🚀 Big News! Absolutely stoked to share that I am now officially an n8n Verified Template Creator! A massive thank you to the awesome team at n8n for the recognition and for building a product that empowers so many of us to create. This is a huge milestone and a testament to the incredible power of this community. I can't wait to bring even more high-quality, verified templates and projects to AIC and AIC+ Skool community. We're just getting started! #n8n #AI #Automation #Community #EdTech #FastTrackAIMastery

If you’re building RAG agents in n8n, this is one of the most important tutorials you’ll ever watch. In this step-by-step video, I’ll show you how to build a RAG (Retrieval-Augmented Generation) pipeline completely with no code. This setup automatically keeps your database synced with your source files, so when you update or delete a file, your database updates too. That means your AI agents always search through accurate, trustworthy data instead of outdated information. Without this system in place, you can’t rely on your AI’s answers at all. By the end of this video, you’ll understand exactly how to connect everything inside n8n, Google Drive, and Supabase, even if you’re a complete beginner.

5 Years of AWS & DevOps CI/CD Knowledge in 40 Seconds! 🚀Self hosting n8n for enterprise on AWS🚀 Just dropped a quick video showing how to deploy n8n for enterprise on AWS—packed with best practices from years in the field. Tools & Services Used: - AWS ECS (Fargate) - Application Load Balancer (ALB) - AWS ACM (SSL) - Amazon RDS (Postgres, Multi-AZ) - Amazon EFS (Shared Storage) - Docker - Custom Domain - CI/CD pipelines If you want to see a highly available, secure, and scalable n8n deployment in action— check it out!👉 https://youtu.be/c7AAI2LoywM Explainer Video - https://www.youtube.com/watch?v=ne0q45S1gww #AWS #DevOps #CICD #n8n #CloudComputing #Automation #Docker #ECS #Fargate #RDS #EFS #Enterprise #BestPractices

Agentic RAGs: The Future of AI Workflows Leading AI companies like Glean, Perplexity, and Harvey use sophisticated Agentic RAGs to handle complex enterprise tasks. This powerful combination leverages the strengths of both: - RAG (Retrieval Augmented Generation): - AI Agents: How Agentic RAGs Combine Strengths: - Smarter Retrieval: AI agents intelligently manage RAG's data retrieval, dynamically selecting sources based on query needs. - Enhanced Prompts: Agents build on RAG's augmented prompts by adding planning and real-time, tool-based data, feeding a highly refined input to the LLM. Operational Workflow (Simplified): 1. Query In: Agent receives user query. 2. Context & Plan: Agent uses memory and plans data retrieval strategy. 3. Data Fetch: Tools (like vector search) gather relevant data. 4. Prompt Optimize: Agent combines data, query, and prompt, applying reasoning. 5. Response Out: LLM generates final, intelligent output. Agentic RAGs are transforming how AI tackles complex challenges in the tech industry.

UPDATE- Created a Video course for Level 1. Access it --> HERE <-- I am super gald to announce that I cleared two official n8n Courses If anyone is interested here are the official links. They are not that crazy so definitely give it a shot. https://docs.n8n.io/courses/level-one/ https://docs.n8n.io/courses/level-two/