Added another diagram

Author: HeidiSteen

articles/search/media/agentic-retrieval/agent-to-agent-pipeline.png

@@ -31,6 +31,8 @@ The *retrieval* component is the ability to run subqueries simultaneously, merge
 
 Query expansion and parallel execution, plus the retrieval response, are the key capabilities of agentic retrieval that make it the best choice for generative AI (RAG) applications.
 
+:::image type="content" source="media/agentic-retrieval/agentric-retrieval-example.png" alt-text="Diagram of a complex query with implied context and an intentional typo." lightbox="media/agentic-retrieval/agentric-retrieval-example.png" :::
+
 Agentic retrieval adds latency to query processing, but it makes up for it by adding these capabilities:
 
 + Reads in chat history as an input to the retrieval pipeline.

articles/search/search-agentic-retrieval-concept.md

@@ -5,7 +5,7 @@ description: Learn how to design and build a custom agentic retrieval solution w
 author: HeidiSteen
 ms.author: heidist
 manager: nitinme
-ms.date: 05/21/2025
+ms.date: 06/08/2025
 ms.service: azure-ai-search
 ms.topic: how-to
 ms.custom:
@@ -16,7 +16,9 @@ ms.custom:
 
 [!INCLUDE [Feature preview](./includes/previews/preview-generic.md)]
 
-This article describes an approach or pattern for building a solution that uses Azure AI Search for knowledge retrieval, and how to integrate knowledge retrieval into a custom solution that includes Azure AI Agent.
+This article describes an approach or pattern for building a solution that uses Azure AI Search for knowledge retrieval, and how to integrate knowledge retrieval into a custom solution that includes Azure AI Agent. This pattern uses an agent tool to invoke an agentic retrieval pipeline in Azure AI Search.
+
+:::image type="content" source="media/agentic-retrieval/agent-to-agent-pipeline.png" alt-text="Diagram of Azure AI Search integration with Azure AI Agent service." lightbox="media/agentic-retrieval/agent-to-agent-pipeline.png" :::
 
 This article supports the [agentic-retrieval-pipeline-example](https://github.com/Azure-Samples/azure-search-python-samples/tree/main/agentic-retrieval-pipeline-example) Python sample on GitHub.
 

articles/search/search-agentic-retrieval-how-to-pipeline.md

@@ -17,8 +17,6 @@ ms.date: 06/08/2025
 
 In Azure AI Search, *agentic retrieval* is a new parallel query architecture that uses a large language model (LLM) for query planning. It generates subqueries that broaden the scope of what's searchable and relevant. It incorporates chat history for context. The LLM studies the query and subdivides it into more targeted queries, using different phrases and terminology for subquery composition.
 
-:::image type="content" source="media/agentic-retrieval/agentric-retrieval-example.png" alt-text="Diagram of a complex query with implied context and an intentional typo." lightbox="media/agentic-retrieval/agentric-retrieval-example.png" :::
-
 This article explains how to use the [**retrieve method**](/rest/api/searchservice/knowledge-retrieval/retrieve?view=rest-searchservice-2025-05-01-preview&preserve-view=true) that invokes a knowledge agent and parallel query processing. This article also explains the three components of the retrieval response: 
 
 + *extracted response for the LLM*