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      <title>DoorDash’s Flux Runs 130,000 Engineering Tasks through Cloud-Based Agents</title>
      <link>https://www.infoq.com/news/2026/08/doordash-flux-cloud-agent/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI+Security-news</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;DoorDash has moved engineering agent workloads from developer laptops to its Flux cloud platform. The platform automated 130,000 engineering tasks in one month and supports more than 25,000 automated code reviews weekly. Flux uses isolated Firecracker microVMs, an MCP gateway, reusable playbooks, and multiple invocation surfaces to run agent workflows with scoped access and centralized auditing.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Continuous Improvement</category>
      <category>Infrastructure</category>
      <category>AI Security</category>
      <category>AI Development</category>
      <category>AI Harness</category>
      <category>Cloud</category>
      <category>Code Reviews</category>
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      <category>AI Coding</category>
      <category>VM</category>
      <category>Software Engineering</category>
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      <category>AIOps</category>
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      <pubDate>Mon, 31 Aug 2026 14:28:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/doordash-flux-cloud-agent/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI+Security-news</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-08-31T14:28:00Z</dc:date>
      <dc:identifier>/news/2026/08/doordash-flux-cloud-agent/en</dc:identifier>
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    <item>
      <title>Microsoft Moves AI Governance from Policy to Runtime Enforcement</title>
      <link>https://www.infoq.com/news/2026/08/microsoft-ai-governance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI+Security-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/microsoft-ai-governance/en/headerimage/generatedHeaderImage-1786848804302.jpg"/&gt;&lt;p&gt;Microsoft has outlined an AI governance architecture spanning nine governance domains and four functions: policy, control, visibility, and proof. The approach connects policies with runtime enforcement, continuous evaluation, observability, identity, security, and audit evidence to help organizations verify governance requirements as AI applications and agents operate in production.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Compliance</category>
      <category>Cloud Foundry</category>
      <category>AI Security</category>
      <category>API Gateway</category>
      <category>Model Context Protocol (MCP)</category>
      <category>AI Policy</category>
      <category>Agents</category>
      <category>Observability</category>
      <category>Model Evaluation</category>
      <category>Governance</category>
      <category>Microsoft</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Mon, 24 Aug 2026 13:49:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/microsoft-ai-governance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI+Security-news</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-08-24T13:49:00Z</dc:date>
      <dc:identifier>/news/2026/08/microsoft-ai-governance/en</dc:identifier>
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