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    <title>InfoQ - Programming</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Programming feed</description>
    <item>
      <title>Article: Post-Quantum Cryptography in Spring Boot: Four Patterns You Can Ship This Sprint</title>
      <link>https://www.infoq.com/articles/pqc-in-spring-boot/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</link>
      <description>&lt;img src="https://res.infoq.com/articles/pqc-in-spring-boot/en/headerimage/pqc-in-spring-boot-header-1787646727709.jpg"/&gt;&lt;p&gt;There are four patterns that bring PQC into a Spring Boot fleet: encrypting payloads between services, locking down database fields, signing documents that need to hold up for decades, and moving service tokens off RS256. Along the way, we discuss why Harvest Now, Decrypt Later is already happening, and why none of this is production-safe until KMS or Vault is in place.&lt;/p&gt; &lt;i&gt;By Pankaj Sharma&lt;/i&gt;</description>
      <category>Java</category>
      <category>Spring Boot</category>
      <category>Quantum Computing</category>
      <category>Spring Security</category>
      <category>Hashicorp</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Fri, 28 Aug 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/pqc-in-spring-boot/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</guid>
      <dc:creator>Pankaj Sharma</dc:creator>
      <dc:date>2026-08-28T09:00:00Z</dc:date>
      <dc:identifier>/articles/pqc-in-spring-boot/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Python, Numba, and Algorithm Design: Building Efficient Models in Financial Services</title>
      <link>https://www.infoq.com/presentations/numba/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</link>
      <description>&lt;img src="https://res.infoq.com/presentations/numba/en/mediumimage/chad-schuster-medium-1787217755995.jpeg"/&gt;&lt;p&gt;Chad Schuster discusses bridging Python's developer velocity with C-like performance using Numba JIT and GPUs. Drawing from large-scale actuarial modeling, he explains LLVM pipeline architecture, performance gains up to 750x, and essential trade-offs like OOP limits, type inference errors, and compile-time overhead for engineering leaders scaling compute-heavy enterprise systems.&lt;/p&gt; &lt;i&gt;By Chad Schuster&lt;/i&gt;</description>
      <category>Language Design</category>
      <category>QCon San Francisco 2025</category>
      <category>Transcripts</category>
      <category>Python</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Thu, 27 Aug 2026 09:23:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/numba/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</guid>
      <dc:creator>Chad Schuster</dc:creator>
      <dc:date>2026-08-27T09:23:00Z</dc:date>
      <dc:identifier>/presentations/numba/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Can Claude Fix Itself? Using LLMs for Incident Response</title>
      <link>https://www.infoq.com/presentations/claude-sre-incidents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</link>
      <description>&lt;img src="https://res.infoq.com/presentations/claude-sre-incidents/en/mediumimage/alex-palcuie-medium-1786539336984.jpg"/&gt;&lt;p&gt;Anthropic reliability engineer Alex Palcuie shares practical lessons on using LLMs for real-world incident response. He explains where AI acts as a superhuman for observing logs and traces, why it still struggles with causation versus correlation during root-cause analysis, and how engineering leaders can integrate AI into on-call workflows without eroding human expertise.&lt;/p&gt; &lt;i&gt;By Alex Palcuie&lt;/i&gt;</description>
      <category>On-call</category>
      <category>Automation</category>
      <category>Claude</category>
      <category>QCon London 2026</category>
      <category>Large language models</category>
      <category>Artificial Intelligence</category>
      <category>Site Reliability Engineering</category>
      <category>Transcripts</category>
      <category>Incident Response</category>
      <category>Observability</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Wed, 26 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/claude-sre-incidents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</guid>
      <dc:creator>Alex Palcuie</dc:creator>
      <dc:date>2026-08-26T11:00:00Z</dc:date>
      <dc:identifier>/presentations/claude-sre-incidents/en</dc:identifier>
    </item>
    <item>
      <title>Article: Rightsizing Platform Engineering: Building the Platform Your Organization Actually Needs</title>
      <link>https://www.infoq.com/articles/rightsizing-platform-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</link>
      <description>&lt;img src="https://res.infoq.com/articles/rightsizing-platform-engineering/en/smallimage/rightsizing-platform-engineering-thumbnail-1787296955801.jpg"/&gt;&lt;p&gt;Shift-left and DevOps have impacted how we flow changes from inception to production, but at the cost of increased cognitive load and duplication of effort across testing, security, and maintenance. This article explores the real-world challenges of rightsizing developer platforms and finding a cultural match for engineering teams who use them to reduce cognitive load and deliver change faster.&lt;/p&gt; &lt;i&gt;By John Keates&lt;/i&gt;</description>
      <category>Artifacts &amp; Tools</category>
      <category>Coding Standards</category>
      <category>Architecture</category>
      <category>Infrastructure</category>
      <category>Delivering Quality</category>
      <category>Developer Experience</category>
      <category>Platforms</category>
      <category>Stories &amp; Case Studies</category>
      <category>Platform Engineering</category>
      <category>Culture &amp; Methods</category>
      <category>article</category>
      <pubDate>Mon, 24 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/rightsizing-platform-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</guid>
      <dc:creator>John Keates</dc:creator>
      <dc:date>2026-08-24T11:00:00Z</dc:date>
      <dc:identifier>/articles/rightsizing-platform-engineering/en</dc:identifier>
    </item>
    <item>
      <title>Podcast: The Human Edge: Why Brownfield Codebases Need Mob Programming, Not Just AI Vibes</title>
      <link>https://www.infoq.com/podcasts/brownfield-codebases-mob-programming/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</link>
      <description>&lt;img src="https://res.infoq.com/podcasts/brownfield-codebases-mob-programming/en/smallimage/infoq-podcast-500-1787057874183.jpg"/&gt;&lt;p&gt;Asgaut Mjølne Söderbom and Ola Hast discuss the evolution of their software engineering practices past continuous deployment and pair engineering. The conversation continues where it left off in the previous episode and focuses on the experiments in adopting Claude Code and the reasons why they consider it good for everything else, but not coding.&lt;/p&gt; &lt;i&gt;By Asgaut Mjølne Söderbom, Ola Hast&lt;/i&gt;</description>
      <category>Continuous Deployment</category>
      <category>Continuous Improvement</category>
      <category>TDD</category>
      <category>Team Performance</category>
      <category>Artificial Intelligence</category>
      <category>The InfoQ Podcast</category>
      <category>Performance</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>podcast</category>
      <pubDate>Mon, 24 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/podcasts/brownfield-codebases-mob-programming/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</guid>
      <dc:creator>Asgaut Mjølne Söderbom, Ola Hast</dc:creator>
      <dc:date>2026-08-24T11:00:00Z</dc:date>
      <dc:identifier>/podcasts/brownfield-codebases-mob-programming/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Prompt to Prod: Engineering an Autonomous SDLC at Scale</title>
      <link>https://www.infoq.com/presentations/autonomous-ai-software-development-roblox/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</link>
      <description>&lt;img src="https://res.infoq.com/presentations/autonomous-ai-software-development-roblox/en/mediumimage/andrew-swerdlow-medium-1787218240356.jpg"/&gt;&lt;p&gt;Andrew Swerdlow shares how Roblox scales autonomous software development from prompt to production. He discusses building robust security sandboxes, extracting institutional knowledge via code review exemplars, updating engineering infrastructure, and redefining productivity metrics around feature velocity and long-running AI turns to achieve trusted, automated deployment at scale.&lt;/p&gt; &lt;i&gt;By Andrew Swerdlow&lt;/i&gt;</description>
      <category>Architecture</category>
      <category>QCon AI Boston 2026</category>
      <category>Metrics</category>
      <category>Productivity</category>
      <category>autonomous</category>
      <category>Code Reviews</category>
      <category>Developer Experience</category>
      <category>Orchestration</category>
      <category>Prompt Engineering</category>
      <category>Transcripts</category>
      <category>Platform Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Mon, 24 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/autonomous-ai-software-development-roblox/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</guid>
      <dc:creator>Andrew Swerdlow</dc:creator>
      <dc:date>2026-08-24T11:00:00Z</dc:date>
      <dc:identifier>/presentations/autonomous-ai-software-development-roblox/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: SafeChat: Building AI-Powered Safety Systems at Scale in a Real-Time Marketplace</title>
      <link>https://www.infoq.com/presentations/doordash-llm-ai-moderation-platform/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</link>
      <description>&lt;img src="https://res.infoq.com/presentations/doordash-llm-ai-moderation-platform/en/mediumimage/bruna-pereira-medium-1786539036040.jpeg"/&gt;&lt;p&gt;Bruna Pereira explains how DoorDash built a content-agnostic AI moderation platform. She covers replacing costly LLM-only pipelines with a hybrid pattern: using fast internal models to filter obvious cases, LLM multi-axis scoring for nuanced decisions, and no-code workflows with backtesting. Discover how this architectural pattern cut safety incidents while scaling to millions of daily messages.&lt;/p&gt; &lt;i&gt;By Bruna Pereira&lt;/i&gt;</description>
      <category>Cost Optimization</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>QCon AI Boston 2026</category>
      <category>AI Architecture</category>
      <category>Real-Time Data</category>
      <category>Transcripts</category>
      <category>Platform Engineering</category>
      <category>Machine Learning</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Sat, 22 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/doordash-llm-ai-moderation-platform/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</guid>
      <dc:creator>Bruna Pereira</dc:creator>
      <dc:date>2026-08-22T11:00:00Z</dc:date>
      <dc:identifier>/presentations/doordash-llm-ai-moderation-platform/en</dc:identifier>
    </item>
    <item>
      <title>Mini book: Architecture as a Socio-Technical Craft</title>
      <link>https://www.infoq.com/minibooks/architect-sociotechnical-craft/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</link>
      <description>&lt;img src="https://res.infoq.com/minibooks/architect-sociotechnical-craft/en/smallimage/thumb-1787566215701.jpg"/&gt;&lt;p&gt;Architecture is not a fixed choice made once; fitness is a moving target driven by changing regulations, tech, and markets. Even a sound design can silently stop fitting over time without bad calls. Spanning seven articles on context stores, gateways, and topologies, this collection treats architecture as an evolving sociotechnical craft where teams deliberately shape friction, fitness, and flow.&lt;/p&gt; &lt;i&gt;By InfoQ&lt;/i&gt;</description>
      <category>Agile</category>
      <category>Architecture ICSAET</category>
      <category>Topology</category>
      <category>Domain Driven Design</category>
      <category>Evolutionary Architecture</category>
      <category>InfoQ Certification Program</category>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>AI Security</category>
      <category>Sociotechnical Architecture</category>
      <category>Leadership</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>minibook</category>
      <pubDate>Fri, 21 Aug 2026 11:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/minibooks/architect-sociotechnical-craft/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</guid>
      <dc:creator>InfoQ</dc:creator>
      <dc:date>2026-08-21T11:30:00Z</dc:date>
      <dc:identifier>/minibooks/architect-sociotechnical-craft/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Enchant Your AI and APIs with eBPF Magic &#x1fa84;</title>
      <link>https://www.infoq.com/presentations/ebpf-ai-gateway-kubernetes-security/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ebpf-ai-gateway-kubernetes-security/en/mediumimage/dan-finneran-medium-1786539181222.jpeg"/&gt;&lt;p&gt;Dan Finneran discusses the risks of unowned AI-generated code in production and demonstrates how eBPF can intercept and control AI API traffic in Kubernetes. He explains how kernel-level socket hooks enable transparent prompt filtering, model swapping, token limits, and syscall restrictions to secure AI agents without modifying application source code or restarting containers.&lt;/p&gt; &lt;i&gt;By Dan Finneran&lt;/i&gt;</description>
      <category>API</category>
      <category>QCon London 2026</category>
      <category>Cloud-Native</category>
      <category>API Gateway</category>
      <category>Linux</category>
      <category>eBPF</category>
      <category>Artificial Intelligence</category>
      <category>Kubernetes</category>
      <category>Transcripts</category>
      <category>Security</category>
      <category>Observability</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Fri, 21 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ebpf-ai-gateway-kubernetes-security/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Programming</guid>
      <dc:creator>Dan Finneran</dc:creator>
      <dc:date>2026-08-21T11:00:00Z</dc:date>
      <dc:identifier>/presentations/ebpf-ai-gateway-kubernetes-security/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=Programming</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=Programming</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>
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