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Embeddings don't solve RAG

Hosted by Doug Turnbull (Maven)

Mon, Sep 28, 2026

5:00 PM UTC (1 hour)

Virtual (Zoom)

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Cheat at Search with Agents
Doug Turnbull
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What you'll learn

The partial promise of embeddings in RAG

Where do embeddings sit in the family of search solutions? When does the promise fall apart

What they're not teaching you about search

From BM25, to pagerank, to late interaction, to query understanding. The pieces of search.

How to actually build RAG in 2026

It's easy to fix one problem and then inadvertantly break the rest of the product. Learn how search evals prevent that.

Why this topic matters

You've been fed a false narrative. That RAG means embeddings. Ask a retrieval engineer they'll only be one small piece of a good RAG solution. By questioning embeddings as a search solution, we'll take a chance to talk about other ways of thinking of search and retrieval. Come hang out and learn about the many ways to think about search in 2026.

You'll learn from

Doug Turnbull (Maven)

Led teams at Shopify, Reddit, Wikipedia

In 2012, Doug got bit by the search bug and he's still trying to keep up. From full-text search, to Learning to Rank models, to search agents that generate their own code, he knows the endless landscape first hand. Yet Doug wants to deeply understand the what / how / why, and help teams use these technologies practically, distinguishing hype from reality.

He’s led search at Reddit, Shopify, and Wikipedia, authored Relevant Search and AI Powered Search, and advised 100+ organizations over the years - all in pursuit of the same question: how does search actually work?

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