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      <title>Presentation: From OTEL to SLMs: Distilling Frontier Model Behaviour from Production Telemetry</title>
      <link>https://www.infoq.com/presentations/otel-slm-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Languages-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/otel-slm-ai/en/mediumimage/benomahony-medium-1783500827260.jpeg"/&gt;&lt;p&gt;Ben O'Mahony discusses building custom AI-powered Language Server Protocols (LSPs) that go beyond standard rule-based checkers. He explains how to instrument AI agents natively with OpenTelemetry to track concrete user actions (accepting, dismissing, or regenerating code fixes) as implicit labels, creating a continuous data flywheel to distill frontier capabilities into cheaper, local SLMs.&lt;/p&gt; &lt;i&gt;By Ben O'Mahony&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Telemetry</category>
      <category>QCon AI 2025</category>
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      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Fri, 17 Jul 2026 13:17:00 GMT</pubDate>
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      <dc:creator>Ben O'Mahony</dc:creator>
      <dc:date>2026-07-17T13:17:00Z</dc:date>
      <dc:identifier>/presentations/otel-slm-ai/en</dc:identifier>
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