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    <title>InfoQ - Artificial Intelligence - Presentations</title>
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    <description>InfoQ Artificial Intelligence Presentations feed</description>
    <item>
      <title>Presentation: Accelerating LLM-Driven Developer Productivity at Zoox</title>
      <link>https://www.infoq.com/presentations/ai-software-development/?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-software-development/en/mediumimage/medium-1778065503665.jpg"/&gt;&lt;p&gt;Amit Navindgi discusses the systematic shift at Zoox from fragmented documentation to an AI-driven ecosystem. He explains how they built "Cortex," a secure platform integrating RAG, multi-modal LLMs, and contributor-friendly agent APIs.  He shares practical strategies for driving adoption through AI champions and hackathons, emphasizing the move from deterministic workflows to autonomous agents.&lt;/p&gt; &lt;i&gt;By Amit Navindgi&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Transcripts</category>
      <category>Software Development</category>
      <category>Artificial Intelligence</category>
      <category>QCon San Francisco 2025</category>
      <category>Culture &amp; Methods</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Thu, 14 May 2026 13:05:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-software-development/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Amit Navindgi</dc:creator>
      <dc:date>2026-05-14T13:05:00Z</dc:date>
      <dc:identifier>/presentations/ai-software-development/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: What I Learned Building Multi-Agent Systems From Scratch</title>
      <link>https://www.infoq.com/presentations/multi-agent-system-lessons/?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/multi-agent-system-lessons/en/mediumimage/medium-1778068150406.jpeg"/&gt;&lt;p&gt;Paulo Arruda discusses Shopify’s evolution in AI adoption, moving from simple chat tools to a sophisticated swarm of specialized agents. He explains the transition from massive "all-in-one" prompts to lean, narrow-focused agent microservices that slash task times from hours to minutes. He also shares a future-looking hypothesis on using filesystem-based adapters to solve context bloat.&lt;/p&gt; &lt;i&gt;By Paulo Arruda&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Wed, 13 May 2026 12:01:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/multi-agent-system-lessons/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Paulo Arruda</dc:creator>
      <dc:date>2026-05-13T12:01:00Z</dc:date>
      <dc:identifier>/presentations/multi-agent-system-lessons/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Leadership in AI-Assisted Engineering</title>
      <link>https://www.infoq.com/presentations/ai-assisted-engineering/?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-assisted-engineering/en/mediumimage/justin-medium-1777371783790.jpg"/&gt;&lt;p&gt;Justin Reock discusses the reality of AI’s impact on engineering, moving past anecdotes to hard data from DORA and DX research.  He explains the "GenAI Divide" - where 95% of pilots fail - and shares how leaders can use the SPACE and Core 4 frameworks to measure true ROI.  He explains how to balance speed with quality, reduce developer fear, and apply agentic solutions across the entire SDLC.&lt;/p&gt; &lt;i&gt;By Justin Reock&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Software Development</category>
      <category>Leadership</category>
      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Fri, 08 May 2026 12:40:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-assisted-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Justin Reock</dc:creator>
      <dc:date>2026-05-08T12:40:00Z</dc:date>
      <dc:identifier>/presentations/ai-assisted-engineering/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Engineering at AI Speed: Lessons from the First Agentically Accelerated Software Project</title>
      <link>https://www.infoq.com/presentations/engineering-ai/?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/engineering-ai/en/mediumimage/medium-1777370739830.jpg"/&gt;&lt;p&gt;Adam Wolff discusses the evolution of Claude Code, explaining how AI shifts the SDLC bottleneck from implementation to architectural decision-making. He shares three "war stories" to show why dogfooding and rapid unshipping are vital. He explains that when coding costs drop to zero, the speed of learning becomes the only competitive advantage.&lt;/p&gt; &lt;i&gt;By Adam Wolff&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Software Development</category>
      <category>Artificial Intelligence</category>
      <category>QCon San Francisco 2025</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Thu, 07 May 2026 14:07:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/engineering-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Adam Wolff</dc:creator>
      <dc:date>2026-05-07T14:07:00Z</dc:date>
      <dc:identifier>/presentations/engineering-ai/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: AI-First Software Delivery: Balancing Innovation with Proven Practices</title>
      <link>https://www.infoq.com/presentations/ai-first-practices/?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-first-practices/en/mediumimage/medium-1777371216610.jpeg"/&gt;&lt;p&gt;Wes Reisz discusses the shift toward AI-first software delivery, emphasizing that agentic workflows are not one-size-fits-all.  He explains a strategic two-by-two model based on code longevity and automated verification to decide between supervised and unsupervised agents.  He shares the RIPER-5 framework - Research, Innovate, Plan, Execute, Review - to amplify engineering discipline.&lt;/p&gt; &lt;i&gt;By Wesley Reisz&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Best Practices</category>
      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Wed, 06 May 2026 11:12:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-first-practices/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence-presentations</guid>
      <dc:creator>Wesley Reisz</dc:creator>
      <dc:date>2026-05-06T11:12:00Z</dc:date>
      <dc:identifier>/presentations/ai-first-practices/en</dc:identifier>
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