How to build advanced RAG systems with AI-generated SQL
Using AI to generate SQL queries to power a RAG (retrieval augmented generation) application is a powerful way to add an AI layer to your product. I have built several applications like this for my enterprise software clients and today I'll share the fundamentals of building such apps with you. This is an in-depth hands-on tutorial about building AI-powered applications with the power of AI-generated SQL to answer user questions. 📚 Resources: Code and diagram used in video: https://github.com/VoloBuilds/ai-sql-... 🔧Tools Used: OpenAI GPT-4o-mini Cursor + Claude Sonnet 3.5 Postgres MERN (Mongo, Express, React, NodeJS) Tailwind, ShadCN 🚀 In This Video, You'll learn: How to build RAG systems How to use AI with your own data How to generate SQL with AI How to build enterprise AI-powered applications AI to query a database AI-powered chatbot architecture What is RAG (retrieval augmented generation) Vector RAG vs Query RAG How to build a custom chatbot Tips for building RAG pipelines Limitations of AI RAG 💡 Perfect for Viewers Interested in: Full Stack software development Best AI applications Business AI usecases AI-generated SQL Software Development Coding with AI Learning about the latest AI tech Generative AI GenAI chatbots Subscribe for more tutorials on AI and programming and to stay up to date on the latest AI tools and updates!! 💬 Questions or Feedback? Drop your thoughts in the comments below, and I'll be sure to get back to you! Chapters 00:00 - Intro to RAG 01:29 - Architecture 09:15 - Coding 19:23 - Prompt Engineering 29:32 - Tips & Limitations
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