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      <title>Presentation: From Retrieval to Reasoning: Building Production-Ready Agentic AI Systems with Knowledge Graphs</title>
      <link>https://www.infoq.com/presentations/knowledge-graphs-agentic-systems-patterns/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Retrieval-Augmented+Generation</link>
      <description>&lt;img src="https://res.infoq.com/presentations/knowledge-graphs-agentic-systems-patterns/en/mediumimage/cassie-shum-medium-1788338916792.jpeg"/&gt;&lt;p&gt;Cassie Shum discusses why knowledge graphs serve as a critical foundation for agentic systems. Moving beyond basic RAG, she explains 4 practical architectural patterns: context bundling, decision provenance, code as truth, and agent visibility. She demonstrates an engineering harness built on a knowledge graph to streamline feedback loops, optimize token usage, and maintain system reliability.&lt;/p&gt; &lt;i&gt;By Cassie Shum&lt;/i&gt;</description>
      <category>Agentic AI Architecture</category>
      <category>Large language models</category>
      <category>Retrieval-Augmented Generation</category>
      <category>Agents</category>
      <category>QCon AI Boston 2026</category>
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      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Sat, 12 Sep 2026 11:00:00 GMT</pubDate>
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      <dc:creator>Cassie Shum</dc:creator>
      <dc:date>2026-09-12T11:00:00Z</dc:date>
      <dc:identifier>/presentations/knowledge-graphs-agentic-systems-patterns/en</dc:identifier>
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