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 25% off 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. Register here to join live or get the recording after.
Links and Resources
Guests
Books
Blog Posts
Roaming RAG – RAG without the Vector Database by John Berryman
Agents Turn Simple Keyword Search into Compelling Search Experiences by Doug Turnbull
A Simple Agentic Loop with Just Python Functions by Doug Turnbull
Agentic Code Generation to Optimize a Search Reranker by Doug Turnbull
LLM Judges Aren’t the Shortcut You Think by Doug Turnbul (Hugo’s 5 minute video below)
Patterns and Anti-Patterns for Building with AI by Hugo Bowne-Anderson
Other Resources
The Rise of Agentic Search, a recent VG Podcast with Jeff Huber
Cheat at Search with Agents course by Doug Turnbull (use code: vanishinggradients for $200 off)
Join the final cohort of our Building AI Applications course in Q1, 2026 (25% off for listeners)
Timestamps (for YouTube livestream)
00:00 How to Build Agentic Search & Retrieval Systems
02:48 Defining Search and AI
03:26 Evolution of Search Technologies
08:46 Search in E-commerce and Other Domains
12:15 Combining Search and AI: RAG and LLMs
23:50 User Intent and Search Optimization
29:47 Levels of AI Integration in Search
32:25 Exploring the Complexity of Search in Various Domains
33:49 The Evolution and Impact of Agentic Search
34:07 Defining Terms: RAG and Agentic Search
34:52 The Research Loop and Tool Interaction
35:55 Formal Protocols and Structured Outputs
38:39 Building Agentic Search Experiences: Tips and Advice
41:50 The Importance of Empathy in AI and Search Development
54:30 The Role of UX in Search Applications
01:01:15 Future of Search: Malleable User Interfaces
01:02:38 Exploring Malleable Software
01:04:20 The Coordination Challenge in Software Development
01:05:23 The Impact of Claude Code & Claude Cowork
01:06:22 The Future of Knowledge Work with AI
01:12:39 Evaluating Search Algorithms with AI
01:15:15 The Role of Agents in Search Optimization
01:29:55 Teaching AI and Search Techniques
01:34:25 Final Thoughts and Farewell
👉 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 25% off discount code for readers. 👈
https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=vgpod
