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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)

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