted (red <85%, yellow 85-95%, green >95%) Editable fields for corrections One-click approve Mobile friendly. Review from phone. THE METRICS: 500 invoices monthly 45 flagged (9%) 80 seconds average review 60 minutes total monthly Errors caught: 100% TIME COMPARISON: Manual review ALL: 500 × 2 min = 16 hours monthly Smart queue UNCERTAIN: 45 × 1.3 min = 1 hour monthly Saved: 15 hours monthly Template in n8n with review queue here THE LESSON: Automation doesn't mean zero human involvement. Means intelligent involvement only where needed.
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AI-Powered Customer Feedback & Automation System
Client: Roschiat Perfumes Built with: n8n · AI Agents (Gemini) · Airtable · Slack · Gmail Project Value: $200 Ongoing Maintenance: $50/month Project Overview Roschiat Perfumes needed a smart, scalable way to capture customer feedback, categorize it intelligently, and respond professionally—without manual effort. To solve this, I designed and implemented an AI-driven feedback automation system that transforms raw customer inputs into structured insights and automated actions. This system ensures no feedback is missed, improves response time, and gives the brand a clear understanding of customer sentiment. Key Use Cases - E-commerce Feedback Management - Customer Support Automation - Brand Reputation Monitoring - Product Improvement Insights - Internal Team Notifications Business Impact ⚡ Zero manual sorting of feedback ⚡ Instant AI-driven responses ⚡ Centralized customer insights ⚡ Improved customer experience & trust ⚡ Scales effortlessly as the brand grows Please review my project and share your suggestions for future enhancements. I have attached the production URL for your reference.https://n8n.srv1187080.hstgr.cloud/form/349ac866-9e24-4f8e-a5f7-05e4207828c8
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