Traditional keyword search often fails when users look for "dripping tap" but miss results for "leaky faucet." Join me as we code an intelligent search using OpenAI embeddings and Pinecone that truly understands user intent.

Through real examples and hands-on coding, we'll cover the entire process: embedding text into vectors, indexing for quick retrieval, adding data to Pinecone, and querying with cosine similarity to find the closest matches on the vector plane. Watch as we create a search that links "budget car" to "affordable vehicle" and "Python error" to "programming bug fixes." Understanding user intent should not be this difficult in 2025.