Explains GitHub’s screen-reader improvements for issue and pull request timelines and the accessible web design practices behind meaningful navigation and dynamic updates.
Learn how GitHub's draft pull request counting setting helps maintainers enforce contributor pull request limits through repository settings or the REST API.
GitHub now allows users with triage and higher repository roles to archive and unarchive pull requests. Learn how archiving differs from closing and locking pull requests.
Explains how GitHub's AI-based secret detection complements pattern scanning, reduces false positives, and guides developers in validating, revoking, and rotating exposed credentials.
Learn how Claude Haiku 5.5 expands GitHub Copilot model choices and how to select models for coding, debugging, refactoring, and agentic workflows.
Learn how GitHub Copilot CLI can discover local AI models and what local inference means for coding-agent privacy, hardware, latency, capability, and operational control.
Learn how GitHub Copilot local sandboxing restricts AI coding agent commands to help protect developer machines, repositories, credentials, and other host resources.
Learn how GitHub Security Overview displays effective AI Scan status across repositories, supports filtering and CSV exports, and helps teams identify gaps in pull request security coverage.
Learn why GitHub Copilot agent activity may be undercounted or attributed to Copilot CLI, and why updating supported IDEs is necessary for accurate usage metrics.
Explains why AI coding agents need Git workflows built for isolated worktrees, temporary state, concurrent tasks, and safe automated repository operations.
Learn how GitHub stacked pull requests split dependent changes into smaller reviews, manage branch dependencies, and improve review feedback cycles.
Learn how GitHub's Security Advisory API exposes CVE and dependency vulnerability data for automated security workflows, with a C# API client example.
Learn how npm trusted publishing uses CI/CD identities and OIDC, why configurations can expire, and what to review in GitHub Actions package publishing workflows.
Learn how npm staged publishing separates package preparation from promotion, enabling validation, safer CI/CD workflows, and reduced risk from incorrect releases.
Learn how GitHub Secret Scanning detects Supabase and Pydantic tokens, and how to rotate exposed credentials, clean Git history, and use secure configuration.
Learn how to prepare applications for longer GitHub App tokens by removing format assumptions and reviewing credential storage, validation, logging, and transmission.
Learn how to design asynchronous GitHub pull request merge automation with ASP.NET Core background workers, queues, retries, and idempotent job processing.
Learn how to integrate the GitHub Copilot Code Review API into internal tools, CI/CD workflows, and developer portals while handling authentication, permissions, and human review.
Learn how GitHub Copilot Computer Use lets AI agents interact with desktop apps, including GUI workflows, limitations, use cases, and how it compares with APIs and traditional automation.
AI agents are becoming capable of performing tasks that previously required direct developer involvement. An agent can generate code, execute scripts, process files, query services, and combine multiple tools to complete a request. That capability creates a security problem that traditional applicat
Learn how to configure Podman with Visual Studio Container Tools and debug containerized .NET and ASP.NET Core applications using breakpoints and IDE diagnostics.
Learn how to use Visual Studio's Git Agent to review pull requests with repository context, assess code and tests, and identify security and regression risks.
Learn how Visual Studio and NuGet auditing identify vulnerable direct and transitive packages, and how to review and safely remediate dependency updates.
Learn how to connect your own AI model or deployment to Visual Studio BYOM, configure supported providers, and use the model with the Agent experience.
Learn how to prepare Kubernetes clusters and workloads for cgroup v2, including node checks, cgroup drivers, runtime compatibility, and resource-limit testing.
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