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      <title>Presentation: Architecting a Centralized Platform for Data Deletion at Netflix</title>
      <link>https://www.infoq.com/presentations/architecting-deletion-system/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Reliability-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/architecting-deletion-system/en/mediumimage/medium-1779869686290.jpg"/&gt;&lt;p&gt;The speakers discuss the architectural challenges of executing safe data deletion across distributed datastores. Balancing durability, availability &amp;  correctness, they explain how to orchestrate multi-system deletion propagation without impacting live traffic. They share lessons on controlling tombstone accumulation, building continuous audit loops, and gaining trust with a centralized platform.&lt;/p&gt; &lt;i&gt;By Vidhya Arvind, Shawn Liu&lt;/i&gt;</description>
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      <category>Platform Engineering</category>
      <category>QCon San Francisco 2025</category>
      <category>Performance &amp; Scalability</category>
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      <category>Reliability</category>
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      <pubDate>Thu, 04 Jun 2026 10:26:00 GMT</pubDate>
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      <dc:creator>Vidhya Arvind, Shawn Liu</dc:creator>
      <dc:date>2026-06-04T10:26:00Z</dc:date>
      <dc:identifier>/presentations/architecting-deletion-system/en</dc:identifier>
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      <title>Presentation: Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery</title>
      <link>https://www.infoq.com/presentations/ai-platforms-reliability/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Reliability-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-platforms-reliability/en/mediumimage/medium-1779182751443.jpg"/&gt;&lt;p&gt;Aaron Erickson discusses the evolution of AI workflows, shifting from "vibe checking" to building reliable, multi-agent frameworks. He explains how to combine deterministic software guardrails with agentic discovery, optimize agent hierarchies, leverage time-series foundation models, and implement rigorous evaluation pyramids to ensure architecture scales effectively in production.&lt;/p&gt; &lt;i&gt;By Aaron Erickson&lt;/i&gt;</description>
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      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
      <category>Reliability</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Wed, 27 May 2026 09:04:00 GMT</pubDate>
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      <dc:creator>Aaron Erickson</dc:creator>
      <dc:date>2026-05-27T09:04:00Z</dc:date>
      <dc:identifier>/presentations/ai-platforms-reliability/en</dc:identifier>
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