Episode
Episode 68: A Builder’s Guide to Agentic Search & Retrieval with Doug Turnbull & John Berryman
- Podcast
- Vanishing Gradients
- Published
- Jan 23, 2026
- Duration seconds
- 5322
- Processing state
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Summary
The best way to build a horrible search product? Don’t ever measure anything against what a user wants. Search veterans Doug Turnbull (Led Search at Reddit + Shopify; Wrote Relevant Search + AI Powered Search ) and John Berryman (Early Engineer on Github Copilot; Author of Relevant Search + Prompt Engineering for LLMs ), join Hugo to talk about how to build Agentic Search Applications. We Discuss: * The evolution of information retrieval as it moves from traditional keyword search toward “ agentic search “ and what this means for builders . * John’s five-level maturity model (you can prototype today!) for AI adoption, moving from Trad Search to conversational AI to asynchronous research assistants that reason about result quality. * The Agentic Search Builders Playbook , including why and how you should “hand-roll” your own agentic loops to maintain control; * The importance of “revealed preferences” that LLM-judges often miss ( evaluations must use real clickstream data to capture “revealed preferences” that semantic relevance alone cannot infer) * Patterns and Anti-Patterns for Agentic Search Applications * Learning and teaching Search in the Age of Agents You can find the full episode on Spotify , Apple Podcasts , and YouTube . You can also interact directly with the transcript here in NotebookLM : If you do so, let us know anything you find in the comments! 👉 Want to learn more about Building AI-Powered Software? Check out our Building AI Applications course . It’s a live cohort with hands on exercises and office hours. Here is a discount code for readers. 👈 Doug and Hugo are also doing a free lightning lesson on Feb 20 about How To Build Your First Agentic Search Application ! You’ll walk away with a framework & code to build your first agentic search app . Regist…