Is Agentic RAG A Game Changer?

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In this video, I dive into the future of Retrieval-Augmented Generation (RAG) with a powerful, no-code Agentic RAG blogging system built entirely on N8N. Traditional RAG has its limitations—single source querying, poor result quality, and hallucinations. But with Agentic RAG, your AI agent can think, reason, and autonomously plan its retrieval strategy across multiple data sources, including:

Whether you're a blogger, content marketer, or automation enthusiast, you'll see how this workflow creates deeply-researched article outlines, complete with stats, citations, and media—without writing a single line of code!

🔗 Related Videos & Links:
Chat to a Database (NLQ):    • AI Agent that Chats to a Database!  
Jina Deep Search: https://jina.ai/
Spider Cloud: https://spider.cloud/
NocoDB: https://nocodb.com/
Perplexity: https://www.perplexity.ai/

💡 What You’ll Learn:

How Agentic RAG solves traditional RAG’s limitations
Setting up automated web scraping with Spider Cloud
Embedding documents to Pinecone from Google Drive
Managing structured data in No-Code DB
Connecting to external research tools like Perplexity & Jina.ai
Watch an article go from title to publish in minutes!

💬 Drop a comment if you think Agentic RAG is the future of AI automation.

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📌 Timestamps

00:00 Demo
04:48 Traditional RAG vs Agentic RAG
09:51 RAG Web Scraping
13:25 RAG Document Upserting
15:36 Structured Query
18:11 Which is Better?