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    <title>Agentic RAG Series on Jason Haley</title>
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      <title>Agentic RAG Chronicles</title>
      <link>https://jasonhaley.com/2025/10/19/introducing-agentic-rag-chronicles-series/</link>
      <pubDate>Sun, 19 Oct 2025 00:00:00 +0000</pubDate>
      <author>info@jasonhaley.com (Jason Haley)</author>
      <dc:creator>Jason Haley</dc:creator>
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      <description>&lt;h1 id=&#34;introducing-the-agentic-rag-chronicles-blog-series&#34;&gt;Introducing: The Agentic RAG Chronicles (Blog Series)&lt;/h1&gt;&#xA;&lt;p&gt;Last year I &lt;a href=&#34;https://jasonhaley.com/2024/02/04/introducing-rag-demo-chronicles-series/&#34;&gt;chronicled several RAG Demos &lt;/a&gt; with the idea I would have a documented place to return to when I was looking for specify RAG features. Having those demos documented and all the reference links in one location really was useful for me - so I am going to do the same thing this year, but with Agentic RAG components.&lt;/p&gt;&#xA;&lt;h2 id=&#34;agentic-rag&#34;&gt;Agentic RAG&lt;/h2&gt;&#xA;&lt;p&gt;Last year when I was learning RAG, that technique became known as Standard RAG or Semantic RAG. At its core, it&amp;rsquo;s a system that uses semantic search—understanding meaning rather than just matching keywords—to find relevant information, then feeds that information to an LLM to answer a user&amp;rsquo;s question. When you first build one of these systems, the results feel almost magical. But it doesn&amp;rsquo;t take long before you encounter questions the system can&amp;rsquo;t answer using semantic search alone.&lt;/p&gt;</description>
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