n8n just released a brand-new feature: native data tables. This makes it possible to store and manage data directly inside your n8n environment without needing an external database or constant API calls. In this video, I walk you through how these tables work, how to set them up, and how you can connect them to your workflows or AI agents in just a few clicks. I also cover the pros and cons, and when you might still want to use a traditional database instead. If you’re building quick proof of concepts, demos, or just want a simple way to manage data without latency or rate limit issues, this feature is a game-changer. The google sheets templates: Contacts Sales Test

In this video I walk through a live step-by-step build of an AI-powered newsletter using no code. All you have to do is set your search topic and the system takes care of the rest. It starts by doing initial research, then an agent plans out the structure of the newsletter. From there, each section gets its own research and is written by different agents. An editor agent pulls everything together, adds the sources so you know exactly where the information came from, and creates a clean final draft. At the end, the system even sends the draft straight to your inbox so you can forward or share it however you like. I recorded this one live so you can see why I’m connecting nodes, how variables work, and how the whole workflow comes together in about half an hour. RESOURCE PACK HERE

Hi, how can i perform hybrid search using Pinecone? Thanks

In this video, I walk you through how to make your n8n RAG agents instantly smarter using re-rankers and metadata. If you've ever had your AI agent return the wrong information or pull irrelevant chunks from your vector database, this is the fix. Re-rankers help prioritize the most relevant chunks after your initial search, making the results dramatically more accurate. I also show you how to use metadata both when vectorizing and when retrieving, so your agents can filter and find exactly what they need with precision. These techniques are simple to implement but make a huge difference in how well your agents understand and respond. If you're building AI agents in n8n, this video will help you take them to the next level. Must be on version 1.98 or higher to access rerankers.

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