Mar 9
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Welcome back to The Data Key! 🗝️ Everyone is building RAG (Retrieval-Augmented Generation) systems today, but why do so many fail in production? The difference between a cool demo and a billion-dollar product is Reliability. In this video, generated using Google's NotebookLM, we take a deep dive into the blueprint for building RAG systems that actually work. We move beyond simple "retrieve and generate" to explore Agentic Workflows—systems that can plan, reason, and verify their own answers. If you are a Data Scientist or AI Engineer trying to reduce hallucinations and improve accuracy, this breakdown is for you. -------‐---‐-------------------------------------------------------------------- 👇 In this video, we cover: Why 90% of RAG failures are due to Retrieval, not Generation. Level 1: Upgrading your engine with Hybrid Search, Rerankers, and Semantic Chunking. Level 2: Giving your RAG a "Brain" with Agentic capabilities (Planning & Tool Use). Level 3: How to measure success using Faithfulness and Relevancy metrics. How Advanced RAG can reduce hallucinations by up to 90%. -------‐---‐-------------------------------------------------------------------- 📚 Important Resources & Documentation : Here are the official docs and guides for the tools mentioned in this video: 🔹 The Foundations What is RAG? (AWS Guide): https://aws.amazon.com/what-is/retrieval-augmented-generation/ Hybrid Search Explained (Pinecone): https://docs.pinecone.io/guides/search/hybrid-search Reranking Models (Cohere): https://docs.cohere.com/docs/rerank 🔹 Building Agentic RAG LangChain Agentic RAG Tutorial: https://docs.langchain.com/oss/python/langgraph/agentic-rag LlamaIndex Agents Guide: https://www.llamaindex.ai/blog/agentic-rag-with-llamaindex-2721b8a49ff6 🔹 Evaluating Your System (The Scoreboard) Ragas Framework (Metrics): https://docs.ragas.io/en/latest/ TruLens (Tracking & Evals): https://www.trulens.org/ -------‐---‐-------------------------------------------------------------------- ⏳ Timestamps 0:00:00 - The Challenge: From Prototype to Production 0:00:18 - The $11 Billion RAG Opportunity 0:00:35 - Why RAG Projects Fail (It's the Retrieval) 0:01:06 - Level 1: Mastering Retrieval (Hybrid Search Explained) 0:02:00 - The Power of Reranking 0:02:29 - Smart vs. Bad Chunking 0:02:52 - Level 2: Agentic RAG (Giving AI a Brain) 0:03:29 - Agentic Capabilities: Planning & Tool Use 0:04:16 - Level 3: Mastering Evaluation (The Scoreboard) 0:04:30 - Key Metrics: Faithfulness & Answer Relevance 0:05:25 - Summary: The 3-Step Journey 0:06:01 - Reducing Hallucinations by 90% 0:06:20 - The Future: What should humans keep for themselves? -------‐---‐-------------------------------------------------------------------- 👨💻 Connect with The Data Key Subscribe: https://youtube.com/@The_Data_Key -------‐---‐-------------------------------------------------------------------- #RAG #rag #datascience #ai #machinelearning #datasciencecourse #machinelearningfullcourse #notebooklm #agenticai #llm #thedatakey #artificialintelligence #tech #newvideo #trendingvideo #trendingtopic #popularvideo #subscribe #retrievalaugmentedgeneration #chatgpt #pythoncoding #langchain #aws #aiengineer #viralvideo #mastering #whatisrag