RAG isn't a vector search problem

Hosted by John Berryman and Doug Turnbull

221 students

In this video

What you'll learn

Rethink RAG

The marketing hype says you should deploy billion scale vector search before RAG. Is this true?

Solve RAG faster

Bulid RAG with the retrieval systems you already have on hand

Lexical RAG and more

Build a RAG with easier to manage lexical search. Using tried and true search methods.

Why this topic matters

RAG is often framed as a vector search problem, turning it into a black box of embeddings and magic. This lesson shows how RAG doesn’t have to be opaque – starting from traditional search, you can incrementally and safely adopt agentic RAG, skip the hype, and keep your system transparent and understandable.

You'll learn from

John Berryman

Ex-Github Copilot; AI Consultant

John Berryman is the founder and principal consultant of Arcturus Labs, where he specializes in AI application development (Agency and RAG). As an early engineer on GitHub Copilot, John contributed to the development of its completions and chat functionalities, working at the forefront of AI-assisted coding tools. John is coauthor of Prompt Engineering for LLMs (O'Reilly). Before his work on Copilot, John's focus was search technology. His diverse experience includes helping to develop next-generation search system for the US Patent Office, building search and recommendations for Eventbrite, and contributing to GitHub's code search infrastructure. John is also coauthor of Relevant Search (Manning), a book that distills his expertise in the field. John feels fortunate to have worked at the intersection of cutting-edge AI applications and foundational search technologies, giving him the opportunity to contribute to innovation in both LLM applications and information retrieval.

Doug Turnbull

Agentic Search Consultant

Doug Turnbull helps clients build better agentic search systems. He led machine-learning-driven search initiatives at Reddit, significantly improving search relevance through Learning to Rank methods. Doug also advanced e-commerce search at Shopify and served as CTO at OpenSource Connections. He co-authored the influential book Relevant Search (Manning, 2016) and created popular open-source tools, including Quepid and the Elasticsearch Learning to Rank plugin. He regularly speaks at industry conferences, making search relevance accessible to engineers.

Previously at