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    <title>InfoQ</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ feed</description>
    <item>
      <title>Kubernetes Confidential Containers Get Fortanix Attestation and Key Management</title>
      <link>https://www.infoq.com/news/2026/10/k8s-confidential-containers/?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/2026/10/k8s-confidential-containers/en/headerimage/header-1793049721702.jpeg"/&gt;&lt;p&gt;Fortanix's CoCo integration connects workload attestation to decryption-key release for Kubernetes AI workloads. GPU-verification settings affect protection, while upstream Trustee and Azure Secure Key Release offer alternative routes to attestation-based key release.&lt;/p&gt; &lt;i&gt;By Mark Silvester&lt;/i&gt;</description>
      <category>Containers</category>
      <category>Application Security</category>
      <category>Cloud Native Computing Foundation</category>
      <category>Kubernetes</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Sat, 31 Oct 2026 08:18:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/k8s-confidential-containers/?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>2026-10-31T08:18:00Z</dc:date>
      <dc:identifier>/news/2026/10/k8s-confidential-containers/en</dc:identifier>
    </item>
    <item>
      <title>LocalStack for Azure Enters Public Preview with Security Settings Stored but Not Enforced</title>
      <link>https://www.infoq.com/news/2026/10/localstack-azure-preview/?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/2026/10/localstack-azure-preview/en/headerimage/generatedHeaderImage-1793037893055.jpg"/&gt;&lt;p&gt;LocalStack has opened its Azure emulator to a free public preview, running Azure services locally and accepting existing ARM, Bicep, and Terraform without rewrites. Its own documentation reports partial operation coverage per service and a consistent pattern: configuration is stored and returned, while enforcement of access restrictions, TLS, and network rules is not implemented.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>Infrastructure as Code</category>
      <category>Azure</category>
      <category>Developer Experience</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Sat, 31 Oct 2026 07:57:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/localstack-azure-preview/?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>2026-10-31T07:57:00Z</dc:date>
      <dc:identifier>/news/2026/10/localstack-azure-preview/en</dc:identifier>
    </item>
    <item>
      <title>Google Discloses PageBreak AI Security Agent That Found 500+ XSS Bugs</title>
      <link>https://www.infoq.com/news/2026/10/google-pagebreak-security-agent/?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/2026/10/google-pagebreak-security-agent/en/headerimage/generatedHeaderImage-1791008728252.jpg"/&gt;&lt;p&gt;According to a paper published by Google, its AI-powered security agent has uncovered more than 500 XSS vulnerabilities across its web applications since entering full operation in January. PageBreak uses Gemini models to autonomously investigate potential vulnerabilities, but reports them only after deterministic validators successfully reproduce the exploit against a running application.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Security Vulnerabilities</category>
      <category>Gemini</category>
      <category>Agents</category>
      <category>DevSecOps</category>
      <category>Google</category>
      <category>AI Security</category>
      <category>Information Security</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sat, 31 Oct 2026 06:20:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/google-pagebreak-security-agent/?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>2026-10-31T06:20:00Z</dc:date>
      <dc:identifier>/news/2026/10/google-pagebreak-security-agent/en</dc:identifier>
    </item>
    <item>
      <title>DoorDash Cuts Grocery Reorder Latency from 16 to 2 Seconds with AI Agents</title>
      <link>https://www.infoq.com/news/2026/10/doordash-ai-grocery-reorder/?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 reduced grocery reorder latency from 16 to 2 seconds by precomputing recurring purchase needs using batch LLM inference and deterministic validation. Live catalog resolution keeps product selections current, while an editable shopping interface avoids unnecessary model calls. The company reports that shopping list views doubled and the flow’s order rate increased by approximately 34%&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Agentic AI Architecture</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Low Latency</category>
      <category>Orchestration</category>
      <category>Data Catalog</category>
      <category>Model Inference</category>
      <category>AI Architecture</category>
      <category>API Gateway</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Fri, 30 Oct 2026 13:31:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/doordash-ai-grocery-reorder/?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>2026-10-30T13:31:00Z</dc:date>
      <dc:identifier>/news/2026/10/doordash-ai-grocery-reorder/en</dc:identifier>
    </item>
    <item>
      <title>Netflix Treats GPU Reliability as a Distributed Systems Problem</title>
      <link>https://www.infoq.com/news/2026/10/netflix-gpu-distributed-systems/?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/2026/10/netflix-gpu-distributed-systems/en/headerimage/generatedHeaderImage-1792576903003.jpg"/&gt;&lt;p&gt;Netflix has detailed how it is building a reliability platform for large-scale GPU training and inference, using layered health checks, automated remediation, and fault-tolerant training to keep jobs running despite hardware failures.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>Hardware</category>
      <category>Netflix</category>
      <category>Kubernetes</category>
      <category>Distributed Systems</category>
      <category>AWS</category>
      <category>GPU</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 30 Oct 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/netflix-gpu-distributed-systems/?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>2026-10-30T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/netflix-gpu-distributed-systems/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: The Ladder Is Missing Rungs: Engineering Progression When AI Ate the Middle</title>
      <link>https://www.infoq.com/presentations/ai-software-engineering-pipeline/?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-software-engineering-pipeline/en/mediumimage/alasdair-allan-medium-1791451156021.jpeg"/&gt;&lt;p&gt;Alasdair Allan discusses empirical research from METR and Anthropic on AI coding adoption. He explains the "supervision paradox," where reliance on AI tools disrupts junior skill development, risks institutional context loss, and threatens the long-term engineering pipeline needed to oversee autonomous systems effectively.&lt;/p&gt; &lt;i&gt;By Alasdair Allan&lt;/i&gt;</description>
      <category>Code Reviews</category>
      <category>Careers</category>
      <category>AI Coding</category>
      <category>Claude</category>
      <category>Context Engineering</category>
      <category>Transcripts</category>
      <category>QCon London 2026</category>
      <category>Anthropic</category>
      <category>Leadership</category>
      <category>Productivity</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Culture &amp; Methods</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Fri, 30 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-software-engineering-pipeline/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Alasdair Allan</dc:creator>
      <dc:date>2026-10-30T11:00:00Z</dc:date>
      <dc:identifier>/presentations/ai-software-engineering-pipeline/en</dc:identifier>
    </item>
    <item>
      <title>Netflix Titus Adds Single-Tenant VM Isolation for Containers</title>
      <link>https://www.infoq.com/news/2026/10/netflix-titus-kubernetes-microvm/?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/2026/10/netflix-titus-kubernetes-microvm/en/headerimage/generatedHeaderImage-1793268697529.jpg"/&gt;&lt;p&gt;Netflix has added single-tenant Titus, a mode that runs one task alone on its own right-sized EC2 instance. The Compute/Platform team still owns and patches the host, so application teams keep the same API and deployment path&lt;/p&gt; &lt;i&gt;By Claudio Masolo&lt;/i&gt;</description>
      <category>Netflix</category>
      <category>Kubernetes</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 30 Oct 2026 10:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/netflix-titus-kubernetes-microvm/?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>2026-10-30T10:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/netflix-titus-kubernetes-microvm/en</dc:identifier>
    </item>
    <item>
      <title>Article: InfoQ AI, ML and Data Engineering Trends Report - 2026</title>
      <link>https://www.infoq.com/articles/ai-ml-data-engineering-trends-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/articles/ai-ml-data-engineering-trends-2026/en/headerimage/ai-ml-de-graph-2026-1793191771570.jpg"/&gt;&lt;p&gt;This InfoQ Trends Report offers readers a comprehensive overview of emerging trends and technologies in the areas of AI, ML, and Data Engineering. This report summarizes the InfoQ editorial team’s and external guests' view on the current trends in AI and ML technologies and what to look out for in the next 12 months.&lt;/p&gt; &lt;i&gt;By Srini Penchikala, Chip Huyen, Daniel Dominguez, Hien Luu, Arthur Casals&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Model Context Protocol (MCP)</category>
      <category>InfoQ Trends Report</category>
      <category>Artificial Intelligence</category>
      <category>Agent2Agent</category>
      <category>AI coding agents</category>
      <category>InfoQ Trends Report 2026</category>
      <category>Robotics</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>article</category>
      <pubDate>Fri, 30 Oct 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/ai-ml-data-engineering-trends-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Srini Penchikala, Chip Huyen, Daniel Dominguez, Hien Luu, Arthur Casals</dc:creator>
      <dc:date>2026-10-30T09:00:00Z</dc:date>
      <dc:identifier>/articles/ai-ml-data-engineering-trends-2026/en</dc:identifier>
    </item>
    <item>
      <title>Podcast: AI, ML, and Data Engineering InfoQ Trends Report 2026</title>
      <link>https://www.infoq.com/podcasts/ai-ml-data-engineering-trends-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/podcasts/ai-ml-data-engineering-trends-2026/en/smallimage/trend-reports-thumbnail-1793181579584.jpg"/&gt;&lt;p&gt;In this episode, members of the InfoQ AI and ML editorial staff and friends of InfoQ discuss the current trends in the domain of AI, ML and Data Engineering. One of the regular features of InfoQ are the trends reports, which each focus on a different aspect of software dev. These reports provide the InfoQ readers and listeners with a high-level overview of the topics to pay attention to this year.&lt;/p&gt; &lt;i&gt;By Chip Huyen, Daniel Dominguez, Hien Luu, Arthur Casals&lt;/i&gt;</description>
      <category>The InfoQ Podcast</category>
      <category>Model Context Protocol (MCP)</category>
      <category>InfoQ Trends Report</category>
      <category>Context Engineering</category>
      <category>InfoQ Trends Report 2026</category>
      <category>Multi-Model Databases</category>
      <category>AI Harness</category>
      <category>Large language models</category>
      <category>Frontier Model</category>
      <category>Artificial Intelligence</category>
      <category>Agent2Agent</category>
      <category>Spec Driven Development</category>
      <category>Robotics</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>podcast</category>
      <pubDate>Fri, 30 Oct 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/podcasts/ai-ml-data-engineering-trends-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Chip Huyen, Daniel Dominguez, Hien Luu, Arthur Casals</dc:creator>
      <dc:date>2026-10-30T09:00:00Z</dc:date>
      <dc:identifier>/podcasts/ai-ml-data-engineering-trends-2026/en</dc:identifier>
    </item>
    <item>
      <title>Microsoft Retires Azure Deployment Environments with No Replacement Product</title>
      <link>https://www.infoq.com/news/2026/10/ade-dev-box-retirement/?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/2026/10/ade-dev-box-retirement/en/headerimage/generatedHeaderImage-1792499241111.jpg"/&gt;&lt;p&gt;Azure Deployment Environments retires on February 22, 2027 and Microsoft names no successor, telling teams to use Bicep or ARM templates directly. Microsoft Dev Box follows on September 18, 2028, pointed at Windows 365, which Microsoft says is not a one-to-one replacement. Remaining Dev Box workloads should expect deletion.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>Azure</category>
      <category>Software Development</category>
      <category>Culture &amp; Methods</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 30 Oct 2026 08:13:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/ade-dev-box-retirement/?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>2026-10-30T08:13:00Z</dc:date>
      <dc:identifier>/news/2026/10/ade-dev-box-retirement/en</dc:identifier>
    </item>
    <item>
      <title>Google Adopts DPoP to Strengthen OAuth 2.0 against Token Theft and Replay Attacks</title>
      <link>https://www.infoq.com/news/2026/10/google-dpop-oauth2/?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;Google's OAuth Platform has recently introduces support for Demonstrating Proof-of-Possession (DPoP), an OAuth 2.0 security mechanism designed to mitigate token theft and replay attacks.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>OAuth</category>
      <category>Cloud Security</category>
      <category>Google</category>
      <category>Cryptography</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 29 Oct 2026 19:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/google-dpop-oauth2/?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>2026-10-29T19:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/google-dpop-oauth2/en</dc:identifier>
    </item>
    <item>
      <title>Bug0 Releases QA Agent to Automate Regression Testing With Cached Playwright Replays</title>
      <link>https://www.infoq.com/news/2026/10/bug0-agent-testing-cached-replay/?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/2026/10/bug0-agent-testing-cached-replay/en/headerimage/generatedHeaderImage-1793286673185.jpg"/&gt;&lt;p&gt;QA Agent is a new source-available Playwright library for agentic browser regression testing. The agent associates test instructions expressed in natural language to actions on the user interface, caches those when appropriate for faster CI replays, remapping them to test specifications when the user interface changes. Verification is based on multi-model consensus and vision model evaluations.&lt;/p&gt; &lt;i&gt;By Bruno Couriol&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Regression Testing</category>
      <category>AI Coding</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Thu, 29 Oct 2026 15:17:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/bug0-agent-testing-cached-replay/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Bruno Couriol</dc:creator>
      <dc:date>2026-10-29T15:17:00Z</dc:date>
      <dc:identifier>/news/2026/10/bug0-agent-testing-cached-replay/en</dc:identifier>
    </item>
    <item>
      <title>How to Make Artificial Intelligence More Environmentally Sustainable</title>
      <link>https://www.infoq.com/news/2026/10/AI-environmentally-sustainable/?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/2026/10/AI-environmentally-sustainable/en/headerimage/header-1793174464846.jpg"/&gt;&lt;p&gt;IT is responsible for about 2 - 4% of all global emissions, and electricity use at Microsoft and Google has climbed because of AI, according to their own reports. Sustainability ought to be a top-level architectural concern. Some recommendations are: use pre-built and smaller models, run compute where low-carbon electricity is abundant, and train on renewable energy.&lt;/p&gt; &lt;i&gt;By Ben Linders&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>GOTO Conference</category>
      <category>Data</category>
      <category>Green Software</category>
      <category>IT</category>
      <category>Sustainable Computing</category>
      <category>Cloud Computing</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Culture &amp; Methods</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 29 Oct 2026 11:41:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/AI-environmentally-sustainable/?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>2026-10-29T11:41:00Z</dc:date>
      <dc:identifier>/news/2026/10/AI-environmentally-sustainable/en</dc:identifier>
    </item>
    <item>
      <title>QCon AI New York 2026 Program Committee Picks: Agent Identity, Context Costs, and Open-Source Infere</title>
      <link>https://www.infoq.com/news/2026/10/qcon-ai-newyork-2026-pc-picks/?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/2026/10/qcon-ai-newyork-2026-pc-picks/en/headerimage/qcon-ai-newyork-2026-pc-picks-1793192613417.jpg"/&gt;&lt;p&gt;Who authorizes an agent’s actions, and how should teams manage growing context costs? The QCon AI New York 2026 program committee shares six session picks that tackle these questions, alongside open-source inference, agent standards, and audio AI.&lt;/p&gt; &lt;i&gt;By Artenisa Chatziou&lt;/i&gt;</description>
      <category>Open Source</category>
      <category>QCon AI New York 2026</category>
      <category>Agents</category>
      <category>QCon Software Development Conference</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Thu, 29 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/qcon-ai-newyork-2026-pc-picks/?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>2026-10-29T11:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/qcon-ai-newyork-2026-pc-picks/en</dc:identifier>
    </item>
    <item>
      <title>Anthropic Says Nobody Needs a Mental Model of Claude Code. Practitioners Are Testing That</title>
      <link>https://www.infoq.com/news/2026/10/anthropic-code-review/?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/2026/10/anthropic-code-review/en/headerimage/generatedHeaderImage-1792959100117.jpg"/&gt;&lt;p&gt;Anthropic has published how the Claude Code team reviews code now that Claude writes roughly 90% of it, including a claim that nobody keeps a complete mental model of the codebase. The post documents a pull request that ran more than fifty review rounds overnight, a reviewer spending most of its effort on pre-existing code, and a control the team says it does not yet have.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Code Reviews</category>
      <category>Anthropic</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Culture &amp; Methods</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Thu, 29 Oct 2026 09:58:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/anthropic-code-review/?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>2026-10-29T09:58:00Z</dc:date>
      <dc:identifier>/news/2026/10/anthropic-code-review/en</dc:identifier>
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