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    <title>InfoQ - Agents</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Agents feed</description>
    <item>
      <title>Cloudflare Extends AI Search to Make it Easier for Agents and Developers to Search Custom Data</title>
      <link>https://www.infoq.com/news/2026/08/cloudflare-ai-search/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/cloudflare-ai-search/en/headerimage/cloudflare-ai-search-1788105575745.jpeg"/&gt;&lt;p&gt;Cloudflare AI Search is a built-in search and retrieval service designed to give AI agents and applications a ready-to-use search engine over custom data. It supports agent integration, multimodal search, and seamless integration with other Cloudflare tools.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Search Engine</category>
      <category>Cloudflare</category>
      <category>Large language models</category>
      <category>Cloud</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sun, 30 Aug 2026 19:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/cloudflare-ai-search/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-08-30T19:00:00Z</dc:date>
      <dc:identifier>/news/2026/08/cloudflare-ai-search/en</dc:identifier>
    </item>
    <item>
      <title>AWS Open Sources Kiro Crew for Asynchronous Coding Agents</title>
      <link>https://www.infoq.com/news/2026/08/kiro-crew-coding-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/kiro-crew-coding-agents/en/headerimage/generatedHeaderImage-1786904775247.jpg"/&gt;&lt;p&gt;Amazon recently announced Kiro Crew, an open-source system for running multiple Kiro coding agents across sessions, tools, and tasks. The new workspace lets developers assign asynchronous coding tasks to AI agents, allowing work such as incident investigation, ticket triage, migrations, and PR monitoring to continue without active supervision.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Agents</category>
      <category>AI Development</category>
      <category>AI Assisted Coding</category>
      <category>AWS</category>
      <category>AI Coding</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sun, 30 Aug 2026 08:23:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/kiro-crew-coding-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-08-30T08:23:00Z</dc:date>
      <dc:identifier>/news/2026/08/kiro-crew-coding-agents/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Architecting the Data Layer for AI Agents: from Transactional Systems to MCP and Semantic Models</title>
      <link>https://www.infoq.com/presentations/enterprise-data-architecture-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/presentations/enterprise-data-architecture-ai-agents/en/mediumimage/fabiane-nardon-medium-1787218382028.jpeg"/&gt;&lt;p&gt;Fabiane Nardon shares how TOTVS prepares enterprise data for token-hungry AI agents. She discusses balancing deterministic logic and non-deterministic LLMs across precision, security, and cost. Nardon details using data mesh, low-latency database architectures, semantic ontologies, and dynamic MCP tool selection to optimize context windows and reduce token overhead in transactional systems.&lt;/p&gt; &lt;i&gt;By Fabiane Nardon&lt;/i&gt;</description>
      <category>Agents</category>
      <category>QCon AI Boston 2026</category>
      <category>AI Architecture</category>
      <category>AI Security</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Agentic AI Architecture</category>
      <category>AI Cost Optimisation</category>
      <category>Semantic Web</category>
      <category>Large language models</category>
      <category>Data Mesh</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Sat, 29 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/enterprise-data-architecture-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Fabiane Nardon</dc:creator>
      <dc:date>2026-08-29T11:00:00Z</dc:date>
      <dc:identifier>/presentations/enterprise-data-architecture-ai-agents/en</dc:identifier>
    </item>
    <item>
      <title>Uber Builds GitFarm to Run Git Operations as a Service for Large-Scale Monorepos</title>
      <link>https://www.infoq.com/news/2026/08/uber-gitfarm-git-as-a-service/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;Uber’s GitFarm provides Git operations as a centralized service, eliminating local repository clones across large scale monorepo workloads. The platform uses prewarmed checkouts, ephemeral sandboxes, repository synchronization, and gRPC streaming to reduce resource consumption and startup latency for automation services operating across thousands of repositories.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Continuous Integration</category>
      <category>git</category>
      <category>Infrastructure</category>
      <category>Microservices</category>
      <category>GitOps</category>
      <category>Agents</category>
      <category>github</category>
      <category>Continuous Delivery</category>
      <category>GitLab</category>
      <category>Developer Experience</category>
      <category>gRPC</category>
      <category>Management</category>
      <category>Distributed Systems</category>
      <category>Repository</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Fri, 28 Aug 2026 14:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/uber-gitfarm-git-as-a-service/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-08-28T14:30:00Z</dc:date>
      <dc:identifier>/news/2026/08/uber-gitfarm-git-as-a-service/en</dc:identifier>
    </item>
    <item>
      <title>Google Cloud Launches AI-powered Agents to Simplify Database Lifecycle Management</title>
      <link>https://www.infoq.com/news/2026/08/google-database-operation-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/google-database-operation-agents/en/headerimage/google-database-operations-agents-1787842474177.jpeg"/&gt;&lt;p&gt;Google Cloud has introduced AI-powered Database Operations Agents, featuring an Onboarding Agent that streamlines database setup and an Observability Agent that helps automate troubleshooting, performance optimization, and tuning. Integrated with Gemini Cloud Assist, these agents support multiple database services, including AlloyDB, Bigtable, and Spanner.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>Google Cloud</category>
      <category>Gemini</category>
      <category>Cloud</category>
      <category>Database</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 27 Aug 2026 15:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/google-database-operation-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-08-27T15:00:00Z</dc:date>
      <dc:identifier>/news/2026/08/google-database-operation-agents/en</dc:identifier>
    </item>
    <item>
      <title>Cloudflare Wallets Arrives Late to x402, and the Spending Controls Stop at the Payment</title>
      <link>https://www.infoq.com/news/2026/08/agent-payment-rails-x402/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/agent-payment-rails-x402/en/headerimage/generatedHeaderImage-1787649155466.jpg"/&gt;&lt;p&gt;Cloudflare announced Wallets, giving agents a stablecoin balance and spending controls, though only handle claiming is live and squatting complaints have already surfaced. Payments run on x402, now hosted by the Linux Foundation. The controls bound single payments, not sequences, leaving composition to the application above.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Cloudflare</category>
      <category>Generative AI</category>
      <category>Cloud</category>
      <category>Cost Optimization</category>
      <category>Access Control</category>
      <category>DevOps</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 27 Aug 2026 09:04:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/agent-payment-rails-x402/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-08-27T09:04:00Z</dc:date>
      <dc:identifier>/news/2026/08/agent-payment-rails-x402/en</dc:identifier>
    </item>
    <item>
      <title>Diagrid Catalyst 2.0 Adds Durable and Verifiable Execution for AI Agents</title>
      <link>https://www.infoq.com/news/2026/08/diagrid-catalyst-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/diagrid-catalyst-ai-agents/en/headerimage/header-1787430272425.jpeg"/&gt;&lt;p&gt;Diagrid Catalyst 2.0 applies Dapr-based recovery, signed workflow history and execution attestation across several agent frameworks. Architects should compare it with framework-native durability and established workflow engines, while evaluating benchmark evidence and operational trade-offs.&lt;/p&gt; &lt;i&gt;By Mark Silvester&lt;/i&gt;</description>
      <category>Agents</category>
      <category>AI Architecture</category>
      <category>dapr</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Wed, 26 Aug 2026 07:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/diagrid-catalyst-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Mark Silvester</dc:creator>
      <dc:date>2026-08-26T07:00:00Z</dc:date>
      <dc:identifier>/news/2026/08/diagrid-catalyst-ai-agents/en</dc:identifier>
    </item>
    <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=Agents</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>Agents</category>
      <category>Governance</category>
      <category>AI Security</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Cloud Foundry</category>
      <category>Compliance</category>
      <category>AI Policy</category>
      <category>API Gateway</category>
      <category>Microsoft</category>
      <category>Observability</category>
      <category>Model Evaluation</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</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=Agents</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>
    </item>
    <item>
      <title>Google's HEIR Aims to Make Homomorphic-Encrypted Inference a One-Click Capability</title>
      <link>https://www.infoq.com/news/2026/08/google-heir-homomorphic-llm/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/google-heir-homomorphic-llm/en/headerimage/google-heir-llm-1787505393014.jpeg"/&gt;&lt;p&gt;Google is introducing HEIR (Homomorphic Encryption Intermediate Representation), an open-source compiler and development toolchain designed to make encrypted computation easier to deploy. In particular, HEIR can compile pre-trained AI models built for conventional, unencrypted inputs so they can instead operate on encrypted data.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Google</category>
      <category>Open Source</category>
      <category>Large language models</category>
      <category>Fully homomorphic encryption</category>
      <category>PyTorch</category>
      <category>Differential Privacy</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sun, 23 Aug 2026 18:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/google-heir-homomorphic-llm/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-08-23T18:00:00Z</dc:date>
      <dc:identifier>/news/2026/08/google-heir-homomorphic-llm/en</dc:identifier>
    </item>
    <item>
      <title>Cloudflare Announces Kitesurf, a Browser Engine for Agents</title>
      <link>https://www.infoq.com/news/2026/08/cloudflare-kitesurf-browser/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/cloudflare-kitesurf-browser/en/headerimage/generatedHeaderImage-1786287857420.jpg"/&gt;&lt;p&gt;Cloudflare recently introduced Kitesurf, a lightweight browser built for automated workloads. Kitesurf runs browser components in isolated WebAssembly/Rust environments on Cloudflare Workers and supports the Chrome DevTools Protocol, allowing tools such as Playwright and Puppeteer to drive it with lower resource overhead than a full Chromium browser.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Cloudflare</category>
      <category>Generative AI</category>
      <category>Cloud</category>
      <category>WebAssembly</category>
      <category>Web Browser</category>
      <category>Chromium</category>
      <category>Rust</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sat, 22 Aug 2026 15:01:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/cloudflare-kitesurf-browser/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-08-22T15:01:00Z</dc:date>
      <dc:identifier>/news/2026/08/cloudflare-kitesurf-browser/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: SafeChat: Building AI-Powered Safety Systems at Scale in a Real-Time Marketplace</title>
      <link>https://www.infoq.com/presentations/doordash-llm-ai-moderation-platform/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/presentations/doordash-llm-ai-moderation-platform/en/mediumimage/bruna-pereira-medium-1786539036040.jpeg"/&gt;&lt;p&gt;Bruna Pereira explains how DoorDash built a content-agnostic AI moderation platform. She covers replacing costly LLM-only pipelines with a hybrid pattern: using fast internal models to filter obvious cases, LLM multi-axis scoring for nuanced decisions, and no-code workflows with backtesting. Discover how this architectural pattern cut safety incidents while scaling to millions of daily messages.&lt;/p&gt; &lt;i&gt;By Bruna Pereira&lt;/i&gt;</description>
      <category>Agents</category>
      <category>QCon AI Boston 2026</category>
      <category>AI Architecture</category>
      <category>Large language models</category>
      <category>Cost Optimization</category>
      <category>Real-Time Data</category>
      <category>Machine Learning</category>
      <category>Transcripts</category>
      <category>Platform Engineering</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Sat, 22 Aug 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/doordash-llm-ai-moderation-platform/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Bruna Pereira</dc:creator>
      <dc:date>2026-08-22T11:00:00Z</dc:date>
      <dc:identifier>/presentations/doordash-llm-ai-moderation-platform/en</dc:identifier>
    </item>
    <item>
      <title>AI Code Review at Scale: LinkedIn's Multi-Agent Approach</title>
      <link>https://www.infoq.com/news/2026/08/linkedin-ai-code-review/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/linkedin-ai-code-review/en/headerimage/linkedin-code-review-1787387463447.jpeg"/&gt;&lt;p&gt;At LinkedIn's scale, relying solely on human reviewers or simply putting an off-the-shelf AI reviewer in front of GitHub is not an effective way to manage PRs. To address this, LinkedIn engineers built a multi-agent AI code review platform that understands the organization's coding context, treats code review as production infrastructure, and minimizes hallucinations and low-signal feedback.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Kubernetes</category>
      <category>Code Reviews</category>
      <category>LinkedIn</category>
      <category>Large language models</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sat, 22 Aug 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/linkedin-ai-code-review/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-08-22T09:00:00Z</dc:date>
      <dc:identifier>/news/2026/08/linkedin-ai-code-review/en</dc:identifier>
    </item>
    <item>
      <title>AWS Releases aws-bench to Evaluate Agents on Cloud Tasks</title>
      <link>https://www.infoq.com/news/2026/08/aws-bench-agent-evaluation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/aws-bench-agent-evaluation/en/headerimage/generatedHeaderImage-1787307655540.jpg"/&gt;&lt;p&gt;AWS has released aws-bench, an open-source benchmark for evaluating AI agents on real AWS tasks such as misconfigurations and infrastructure provisioning. Unlike traditional benchmarks, it uses real resources in disposable AWS accounts, scoring agent performance through automated verifiers.&lt;/p&gt; &lt;i&gt;By Gianmarco Nalin&lt;/i&gt;</description>
      <category>Agents</category>
      <category>AI Development</category>
      <category>Open Source</category>
      <category>Large language models</category>
      <category>Cloud</category>
      <category>Benchmark</category>
      <category>AWS</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sat, 22 Aug 2026 08:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/aws-bench-agent-evaluation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Gianmarco Nalin</dc:creator>
      <dc:date>2026-08-22T08:00:00Z</dc:date>
      <dc:identifier>/news/2026/08/aws-bench-agent-evaluation/en</dc:identifier>
    </item>
    <item>
      <title>Cloudflare Cuts Astro GitHub Issues by 85% with AI Agents</title>
      <link>https://www.infoq.com/news/2026/08/cloudflare-astro-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/cloudflare-astro-ai-agents/en/headerimage/generatedHeaderImage-1786846443074.jpg"/&gt;&lt;p&gt;Cloudflare, Astro, AI agents, GitHub Actions, issue triage, agentic AI, software architecture, open source, developer tools, AI automation, automated testing, human in the loop, agent workflows, GitHub, software engineering, AI software development, bug triage, continuous integration, developer productivity, autonomous agents, AI coding, Cloudflare Workers, Flue, triagebot&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Agents</category>
      <category>github</category>
      <category>AI Architecture</category>
      <category>Open Source</category>
      <category>Developer Experience</category>
      <category>Cloudflare</category>
      <category>GitHub Actions</category>
      <category>Workflow / BPM</category>
      <category>Bug Triaging</category>
      <category>Automation</category>
      <category>Issue Tracking Tools</category>
      <category>Automated testing</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Fri, 21 Aug 2026 14:09:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/cloudflare-astro-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-08-21T14:09:00Z</dc:date>
      <dc:identifier>/news/2026/08/cloudflare-astro-ai-agents/en</dc:identifier>
    </item>
    <item>
      <title>Mini book: Architecture as a Socio-Technical Craft</title>
      <link>https://www.infoq.com/minibooks/architect-sociotechnical-craft/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</link>
      <description>&lt;img src="https://res.infoq.com/minibooks/architect-sociotechnical-craft/en/smallimage/thumb-1787566215701.jpg"/&gt;&lt;p&gt;Architecture is not a fixed choice made once; fitness is a moving target driven by changing regulations, tech, and markets. Even a sound design can silently stop fitting over time without bad calls. Spanning seven articles on context stores, gateways, and topologies, this collection treats architecture as an evolving sociotechnical craft where teams deliberately shape friction, fitness, and flow.&lt;/p&gt; &lt;i&gt;By InfoQ&lt;/i&gt;</description>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>Leadership</category>
      <category>AI Security</category>
      <category>Sociotechnical Architecture</category>
      <category>Evolutionary Architecture</category>
      <category>InfoQ Certification Program</category>
      <category>Agile</category>
      <category>Domain Driven Design</category>
      <category>Topology</category>
      <category>Architecture ICSAET</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>minibook</category>
      <pubDate>Fri, 21 Aug 2026 11:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/minibooks/architect-sociotechnical-craft/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Agents</guid>
      <dc:creator>InfoQ</dc:creator>
      <dc:date>2026-08-21T11:30:00Z</dc:date>
      <dc:identifier>/minibooks/architect-sociotechnical-craft/en</dc:identifier>
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