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      <title>Presentation: Week-Long Outage: Lifelong Lessons</title>
      <link>https://www.infoq.com/presentations/outage-lessons/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+San+Francisco+2025-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/outage-lessons/en/mediumimage/molly-struve-medium-1776864399990.jpeg"/&gt;&lt;p&gt;Molly Struve discusses a brutal six-day outage that nearly sank a company. She explains technical lessons like the importance of FMEAs, shadow traffic, and exercising rollback mechanisms. She shares why the human elements - widening your circle early and having a VP who acts as a defender - are what truly build psychological safety.&lt;/p&gt; &lt;i&gt;By Molly Struve&lt;/i&gt;</description>
      <category>Site Reliability Engineering</category>
      <category>Best Practices</category>
      <category>Incident Response</category>
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      <category>QCon San Francisco 2025</category>
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      <pubDate>Tue, 28 Apr 2026 10:13:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/outage-lessons/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+San+Francisco+2025-presentations</guid>
      <dc:creator>Molly Struve</dc:creator>
      <dc:date>2026-04-28T10:13:00Z</dc:date>
      <dc:identifier>/presentations/outage-lessons/en</dc:identifier>
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      <title>Presentation: How to Build an Exchange: Sub Millisecond Response Times and 24/7 Uptimes in the Cloud</title>
      <link>https://www.infoq.com/presentations/exchange-systems-cloud/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+San+Francisco+2025-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/exchange-systems-cloud/en/mediumimage/frank-yu-medium-1776173818222.jpeg"/&gt;&lt;p&gt;Frank Yu shares Coinbase’s engineering philosophy for building resilient, fair, and fast financial exchanges. He explains the power of a single-threaded architecture combined with the Raft consensus algorithm to maintain 24/7 availability.  He discusses how determinism enables zero-downtime rolling deployments and the ability to replay production logs for perfect bug reproduction.&lt;/p&gt; &lt;i&gt;By Frank Yu&lt;/i&gt;</description>
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      <category>Performance &amp; Scalability</category>
      <category>Low Latency</category>
      <category>QCon San Francisco 2025</category>
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      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Thu, 23 Apr 2026 09:29:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/exchange-systems-cloud/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+San+Francisco+2025-presentations</guid>
      <dc:creator>Frank Yu</dc:creator>
      <dc:date>2026-04-23T09:29:00Z</dc:date>
      <dc:identifier>/presentations/exchange-systems-cloud/en</dc:identifier>
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      <title>Presentation: Dynamic Moments: Weaving LLMs into Deep Personalization at DoorDash</title>
      <link>https://www.infoq.com/presentations/llm-personalization/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+San+Francisco+2025-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/llm-personalization/en/mediumimage/Sudeep-Das-Pradeep-Muthukrishnan-medium-1776173227456.jpg"/&gt;&lt;p&gt;Sudeep Das and Pradeep Muthukrishnan explain the shift from static merchandising to dynamic, moment-aware personalization at DoorDash. They share how LLMs generate natural-language "consumer profiles" and content blueprints, while traditional deep learning handles last-mile ranking. This hybrid approach allows the platform to adapt to short-lived user intent and massive catalog abundance.&lt;/p&gt; &lt;i&gt;By Sudeep Das, Pradeep Muthukrishnan&lt;/i&gt;</description>
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      <category>Use Cases</category>
      <category>QCon San Francisco 2025</category>
      <category>Large language models</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Tue, 21 Apr 2026 10:35:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/llm-personalization/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+San+Francisco+2025-presentations</guid>
      <dc:creator>Sudeep Das, Pradeep Muthukrishnan</dc:creator>
      <dc:date>2026-04-21T10:35:00Z</dc:date>
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