---
title: "Agentic search - retrieval, harness, or model?"
url: https://daily.dev/posts/agentic-search---retrieval-harness-or-model--caehzlaqp
source_url: http://softwaredoug.com/blog/2026/06/08/three-kinds-of-agentic-search.html
type: article
source: "Software Doug"
published: 2026-06-09T09:22:52.756Z
updated: 2026-06-09T09:23:15.268Z
tags: ["llm", "deep-learning", "rag"]
reading_time: 8
upvotes: 0
comments: 0
language: en
---

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# Agentic search - retrieval, harness, or model?

**[Software Doug](https://daily.dev/sources/softwaredoug)** · 8 min read · 0 upvotes · 0 comments

## Summary

Agentic search is an ambiguous term that covers three distinct implementation patterns. Retrieval-centric approaches build high-quality search so agents can find relevant context on their own, but are limited by imperfect retrieval quality. Harness-centric approaches put the agent in charge of exploration, using relevance feedback and external judges to steer it toward correct results — effective but token-expensive. Model-centric approaches fine-tune an LLM specifically on search tool-calling traces, enabling efficient, domain-aware retrieval without repeating costly exploration steps. Each pattern has trade-offs, and the field is converging toward hybrid designs borrowing patterns from coding agents.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <http://softwaredoug.com/blog/2026/06/08/three-kinds-of-agentic-search.html>

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---

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

[View this post on daily.dev](https://daily.dev/posts/agentic-search---retrieval-harness-or-model--caehzlaqp)