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      <title>Presentation: Architecting AI Systems for the Messy Reality of Enterprises: Why Agentic Compute is the Missing Layer</title>
      <link>https://www.infoq.com/presentations/agentic-compute/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/agentic-compute/en/mediumimage/ArunJoseph-medium-1785311900135.jpeg"/&gt;&lt;p&gt;Arun Joseph shares real-world insights on scaling enterprise agentic platforms like Deutsche Telekom’s LMOS. He discusses bridging organizational fault lines, replacing tool sprawl with core platform abstractions, and moving beyond basic chatbots to operational intelligence systems through ephemeral agents and an Agent Definition Language (ADL).&lt;/p&gt; &lt;i&gt;By Arun Joseph&lt;/i&gt;</description>
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      <category>AI Architecture</category>
      <category>InfoQ Dev Summit Munich 2025</category>
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      <pubDate>Mon, 03 Aug 2026 08:08:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/agentic-compute/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-presentations</guid>
      <dc:creator>Arun Joseph</dc:creator>
      <dc:date>2026-08-03T08:08:00Z</dc:date>
      <dc:identifier>/presentations/agentic-compute/en</dc:identifier>
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      <title>Presentation: Getting Rid of LeetCode Interviews in the World of AI</title>
      <link>https://www.infoq.com/presentations/ai-lead-interview/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-lead-interview/en/mediumimage/daniel-medium-1784808762941.jpeg"/&gt;&lt;p&gt;Daniel Doubrovkine explains why traditional LeetCode whiteboard interviews fail to evaluate senior engineering talent. He discusses his own experience bombing basic algorithm tests despite decades of leadership, and shares actionable frameworks for redefining the interview loop. Discover how evaluating human judgment, system design, and hands-on AI collaboration yields far better hiring signals.&lt;/p&gt; &lt;i&gt;By Daniel Doubrovkine&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>interviewing</category>
      <category>QCon AI 2025</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
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      <pubDate>Wed, 29 Jul 2026 10:25:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-lead-interview/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-presentations</guid>
      <dc:creator>Daniel Doubrovkine</dc:creator>
      <dc:date>2026-07-29T10:25:00Z</dc:date>
      <dc:identifier>/presentations/ai-lead-interview/en</dc:identifier>
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      <title>Presentation: The Future of Engineering: Mindsets That Matter When Code Isn’t Enough</title>
      <link>https://www.infoq.com/presentations/ai-future-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-future-engineering/en/mediumimage/ben-greene-mediumm-1784809015374.jpeg"/&gt;&lt;p&gt;Ben Greene discusses how software engineers can adapt and thrive in an era of rapid AI code automation. Drawing on his startup experience, he explains key mindsets like starting simple, maintaining code comprehension, attacking hard problems first, and focusing on customer impact. He shares why human empathy, agency, and practical problem-solving remain irreplaceable when code is automated.&lt;/p&gt; &lt;i&gt;By Ben Greene&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Software Engineering</category>
      <category>QCon San Francisco 2025</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Tue, 28 Jul 2026 11:10:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-future-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-presentations</guid>
      <dc:creator>Ben Greene</dc:creator>
      <dc:date>2026-07-28T11:10:00Z</dc:date>
      <dc:identifier>/presentations/ai-future-engineering/en</dc:identifier>
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    <item>
      <title>Presentation: Autonomous Data Products for the Autonomous Era: Rethinking Data Architecture for GenAI</title>
      <link>https://www.infoq.com/presentations/ai-framework-data-infrastructure/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-framework-data-infrastructure/en/mediumimage/medium-1784107102579.jpeg"/&gt;&lt;p&gt;Jörg Schad explains how to tame the complex "data management hairball" to build scalable, safe architectures for AI. He shares how autonomous data products act like containers for data, encapsulating pipelines, schemas, and metadata. Discover how progressive tool discovery via protocols like MCP limits context rot, enforces governance policies, and ensures reliable, multi-modal access.&lt;/p&gt; &lt;i&gt;By Jörg Schad&lt;/i&gt;</description>
      <category>Data</category>
      <category>Infrastructure</category>
      <category>QCon AI 2025</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Fri, 24 Jul 2026 13:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-framework-data-infrastructure/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-presentations</guid>
      <dc:creator>Jörg Schad</dc:creator>
      <dc:date>2026-07-24T13:30:00Z</dc:date>
      <dc:identifier>/presentations/ai-framework-data-infrastructure/en</dc:identifier>
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