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    <title>InfoQ</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ feed</description>
    <item>
      <title>Java News Roundup: Value Objects, WildFly 41, TornadoVM, LangChain4j, Oracle AI Agent Studio</title>
      <link>https://www.infoq.com/news/2026/07/java-news-roundup-jul13-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/java-news-roundup-jul13-2026/en/headerimage/java-news-roundup-image-1784573126569.jpg"/&gt;&lt;p&gt;This week's Java roundup for July 13th, 2026, features news highlighting: a reintroduction of Value Objects (Preview); the GA release of WildFly 41; the July 2026 edition of Open Liberty 26.0.0.7; point releases of TornadoVM, Apache TomEE, Java Operator SDK and LangChain4j; a maintenance release of Micronaut; a new extension, Quarkus Shim; and a new Oracle AI Agent Studio for Fusion Applications.&lt;/p&gt; &lt;i&gt;By Michael Redlich&lt;/i&gt;</description>
      <category>LangChain</category>
      <category>JDK 28</category>
      <category>Open Liberty</category>
      <category>JBoss WildFly</category>
      <category>Oracle</category>
      <category>Micronaut</category>
      <category>TornadoVM</category>
      <category>Java</category>
      <category>Apache TomEE</category>
      <category>Quarkus</category>
      <category>JDK 27</category>
      <category>Open JDK</category>
      <category>Java Operator SDK</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Mon, 20 Jul 2026 18:45:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/java-news-roundup-jul13-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Michael Redlich</dc:creator>
      <dc:date>2026-07-20T18:45:00Z</dc:date>
      <dc:identifier>/news/2026/07/java-news-roundup-jul13-2026/en</dc:identifier>
    </item>
    <item>
      <title>DoorDash Uses Envoy and Valkey for a 1.5M RPS Proxy Cache with 99.99999% Availability</title>
      <link>https://www.infoq.com/news/2026/07/doordash-entity-cache-proxy/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;DoorDash has developed Entity Cache, a transparent proxy caching platform built on Envoy and Valkey to reduce redundant service-to-service requests across its microservices architecture. Operating within DoorDash’s service mesh, the platform serves over 1.5M requests per second with 99.99999% availability through caching, event-driven invalidation, failure handling, and performance optimizations.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Distributed Cache</category>
      <category>Cloud Architecture</category>
      <category>Service Mesh</category>
      <category>Envoy</category>
      <category>Microservices</category>
      <category>Algorithms</category>
      <category>Performance</category>
      <category>Optimization</category>
      <category>Backend For Frontend</category>
      <category>Availability</category>
      <category>Service Reliability</category>
      <category>gRPC</category>
      <category>Valkey</category>
      <category>Caching</category>
      <category>HTTP</category>
      <category>Distributed Systems</category>
      <category>Reliability</category>
      <category>Event Driven Architecture</category>
      <category>Apache Kafka</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Mon, 20 Jul 2026 13:53:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/doordash-entity-cache-proxy/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-07-20T13:53:00Z</dc:date>
      <dc:identifier>/news/2026/07/doordash-entity-cache-proxy/en</dc:identifier>
    </item>
    <item>
      <title>Three InfoQ Certification Cohorts Start This August: Meet the Facilitators</title>
      <link>https://www.infoq.com/news/2026/07/infoq-online-cohorts-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/infoq-online-cohorts-2026/en/headerimage/infoq-online-cohorts-2026-1784536581240.jpg"/&gt;&lt;p&gt;InfoQ has opened enrollment for three five-week online certification cohorts starting in August, each led by a senior practitioner applying QCon talk frameworks to participants' own work: architecture with Luca Mezzalira, engineering leadership with Michelle Brush, and AI security and privacy with Katharine Jarmul.&lt;/p&gt; &lt;i&gt;By Artenisa Chatziou&lt;/i&gt;</description>
      <category>Leadership</category>
      <category>AI Security</category>
      <category>Software Engineering</category>
      <category>InfoQ Certification Program</category>
      <category>Privacy</category>
      <category>Architecture ICSAET</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Mon, 20 Jul 2026 13:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/infoq-online-cohorts-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Artenisa Chatziou</dc:creator>
      <dc:date>2026-07-20T13:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/infoq-online-cohorts-2026/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Platform Engineering for Everyone - Success Can’t Be Coded</title>
      <link>https://www.infoq.com/presentations/platform-engineering-product-mindset/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/presentations/platform-engineering-product-mindset/en/mediumimage/medium-1784106920162.jpeg"/&gt;&lt;p&gt;Max Korbacher explains why successful internal development platforms cannot be built on tech alone. He discusses the pitfalls of infrastructure-first thinking, the importance of a clear product mindset, and how to measure real value using DevEx and SPACE metrics. Learn how to align your team, manage tech debt, and foster a thriving community to ensure lasting platform adoption.&lt;/p&gt; &lt;i&gt;By Max Körbächer&lt;/i&gt;</description>
      <category>InfoQ Dev Summit Munich 2025</category>
      <category>Infrastructure</category>
      <category>Platform Engineering</category>
      <category>Transcripts</category>
      <category>DevOps</category>
      <category>Culture &amp; Methods</category>
      <category>presentation</category>
      <pubDate>Mon, 20 Jul 2026 11:50:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/platform-engineering-product-mindset/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Max Körbächer</dc:creator>
      <dc:date>2026-07-20T11:50:00Z</dc:date>
      <dc:identifier>/presentations/platform-engineering-product-mindset/en</dc:identifier>
    </item>
    <item>
      <title>Podcast: Strands Agents with Clare Liguori</title>
      <link>https://www.infoq.com/podcasts/strands-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/podcasts/strands-agents/en/smallimage/the-infoq-podcast-logo-thumbnail-1784037070015.jpg"/&gt;&lt;p&gt;Thomas Betts talks with Clare Liguori, the technical lead on the open source Strands Agents SDK. The conversation covers how Strands Agents has grown from a Python SDK to a full agent harness running in production. Clare shares some lessons learned from building agents at scale, shifting to a model-driven architecture, and what comes next as the LLMs that underpin agents continue to improve.&lt;/p&gt; &lt;i&gt;By Clare Liguori&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>AI Architecture</category>
      <category>The InfoQ Podcast</category>
      <category>Large language models</category>
      <category>Architecture</category>
      <category>Design and Technology</category>
      <category>Architecture &amp; Design</category>
      <category>podcast</category>
      <pubDate>Mon, 20 Jul 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/podcasts/strands-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Clare Liguori</dc:creator>
      <dc:date>2026-07-20T11:00:00Z</dc:date>
      <dc:identifier>/podcasts/strands-agents/en</dc:identifier>
    </item>
    <item>
      <title>AWS Releases Loom, an Open-Source Reference Platform for Governing AI Agents at Enterprise Scale</title>
      <link>https://www.infoq.com/news/2026/07/loom-aws-agent-platform/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/loom-aws-agent-platform/en/headerimage/generatedHeaderImage-1784031634775.jpg"/&gt;&lt;p&gt;AWS released Loom, an open-source reference platform on AWS Labs for governing AI agents at scale. Built on Strands Agents and Bedrock AgentCore Runtime, it implements RFC 8693 token exchange for identity propagation through delegated actor chains, config-driven deployments without runtime code generation, and mandatory tagging. AWS positions it as an example, not a managed service.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>AI Architecture</category>
      <category>Cloud</category>
      <category>Access Control</category>
      <category>AWS</category>
      <category>Open Source Project Releases</category>
      <category>DevOps</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Mon, 20 Jul 2026 10:04:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/loom-aws-agent-platform/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-07-20T10:04:00Z</dc:date>
      <dc:identifier>/news/2026/07/loom-aws-agent-platform/en</dc:identifier>
    </item>
    <item>
      <title>How Netflix Built GenPage: a Single GenAI Model to Build Personalized Homepages</title>
      <link>https://www.infoq.com/news/2026/07/netflix-llm-homepage-generation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/netflix-llm-homepage-generation/en/headerimage/netflix-genpage-recommender-1784476882801.jpeg"/&gt;&lt;p&gt;GenPage is a generative AI system developed by Netflix to replace its traditional multi-stage recommendation pipeline by directly generating personalized user homepages. GenPage leverages user history and request context as a prompt to produce the entire page, resulting in improved user engagement and reduced serving latency.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Netflix</category>
      <category>Large language models</category>
      <category>Generative AI</category>
      <category>A/B Testing</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sun, 19 Jul 2026 20:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/netflix-llm-homepage-generation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-07-19T20:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/netflix-llm-homepage-generation/en</dc:identifier>
    </item>
    <item>
      <title>Google's AlphaEvolve Reaches General Availability with Evolutionary Code Optimization as a Service</title>
      <link>https://www.infoq.com/news/2026/07/alphaevolve-generally-available/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/alphaevolve-generally-available/en/headerimage/generatedHeaderImage-1783873354690.jpg"/&gt;&lt;p&gt;Google's AlphaEvolve reached general availability on the Gemini Enterprise Agent Platform, turning the DeepMind research project into an evolutionary code optimization service. Evaluators run client-side so code never leaves the customer's infrastructure. Klarna doubled ML training throughput; practitioners note it only works where a measurable evaluation function exists.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Google Cloud</category>
      <category>AI Architecture</category>
      <category>Cloud</category>
      <category>Code Generation</category>
      <category>Google Cloud Platform</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sun, 19 Jul 2026 10:16:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/alphaevolve-generally-available/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-07-19T10:16:00Z</dc:date>
      <dc:identifier>/news/2026/07/alphaevolve-generally-available/en</dc:identifier>
    </item>
    <item>
      <title>AWS Introduces CloudFormation Express Mode for Faster Infrastructure Deployments</title>
      <link>https://www.infoq.com/news/2026/07/cloudformation-express-mode/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/cloudformation-express-mode/en/headerimage/generatedHeaderImage-1783162016860.jpg"/&gt;&lt;p&gt;AWS has recently introduced CloudFormation express mode, a deployment option that can reduce infrastructure deployment times by marking stack operations complete once resource configuration is applied, rather than waiting for full resource stabilization.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>CloudFormation</category>
      <category>Infrastructure as Code</category>
      <category>Terraform</category>
      <category>AWS</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Sun, 19 Jul 2026 05:59:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/cloudformation-express-mode/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-07-19T05:59:00Z</dc:date>
      <dc:identifier>/news/2026/07/cloudformation-express-mode/en</dc:identifier>
    </item>
    <item>
      <title>Pinecone Introduces Nexus Engine for Compiling Business Context into Structured Data for AI Agents</title>
      <link>https://www.infoq.com/news/2026/07/pinecon-nexus-knowledge-engine/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;Now generally available, Pinecone Nexus is a "knowledge engine" for AI agents that transforms enterprise data into a structured layer agents can query directly. It enables teams to ingest and curate business context once for all, making it reusable across agents and reducing token costs while improving accuracy.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Retrieval-Augmented Generation</category>
      <category>Large language models</category>
      <category>Enterprise</category>
      <category>vector databases</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sat, 18 Jul 2026 14:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/pinecon-nexus-knowledge-engine/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-07-18T14:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/pinecon-nexus-knowledge-engine/en</dc:identifier>
    </item>
    <item>
      <title>Version Controlled SQL Database Dolt Releases 2.0 with Automatic Storage Cleanup and Compression</title>
      <link>https://www.infoq.com/news/2026/07/dolt-version-control/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/dolt-version-control/en/headerimage/generatedHeaderImage-1783067948773.jpg"/&gt;&lt;p&gt;DoltHub has recently released Dolt 2.0, a major update to the open source version-controlled SQL database. The latest major version adds automatic storage optimization, including garbage collection and compression, along with improved support for large and vector data types.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>MySQL</category>
      <category>Version Control</category>
      <category>Database</category>
      <category>Git</category>
      <category>Data Lake</category>
      <category>vector databases</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sat, 18 Jul 2026 07:28:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/dolt-version-control/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-07-18T07:28:00Z</dc:date>
      <dc:identifier>/news/2026/07/dolt-version-control/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: From OTEL to SLMs: Distilling Frontier Model Behaviour from Production Telemetry</title>
      <link>https://www.infoq.com/presentations/otel-slm-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/presentations/otel-slm-ai/en/mediumimage/benomahony-medium-1783500827260.jpeg"/&gt;&lt;p&gt;Ben O'Mahony discusses building custom AI-powered Language Server Protocols (LSPs) that go beyond standard rule-based checkers. He explains how to instrument AI agents natively with OpenTelemetry to track concrete user actions (accepting, dismissing, or regenerating code fixes) as implicit labels, creating a continuous data flywheel to distill frontier capabilities into cheaper, local SLMs.&lt;/p&gt; &lt;i&gt;By Ben O'Mahony&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Telemetry</category>
      <category>QCon AI 2025</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Fri, 17 Jul 2026 13:17:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/otel-slm-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Ben O'Mahony</dc:creator>
      <dc:date>2026-07-17T13:17:00Z</dc:date>
      <dc:identifier>/presentations/otel-slm-ai/en</dc:identifier>
    </item>
    <item>
      <title>Cloud Native Infrastructure Emerges as the Foundation for Trustworthy Agentic AI</title>
      <link>https://www.infoq.com/news/2026/07/cncf-trustworthy-agentic-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/cncf-trustworthy-agentic-ai/en/headerimage/generatedHeaderImage-1783856714710.jpg"/&gt;&lt;p&gt;A new technical analysis published by the Cloud Native Computing Foundation (CNCF) argues that the future of agentic AI will be built not on entirely new infrastructure, but on the mature cloud-native ecosystem that already powers modern distributed applications&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Kubernetes</category>
      <category>OpenTelemetry</category>
      <category>Cloud Native Computing Foundation</category>
      <category>GitOps</category>
      <category>Apache Kafka</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 17 Jul 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/cncf-trustworthy-agentic-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Craig Risi</dc:creator>
      <dc:date>2026-07-17T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/cncf-trustworthy-agentic-ai/en</dc:identifier>
    </item>
    <item>
      <title>How Uber Builds Zone-Failure-Resilient OpenSearch Clusters</title>
      <link>https://www.infoq.com/news/2026/07/uber-opensearch-zone-failure/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/uber-opensearch-zone-failure/en/headerimage/generatedHeaderImage-1784274349171.jpg"/&gt;&lt;p&gt;Uber explained how it keeps its OpenSearch deployments running during a zone outage. It does this by using OpenSearch's built-in shard allocation and its own isolation-group system, which relies on the Odin container orchestration platform. This way, it maintains both query and ingestion capabilities.&lt;/p&gt; &lt;i&gt;By Claudio Masolo&lt;/i&gt;</description>
      <category>Uber</category>
      <category>OpenSearch</category>
      <category>Architecture</category>
      <category>Reliability</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 17 Jul 2026 10:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/uber-opensearch-zone-failure/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Claudio Masolo</dc:creator>
      <dc:date>2026-07-17T10:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/uber-opensearch-zone-failure/en</dc:identifier>
    </item>
    <item>
      <title>QCon AI Boston: Production AI Moves beyond Prompts to Platforms, Harnesses, and Evals</title>
      <link>https://www.infoq.com/news/2026/07/production-ai-platforms-evals/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/production-ai-platforms-evals/en/headerimage/production-ai-platforms-evals-header-1784186327712.jpg"/&gt;&lt;p&gt;QCon AI Boston 2026 focused on the operational challenges of deploying AI agents, emphasizing the need for robust production infrastructure. Key themes included improving context management, ensuring security through a "harness" around agents, and adopting a comprehensive engineering model for AI.&lt;/p&gt; &lt;i&gt;By Tatiana Fesenko&lt;/i&gt;</description>
      <category>Agents</category>
      <category>QCon AI Boston 2026</category>
      <category>Productivity</category>
      <category>QCon Software Development Conference</category>
      <category>Model</category>
      <category>Infrastructure</category>
      <category>Platforms</category>
      <category>Security</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 17 Jul 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/production-ai-platforms-evals/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Tatiana Fesenko</dc:creator>
      <dc:date>2026-07-17T09:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/production-ai-platforms-evals/en</dc:identifier>
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