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      <title>Presentation: Can Claude Fix Itself? Using LLMs for Incident Response</title>
      <link>https://www.infoq.com/presentations/claude-sre-incidents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Site+Reliability+Engineering-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/claude-sre-incidents/en/mediumimage/alex-palcuie-medium-1786539336984.jpg"/&gt;&lt;p&gt;Anthropic reliability engineer Alex Palcuie shares practical lessons on using LLMs for real-world incident response. He explains where AI acts as a superhuman for observing logs and traces, why it still struggles with causation versus correlation during root-cause analysis, and how engineering leaders can integrate AI into on-call workflows without eroding human expertise.&lt;/p&gt; &lt;i&gt;By Alex Palcuie&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Site Reliability Engineering</category>
      <category>Large language models</category>
      <category>On-call</category>
      <category>Automation</category>
      <category>Claude</category>
      <category>QCon London 2026</category>
      <category>Incident Response</category>
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      <pubDate>Wed, 26 Aug 2026 11:00:00 GMT</pubDate>
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      <dc:creator>Alex Palcuie</dc:creator>
      <dc:date>2026-08-26T11:00:00Z</dc:date>
      <dc:identifier>/presentations/claude-sre-incidents/en</dc:identifier>
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