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    <title>InfoQ - Artificial Intelligence - Presentations</title>
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    <description>InfoQ Artificial Intelligence Presentations feed</description>
    <item>
      <title>Presentation: Context Is the New Code</title>
      <link>https://www.infoq.com/presentations/context-as-code-devops-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/context-as-code-devops-agents/en/mediumimage/patrick-medium-1789632704652.jpeg"/&gt;&lt;p&gt;Patrick Debois discusses how to manage, evaluate, distribute, and observe context using proven software engineering practices. He shares how treating context like code - complete with testing, CI/CD, package managers, and security scanning - enables engineering leaders to reliably scale AI coding agents, maintain control over non-deterministic outputs, and build long-term organizational knowledge.&lt;/p&gt; &lt;i&gt;By Patrick Debois&lt;/i&gt;</description>
      <category>Testing</category>
      <category>Agents</category>
      <category>Monitoring</category>
      <category>Software Development Lifecycle</category>
      <category>QCon London 2026</category>
      <category>Transcripts</category>
      <category>Code Quality</category>
      <category>Artificial Intelligence</category>
      <category>Performance Evaluation</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>Culture &amp; Methods</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Wed, 30 Sep 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/context-as-code-devops-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Patrick Debois</dc:creator>
      <dc:date>2026-09-30T11:00:00Z</dc:date>
      <dc:identifier>/presentations/context-as-code-devops-agents/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: From Consumers to Builders: Turning 200 of our Team into Agent Creators in 2 Weeks</title>
      <link>https://www.infoq.com/presentations/building-internal-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/building-internal-ai-agents/en/mediumimage/medium-1790246283432.jpeg"/&gt;&lt;p&gt;Ben Maraney shares how Forter demystified AI agent creation for technical and non-technical staff. He discusses leveraging custom MCP servers, combining no-code and code-based platforms, sidestepping complex RAG setups, and aligning security and legal teams to accelerate internal agent adoption across R&amp;D.&lt;/p&gt; &lt;i&gt;By Ben Maraney&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Compliance</category>
      <category>Transcripts</category>
      <category>AI Security</category>
      <category>Governance</category>
      <category>Productivity</category>
      <category>QCon AI Boston 2026</category>
      <category>Model Context Protocol (MCP)</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Mon, 28 Sep 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/building-internal-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Ben Maraney</dc:creator>
      <dc:date>2026-09-28T11:00:00Z</dc:date>
      <dc:identifier>/presentations/building-internal-ai-agents/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Designing Fast, Delightful UX with LLMs for Mobile Frontends</title>
      <link>https://www.infoq.com/presentations/llm-mobile-frontend/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/llm-mobile-frontend/en/mediumimage/bala-medium-1789631604448.jpeg"/&gt;&lt;p&gt;Balakrishnan Ramdoss discusses how to architect production-grade, AI-powered conversational apps at scale. He explains how to overcome model latency, leverage server-driven UI and Backend-for-Frontend patterns to dynamically render multi-modal interfaces, optimize prompts for UI selection, and integrate low-latency, privacy-first on-device AI for mobile applications.&lt;/p&gt; &lt;i&gt;By Balakrishnan Ramdoss&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Mobile</category>
      <category>QCon San Francisco 2025</category>
      <category>Transcripts</category>
      <category>Artificial Intelligence</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Thu, 24 Sep 2026 09:24:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/llm-mobile-frontend/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Balakrishnan Ramdoss</dc:creator>
      <dc:date>2026-09-24T09:24:00Z</dc:date>
      <dc:identifier>/presentations/llm-mobile-frontend/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: The Agent Harness: Control Planes, Invariants, and Approval Boundaries for Production AI Agents</title>
      <link>https://www.infoq.com/presentations/ai-agent-harness/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-agent-harness/en/mediumimage/vino-medium-1789631870270.jpeg"/&gt;&lt;p&gt;OpenAI’s Vinoth Govindarajan discusses why production AI agents fail beyond model hallucination. Using real-world case studies like OpenClaw, he explains the key principles of reliable agent harnesses: establishing explicit state ownership, serializing concurrent state mutations, scoping execution authority, and validating actions at the user-visible edge.&lt;/p&gt; &lt;i&gt;By Vinoth Govindarajan&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Transcripts</category>
      <category>QCon AI Boston 2026</category>
      <category>OpenAI</category>
      <category>Architecture</category>
      <category>Distributed Systems</category>
      <category>AI Harness</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Mon, 21 Sep 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-agent-harness/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Vinoth Govindarajan</dc:creator>
      <dc:date>2026-09-21T11:00:00Z</dc:date>
      <dc:identifier>/presentations/ai-agent-harness/en</dc:identifier>
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