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，同时为你留出足够的空间，以便随着技术栈和需求的变化进行调整。 从任务出发 从你需要自动化的那部分 IT 工作开始。如果你要预置基础设施或管理配置，请考虑配置管理工具。如果工作集中在设备、补丁和远程支持上，RMM 更合适。ITSM 工具适用于服务流程，而工作流编排则是为需要跨应用、API 和内部系统流转的流程而构建的。 其他自动化工具可能与这些类别并存。像 GitHub Actions 这样的 CI/CD 工具专注于软件交付，而测试自动化工具则处理验证代码和应用程序等任务。它们属于更广泛的 IT 自动化领域，但解决的问题比本文涵盖的平台更为具体。 在开始比较产品之前，先梳理出你想要自动化的流程以及涉及的系统。这样你缩小选项范围会比在针对完全不同工作的工具之间比较功能列表要容易得多。 确定你需要多少控制权 部署方式也是缩小选项范围的一种有用方法。SaaS 产品可能更容易启动运行，而自托管则让你对自动化程序和数据所在的位置拥有更多控制权。哪种方式更合适取决于你的基础设施、安全要求，以及你希望团队管理多少平台内容。 然后看看当更多人开始使用它时会发生什么。当自动化触及关键系统或跨越多个团队时

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ber 7, 2026 Microsoftは、8月に発表したMAI-Code-1.1-Flashのローカル版を今回用意した。モデルの重みを少ないビット数で表す3ビット量子化などにより、同モデルのクラウド版と比べて容量を約80%削減したという。 処理の振り分けを担うHydraFusionは、性能、費用、応答時間を考慮して、使うAIモデルとその組み合わせ方を選ぶGitHub Copilotの機能。1つのモデルでタスクを解くほか、必要なら高性能なモデルに引き継いだり、別のモデルに回答案をレビューさせてから修正したりする。 HydraFusionは、クラウド上のモデルを対象にリサーチプレビューで提供されている。今回の拡張では、PC上のローカルモデルも自動選択の対象に加え、タスクに応じてローカルとクラウドを使い分ける。この拡張の実験的プレビューは、10月後半にGitHub Copilotアプリ、GitHub Copilot CLI、Visual Studio Codeで提供する予定。 同日にWindows 11での一般提供が発表されたMicrosoft Execution Containers（

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working with Jev and users managing their own decision model. Unsloth’s security-audit workflow uses read-only repository permissions and non-persisted checkout credentials. Every GitHub Action is pinned to a full commit hash, and outbound-network allowlists block unexpected egress. CodeQL covers Python, JavaScript/TypeScript, Rust and GitHub Actions. Unsloth says it runs Codex Security and repeated Codex reviews during development to catch security issues and bugs. Library Access and Changes Un

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gravity, Gemini CLI, Claude Code, or Cursor), install the agents-cli-aqua skill (skills/agents-cli-aqua/SKILL.md) alongside the inner-loop evaluation skill (npx skills add https://github.com/google/agents-cli --skill google-agents-cli-eval). We are sharing AQuA in the open to collaborate with teams running agents in production and shape where this goes together. As you try it on your stack, we'd love to hear what you think: Does a side-by-side quality agent fit your architecture? Which parts of

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for Python 3.9 and adds support for Python 3.15. Highlights include: Stabilized MISSING sentinel; Support for lazy imports; Support for TypeForm You can see the full changelog on GitHub. Quick Reference New Features; Changes; Performance Building agents in production? See what they're actually doing with Logfire — traces, evals, cost, and behavior in one view. New Features Pydantic 2.14 officially supports Python 3.15, including most of the new features it introduces. These are covered first. S

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get’s material contracts Deliverables produced by each model Harvey LAB-AA resources The leaderboard and full results live on the Harvey LAB-AA evaluation page, updated as new models are released; The methodology page documents the full implementation, including the agent and rubric grading prompts; Harvey's original LAB announcement introduces the benchmark and its design; A public set of representative tasks is available on GitHub; Harvey LAB-AA runs on Stirrup, our open-source agent framework

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orward paths: Community feedback and Contributions ML Drift is fully open source under the Apache 2.0 license. We welcome contributions, RFCs, and community feedback: Source Code: github.com/google-ai-edge/ml-drift; Issue Tracker & Feature Requests: File an Issue on GitHub; Discussions & Q&A: Google AI Edge Community Forum; Contributing: Review our Contributing Guide to add new UCL operators or hardware-specific optimizations Acknowledgments: Bring multimodal semantic search to the edge with Emb

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e through Claude Platform on AWS in North America Give Claude Haiku 5.5 a try on the Amazon Bedrock console, in Claude Platform on AWS, or explore the Getting Started notebooks on GitHub. About the authors Aamna Najmi Aamna is a Senior Specialist Solutions Architect for Generative AI focusing on Anthropic models and operationalizing and governing generative AI systems at scale on Amazon Bedrock. She helps ISVs solve their challenges, embrace innovation, and create new business opportunities with

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s can post, without posting its intro; [Claude Tag] Changed the limit on channel rules in Claude Tag admin settings from 20 to 50 for each workspace and for the organization-wide Slack page; [Code Review] Improved Code Review's Add a repository dialog to list each repository that couldn't be added and why, such as missing GitHub write access Uh oh! There was an error while loading. Please reload this page. 👍 11 reactions; 😄 3 reactions; 🎉 7 reactions; ❤️ 5 reactions; 🚀 3 reactions; 👀 4 reactions

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arden your system? RSVP here. • Entire – Git hosting, rebuilt for the agentic era. Entire hosts your code in-region, and is up to 89x faster than any other competitor. Mirror from GitHub with a single click – I’ve already done so. Sam Newman wrote one of the most-read books about microservices (“Building Microservices”), but he calls them an architecture of “last resort.” In this episode of the Pragmatic Engineer podcast, Sam explains his thinking on this, and he’s certainly well placed to do so

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s using eight B200 GPUs Next Steps Run the cuOpt mPDLP tutorial to install cuOpt, configure the solver, and compare solve times across GPU counts; Explore the cuOpt source code on GitHub for APIs, solver settings, and deployment guidance Supply chain problems are expanding across more SKUs, lanes, and constraints than ever before, while energy grids are balancing more distributed sources in real time. To meet these challenges, teams need to evaluate larger models and more uncertainty within a pr

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before executing, following the same human-in-the-loop pattern that the remediation solution itself uses. To deploy manually, follow these steps. Clone the AWS CDK code hosted on GitHub:; Navigate to the directory sample-automate-remediation-post-devops-agent-investigation:; Bootstrap the AWS CDK. This is required the first time you use the AWS CDK in a specific AWS environment (a combination of an AWS account and AWS Region); Deploy the stack: The AWS CDK automatically provisions and configure

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nt. By default, the agent gets tools for every provider connected to the project; you can limit which providers and tools it uses. This example limits the agent to Notion, Linear, GitHub, and Slack, and removes delete, archive, and merge tools: Tool entries accept globs, and new connections show up in the running app without a redeploy. Channels Connections can also put your agents in Slack, Discord, or Telegram. Pass channels() to the Mastra constructor and the platform supplies each channel's

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results. AICR v1.0 sets compatibility rules for: aicr CLI’s public commands, flags, exit semantics, and structured output; aicrd REST API and OpenAPI contract; exported API of the github.com/NVIDIA/aicr/pkg/client/v1 package; generated bundle layout and AICR artifact schemas Each public interface has a committed baseline checked before changes merge. The release policy also defines semantic breaking changes. After v1.0, removing or incompatibly changing a stable public interface requires a new m

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$2 Sonnet vision), with a built-in AWS Budget that alerts at 80 percent and 100 percent of a cap you set. The full source code is available in the sample-agentcore-memory-openclaw GitHub repository. Clean up When you are done experimenting, tear everything down to avoid ongoing charges. Because the whole system is one CloudFormation stack, cleanup is mostly a single delete: Delete the CloudFormation stack. This removes the AgentCore runtime agent, API Gateway, the Lambda functions, the Amazon Ev

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thread while Claude was still on its first request there being held until that request finished, or missed when sent seconds apart; [Claude Tag] Fixed Slack threads woken only by GitHub pull request activity or a routine staying on their original model after an admin changed the channel or workspace default model; [Claude Tag] Fixed Claude sometimes posting a spend limit notice in Slack when the real cause was that your organization had run out of usage credits; [Claude Tag] Fixed a session han

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, compare the outputs, then expand until you are comfortable making Databricks the primary home for your dbt project. Ready to try it? Set up a Databricks free trial; Install the dbt-databricks adapter; Run your first dbt compile against a Databricks Lakehouse warehouse. Afterwards, deploy a Databricks Job to execute a dbt model in production by following the Databricks documentation For more on dbt with Databricks, explore the dbt-databricks adapter on GitHub. Get the latest posts in your inbox

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at this exact point. It came after I had the chance to visit the AI labs OpenAI and Anthropic, meet innovative startups like Ramp, Uber and others, get new, unpublished data from GitHub, Factory AI and Linear. The focus of the talk is trend inside of AI labs, VC-funded startups and Big Tech. Thanks to the kind access to these teams! Before the conference, I spent weeks identifying and recording trends that didn’t exist a year ago – or were much more nascent back then – and also things that are

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onfigured with credentials; AWS CDK CLI 2.x installed with npm install -g aws-cdk, and your account bootstrapped with npx cdk bootstrap; The accompanying code from the aws-samples GitHub repository Deploy the solution with AWS CDK The solution deploys with a single CDK script. Clone the repository, configure your AWS credentials, and run the deployment script. For detailed deployment steps, see the README in the GitHub repository. The sample airline data model API Gateway publishes a REST API wi

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マイクロソフトは9月30日付けでリリースされたVisual Studio Code 1.140（以下、VS Code）で、複数のAIベンダから提供されているAIモデルをオーケストレーションすることでより高品質で低コストを実現するという「HydraFusion」機能をリサーチプレビューとして実装したことを明らかにしました（VS Codeのリリースノート、GitHubブログ）。 HydraFusion is now available in @code as a Research Preview. Instead of relying on a single model, HydraFusion orchestrates multiple models and workflows to tackle coding tasks. Give it a try today! HydraFusionとはマイクロソフトの研究プロジェクトであり、GitHubのブログ「Project HydraFusion: Frontier quality via multi-model orchestration」

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