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      <title>Presentation: Multi-Agent Patterns from Spotify’s AI Powered Advertising Platform</title>
      <link>https://www.infoq.com/presentations/spotify-multi-agent-ai-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/spotify-multi-agent-ai-architecture/en/mediumimage/pratik-rasam-medium-1790847111671.jpeg"/&gt;&lt;p&gt;Pratik Rasam discusses how Spotify Ads Manager runs production-grade multi-agent systems at scale using Google ADK Java. He shares key architectural patterns, domain ownership models, deterministic guardrails, and tracing-based evaluation strategies, detailing hard-learned lessons on drawing agent boundaries, optimizing tool schemas, and managing costs while avoiding monolithic agent pitfalls.&lt;/p&gt; &lt;i&gt;By Pratik Rasam&lt;/i&gt;</description>
      <category>Patterns</category>
      <category>Performance Evaluation</category>
      <category>Prompt Engineering</category>
      <category>Agents</category>
      <category>Generative AI</category>
      <category>Transcripts</category>
      <category>AI Architecture</category>
      <category>QCon AI Boston 2026</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
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      <pubDate>Thu, 08 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/spotify-multi-agent-ai-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents-presentations</guid>
      <dc:creator>Pratik Rasam</dc:creator>
      <dc:date>2026-10-08T11:00:00Z</dc:date>
      <dc:identifier>/presentations/spotify-multi-agent-ai-architecture/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Building Reusable Evaluation Frameworks for Agentic AI Products</title>
      <link>https://www.infoq.com/presentations/elastic-ai-agent-evaluations/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/elastic-ai-agent-evaluations/en/mediumimage/susan-chang-medium-1790846586191.jpeg"/&gt;&lt;p&gt;Susan Chang explains how Elastic transitioned from siloed, ad-hoc AI agent evaluations to a unified, production-grade framework. She discusses balancing LLM-as-a-judge with deterministic rules, bridging Python data science evals with TypeScript production code, and implementing deep tracing to catch regressions across complex RAG and cybersecurity workloads while preserving domain context.&lt;/p&gt; &lt;i&gt;By Susan Chang&lt;/i&gt;</description>
      <category>MLOps</category>
      <category>Performance Evaluation</category>
      <category>ElasticSearch</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Transcripts</category>
      <category>Retrieval-Augmented Generation</category>
      <category>Observability</category>
      <category>QCon AI Boston 2026</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Mon, 05 Oct 2026 11:19:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/elastic-ai-agent-evaluations/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents-presentations</guid>
      <dc:creator>Susan Chang</dc:creator>
      <dc:date>2026-10-05T11:19:00Z</dc:date>
      <dc:identifier>/presentations/elastic-ai-agent-evaluations/en</dc:identifier>
    </item>
    <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=Agents-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>Monitoring</category>
      <category>Performance Evaluation</category>
      <category>Testing</category>
      <category>Software Development Lifecycle</category>
      <category>Agents</category>
      <category>Transcripts</category>
      <category>QCon London 2026</category>
      <category>Code Quality</category>
      <category>Artificial Intelligence</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Culture &amp; Methods</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=Agents-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 Two 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=Agents-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>Model Context Protocol (MCP)</category>
      <category>Governance</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Transcripts</category>
      <category>Compliance</category>
      <category>AI Security</category>
      <category>Productivity</category>
      <category>QCon AI Boston 2026</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=Agents-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>
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