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      <title>Presentation: Teaching Engineers, Trusting AI: How Education Enabled Autonomous Code Review</title>
      <link>https://www.infoq.com/presentations/duolingo-ai-literacy-code-review/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Automation-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/duolingo-ai-literacy-code-review/en/mediumimage/sarah-deitke-medium-1788338781338.jpeg"/&gt;&lt;p&gt;Sarah Deitke discusses how Duolingo drives cultural AI adoption beyond tooling access. She explains their internal AI literacy workshops and observability dashboards, then shares a case study on redesigning code review using an automated PR risk-assessment bot. Deitke demonstrates how pairing targeted developer education with safe AI guardrails speeds up delivery without increasing defect rates.&lt;/p&gt; &lt;i&gt;By Sarah Deitke&lt;/i&gt;</description>
      <category>Developer Experience</category>
      <category>Culture</category>
      <category>QCon London 2026</category>
      <category>Adoption</category>
      <category>Transcripts</category>
      <category>Artificial Intelligence</category>
      <category>Metrics</category>
      <category>Automation</category>
      <category>Code Reviews</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Culture &amp; Methods</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Wed, 16 Sep 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/duolingo-ai-literacy-code-review/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Automation-presentations</guid>
      <dc:creator>Sarah Deitke</dc:creator>
      <dc:date>2026-09-16T11:00:00Z</dc:date>
      <dc:identifier>/presentations/duolingo-ai-literacy-code-review/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: From AI Agent Demo to Production: Automated Testing and Evaluation</title>
      <link>https://www.infoq.com/presentations/ai-agent-testing-evaluation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Automation-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-agent-testing-evaluation/en/mediumimage/zhou-yu-medium-1787813732120.jpeg"/&gt;&lt;p&gt;Zhou Yu discusses why AI agents stall in demo phase and shares how simulation-driven testing solves compliance and reliability bottlenecks. Learn how Columbia and Arklex AI use synthetic user personas, trajectory entropy, and automated CI/CD pipelines to evaluate multi-turn agents, catch edge cases before deployment, and scale self-learning workflows in production.&lt;/p&gt; &lt;i&gt;By Zhou Yu&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Data</category>
      <category>Automated testing</category>
      <category>Testing</category>
      <category>Agents</category>
      <category>Quality</category>
      <category>Reliability</category>
      <category>Performance</category>
      <category>Transcripts</category>
      <category>Simulation</category>
      <category>QCon AI Boston 2026</category>
      <category>Performance Evaluation</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Mon, 07 Sep 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-agent-testing-evaluation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Automation-presentations</guid>
      <dc:creator>Zhou Yu</dc:creator>
      <dc:date>2026-09-07T11:00:00Z</dc:date>
      <dc:identifier>/presentations/ai-agent-testing-evaluation/en</dc:identifier>
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