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    <title>InfoQ - QCon Software Development Conference</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ QCon Software Development Conference feed</description>
    <item>
      <title>How Code in the Age of Artificial Intelligence Becomes Write-Only and Disposable</title>
      <link>https://www.infoq.com/news/2026/08/code-AI-write-only-disposable/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/code-AI-write-only-disposable/en/headerimage/header-1786968412263.jpg"/&gt;&lt;p&gt;Artificial intelligence (AI) makes all code write-only,. It’s too dense to read, and tests define the behaviour and become the documentation. Code is also disposable; it becomes easier to rewrite than to debug. Humans can't review AI-generated code at scale. Intent decouples from implementation; developers should focus on creativity.&lt;/p&gt; &lt;i&gt;By Ben Linders&lt;/i&gt;</description>
      <category>QCon London 2026</category>
      <category>Culture</category>
      <category>Artificial Intelligence</category>
      <category>Code Quality</category>
      <category>Code Reviews</category>
      <category>QCon Software Development Conference</category>
      <category>Code Generation</category>
      <category>Observability</category>
      <category>Development</category>
      <category>Culture &amp; Methods</category>
      <category>news</category>
      <pubDate>Thu, 20 Aug 2026 11:25:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/code-AI-write-only-disposable/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Ben Linders</dc:creator>
      <dc:date>2026-08-20T11:25:00Z</dc:date>
      <dc:identifier>/news/2026/08/code-AI-write-only-disposable/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Understanding Progressive Collapse: How To Avoid A Cascading Failure</title>
      <link>https://www.infoq.com/presentations/progressive-collapse-system-resilience/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/presentations/progressive-collapse-system-resilience/en/mediumimage/sam-newman-medium-1785845419904.jpg"/&gt;&lt;p&gt;Sam Newman discusses the concept of progressive collapse in civil engineering and how it applies to distributed systems. Using real-world examples - from the 1968 Ronan Point tower failure to AWS outages - he shares crucial resilience engineering strategies for software leaders. Learn how to strengthen components, isolate failures, and reduce interconnections to prevent catastrophic cascades.&lt;/p&gt; &lt;i&gt;By Sam Newman&lt;/i&gt;</description>
      <category>Distributed Systems</category>
      <category>QCon London 2026</category>
      <category>Microservices</category>
      <category>Cloud Architecture</category>
      <category>Resilience</category>
      <category>Failure</category>
      <category>Fault Tolerance</category>
      <category>Transcripts</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Wed, 19 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/progressive-collapse-system-resilience/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Sam Newman</dc:creator>
      <dc:date>2026-08-19T11:00:00Z</dc:date>
      <dc:identifier>/presentations/progressive-collapse-system-resilience/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: From Fab To Token - The State Of The Market</title>
      <link>https://www.infoq.com/presentations/ai-hardware-tokenomics/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-hardware-tokenomics/en/mediumimage/jordan-nanos-medium-1786538855211.jpg"/&gt;&lt;p&gt;Jordan Nanos discusses how semiconductor constraints, data center expansion, and networking bottlenecks impact AI software architecture. Drawing from SemiAnalysis research, he shares insights on benchmark performance, GPU scaling, and tokenomics from chip fab to model inference.&lt;/p&gt; &lt;i&gt;By Jordan Nanos&lt;/i&gt;</description>
      <category>Infrastructure</category>
      <category>GPU</category>
      <category>Hardware</category>
      <category>Benchmark</category>
      <category>Large language models</category>
      <category>Model Inference</category>
      <category>QCon AI Boston 2026</category>
      <category>AI Architecture</category>
      <category>AI Security</category>
      <category>Data Analytics</category>
      <category>Performance</category>
      <category>Transcripts</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Tue, 18 Aug 2026 16:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-hardware-tokenomics/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Jordan Nanos</dc:creator>
      <dc:date>2026-08-18T16:00:00Z</dc:date>
      <dc:identifier>/presentations/ai-hardware-tokenomics/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Turning Outward: Growing From Code to Influence</title>
      <link>https://www.infoq.com/presentations/working-across-teams/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/presentations/working-across-teams/en/mediumimage/BradGrantham-medium-1786538733504.jpg"/&gt;&lt;p&gt;Brad Grantham discusses how software engineers and architects can transition from individual contributors to influential technical leaders. Brad shares actionable insights on expanding skills into business and legal domains, adapting communication styles for non-technical stakeholders, moving past ego to empower teams, and navigating complex organizational dynamics to maximize engineering impact.&lt;/p&gt; &lt;i&gt;By Brad Grantham&lt;/i&gt;</description>
      <category>Teamwork</category>
      <category>Collaboration</category>
      <category>QCon San Francisco 2025</category>
      <category>Transcripts</category>
      <category>Culture &amp; Methods</category>
      <category>presentation</category>
      <pubDate>Tue, 18 Aug 2026 12:31:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/working-across-teams/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Brad Grantham</dc:creator>
      <dc:date>2026-08-18T12:31:00Z</dc:date>
      <dc:identifier>/presentations/working-across-teams/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: From Thousands to One: Building LLM-Powered Selection Systems</title>
      <link>https://www.infoq.com/presentations/architecture-patterns-llm/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/presentations/architecture-patterns-llm/en/mediumimage/JendrikJordening-medium-1786535626643.jpeg"/&gt;&lt;p&gt;Jendrik Jördening shares practical engineering strategies for integrating LLMs into production pipelines. He discusses overcoming non-determinism, restricting schemas, separating semantic text extraction from deterministic code, and validating choices using discriminator models. Learn how to structure LLMs with an MVC approach to ensure database integrity, observability, and system reliability.&lt;/p&gt; &lt;i&gt;By Jendrik Jördening&lt;/i&gt;</description>
      <category>InfoQ Dev Summit Munich 2025</category>
      <category>Large language models</category>
      <category>AI Architecture</category>
      <category>Patterns</category>
      <category>Transcripts</category>
      <category>Architecture &amp; Design</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Mon, 17 Aug 2026 09:06:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/architecture-patterns-llm/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Jendrik Jördening</dc:creator>
      <dc:date>2026-08-17T09:06:00Z</dc:date>
      <dc:identifier>/presentations/architecture-patterns-llm/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: From Models to Agents: Building Context-Aware Consumer AI at Scale at DoorDash</title>
      <link>https://www.infoq.com/presentations/ai-agentic-recommendations-semantic-ids/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-agentic-recommendations-semantic-ids/en/mediumimage/sudeep-das-medium-1785845550765.jpeg"/&gt;&lt;p&gt;Sudeep Das shares how DoorDash shifts from legacy one-shot predictions to an agentic recommendation platform. He discusses leveraging language-native consumer memory, RQ-VAE semantic IDs for catalog representation, and grounded search to dramatically boost relevance and conversion metrics.&lt;/p&gt; &lt;i&gt;By Sudeep Das&lt;/i&gt;</description>
      <category>Generative AI</category>
      <category>E-Commerce</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>QCon AI Boston 2026</category>
      <category>AI Architecture</category>
      <category>Rankings</category>
      <category>Agentic AI Architecture</category>
      <category>vector databases</category>
      <category>Search</category>
      <category>Transcripts</category>
      <category>Machine Learning</category>
      <category>Architecture &amp; Design</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Sat, 15 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-agentic-recommendations-semantic-ids/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Sudeep Das</dc:creator>
      <dc:date>2026-08-15T11:00:00Z</dc:date>
      <dc:identifier>/presentations/ai-agentic-recommendations-semantic-ids/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: The Right 300 Tokens Beat 100k Noisy Ones: The Architecture of Context Engineering</title>
      <link>https://www.infoq.com/presentations/architecture-context-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/presentations/architecture-context-engineering/en/mediumimage/partick-baruch-medium-1786008501700.jpg"/&gt;&lt;p&gt;Baruch Sadogursky and Patrick Debois discuss why coding agents fail due to bloated context windows and stuffed prompts. They explain practical context engineering fixes, including lazy-loaded skills, versioned context artifacts, externalized memory banks, and LLM-as-a-judge evals. Software architects &amp; engineering leaders will learn how to turn raw markdown files into reliable agentic workflows.&lt;/p&gt; &lt;i&gt;By Patrick Debois, Baruch Sadogursky&lt;/i&gt;</description>
      <category>QCon London 2026</category>
      <category>Claude</category>
      <category>AI Coding</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>Model Context Protocol (MCP)</category>
      <category>AI Development</category>
      <category>Prompt Engineering</category>
      <category>Transcripts</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Fri, 14 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/architecture-context-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Patrick Debois, Baruch Sadogursky</dc:creator>
      <dc:date>2026-08-14T11:00:00Z</dc:date>
      <dc:identifier>/presentations/architecture-context-engineering/en</dc:identifier>
    </item>
    <item>
      <title>How Artificial Intelligence Disrupts Engineering Progression</title>
      <link>https://www.infoq.com/news/2026/08/AI-disrupts-engineering-progress/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/AI-disrupts-engineering-progress/en/headerimage/header-1786359459457.jpg"/&gt;&lt;p&gt;AI is disrupting career progression by eliminating the learning opportunities at each rung while simultaneously enabling people to perform above their experience level, Alasdair Allan explained in his talk Engineering Progression When AI Ate the Middle at QCon London. Fewer junior developers join the industry, and AI slows hiring at the entry level.&lt;/p&gt; &lt;i&gt;By Ben Linders&lt;/i&gt;</description>
      <category>Artifacts &amp; Tools</category>
      <category>learning</category>
      <category>QCon London 2026</category>
      <category>Artificial Intelligence</category>
      <category>QCon Software Development Conference</category>
      <category>Software Engineering</category>
      <category>Careers</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Culture &amp; Methods</category>
      <category>news</category>
      <pubDate>Thu, 13 Aug 2026 11:28:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/AI-disrupts-engineering-progress/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Ben Linders</dc:creator>
      <dc:date>2026-08-13T11:28:00Z</dc:date>
      <dc:identifier>/news/2026/08/AI-disrupts-engineering-progress/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Migrating Uber Eats Feeds to Webview</title>
      <link>https://www.infoq.com/presentations/migration-mobile-application/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/presentations/migration-mobile-application/en/mediumimage/nickdistefano-medium-1785845098133.jpg"/&gt;&lt;p&gt;Nick DiStefano shares how Uber Eats migrated from traditional native app screens to a native-driven, single-page WebView architecture. He explains key strategies for engineering leaders and software architects looking to bypass native release cycles, manage cross-platform state, build generic native-web message bridges, and execute large-scale UI migrations without degrading metrics.&lt;/p&gt; &lt;i&gt;By Nick DiStefano&lt;/i&gt;</description>
      <category>migration</category>
      <category>Android</category>
      <category>QCon San Francisco 2025</category>
      <category>Mobile</category>
      <category>iOS</category>
      <category>Transcripts</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Thu, 13 Aug 2026 09:26:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/migration-mobile-application/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Nick DiStefano</dc:creator>
      <dc:date>2026-08-13T09:26:00Z</dc:date>
      <dc:identifier>/presentations/migration-mobile-application/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Adopting Memory-Safety and Fine-Grained Compartmentalisation with CHERI</title>
      <link>https://www.infoq.com/presentations/cheri-memory-safety-compartmentalization/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/presentations/cheri-memory-safety-compartmentalization/en/mediumimage/DavidChisnall-medium-1785845255636.jpg"/&gt;&lt;p&gt;David Chisnall discusses how the CHERI hardware architecture redefines pointer safety to solve isolation and sharing challenges. He explains how CHERI enables spatial and temporal memory safety for C/C++, scales down to microcontrollers with CHERIoT, and replaces costly OS-level RPC mechanisms with lightweight, auditable compartmentalization - all without requiring massive codebase rewrites.&lt;/p&gt; &lt;i&gt;By David Chisnall&lt;/i&gt;</description>
      <category>C++</category>
      <category>QCon London 2026</category>
      <category>Risk Management</category>
      <category>Hardware</category>
      <category>Memory</category>
      <category>Performance</category>
      <category>Transcripts</category>
      <category>Security</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Wed, 12 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/cheri-memory-safety-compartmentalization/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>David Chisnall</dc:creator>
      <dc:date>2026-08-12T11:00:00Z</dc:date>
      <dc:identifier>/presentations/cheri-memory-safety-compartmentalization/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Producing the World's Cheapest Tokens: A How-to Guide</title>
      <link>https://www.infoq.com/presentations/ai-token-price/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-token-price/en/mediumimage/meryem-arik-medium-1785844873071.jpg"/&gt;&lt;p&gt;Meryem Arik discusses strategies for designing low-cost LLM inference architectures for high-volume, non-real-time workloads. She explains how software architects and engineering leaders can achieve order-of-magnitude cost reductions by making critical trade-offs across hardware, inference runtimes, speculative decoding, and smart queue reordering.&lt;/p&gt; &lt;i&gt;By Meryem Arik&lt;/i&gt;</description>
      <category>QCon San Francisco 2025</category>
      <category>Artificial Intelligence</category>
      <category>Transcripts</category>
      <category>Performance &amp; Scalability</category>
      <category>Platform Engineering</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Tue, 11 Aug 2026 10:05:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-token-price/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Meryem Arik</dc:creator>
      <dc:date>2026-08-11T10:05:00Z</dc:date>
      <dc:identifier>/presentations/ai-token-price/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Leveraging Adversary Emulation for GenAI Red Teaming</title>
      <link>https://www.infoq.com/presentations/emulation-genai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</link>
      <description>&lt;img src="https://res.infoq.com/presentations/emulation-genai/en/mediumimage/KennedyTorkura-medium-1785396173788.jpeg"/&gt;&lt;p&gt;Kennedy Torkura discusses practical GenAI red teaming techniques to safeguard LLMs and knowledge bases against security threats like data poisoning and LLMjacking on AWS. He explains how engineering leaders and architects can bridge traditional cloud security with MITRE ATLAS frameworks to proactively identify vulnerabilities, implement guardrails, and secure production AI applications.&lt;/p&gt; &lt;i&gt;By Kennedy Torkura&lt;/i&gt;</description>
      <category>InfoQ Dev Summit Munich 2025</category>
      <category>Artificial Intelligence</category>
      <category>Transcripts</category>
      <category>Security</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Mon, 10 Aug 2026 09:32:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/emulation-genai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=QCon+Software+Development+Conference</guid>
      <dc:creator>Kennedy Torkura</dc:creator>
      <dc:date>2026-08-10T09:32:00Z</dc:date>
      <dc:identifier>/presentations/emulation-genai/en</dc:identifier>
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