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    <title>InfoQ</title>
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    <description>InfoQ feed</description>
    <item>
      <title>Open-Source Project Brings Full iOS 27 Virtualization to Apple Silicon</title>
      <link>https://www.infoq.com/news/2026/09/ios-27-virtualization/?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/2026/09/ios-27-virtualization/en/headerimage/ios-27-virtualization-1789227137098.jpeg"/&gt;&lt;p&gt;The open-Source project vphone-cli enables a full iOS 27 system to run as a virtual machine on Apple Silicon. Built on Apple's own Virtualization.framework rather than traditional emulation, the project opens up new possibilities for security research, reverse engineering, and automated iOS testing.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Apple</category>
      <category>Virtualization</category>
      <category>Mobile</category>
      <category>Mobile Testing</category>
      <category>iOS</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sat, 12 Sep 2026 16:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/ios-27-virtualization/?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>2026-09-12T16:00:00Z</dc:date>
      <dc:identifier>/news/2026/09/ios-27-virtualization/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: From Retrieval to Reasoning: Building Production-Ready Agentic AI Systems with Knowledge Graphs</title>
      <link>https://www.infoq.com/presentations/knowledge-graphs-agentic-systems-patterns/?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/knowledge-graphs-agentic-systems-patterns/en/mediumimage/cassie-shum-medium-1788338916792.jpeg"/&gt;&lt;p&gt;Cassie Shum discusses why knowledge graphs serve as a critical foundation for agentic systems. Moving beyond basic RAG, she explains 4 practical architectural patterns: context bundling, decision provenance, code as truth, and agent visibility. She demonstrates an engineering harness built on a knowledge graph to streamline feedback loops, optimize token usage, and maintain system reliability.&lt;/p&gt; &lt;i&gt;By Cassie Shum&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Transcripts</category>
      <category>Agents</category>
      <category>Agentic AI Architecture</category>
      <category>Retrieval-Augmented Generation</category>
      <category>QCon AI Boston 2026</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Sat, 12 Sep 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/knowledge-graphs-agentic-systems-patterns/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Cassie Shum</dc:creator>
      <dc:date>2026-09-12T11:00:00Z</dc:date>
      <dc:identifier>/presentations/knowledge-graphs-agentic-systems-patterns/en</dc:identifier>
    </item>
    <item>
      <title>Lambda SnapStart Comes to Container Images, Ending a Packaging Tradeoff</title>
      <link>https://www.infoq.com/news/2026/09/lambda-snapstart-container-image/?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/2026/09/lambda-snapstart-container-image/en/headerimage/generatedHeaderImage-1789052932475.jpg"/&gt;&lt;p&gt;AWS has extended Lambda SnapStart to container image functions, which hold up to 10 GB against 250 MB for zip archives. Teams previously chose between dependency headroom and sub-second startup. A Reddit thread from a month earlier shows what that cost: stripping whitespace and docstrings from installed packages to stay under the limit.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>AWS</category>
      <category>Containers</category>
      <category>Performance</category>
      <category>Serverless</category>
      <category>Cloud</category>
      <category>Architecture</category>
      <category>AWS Lambda</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Sat, 12 Sep 2026 10:09:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/lambda-snapstart-container-image/?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>2026-09-12T10:09:00Z</dc:date>
      <dc:identifier>/news/2026/09/lambda-snapstart-container-image/en</dc:identifier>
    </item>
    <item>
      <title>One Decade of Rustls: Evolution, Benchmarks, and Future Roadmap</title>
      <link>https://www.infoq.com/news/2026/09/rustls-one-decade/?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/2026/09/rustls-one-decade/en/headerimage/generatedHeaderImage-1789195676316.jpg"/&gt;&lt;p&gt;Rustls,  a  Rust TLS library, marks its decade-long progression from a grassroots project to a funded open-source initiative. Key contributions from organisations boosted development, resulting in features like post-quantum cryptography and robust performance. The upcoming 0.24 release aims to enhance architecture and flexibility, including new input buffering and improved session handling&lt;/p&gt; &lt;i&gt;By Olimpiu Pop&lt;/i&gt;</description>
      <category>Memory Safety</category>
      <category>Security</category>
      <category>Rust</category>
      <category>Memory Leaks</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sat, 12 Sep 2026 07:07:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/rustls-one-decade/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Olimpiu Pop</dc:creator>
      <dc:date>2026-09-12T07:07:00Z</dc:date>
      <dc:identifier>/news/2026/09/rustls-one-decade/en</dc:identifier>
    </item>
    <item>
      <title>NVIDIA Personal AI Router Distributes AI Tasks across Local Compute</title>
      <link>https://www.infoq.com/news/2026/09/nvidia-pair-ai-task-router/?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/2026/09/nvidia-pair-ai-task-router/en/headerimage/nvidia-ingest-1789135586036.jpeg"/&gt;&lt;p&gt;NVIDIA Personal AI Router (PAIR), now available in beta, lets you combine the inference capacity of multiple computers on your local network and automatically distribute AI requests among them. It is primarily designed for local multi-agent AI workloads, where multiple independent model calls can otherwise overwhelm one GPU.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>GPU</category>
      <category>Large language models</category>
      <category>Orchestration</category>
      <category>Performance</category>
      <category>Agents</category>
      <category>Open Source</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 11 Sep 2026 15:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/nvidia-pair-ai-task-router/?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>2026-09-11T15:00:00Z</dc:date>
      <dc:identifier>/news/2026/09/nvidia-pair-ai-task-router/en</dc:identifier>
    </item>
    <item>
      <title>Netflix Reworks Conductor for 420 Million Monthly Workflow Executions and 10X Larger Workflows</title>
      <link>https://www.infoq.com/news/2026/09/netflix-conductor-4-workflow/?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/2026/09/netflix-conductor-4-workflow/en/headerimage/generatedHeaderImage-1787938102526.jpg"/&gt;&lt;p&gt;Netflix has reworked its Conductor workflow orchestration engine to handle larger workloads, increasing supported workflow size from about 2,500 to 30,000 tasks and reducing p99 workflow evaluation latency by about 40%. Conductor 4.0 separates workflow metadata from task data, moves evaluation to asynchronous processing, and introduces dynamic worker allocation and concurrency controls.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Asynchronous Architecture</category>
      <category>Windows Workflow Foundation</category>
      <category>Orchestration</category>
      <category>Microservices</category>
      <category>Concurrency</category>
      <category>Cloud Architecture</category>
      <category>Java Operator SDK</category>
      <category>Scalability</category>
      <category>Netflix</category>
      <category>Apache Kafka</category>
      <category>Cassandra</category>
      <category>S3</category>
      <category>Distributed Systems</category>
      <category>ElasticSearch</category>
      <category>Workflow Foundation</category>
      <category>Apache Iceberg</category>
      <category>Workflow / BPM</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 11 Sep 2026 14:17:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/netflix-conductor-4-workflow/?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>2026-09-11T14:17:00Z</dc:date>
      <dc:identifier>/news/2026/09/netflix-conductor-4-workflow/en</dc:identifier>
    </item>
    <item>
      <title>tsgolint Reaches Stable v7, Bringing Go-Powered Type-Aware Linting to Oxlint</title>
      <link>https://www.infoq.com/news/2026/09/tsgolint-oxlint-typescript/?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/2026/09/tsgolint-oxlint-typescript/en/headerimage/generatedHeaderImage-1789113850089.jpg"/&gt;&lt;p&gt;tsgolint has released a stable v7, enhancing TypeScript linting with native Go speed. It offers type-aware linting, leveraging TypeScript's semantic analysis through the typescript-go compiler. Oxlint manages configurations and file discovery. The release, compatible with TypeScript 7.0.2, handles 59 of 61 type-aware rules and shows significant performance improvements over ESLint.&lt;/p&gt; &lt;i&gt;By Daniel Curtis&lt;/i&gt;</description>
      <category>Web Development</category>
      <category>Go Language</category>
      <category>ESLint</category>
      <category>TypeScript</category>
      <category>JavaScript</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Fri, 11 Sep 2026 12:02:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/tsgolint-oxlint-typescript/?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>2026-09-11T12:02:00Z</dc:date>
      <dc:identifier>/news/2026/09/tsgolint-oxlint-typescript/en</dc:identifier>
    </item>
    <item>
      <title>Terraform AWS Provider Continues Rapid Expansion as AWS Infrastructure Becomes More Complex</title>
      <link>https://www.infoq.com/news/2026/09/terraform-aws-provider-6-62/?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/2026/09/terraform-aws-provider-6-62/en/headerimage/generatedHeaderImage-1788446872951.jpg"/&gt;&lt;p&gt;The Terraform AWS Provider continues its rapid evolution, with v6.62.0 adding support for new AWS capabilities while improving how Terraform understands and manages existing infrastructure.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>AWS</category>
      <category>Terraform</category>
      <category>Infrastructure as Code</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 11 Sep 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/terraform-aws-provider-6-62/?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>2026-09-11T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/09/terraform-aws-provider-6-62/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: How To Run on Three Clouds at Once, and When Not To</title>
      <link>https://www.infoq.com/presentations/form3-multicloud-architecture/?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/form3-multicloud-architecture/en/mediumimage/ross-mcfarlane-kevin-holditch-medium-1788338652847.jpg"/&gt;&lt;p&gt;Ross McFarlane and Kevin Holditch discuss Form3's evolution from a single-cloud setup to a triple active multi-cloud architecture. They share key engineering strategies for cross-cloud networking, distributed databases with CockroachDB and NATS, custom Kubernetes operators, and navigating distinct regional disaster recovery expectations across the UK, Europe, and US financial markets.&lt;/p&gt; &lt;i&gt;By Ross McFarlane, Kevin Holditch&lt;/i&gt;</description>
      <category>Fintech</category>
      <category>AWS</category>
      <category>Transcripts</category>
      <category>QCon London 2026</category>
      <category>Microservices</category>
      <category>Kubernetes</category>
      <category>CockroachDB</category>
      <category>Architecture</category>
      <category>Cloud</category>
      <category>Resilience</category>
      <category>Availability</category>
      <category>Disaster Recovery</category>
      <category>Architecture &amp; Design</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Fri, 11 Sep 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/form3-multicloud-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Ross McFarlane, Kevin Holditch</dc:creator>
      <dc:date>2026-09-11T11:00:00Z</dc:date>
      <dc:identifier>/presentations/form3-multicloud-architecture/en</dc:identifier>
    </item>
    <item>
      <title>How LinkedIn Trains AI Job Search 8x Faster with Multi-Teacher Distillation</title>
      <link>https://www.infoq.com/news/2026/09/linkedin-ai-multi-teacher/?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/2026/09/linkedin-ai-multi-teacher/en/headerimage/generatedHeaderImage-1789047107399.jpg"/&gt;&lt;p&gt;LinkedIn has published details of the training infrastructure behind its AI-powered job search, describing a multi-teacher distillation pipeline that compresses knowledge from large teacher models into a compact 0.6B-parameter ranking model.&lt;/p&gt; &lt;i&gt;By Claudio Masolo&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Agentic AI Architecture</category>
      <category>Artificial Intelligence</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 11 Sep 2026 10:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/linkedin-ai-multi-teacher/?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>2026-09-11T10:00:00Z</dc:date>
      <dc:identifier>/news/2026/09/linkedin-ai-multi-teacher/en</dc:identifier>
    </item>
    <item>
      <title>Session Traces and Cost Controls Help Diagnose AI Agent Failures</title>
      <link>https://www.infoq.com/news/2026/09/observability-ai-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/2026/09/observability-ai-agents/en/headerimage/header-1788722438219.jpeg"/&gt;&lt;p&gt;Session traces and cost controls are emerging as key observability techniques for diagnosing AI agent failures, helping teams spot tool-call loops and runaway spend while preserving enough execution context for post-incident debugging.&lt;/p&gt; &lt;i&gt;By Mark Silvester&lt;/i&gt;</description>
      <category>Observability</category>
      <category>Agents</category>
      <category>OpenTelemetry</category>
      <category>Monitoring</category>
      <category>Artificial Intelligence</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 11 Sep 2026 08:14:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/observability-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Mark Silvester</dc:creator>
      <dc:date>2026-09-11T08:14:00Z</dc:date>
      <dc:identifier>/news/2026/09/observability-ai-agents/en</dc:identifier>
    </item>
    <item>
      <title>Advancing Embedded Go: Recoverable Panics, UEFI, Radio and Hardware Dev Kit</title>
      <link>https://www.infoq.com/news/2026/09/tinygo-devkit/?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;TinyGo version 0.42 introduces significant updates, including recoverable panics and support for Go 1.27 and LLVM 22, improving error handling and enabling Go code to run as UEFI applications. The TinyGo Starter Kit with Seeed Studio XIAO facilitates hardware use for developers, featuring an ESP32-C3 board and modular sensors. These features enhance its functionality for embedded systems and Wasm.&lt;/p&gt; &lt;i&gt;By Olimpiu Pop&lt;/i&gt;</description>
      <category>Tiny Go</category>
      <category>WebAssembly</category>
      <category>Embedded Software Dev</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Fri, 11 Sep 2026 05:05:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/tinygo-devkit/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Olimpiu Pop</dc:creator>
      <dc:date>2026-09-11T05:05:00Z</dc:date>
      <dc:identifier>/news/2026/09/tinygo-devkit/en</dc:identifier>
    </item>
    <item>
      <title>OpenAI Releases GPT-6 Astra for Coding and Computer Use</title>
      <link>https://www.infoq.com/news/2026/09/openai-gpt6-astra/?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/2026/09/openai-gpt6-astra/en/headerimage/generatedHeaderImage-1789052348407.jpg"/&gt;&lt;p&gt;OpenAI has released GPT-6 Astra, a new model focused on coding, computer use, long-running agentic tasks, and cybersecurity, with availability across ChatGPT, Codex, and the OpenAI API.&lt;/p&gt; &lt;i&gt;By Daniel Dominguez&lt;/i&gt;</description>
      <category>OpenAI</category>
      <category>Large language models</category>
      <category>Anthropic</category>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>ChatGPT</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Thu, 10 Sep 2026 17:49:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/openai-gpt6-astra/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Daniel Dominguez</dc:creator>
      <dc:date>2026-09-10T17:49:00Z</dc:date>
      <dc:identifier>/news/2026/09/openai-gpt6-astra/en</dc:identifier>
    </item>
    <item>
      <title>Beyond Autonomous Teams in Software Product Development</title>
      <link>https://www.infoq.com/news/2026/09/autonomous-software-teams/?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/2026/09/autonomous-software-teams/en/headerimage/Beyond-Autonomous-Teams-in-Software-Product-Development-header-1788790952346.jpg"/&gt;&lt;p&gt;Autonomous teams are an article of faith in modern software development. The shape of our value determines what we can do; it determines our trade-offs between agency and coherence. We all have a purpose, and we all have agency to do something, hence the suggestion is moving from product focus to value center thinking.&lt;/p&gt; &lt;i&gt;By Ben Linders&lt;/i&gt;</description>
      <category>Scrum</category>
      <category>Product Development</category>
      <category>Self-organizing Team</category>
      <category>Business Value</category>
      <category>Complex Systems</category>
      <category>Delivering Value</category>
      <category>Agile Conferences</category>
      <category>autonomous</category>
      <category>Teamwork</category>
      <category>Culture &amp; Methods</category>
      <category>news</category>
      <pubDate>Thu, 10 Sep 2026 10:29:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/autonomous-software-teams/?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>2026-09-10T10:29:00Z</dc:date>
      <dc:identifier>/news/2026/09/autonomous-software-teams/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Accelerating Performance by Incrementally Integrating Rust Into Existing Codebase</title>
      <link>https://www.infoq.com/presentations/rust-refactoring/?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/rust-refactoring/en/mediumimage/lily-mara-medium-1788338447565.jpeg"/&gt;&lt;p&gt;Lily Mara explains how to avoid high-risk software rewrites through incremental FFI refactoring. She shares how engineering teams can replace Python bottlenecks with Rust via PyO3, demonstrating how to achieve dramatic function-level speedups, seamless integration testing, and meaningful infrastructure cost savings without microservice overhead.&lt;/p&gt; &lt;i&gt;By Lily Mara&lt;/i&gt;</description>
      <category>Refactoring</category>
      <category>Transcripts</category>
      <category>QCon San Francisco 2025</category>
      <category>Rust</category>
      <category>Culture &amp; Methods</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Thu, 10 Sep 2026 09:34:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/rust-refactoring/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Lily Mara</dc:creator>
      <dc:date>2026-09-10T09:34:00Z</dc:date>
      <dc:identifier>/presentations/rust-refactoring/en</dc:identifier>
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