In "The Hitchhiker's Guide to Vector Search," Clelia Astra Bertelli shares insights and practical advice from her extensive experience in the AI space, particularly focusing on vector search and its applications in Retrieval Augmented Generation (RAG). The blog post covers key aspects of vector search, including the importance of text extraction, chunking strategies, and embedding techniques, emphasizing the significance of clean data and meaningful chunks for effective RAG pipelines. Bertelli discusses hybrid searches that combine dense and sparse embeddings to enhance semantic understanding while maintaining keyword accuracy, and highlights the value of semantic caching and binary quantization for boosting search efficiency. The post also underscores the critical role of query optimization and evaluation metrics in building reliable vector search systems, encouraging a cycle of iteration and improvement. Throughout, Bertelli advocates for practical experimentation and continuous learning as essential components of advancing in the field of AI and vector search technology.