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      <title>Presentation: Postgres for Production Agents: Your Relational Foundation for Enterprise AI</title>
      <link>https://www.infoq.com/presentations/postgres-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/postgres-ai-agents/en/mediumimage/gwen-shapira-medium-1783500671134.jpeg"/&gt;&lt;p&gt;Gwen Shapira shares how teams are scaling AI features using PostgreSQL for mission-critical apps. She explains how to leverage Postgres's multi-modal capabilities - including JSONB parsing and high-recall HNSW vector indexing - to deliver deterministic and semantic context to LLMs. She also discusses vector quantization to speed up queries by 4x and strategies for managing agentic memory.&lt;/p&gt; &lt;i&gt;By Gwen Shapira&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>Postgres</category>
      <category>QCon AI 2025</category>
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      <category>AI, ML &amp; Data Engineering</category>
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      <pubDate>Wed, 15 Jul 2026 12:57:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/postgres-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Gwen Shapira</dc:creator>
      <dc:date>2026-07-15T12:57:00Z</dc:date>
      <dc:identifier>/presentations/postgres-ai-agents/en</dc:identifier>
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    <item>
      <title>Presentation: The Multi-Agent Approach: Building Reliable and Controllable Software Development Automation</title>
      <link>https://www.infoq.com/presentations/multi-agent-ai-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/multi-agent-ai-architecture/en/mediumimage/itamar-friedman-medium-1782818996066.jpeg"/&gt;&lt;p&gt;Itamar Friedman discusses how architects and engineering leaders can break through the AI productivity ceiling using adaptive multi-agent systems. He shares insights on moving past simple autocomplete to resilient workflows by integrating autonomous testing, intelligent code review, and robust arbitration. Learn how to govern agent communication and build a context-driven SDLC that scales.&lt;/p&gt; &lt;i&gt;By Itamar Friedman&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
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      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Wed, 08 Jul 2026 14:06:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/multi-agent-ai-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Itamar Friedman</dc:creator>
      <dc:date>2026-07-08T14:06:00Z</dc:date>
      <dc:identifier>/presentations/multi-agent-ai-architecture/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery</title>
      <link>https://www.infoq.com/presentations/reliable-ai-platforms/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/reliable-ai-platforms/en/mediumimage/aaron-erickson-medium-1782819611516.jpg"/&gt;&lt;p&gt;Aaron Erickson explains how NVIDIA designs and tests purpose-built AI agent hierarchies. For senior developers and architects, he outlines why balancing deterministic tools with agentic discovery is crucial. Discover how to leverage rare context, implement LLM-as-a-judge test pyramids, and avoid the paradox of choice to build highly reliable, production-grade AI systems at scale.&lt;/p&gt; &lt;i&gt;By Aaron Erickson&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Model</category>
      <category>QCon San Francisco 2025</category>
      <category>Reliability</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Tue, 07 Jul 2026 08:03:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/reliable-ai-platforms/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Aaron Erickson</dc:creator>
      <dc:date>2026-07-07T08:03:00Z</dc:date>
      <dc:identifier>/presentations/reliable-ai-platforms/en</dc:identifier>
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