---
title: "Agentic search models"
url: https://daily.dev/posts/agentic-search-models-qcwmigdv3
source_url: http://softwaredoug.com/blog/2026/05/11/the-new-agentic-search-models.html
type: article
source: "Software Doug"
published: 2026-05-12T13:50:55.620Z
updated: 2026-05-12T13:51:19.028Z
tags: ["llm", "rag"]
reading_time: 5
upvotes: 5
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
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# Agentic search models

**[Software Doug](https://daily.dev/sources/softwaredoug)** · 5 min read · 5 upvotes · 0 comments

## Summary

Traditional search stacks are built from discrete, manually orchestrated components — embeddings, rerankers, BM25, query classifiers — each unaware of the whole pipeline. Agentic search replaces this monolith with an LLM that orchestrates simpler retrieval primitives end-to-end. Frontier models like GPT-5 handle the generic 80% but miss domain-specific nuances (e.g., 'bistro tables' meaning outdoor furniture in a specific store). Purpose-trained agentic search models like SID-1 and Glean's Waldo aim to fill that last 20% by being smaller, faster, and tuned to specific domains and user behaviors. The author predicts a future ecosystem of domain-specific agentic search models — analogous to today's specialized embedding models on HuggingFace — covering e-commerce, job search, and more.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <http://softwaredoug.com/blog/2026/05/11/the-new-agentic-search-models.html>

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---

Tags: [#llm](https://daily.dev/tags/llm), [#rag](https://daily.dev/tags/rag)

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