Build a Semantic Search Engine using Next.js, AI SDK, Embeddings and PostgreSQL

Description

Does your app's search bar return "0 results" unless the user types the exact word? It’s time to upgrade your stack. In this video, we break through the barriers of traditional web development and dive into AI Engineering. I’ll show you, step by step, how to build a production ready Hybrid Semantic Search system (RAG) that actually understands user intent. We will be using the modern JavaScript stack: Next.js, Prisma, PostgreSQL (pgvector), and the Vercel AI SDK. 🚀 What you will learn: - The Theory: How Embeddings work and how machines understand "meaning." - The Infrastructure: Vector Databases vs. Traditional SQL. - The Architecture: Understanding RAG (Retrieval Augmented Generation). - The Code: Moving from SQL LIKE operators to Cosine Similarity. 👍 Like the video if it helped 🔔 Subscribe for more AI engineering deep dives 🚀 Build AI apps that feel fast, not broken jsengineer.ai