<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>InfoQ</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ feed</description>
    <item>
      <title>How OpenAI Built a Secure Windows Sandbox for Codex Agents</title>
      <link>https://www.infoq.com/news/2026/06/codex-windows-sandbox-design/?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/2026/06/codex-windows-sandbox-design/en/headerimage/generatedHeaderImage-1780184710031.jpg"/&gt;&lt;p&gt;OpenAI details Codex Windows sandbox architecture, showing how SIDs, ACLs, restricted tokens, and dedicated sandbox accounts enable safe execution of autonomous coding tasks. The design balances isolation with real developer workflows and shows how OS security primitives must be composed for AI agents on local development environments.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Identity Management</category>
      <category>IDE</category>
      <category>Access Control</category>
      <category>Security</category>
      <category>AI Assisted Coding</category>
      <category>Integrated Development Environment</category>
      <category>CLI</category>
      <category>Operating Systems</category>
      <category>Design Systems</category>
      <category>Windows</category>
      <category>Agents</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Fri, 05 Jun 2026 14:37:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/codex-windows-sandbox-design/?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>2026-06-05T14:37:00Z</dc:date>
      <dc:identifier>/news/2026/06/codex-windows-sandbox-design/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Platform Teams Enabling AI - MCP/Multi-Agentic Tools Across Linkedin</title>
      <link>https://www.infoq.com/presentations/ai-multi-agentic-tools/?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/ai-multi-agentic-tools/en/mediumimage/medium-1779867927919.jpg"/&gt;&lt;p&gt;LinkedIn’s Karthik Ramgopal and Prince Valluri discuss leveraging AI as a new execution model for large-scale engineering. They explain how to move beyond fragmented implementations by building platform abstractions for orchestration, structured context, and safe tooling like MCP. They share architectural insights from real-world coding, observation, and UI testing agents built at LinkedIn.&lt;/p&gt; &lt;i&gt;By Karthik Ramgopal, Prince Valluri&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Case Study</category>
      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
      <category>Agents</category>
      <category>Artifacts &amp; Tools</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Fri, 05 Jun 2026 12:23:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-multi-agentic-tools/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Karthik Ramgopal, Prince Valluri</dc:creator>
      <dc:date>2026-06-05T12:23:00Z</dc:date>
      <dc:identifier>/presentations/ai-multi-agentic-tools/en</dc:identifier>
    </item>
    <item>
      <title>Dropbox Introduces Nova, an Internal Platform for Running AI Coding Agents at Scale</title>
      <link>https://www.infoq.com/news/2026/06/dropbox-nova-ai-coding-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/news/2026/06/dropbox-nova-ai-coding-agents/en/headerimage/generatedHeaderImage-1779952906697.jpg"/&gt;&lt;p&gt;Dropbox has unveiled Nova, an internal platform designed to orchestrate and operationalize AI coding agents across the company's engineering workflows.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>AI Assisted Coding</category>
      <category>Artificial Intelligence</category>
      <category>AI Coding</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Fri, 05 Jun 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/dropbox-nova-ai-coding-agents/?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>2026-06-05T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/06/dropbox-nova-ai-coding-agents/en</dc:identifier>
    </item>
    <item>
      <title>How Netflix Maps Thousands of Microservices in Real-Time</title>
      <link>https://www.infoq.com/news/2026/06/netflix-microservices-realtime/?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;Netflix has shared details about Service Topology. This internal system creates and updates a live dependency graph for thousands of microservices. It helps engineers see how services connect and resolve issues more quickly. The system merges three separate data sources into a single, queryable graph. It updates almost in real-time as traffic patterns shift.&lt;/p&gt; &lt;i&gt;By Claudio Masolo&lt;/i&gt;</description>
      <category>Observability</category>
      <category>eBPF</category>
      <category>Microservices</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 05 Jun 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/netflix-microservices-realtime/?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>2026-06-05T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/06/netflix-microservices-realtime/en</dc:identifier>
    </item>
    <item>
      <title>Article Series: Securing the AI Stack: From Model to Production</title>
      <link>https://www.infoq.com/articles/secure-ai-stack-model-production-series/?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/articles/secure-ai-stack-model-production-series/en/headerimage/Article-Series-Securing-the-AI-Stack-From-Model-to-Production-header-image-1780040531515.jpg"/&gt;&lt;p&gt;This series provides your roadmap for the machine age, exploring how to move from vulnerable prototypes to resilient systems through layered defense, robust MLOps, and integrated governance.&lt;/p&gt; &lt;i&gt;By Claudio Masolo&lt;/i&gt;</description>
      <category>Security</category>
      <category>AI Security</category>
      <category>Artificial Intelligence</category>
      <category>Article Series</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>article</category>
      <pubDate>Fri, 05 Jun 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/secure-ai-stack-model-production-series/?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>2026-06-05T09:00:00Z</dc:date>
      <dc:identifier>/articles/secure-ai-stack-model-production-series/en</dc:identifier>
    </item>
    <item>
      <title>Google LiteRT-LM Speeds Up Local Inference Up to 2.2x With Gemma 4 Multi-Token Prediction</title>
      <link>https://www.infoq.com/news/2026/06/google-litertlm-gemma4/?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/2026/06/google-litertlm-gemma4/en/headerimage/google-litert-ml-gemma4-1780649451174.jpeg"/&gt;&lt;p&gt;LiteRT-LM brings native support for Gemma 4 Multi-Token Prediction (MTP) drafters, enabling up to 2.2x faster inference. The framework is expanding beyond Kotlin and C++ adding support for new Swift and a JavaScript APIs.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Edge Computing</category>
      <category>Gemma</category>
      <category>TensorFlow</category>
      <category>Google</category>
      <category>Large language models</category>
      <category>Mobile</category>
      <category>Agents</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Fri, 05 Jun 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/google-litertlm-gemma4/?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>2026-06-05T09:00:00Z</dc:date>
      <dc:identifier>/news/2026/06/google-litertlm-gemma4/en</dc:identifier>
    </item>
    <item>
      <title>TypeORM Reaches 1.0 After Nearly a Decade, Signalling Renewed Maintenance</title>
      <link>https://www.infoq.com/news/2026/06/typeorm-1-released/?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/2026/06/typeorm-1-released/en/headerimage/generatedHeaderImage-1780570519122.jpg"/&gt;&lt;p&gt;TypeORM 1.0 is the first major release of the open-source TypeScript and JavaScript ORM since its inception in 2016. This version modernizes platform requirements, removes deprecated APIs, and introduces numerous bug fixes and new features. TypeORM now supports ECMAScript 2023, dropping older Node.js versions and dependencies while enhancing security and migration processes.&lt;/p&gt; &lt;i&gt;By Daniel Curtis&lt;/i&gt;</description>
      <category>JavaScript</category>
      <category>Web Development</category>
      <category>Database</category>
      <category>ORM</category>
      <category>TypeScript</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Fri, 05 Jun 2026 06:52:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/typeorm-1-released/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Daniel Curtis</dc:creator>
      <dc:date>2026-06-05T06:52:00Z</dc:date>
      <dc:identifier>/news/2026/06/typeorm-1-released/en</dc:identifier>
    </item>
    <item>
      <title>30+ Updates per Second per Account: Uber Scales Ledger Processing with Batching</title>
      <link>https://www.infoq.com/news/2026/06/uber-payment-batching-system/?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/2026/06/uber-payment-batching-system/en/headerimage/generatedHeaderImage-1779570527807.jpg"/&gt;&lt;p&gt;Uber introduced a high-throughput financial ledger processing system designed to handle hot account write contention at scale. Using 250ms batching, Redis coordination, and optimistic atomic updates, the system supports 30+ updates per second per account while preserving consistency and auditability, reducing multi-hour processing pipelines to minutes in its distributed accounting infrastructure.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Distributed Systems</category>
      <category>HotSpot</category>
      <category>Event Driven Architecture</category>
      <category>Low Latency</category>
      <category>payment</category>
      <category>Transactions Processing</category>
      <category>Consistency</category>
      <category>Optimization</category>
      <category>Event Stream Processing</category>
      <category>Financial Applications</category>
      <category>Batch Processing</category>
      <category>Performance</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Thu, 04 Jun 2026 14:02:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/uber-payment-batching-system/?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>2026-06-04T14:02:00Z</dc:date>
      <dc:identifier>/news/2026/06/uber-payment-batching-system/en</dc:identifier>
    </item>
    <item>
      <title>How a Culture of Data-Driven Conversations Can Support Platform Engineering</title>
      <link>https://www.infoq.com/news/2026/06/data-driven-platform-engineering/?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/2026/06/data-driven-platform-engineering/en/headerimage/generatedHeaderImage-1780255652688.jpg"/&gt;&lt;p&gt;To provide SRE as a service, a team built a center of excellence, introducing Federated SREs and roles like production manager and technical tribe lead. They created a culture of data-driven conversations where SLOs and SLAs were democratised. Surviving growing cognitive load meant continuously simplifying architecture and embedding sovereignty and resilience into platform design decisions.&lt;/p&gt; &lt;i&gt;By Ben Linders&lt;/i&gt;</description>
      <category>Value &amp; Metrics</category>
      <category>Platform Engineering</category>
      <category>InfoQ Dev Summit Munich 2025</category>
      <category>QCon Software Development Conference</category>
      <category>Resilience</category>
      <category>Platforms</category>
      <category>Metrics</category>
      <category>Cloud</category>
      <category>Site Reliability Engineering</category>
      <category>Culture &amp; Methods</category>
      <category>news</category>
      <pubDate>Thu, 04 Jun 2026 11:54:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/data-driven-platform-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Ben Linders</dc:creator>
      <dc:date>2026-06-04T11:54:00Z</dc:date>
      <dc:identifier>/news/2026/06/data-driven-platform-engineering/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Architecting a Centralized Platform for Data Deletion at Netflix</title>
      <link>https://www.infoq.com/presentations/architecting-deletion-system/?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/architecting-deletion-system/en/mediumimage/medium-1779869686290.jpg"/&gt;&lt;p&gt;The speakers discuss the architectural challenges of executing safe data deletion across distributed datastores. Balancing durability, availability &amp;  correctness, they explain how to orchestrate multi-system deletion propagation without impacting live traffic. They share lessons on controlling tombstone accumulation, building continuous audit loops, and gaining trust with a centralized platform.&lt;/p&gt; &lt;i&gt;By Vidhya Arvind, Shawn Liu&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Platform Engineering</category>
      <category>QCon San Francisco 2025</category>
      <category>Data</category>
      <category>Performance &amp; Scalability</category>
      <category>Reliability</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Thu, 04 Jun 2026 10:26:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/architecting-deletion-system/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Vidhya Arvind, Shawn Liu</dc:creator>
      <dc:date>2026-06-04T10:26:00Z</dc:date>
      <dc:identifier>/presentations/architecting-deletion-system/en</dc:identifier>
    </item>
    <item>
      <title>Article: Architectural Change Cases: A Practical Tool for Evolutionary Architectures</title>
      <link>https://www.infoq.com/articles/architectural-change-cases/?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/articles/architectural-change-cases/en/headerimage/architectural-change-cases-header-1780316814045.jpg"/&gt;&lt;p&gt;Architectural change cases extend architecture decision record (ADR) thinking by evaluating how decisions may evolve over time. Change cases expose hidden assumptions and help teams estimate the reversibility and cost of change.&lt;/p&gt; &lt;i&gt;By Pierre Pureur, Kurt Bittner&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Architecture Documentation</category>
      <category>Architecture Evaluation</category>
      <category>Architecture Decision Records</category>
      <category>Evolutionary Architecture</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Thu, 04 Jun 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/architectural-change-cases/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Pierre Pureur, Kurt Bittner</dc:creator>
      <dc:date>2026-06-04T09:00:00Z</dc:date>
      <dc:identifier>/articles/architectural-change-cases/en</dc:identifier>
    </item>
    <item>
      <title>AWS Replaces Fat-Tree Data Center Networks with Random Graph Theory, Cutting Routers by 69%</title>
      <link>https://www.infoq.com/news/2026/06/aws-random-graph-data-center/?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/2026/06/aws-random-graph-data-center/en/headerimage/generatedHeaderImage-1780475849954.jpg"/&gt;&lt;p&gt;AWS disclosed that Resilient Network Graphs, a flat network architecture based on quasi-random graph theory, is now the default for most new data center builds. The design replaces fat-tree hierarchies with direct ToR-to-ToR mesh connections using passive optical ShuffleBoxes, cutting routers by 69%, boosting throughput by 33%, and reducing network power consumption by 40%.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Amazon Web Services</category>
      <category>AWS</category>
      <category>Infrastructure</category>
      <category>Deployment / Datacenter</category>
      <category>Cloud</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Thu, 04 Jun 2026 08:25:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/aws-random-graph-data-center/?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>2026-06-04T08:25:00Z</dc:date>
      <dc:identifier>/news/2026/06/aws-random-graph-data-center/en</dc:identifier>
    </item>
    <item>
      <title>Next.js 16.2: 400% Faster Dev Startup, Faster Rendering, and Deeper Tooling for AI Agents</title>
      <link>https://www.infoq.com/news/2026/06/nextjs-6-2/?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;Vercel has released Next.js 16.2, featuring performance enhancements that make development startup 400% faster and rendering up to 60% quicker. The update includes AI-assisted development tools, improved Turbopack efficiency, and better error reporting. Migration from Next.js 15 is supported, and compatibility is set for Node.js 20.9 and TypeScript 5.1 or newer.&lt;/p&gt; &lt;i&gt;By Daniel Curtis&lt;/i&gt;</description>
      <category>Next.js</category>
      <category>React</category>
      <category>JavaScript</category>
      <category>Web Development</category>
      <category>TypeScript</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 04 Jun 2026 06:47:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/nextjs-6-2/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Daniel Curtis</dc:creator>
      <dc:date>2026-06-04T06:47:00Z</dc:date>
      <dc:identifier>/news/2026/06/nextjs-6-2/en</dc:identifier>
    </item>
    <item>
      <title>Inside Google’s System for Coordinated A/B Testing across its Global Service Fleet</title>
      <link>https://www.infoq.com/news/2026/06/google-fleet-ab-experimentation/?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/2026/06/google-fleet-ab-experimentation/en/headerimage/generatedHeaderImage-1779569949510.jpg"/&gt;&lt;p&gt;Google has shared details of its fleet wide large scale A/B experimentation system designed to standardize experiment assignment, exposure logging, and configuration propagation across distributed services. The approach enables consistent measurement across products, reduces experiment conflicts, and improves reliability of data driven decision making at scale.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Distributed Systems</category>
      <category>Data-Driven Decision Making Series</category>
      <category>Infrastructure</category>
      <category>Feature Toggle</category>
      <category>Platforms</category>
      <category>Systems Thinking</category>
      <category>Logging</category>
      <category>User Experience</category>
      <category>A/B Testing</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Wed, 03 Jun 2026 14:54:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/google-fleet-ab-experimentation/?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>2026-06-03T14:54:00Z</dc:date>
      <dc:identifier>/news/2026/06/google-fleet-ab-experimentation/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Choosing Your AI Copilot: Maximizing Developer Productivity</title>
      <link>https://www.infoq.com/presentations/choosing-ai-copilot/?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/choosing-ai-copilot/en/mediumimage/medium-1779867439150.jpg"/&gt;&lt;p&gt;Sepehr Khosravi discusses the evolution of developer productivity tools. Evaluating the strengths of tools like Cursor and Claude Code, he explains actionable techniques for senior engineers - including context engineering, custom rules, and Model Context Protocol (MCP) integrations. He shares real-world benchmarks and strategic frameworks for balancing AI adoption with clean code quality.&lt;/p&gt; &lt;i&gt;By Sepehr Khosravi&lt;/i&gt;</description>
      <category>Transcripts</category>
      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
      <category>Agents</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Wed, 03 Jun 2026 11:05:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/choosing-ai-copilot/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Sepehr Khosravi</dc:creator>
      <dc:date>2026-06-03T11:05:00Z</dc:date>
      <dc:identifier>/presentations/choosing-ai-copilot/en</dc:identifier>
    </item>
  </channel>
</rss>
