Vanishing Gradients Episode 68: A Builder’s Guide to Agentic Search & Retrieval with Doug Turnbull & John Berryman
24 snips
Jan 23, 2026 Join search guru Doug Turnbull, who shaped systems at Reddit and Shopify, and John Berryman, the brain behind GitHub Copilot, as they dive into the future of agentic search. They explore the evolution from traditional search to agentic retrieval, spotlighting John's five-level maturity model for AI adoption. Learn why understanding user intent is paramount and discover practical steps to create your own agentic loops. They also share insights on avoiding common pitfalls in search design, emphasizing the importance of real user feedback.
AI Snips
Chapters
Books
Transcript
Episode notes
Prototype A Minimal Agentic Loop
- Build a simple agentic loop around something that matters to you before choosing frameworks.
- Make one input call a model, enable tool calls, then wrap an outer loop to include the user as an assistant.
Search Is A Spectrum Of Intents
- Search intent sits on a spectrum from navigational to exploratory and conversational.
- Different intents demand different UI affordances and agent behaviors to be useful.
Use LLMs For Intent Understanding And State
- Use LLMs to infer intent from queries and facets, then take control to apply filters or ask clarifying questions.
- Wrap an outer assistant loop to keep state and support back-and-forth corrections.
