<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>InfoQ - Architecture</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Architecture feed</description>
    <item>
      <title>AWS Introduces Specification Driven Composition for Flexible Data Workflows</title>
      <link>https://www.infoq.com/news/2026/08/aws-spec-driven-data-workflow/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/aws-spec-driven-data-workflow/en/headerimage/generatedHeaderImage-1786944784495.jpg"/&gt;&lt;p&gt;AWS describes a specification-driven approach for composing flexible data workflows by separating intent from processing logic. Architecture uses declarative specifications, reusable processing capabilities, and validation before execution. AWS reports that the approach can reduce dataset onboarding from weeks to days while supporting traceability, versioning, data classification, and governance.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>ETL</category>
      <category>AWS Lambda</category>
      <category>Serverless</category>
      <category>OpenSearch</category>
      <category>Automation</category>
      <category>Architecture</category>
      <category>Data Pipelines</category>
      <category>Orchestration</category>
      <category>S3</category>
      <category>Declarative Programming</category>
      <category>Software Engineering</category>
      <category>Data</category>
      <category>Workflow Foundation</category>
      <category>Data Governance</category>
      <category>Amazon CloudWatch</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Wed, 26 Aug 2026 14:18:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/aws-spec-driven-data-workflow/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-08-26T14:18:00Z</dc:date>
      <dc:identifier>/news/2026/08/aws-spec-driven-data-workflow/en</dc:identifier>
    </item>
    <item>
      <title>Article: Beyond Offset Lag: Computing Time in Queue for Apache Hudi Data Lake Pipelines at Petabyte Scale</title>
      <link>https://www.infoq.com/articles/beyond-offset-lag-kafka-apache-hudi/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture</link>
      <description>&lt;img src="https://res.infoq.com/articles/beyond-offset-lag-kafka-apache-hudi/en/headerimage/beyond-offset-lag-kafka-apache-hudi-header-1787577734265.jpg"/&gt;&lt;p&gt;In this article, author Srikanth Mamidala discusses the data lake architecture used for analytics, reporting, and machine learning and shows how to manage the consumer lag metrics when using Kafka and Apache Hudi.&lt;/p&gt; &lt;i&gt;By Srikanth Mamidala&lt;/i&gt;</description>
      <category>Messaging</category>
      <category>Data Lake</category>
      <category>Streaming</category>
      <category>Data Pipelines</category>
      <category>Apache Kafka</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>article</category>
      <pubDate>Wed, 26 Aug 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/beyond-offset-lag-kafka-apache-hudi/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture</guid>
      <dc:creator>Srikanth Mamidala</dc:creator>
      <dc:date>2026-08-26T09:00:00Z</dc:date>
      <dc:identifier>/articles/beyond-offset-lag-kafka-apache-hudi/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=Architecture</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>Delivering Quality</category>
      <category>Developer Experience</category>
      <category>Coding Standards</category>
      <category>Artifacts &amp; Tools</category>
      <category>Architecture</category>
      <category>Infrastructure</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=Architecture</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>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=Architecture</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>QCon AI Boston 2026</category>
      <category>Productivity</category>
      <category>Code Reviews</category>
      <category>Metrics</category>
      <category>autonomous</category>
      <category>Developer Experience</category>
      <category>Architecture</category>
      <category>Orchestration</category>
      <category>Prompt Engineering</category>
      <category>Platform Engineering</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>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=Architecture</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=Architecture</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>Agents</category>
      <category>QCon AI Boston 2026</category>
      <category>AI Architecture</category>
      <category>Large language models</category>
      <category>Cost Optimization</category>
      <category>Real-Time Data</category>
      <category>Machine Learning</category>
      <category>Transcripts</category>
      <category>Platform Engineering</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</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=Architecture</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=Architecture</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>Agents</category>
      <category>Artificial Intelligence</category>
      <category>Leadership</category>
      <category>AI Security</category>
      <category>Sociotechnical Architecture</category>
      <category>Evolutionary Architecture</category>
      <category>InfoQ Certification Program</category>
      <category>Agile</category>
      <category>Domain Driven Design</category>
      <category>Topology</category>
      <category>Architecture ICSAET</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</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=Architecture</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=Architecture</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>Artificial Intelligence</category>
      <category>Kubernetes</category>
      <category>Linux</category>
      <category>eBPF</category>
      <category>Cloud-Native</category>
      <category>QCon London 2026</category>
      <category>API</category>
      <category>API Gateway</category>
      <category>Observability</category>
      <category>Transcripts</category>
      <category>Security</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</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=Architecture</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>InfoQ Opens Enrollment for New AI-Assisted Engineering Online Certification Program</title>
      <link>https://www.infoq.com/news/2026/08/ai-assisted-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/ai-assisted-engineering/en/headerimage/infoq-ai-assisted-cohort-1787145000301.jpg"/&gt;&lt;p&gt;InfoQ has opened enrollment for the InfoQ Certified AI-Assisted Engineering Program, a five-week online certification program for senior engineers and architects who already run a coding agent against production code daily, where the open questions have moved past prompting into what the agent is allowed to touch and what catches its mistakes before a human does.&lt;/p&gt; &lt;i&gt;By Artenisa Chatziou&lt;/i&gt;</description>
      <category>Leadership</category>
      <category>Artificial Intelligence</category>
      <category>AI Architecture</category>
      <category>AI Security</category>
      <category>AI-Assisted Engineering Certification</category>
      <category>AI Certification</category>
      <category>InfoQ Certification Program</category>
      <category>Architecture</category>
      <category>Security</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Culture &amp; Methods</category>
      <category>news</category>
      <pubDate>Thu, 20 Aug 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/ai-assisted-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture</guid>
      <dc:creator>Artenisa Chatziou</dc:creator>
      <dc:date>2026-08-20T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/08/ai-assisted-engineering/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=Architecture</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>Fault Tolerance</category>
      <category>Resilience</category>
      <category>Cloud Architecture</category>
      <category>Failure</category>
      <category>Distributed Systems</category>
      <category>QCon London 2026</category>
      <category>Microservices</category>
      <category>Transcripts</category>
      <category>DevOps</category>
      <category>Development</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=Architecture</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=Architecture</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>QCon AI Boston 2026</category>
      <category>AI Architecture</category>
      <category>AI Security</category>
      <category>Large language models</category>
      <category>GPU</category>
      <category>Model Inference</category>
      <category>Hardware</category>
      <category>Benchmark</category>
      <category>Infrastructure</category>
      <category>Performance</category>
      <category>Transcripts</category>
      <category>Data Analytics</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</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=Architecture</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>Article: Agentic Fitness Functions: Extending Evolutionary Architecture Beyond Deterministic Rules</title>
      <link>https://www.infoq.com/articles/agentic-fitness-functions-evolutionary-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture</link>
      <description>&lt;img src="https://res.infoq.com/articles/agentic-fitness-functions-evolutionary-architecture/en/headerimage/header-1786428822427.jpg"/&gt;&lt;p&gt;Deterministic rules safeguard hard metrics, but what about architectural intent? Discover how agentic fitness functions combine AI agents and versioned rubrics to evaluate complex, judgment-heavy concerns—such as boundary fidelity, semantic contract drift, and stale ADR assumptions. Elevate evolutionary architecture governance with continuous, calibrated feedback loops.&lt;/p&gt; &lt;i&gt;By Hemant Kumar Mahato, Łukasz Sieczkowski, Vijayasenthilkumar Kuppusamy&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>AI Architecture</category>
      <category>Governance</category>
      <category>Code Quality</category>
      <category>Agentic AI Architecture</category>
      <category>Evolutionary Architecture</category>
      <category>InfoQ Certification Program</category>
      <category>Architecture Decision Records</category>
      <category>Architecture ICSAET</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Mon, 17 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/agentic-fitness-functions-evolutionary-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture</guid>
      <dc:creator>Hemant Kumar Mahato, Łukasz Sieczkowski, Vijayasenthilkumar Kuppusamy</dc:creator>
      <dc:date>2026-08-17T11:00:00Z</dc:date>
      <dc:identifier>/articles/agentic-fitness-functions-evolutionary-architecture/en</dc:identifier>
    </item>
    <item>
      <title>Podcast: Will Agentic AI Bring Fantasia’s Sorcerer's Apprentice to Life?: A Conversation with Tracy Bannon</title>
      <link>https://www.infoq.com/podcasts/agentic-ai-sorcerers-apprentice/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture</link>
      <description>&lt;img src="https://res.infoq.com/podcasts/agentic-ai-sorcerers-apprentice/en/smallimage/infoq-podcast-500-1787058367301.jpg"/&gt;&lt;p&gt;In this podcast, Michael Stiefel spoke to Tracy Bannon about the role of artificial intelligence in software and the attendant risks in the areas of security, software development, and society at large. While it might be reasonable to assume a certain amount of trust within a software ecosystem, the risks escalate when the boundary between two software ecosystems is crossed.&lt;/p&gt; &lt;i&gt;By Tracy Bannon&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>AI Architecture</category>
      <category>The InfoQ Podcast</category>
      <category>Large language models</category>
      <category>Software Development Lifecycle</category>
      <category>Architecture</category>
      <category>Security</category>
      <category>Architecture &amp; Design</category>
      <category>podcast</category>
      <pubDate>Mon, 17 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/podcasts/agentic-ai-sorcerers-apprentice/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Architecture</guid>
      <dc:creator>Tracy Bannon</dc:creator>
      <dc:date>2026-08-17T11:00:00Z</dc:date>
      <dc:identifier>/podcasts/agentic-ai-sorcerers-apprentice/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=Architecture</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>AI Architecture</category>
      <category>Patterns</category>
      <category>Large language models</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, 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=Architecture</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>
  </channel>
</rss>
