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    <title>InfoQ - Artificial Intelligence</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Artificial Intelligence feed</description>
    <item>
      <title>Presentation: AI is an Amplifier: Scale High Performance, Not Dysfunction</title>
      <link>https://www.infoq.com/presentations/dora-ai-adoption-engineering-performance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</link>
      <description>&lt;img src="https://res.infoq.com/presentations/dora-ai-adoption-engineering-performance/en/mediumimage/medium-1791447741420.jpg"/&gt;&lt;p&gt;Nathen Harvey shares insights from DORA research on AI adoption in software delivery. He explains why AI acts as an amplifier, how the DORA AI Capabilities Model drives outcomes, and why engineering leaders must evolve beyond bottlenecks like code reviews to achieve sustainable productivity, reduce delivery instability, and empower developers without burning out their teams.&lt;/p&gt; &lt;i&gt;By Nathen Harvey&lt;/i&gt;</description>
      <category>Performance</category>
      <category>Continuous Improvement</category>
      <category>Adoption</category>
      <category>Management</category>
      <category>Transcripts</category>
      <category>QCon London 2026</category>
      <category>Continuous Delivery</category>
      <category>Code Quality</category>
      <category>Artificial Intelligence</category>
      <category>Productivity</category>
      <category>Culture &amp; Methods</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Wed, 21 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/dora-ai-adoption-engineering-performance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</guid>
      <dc:creator>Nathen Harvey</dc:creator>
      <dc:date>2026-10-21T11:00:00Z</dc:date>
      <dc:identifier>/presentations/dora-ai-adoption-engineering-performance/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Beyond the Prototype: Scaling Framework Agnostic AI Agent Infrastructure with Ray</title>
      <link>https://www.infoq.com/presentations/scale-llm-agents-production-ray/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</link>
      <description>&lt;img src="https://res.infoq.com/presentations/scale-llm-agents-production-ray/en/mediumimage/medium-1792065446239.jpg"/&gt;&lt;p&gt;The speakers discuss transitioning AI agents from local FastAPI prototypes to resilient production systems on Kubernetes using Ray. They share operational insights on RayCluster topology, stateful memory handling, auto-scaling on dynamic traffic, and robust control plane designs, while highlighting critical guardrails, multi-region setups, and LLM-as-a-judge evaluation pipelines.&lt;/p&gt; &lt;i&gt;By Deepak Mohanakumar Chandramouli, Bhumik Vinodkumar Thakkar&lt;/i&gt;</description>
      <category>Scalability</category>
      <category>Machine Learning</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Transcripts</category>
      <category>QCon AI Boston 2026</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Tue, 20 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/scale-llm-agents-production-ray/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</guid>
      <dc:creator>Deepak Mohanakumar Chandramouli, Bhumik Vinodkumar Thakkar</dc:creator>
      <dc:date>2026-10-20T11:00:00Z</dc:date>
      <dc:identifier>/presentations/scale-llm-agents-production-ray/en</dc:identifier>
    </item>
    <item>
      <title>Article: From Microservices to Agents: the Next Evolution of Distributed Systems</title>
      <link>https://www.infoq.com/articles/distributed-systems-microservices-agentic-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</link>
      <description>&lt;img src="https://res.infoq.com/articles/distributed-systems-microservices-agentic-ai/en/headerimage/header-1792138504151.jpg"/&gt;&lt;p&gt;The article examines the transition from microservices to agentic AI architecture in distributed systems. Microservices allow for functional decomposition, while agentic systems focus on decision decomposition. This shift introduces new complexities in observability, reliability, and system design, highlighting the need for updated architectural patterns and practices.&lt;/p&gt; &lt;i&gt;By Mallika Rao&lt;/i&gt;</description>
      <category>Agentic AI Architecture</category>
      <category>Large language models</category>
      <category>Microservices</category>
      <category>Distributed Systems</category>
      <category>Agentic AI Architecture Series</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Mon, 19 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/distributed-systems-microservices-agentic-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</guid>
      <dc:creator>Mallika Rao</dc:creator>
      <dc:date>2026-10-19T11:00:00Z</dc:date>
      <dc:identifier>/articles/distributed-systems-microservices-agentic-ai/en</dc:identifier>
    </item>
    <item>
      <title>Mini book: Evolutionary Architecture in Practice</title>
      <link>https://www.infoq.com/minibooks/evolutionary-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</link>
      <description>&lt;img src="https://res.infoq.com/minibooks/evolutionary-architecture/en/smallimage/thumb-1791282847807.jpg"/&gt;&lt;p&gt;Discover how to keep software evolvable as systems, technology, and teams shift. This edition explores agentic fitness functions for semantic drift, treating human comprehension as a core design metric, cross-cloud guardrails for regional autonomy, and aligning technical boundaries with Conway’s Law. Move beyond static diagrams to continuous feedback systems that keep change safe and intentional.&lt;/p&gt; &lt;i&gt;By InfoQ&lt;/i&gt;</description>
      <category>Evolutionary Architecture</category>
      <category>Agentic AI Architecture</category>
      <category>Domain Driven Design</category>
      <category>InfoQ Certification Program</category>
      <category>Distributed Systems</category>
      <category>Platform Engineering</category>
      <category>Architecture ICSAET</category>
      <category>Leadership</category>
      <category>Artificial Intelligence</category>
      <category>Sociotechnical Architecture</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>minibook</category>
      <pubDate>Fri, 16 Oct 2026 11:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/minibooks/evolutionary-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</guid>
      <dc:creator>InfoQ</dc:creator>
      <dc:date>2026-10-16T11:30:00Z</dc:date>
      <dc:identifier>/minibooks/evolutionary-architecture/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Exploding GPUs and the AI Infrastructure Challenge</title>
      <link>https://www.infoq.com/presentations/ai-security-kubernetes-gpu-threats/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-security-kubernetes-gpu-threats/en/mediumimage/andrew-martin-medium-1790846331295.jpeg"/&gt;&lt;p&gt;Andrew Martin discusses why AI security is fundamentally tied to Kubernetes security. He shares insights into the evolving AI threat landscape, covering non-deterministic agent behavior, GPU supply chain vulnerabilities, shared compute risks, and practical defense strategies - from prompt firewalling to agentic identity - to help secure cloud-native AI workloads in production environments.&lt;/p&gt; &lt;i&gt;By Andrew Martin&lt;/i&gt;</description>
      <category>Containers</category>
      <category>Agents</category>
      <category>Cloud-Native</category>
      <category>Kubernetes</category>
      <category>Transcripts</category>
      <category>Infrastructure</category>
      <category>QCon London 2026</category>
      <category>AI Security</category>
      <category>GPU</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Fri, 16 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-security-kubernetes-gpu-threats/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</guid>
      <dc:creator>Andrew Martin</dc:creator>
      <dc:date>2026-10-16T11:00:00Z</dc:date>
      <dc:identifier>/presentations/ai-security-kubernetes-gpu-threats/en</dc:identifier>
    </item>
    <item>
      <title>AWS Introduces Strands Decider 2B and Strands Box for AI Agent Development</title>
      <link>https://www.infoq.com/news/2026/10/aws-strands-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/aws-strands-agents/en/headerimage/generatedHeaderImage-1792079603910.jpg"/&gt;&lt;p&gt;AWS has introduced two open-source projects for AI agent development: Strands Decider 2B, a small model designed to make decisions within agent workflows, and Strands Box, a sandbox for controlling agent execution. Both projects address different aspects of building agents that use tools, execute code, and interact with external systems.&lt;/p&gt; &lt;i&gt;By Daniel Dominguez&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Typesafe</category>
      <category>AWS</category>
      <category>Artificial Intelligence</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 16 Oct 2026 10:47:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/aws-strands-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</guid>
      <dc:creator>Daniel Dominguez</dc:creator>
      <dc:date>2026-10-16T10:47:00Z</dc:date>
      <dc:identifier>/news/2026/10/aws-strands-agents/en</dc:identifier>
    </item>
    <item>
      <title>Optimizing Software Workflow: Exploring Fundamental Impacts in Technology</title>
      <link>https://www.infoq.com/news/2026/10/optimize-software-workflow/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/optimize-software-workflow/en/headerimage/header-1791282094936.jpg"/&gt;&lt;p&gt;Software only has value when shipped; faster release cadence matters. Development, deployment, and operations require different thinking, metrics, and investments. There are four impacts in tech: product success, compute capacity, engineering capacity, and strategic innovation. The biggest expense is people. AI shifts engineers toward deeper problem understanding, not fewer engineers.&lt;/p&gt; &lt;i&gt;By Ben Linders&lt;/i&gt;</description>
      <category>Capacity Planning</category>
      <category>Measurement</category>
      <category>Metrics</category>
      <category>Software Engineering</category>
      <category>Agile Conferences</category>
      <category>Applied Research</category>
      <category>Planning</category>
      <category>Artificial Intelligence</category>
      <category>Delivering Value</category>
      <category>Culture &amp; Methods</category>
      <category>news</category>
      <pubDate>Thu, 15 Oct 2026 11:33:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/optimize-software-workflow/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</guid>
      <dc:creator>Ben Linders</dc:creator>
      <dc:date>2026-10-15T11:33:00Z</dc:date>
      <dc:identifier>/news/2026/10/optimize-software-workflow/en</dc:identifier>
    </item>
    <item>
      <title>Production Patterns for Agents, Evals, and LLM Costs: QCon AI New York 2026</title>
      <link>https://www.infoq.com/news/2026/10/qcon-ai-newyork-2026-sessionsv2/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/qcon-ai-newyork-2026-sessionsv2/en/headerimage/qcon-ai-new-york-2026-1791875885339.jpg"/&gt;&lt;p&gt;Once AI is in production, code arrives faster than it can be reviewed, token costs rise, evals have to be good enough to act on, and agents need permissions and guardrails. QCon AI New York 2026 (December 15-16) has confirmed sessions from engineers sharing how they handle these constraints.&lt;/p&gt; &lt;i&gt;By Artenisa Chatziou&lt;/i&gt;</description>
      <category>QCon AI New York 2026</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>AI Architecture</category>
      <category>Artificial Intelligence</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/qcon-ai-newyork-2026-sessionsv2/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</guid>
      <dc:creator>Artenisa Chatziou</dc:creator>
      <dc:date>2026-10-13T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/qcon-ai-newyork-2026-sessionsv2/en</dc:identifier>
    </item>
    <item>
      <title>Podcast: What Does it Really Mean to Program with AI: a Conversation with Joy Ebertz</title>
      <link>https://www.infoq.com/podcasts/what-really-mean-program-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</link>
      <description>&lt;img src="https://res.infoq.com/podcasts/what-really-mean-program-ai/en/smallimage/infoq-podcast-500-1791359941231.jpg"/&gt;&lt;p&gt;In this podcast, Michael Stiefel spoke to Joy Ebertz about how the use of artificial intelligence is changing the way architects and developers do their jobs. Focusing on the long term success of the business is one of the most neglected tasks of an architect. This task becomes particularly important as the nature of artificial intelligence changes the landscape of software development.&lt;/p&gt; &lt;i&gt;By Joy Ebertz&lt;/i&gt;</description>
      <category>The InfoQ Podcast</category>
      <category>Modular Monolith</category>
      <category>Microservices</category>
      <category>Architecture</category>
      <category>Requirements</category>
      <category>Artificial Intelligence</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>podcast</category>
      <pubDate>Mon, 12 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/podcasts/what-really-mean-program-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</guid>
      <dc:creator>Joy Ebertz</dc:creator>
      <dc:date>2026-10-12T11:00:00Z</dc:date>
      <dc:identifier>/podcasts/what-really-mean-program-ai/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: You Can't Trust Your AI Bill. And Neither Can I</title>
      <link>https://www.infoq.com/presentations/ai-cloud-cost-economics/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-cloud-cost-economics/en/mediumimage/erik-peterson-medium-1791451373591.jpg"/&gt;&lt;p&gt;Erik Peterson discusses why AI spend is eclipsing cloud bills, triggering a major software engineering cost crisis. He explains tokenmaxxing, unit economics, forced developer promotions, and why fully autonomous AI will write, deploy, and govern code by 2028.&lt;/p&gt; &lt;i&gt;By Erik Peterson&lt;/i&gt;</description>
      <category>Cost Optimization</category>
      <category>FinOps</category>
      <category>Transcripts</category>
      <category>Architecture</category>
      <category>Productivity</category>
      <category>Cloud Computing</category>
      <category>Generative AI</category>
      <category>QCon AI Boston 2026</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Mon, 12 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-cloud-cost-economics/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Artificial+Intelligence</guid>
      <dc:creator>Erik Peterson</dc:creator>
      <dc:date>2026-10-12T11:00:00Z</dc:date>
      <dc:identifier>/presentations/ai-cloud-cost-economics/en</dc:identifier>
    </item>
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