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✅ Looking for AI systems? Work with me: https://www.automatezai.com/ 📍Resources and Prompts: https://yashica.gumroad.com/l/easy-ra... 📞 Looking for my guidance? Book a 1:1 call with me: https://cal.com/yashica-jain/consulting In this video, I’ll show you a clean way to power up an AI Agent with knowledge using n8n, without getting stuck in complex RAG setups. If you’re handling a small batch of documents—around 10–20 PDFs—this method will save you a lot of time and headaches. I'll walk you through two real-world cases: one for a chat-based AI agent and one for structured outputs like JSON, using OpenAI's Assistant API. No vector stores, no overkill. I’ll also clear up a big misconception around RAG that most people get wrong when building lightweight AI workflows. If you want a simple, affordable way to make smarter AI agents without unnecessary tech overhead, you’re going to like this. 🛠TOOLS USED: (some of these are my affiliate links. If you use it, it will get you a free trial, and buy me an extra cup of coffee for the day☕️). 1. N8N: https://n8n.partnerlinks.io/r1csxrj2bf5r 2. Open AI: https://openai.com/ 💁🏼♀️ Connect with me: / yashicajain9 👉🏻 Follow me on X: https://x.com/yashicajain_ I hope this video helped you in some way. If so, let me know in the comments below!👇🏻 #rag #aiagents #n8n 0:00 - Intro 0:03 - Who is this for 0:30 - What we'll cover 2:32 - Chat instance explained 3:35 - Setting up the Assistant (OpenAI setup, API key, file upload) 8:36 - Testing the RAG AI Agent (Chat instance with file search) 13:05 - JSON structured output 15:14 - Testing JSON output 16:48 - Outro