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    <title>InfoQ - Transcripts - Presentations</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Transcripts Presentations feed</description>
    <item>
      <title>Presentation: Keeping ChatGPT Fast as AI Development Accelerates</title>
      <link>https://www.infoq.com/presentations/openai-performance-engineering-agentic-coding/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/openai-performance-engineering-agentic-coding/en/mediumimage/MartinSpier-medium-1785314358072.jpeg"/&gt;&lt;p&gt;Martin Spier explains how agentic workflows dramatically increase code change volume at OpenAI. He discusses the hidden systemic performance costs of rapid shipping beyond GPUs, and shares how deploying always-on AI agents automates profiling, regression detection, and continuous optimization to maintain product speed and scalability at massive global scale.&lt;/p&gt; &lt;i&gt;By Martin Spier&lt;/i&gt;</description>
      <category>Agents</category>
      <category>QCon AI Boston 2026</category>
      <category>Workflow / BPM</category>
      <category>ChatGPT</category>
      <category>OpenAI</category>
      <category>Performance &amp; Scalability</category>
      <category>Observability</category>
      <category>Transcripts</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Sat, 08 Aug 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/openai-performance-engineering-agentic-coding/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</guid>
      <dc:creator>Martin Spier</dc:creator>
      <dc:date>2026-08-08T09:00:00Z</dc:date>
      <dc:identifier>/presentations/openai-performance-engineering-agentic-coding/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Rewriting All of Spotify's Code Base, All the Time</title>
      <link>https://www.infoq.com/presentations/spotify-ai-codebase-migration-agent/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/spotify-ai-codebase-migration-agent/en/mediumimage/medium-1784809804876.jpg"/&gt;&lt;p&gt;Jo Kelly-Fenton and Aleksandar Mitic explain how Spotify created "Honk," an AI coding agent, to handle complex fleet-wide codebase migrations. They share key architectural insights on decoupling CI verification runtimes from AI agents, dealing with automated pull request bottlenecks, and driving aggressive standardization across thousands of engineering repositories.&lt;/p&gt; &lt;i&gt;By Jo Kelly-Fenton, Aleksandar Mitic&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Continuous Delivery</category>
      <category>Standardization</category>
      <category>Continuous Improvement</category>
      <category>Large language models</category>
      <category>migration</category>
      <category>AI Coding</category>
      <category>QCon London 2026</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Fri, 07 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/spotify-ai-codebase-migration-agent/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</guid>
      <dc:creator>Jo Kelly-Fenton, Aleksandar Mitic</dc:creator>
      <dc:date>2026-08-07T11:00:00Z</dc:date>
      <dc:identifier>/presentations/spotify-ai-codebase-migration-agent/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: From ms to µs: OSS Valkey Architecture Patterns for Modern AI</title>
      <link>https://www.infoq.com/presentations/valkey-architecture-patterns/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/valkey-architecture-patterns/en/mediumimage/DumanshuGoyal-medium-1786082640468.jpg"/&gt;&lt;p&gt;Dumanshu Goyal discusses optimizing data layers for low-latency workloads like AI feature stores. Drawing lessons from NASA's Space Shuttle, he explains how proxy architectures introduce hidden CPU costs, elevated tail latencies, and blast-radius risks. He demonstrates how direct-access Valkey architectures achieve microsecond latency, improve resilience, and slash infrastructure costs.&lt;/p&gt; &lt;i&gt;By Dumanshu Goyal&lt;/i&gt;</description>
      <category>Patterns</category>
      <category>Sharding</category>
      <category>QCon San Francisco 2025</category>
      <category>Performance &amp; Scalability</category>
      <category>Platform Engineering</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Thu, 06 Aug 2026 09:34:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/valkey-architecture-patterns/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</guid>
      <dc:creator>Dumanshu Goyal</dc:creator>
      <dc:date>2026-08-06T09:34:00Z</dc:date>
      <dc:identifier>/presentations/valkey-architecture-patterns/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Automatically Retrofitting JIT Compilers</title>
      <link>https://www.infoq.com/presentations/yk-meta-tracing-jit-compiler/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/yk-meta-tracing-jit-compiler/en/mediumimage/medium-1784107493357.jpeg"/&gt;&lt;p&gt;Laurence Tratt discusses yk, an open-source meta-tracing JIT compiler framework. He shares how to automatically speed up C-based language interpreters like Lua and MicroPython with minimal, non-invasive code changes. He explains the inner workings of tracing loops, optimizing compiled traces using developer hints, and managing complex deoptimization back to the interpreter.&lt;/p&gt; &lt;i&gt;By Laurence Tratt&lt;/i&gt;</description>
      <category>LLVM</category>
      <category>Virtual Machines</category>
      <category>Java</category>
      <category>Lua</category>
      <category>JIT</category>
      <category>QCon London 2026</category>
      <category>Performance</category>
      <category>Transcripts</category>
      <category>Python</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Wed, 05 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/yk-meta-tracing-jit-compiler/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</guid>
      <dc:creator>Laurence Tratt</dc:creator>
      <dc:date>2026-08-05T11:00:00Z</dc:date>
      <dc:identifier>/presentations/yk-meta-tracing-jit-compiler/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: The Five Stages of AI Maturity in Engineering Organizations - Where and Why Teams Get Stuck</title>
      <link>https://www.infoq.com/presentations/ai-sdlc-maturity-framework-bottlenecks/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-sdlc-maturity-framework-bottlenecks/en/mediumimage/LizzieMatusov-medium-1785314207748.jpeg"/&gt;&lt;p&gt;Quotient CEO Lizzie Matusov explains why soaring AI spend often fails to improve software delivery. She presents a research-backed AI maturity framework designed to help engineering leaders move beyond vanity metrics like token usage, align organizational AI adoption, and address critical bottlenecks across the software development life cycle to deliver measurable business outcomes.&lt;/p&gt; &lt;i&gt;By Lizzie Matusov&lt;/i&gt;</description>
      <category>QCon AI Boston 2026</category>
      <category>Productivity</category>
      <category>Metrics</category>
      <category>Software Engineering</category>
      <category>Software Development Lifecycle</category>
      <category>Frameworks</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Tue, 04 Aug 2026 16:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-sdlc-maturity-framework-bottlenecks/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</guid>
      <dc:creator>Lizzie Matusov</dc:creator>
      <dc:date>2026-08-04T16:00:00Z</dc:date>
      <dc:identifier>/presentations/ai-sdlc-maturity-framework-bottlenecks/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Microservices Platforms: When Team Topologies Meets Microservices Patterns</title>
      <link>https://www.infoq.com/presentations/microservices-platform-team-topology/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/microservices-platform-team-topology/en/mediumimage/ChrisRichardson-medium-1785312644032.jpeg"/&gt;&lt;p&gt;Chris Richardson discusses leveraging Team Topologies and internal platforms to accelerate microservices delivery. He explains six key platform patterns - from security and observability to build and deployment - and shares strategies for minimizing cognitive load on stream-aligned teams while avoiding common platform engineering pitfalls.&lt;/p&gt; &lt;i&gt;By Chris Richardson&lt;/i&gt;</description>
      <category>QCon San Francisco 2025</category>
      <category>Microservices</category>
      <category>Platforms</category>
      <category>Transcripts</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Tue, 04 Aug 2026 11:45:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/microservices-platform-team-topology/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</guid>
      <dc:creator>Chris Richardson</dc:creator>
      <dc:date>2026-08-04T11:45:00Z</dc:date>
      <dc:identifier>/presentations/microservices-platform-team-topology/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Architecting AI Systems for the Messy Reality of Enterprises: Why Agentic Compute is the Missing Layer</title>
      <link>https://www.infoq.com/presentations/agentic-compute/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/agentic-compute/en/mediumimage/ArunJoseph-medium-1785311900135.jpeg"/&gt;&lt;p&gt;Arun Joseph shares real-world insights on scaling enterprise agentic platforms like Deutsche Telekom’s LMOS. He discusses bridging organizational fault lines, replacing tool sprawl with core platform abstractions, and moving beyond basic chatbots to operational intelligence systems through ephemeral agents and an Agent Definition Language (ADL).&lt;/p&gt; &lt;i&gt;By Arun Joseph&lt;/i&gt;</description>
      <category>Agents</category>
      <category>AI Architecture</category>
      <category>InfoQ Dev Summit Munich 2025</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Mon, 03 Aug 2026 08:08:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/agentic-compute/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</guid>
      <dc:creator>Arun Joseph</dc:creator>
      <dc:date>2026-08-03T08:08:00Z</dc:date>
      <dc:identifier>/presentations/agentic-compute/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: The Free-Lunch Guide to Idea Circularity</title>
      <link>https://www.infoq.com/presentations/tech-hype-cycles-architectural-tradeoffs/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/tech-hype-cycles-architectural-tradeoffs/en/mediumimage/holly-cummins-medium-1783578321356.jpeg"/&gt;&lt;p&gt;Holly Cummins discusses why "nothing is new under the sun" in tech. She maps historical architectural tradeoffs to modern cloud, microservices, and AI hype cycles. She connects financial debt (post-ZIRP) and technical debt to epistemic and sleep debt, showing engineering leaders how to navigate shifts in assumptions, embrace sustainability, and revive proven engineering disciplines.&lt;/p&gt; &lt;i&gt;By Holly Cummins&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Cloud-Native</category>
      <category>Quarkus</category>
      <category>Technical Debt</category>
      <category>QCon London 2026</category>
      <category>Hype</category>
      <category>Transcripts</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>Culture &amp; Methods</category>
      <category>presentation</category>
      <pubDate>Fri, 31 Jul 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/tech-hype-cycles-architectural-tradeoffs/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</guid>
      <dc:creator>Holly Cummins</dc:creator>
      <dc:date>2026-07-31T11:00:00Z</dc:date>
      <dc:identifier>/presentations/tech-hype-cycles-architectural-tradeoffs/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Parting the Clouds: the Rise of Disaggregated Systems</title>
      <link>https://www.infoq.com/presentations/disaggregation-industrial-systems/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/disaggregation-industrial-systems/en/mediumimage/murat-demirbas-medium-1784809202010.jpg"/&gt;&lt;p&gt;Murat Demirbas discusses the shift toward disaggregated cloud database architectures driven by cloud economics. He explains how decoupling compute from storage enables elastic scaling, cost efficiency, and fault isolation. He shares how classical Paxos roles foreshadowed disaggregation, while analyzing network tradeoffs, shared-memory evolution, and self-assembling database designs.&lt;/p&gt; &lt;i&gt;By Murat Demirbas&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>Database</category>
      <category>QCon San Francisco 2025</category>
      <category>Distributed Systems</category>
      <category>Transcripts</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Thu, 30 Jul 2026 13:50:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/disaggregation-industrial-systems/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</guid>
      <dc:creator>Murat Demirbas</dc:creator>
      <dc:date>2026-07-30T13:50:00Z</dc:date>
      <dc:identifier>/presentations/disaggregation-industrial-systems/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Getting Rid of LeetCode Interviews in the World of AI</title>
      <link>https://www.infoq.com/presentations/ai-lead-interview/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-lead-interview/en/mediumimage/daniel-medium-1784808762941.jpeg"/&gt;&lt;p&gt;Daniel Doubrovkine explains why traditional LeetCode whiteboard interviews fail to evaluate senior engineering talent. He discusses his own experience bombing basic algorithm tests despite decades of leadership, and shares actionable frameworks for redefining the interview loop. Discover how evaluating human judgment, system design, and hands-on AI collaboration yields far better hiring signals.&lt;/p&gt; &lt;i&gt;By Daniel Doubrovkine&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>interviewing</category>
      <category>QCon AI 2025</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Culture &amp; Methods</category>
      <category>presentation</category>
      <pubDate>Wed, 29 Jul 2026 10:25:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-lead-interview/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Transcripts-presentations</guid>
      <dc:creator>Daniel Doubrovkine</dc:creator>
      <dc:date>2026-07-29T10:25:00Z</dc:date>
      <dc:identifier>/presentations/ai-lead-interview/en</dc:identifier>
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