Browse All GitHub Copilot Content (395)

Allison announces a public preview feature where GitHub Copilot suggests allowed values while admins define repository custom properties, helping organizations build consistent governance metadata that can be used to scope rulesets across large fleets of repositories.

Pamela_Fox shares the full set of MCP Live session recordings and resources, covering the Model Context Protocol’s latest spec updates, MCP server/client development in VS Code and GitHub Copilot, enterprise governance with Microsoft Foundry Toolboxes, and evolving MCP authentication patterns.

Aaron Powell shows how to baseline and then raise unit test coverage in the Interview Coach app using Visual Studio’s code coverage tooling and GitHub Copilot’s Test Agent, moving from targeted tests for a single class to solution-wide analysis and test generation.

Justin Yoo walks through a sample “Interview Coach” app that uses the GitHub Copilot SDK as an agent runtime (outside the editor) to run an interview workflow: ingest a resume, ask behavioral/technical questions, store session context, and generate end-of-interview feedback using MCP tools and Agent Framework handoffs.

GitHub shows how to hand off an active GitHub Copilot app session into VS Code so you can keep working in your editor without losing context, including the task plan, conversation history, diffs, and an isolated git worktree, then push changes back to a pull request.

Microsoft Developer shows how to use GitHub Copilot with a Microsoft Foundry skill to review and refactor an existing “Sparkle Cupcakes” agent, aligning it with current Foundry patterns and SDK guidance while improving production readiness.

Wuyi Weng explains how Azure SRE Agent can use an Azure Managed Grafana dashboard (via the MCP endpoint) as executable context to investigate GitHub Copilot telemetry in Application Insights, turning panel queries, variables, and descriptions into fast, accurate triage and per-session diagnoses.

Mariyaali announces the general availability of the SQL DW operations skill for Microsoft Fabric Data Warehouse, which lets teams use natural-language prompts (for example via GitHub Copilot CLI) to run bounded, read-only diagnostics and get structured findings, evidence, and recommended next steps for common warehouse incidents.

Allison announces new configuration tiers for GitHub Copilot auto model selection—efficiency, balance, and intelligence—so teams can control how Copilot trades off cost, response quality, and response time per prompt, with billing based on the model selected.

This week's GitHub Copilot updates pushed agentic workflows from "use at your own risk" toward something admins can govern and teams can run every day. Enterprise managed permissions for agent operations and JetBrains sandbox controls make it possible to enforce runtime guardrails (block, allow, or require approval) across common risk areas like shell access, files, and outbound domains. On the workflow side, the Copilot app, VS Code Agents, and CLI routing updates reduced friction in multi-step work, while code review and Code Quality autofix features moved PRs and static analysis closer to an "agent-assisted" default. Rounding it out, new usage metrics for VS Code Agents, a MAI-Code-1-Flash deprecation, and more guidance on MCP and BYOK setups give platform teams clearer levers for rollout, measurement, and cost control.

Allison announces new generally available GitHub Copilot usage metrics that track activity in the dedicated VS Code Agents window, including both aggregate (enterprise/org) and per-user fields for 1-day and 28-day reporting periods.

Allison announces improvements to GitHub Copilot code review, including automatic resolution of addressed review comments, smarter commit message suggestions when applying Copilot fixes, and deeper review analysis using Copilot SDK shell tools plus an ensemble approach for Lite reviews.

Tomoko Tanaka shows how her team turned event marketing runbooks into “ops as code” using GitHub Issues, GitHub Actions, and GitHub Copilot. The post breaks down the repo patterns (issue forms, labels, skills in Markdown, and a DRY_RUN switch) that automate setup, daily screening, and post-event reporting with guardrails.

John Savill shares a quick Azure Weekly Update covering recent platform changes and previews, including VM ephemeral OS disk caching, Azure Functions Flex Consumption custom TLS, user delegation SAS updates, AZD extension framework work, Azure Load Testing Playwright expansion, and new Copilot-related items.

Martin Woodward shares his pick for a new GitHub Copilot feature: the GitHub Copilot app, a native Windows and Mac experience aimed at agentic coding workflows across issues and pull requests, with isolation via separate Git worktrees.

Fokko at Work demos selected new GitHub Copilot features in Visual Studio Code 1.137, including automations, attaching GitHub issues and pull requests directly in chat, and voice mode, with notes on how enterprise policies and pricing plans can affect feature availability.

Visual Studio Code shows how to connect your own Azure-hosted AI models to GitHub Copilot in VS Code using Bring Your Own Key (BYOK), so teams can control which models are available in Copilot and pick the right model for different coding tasks.

Allison summarizes the September 7 weekly GitHub Copilot releases, including Jira integration in the Copilot app, Project HydraFusion model orchestration in Copilot CLI, new agent automations and voice mode updates in VS Code, and expanded enterprise sandbox controls for Copilot in JetBrains.

Kayla Cinnamon explains how to review agent-generated changes inside the GitHub Copilot app using three built-in panels: a diff view for inspecting edits, a terminal for running project commands, and a browser preview for validating UI changes before creating a pull request.

Allison announces the deprecation of the MAI-Code-1-Flash model across GitHub Copilot experiences and points Copilot Enterprise admins to the steps needed to enable the replacement model via Copilot model policies and settings.

Visual Studio Code announces a new “VS Code pet” coding companion that you can trigger from GitHub Copilot Chat in VS Code using the /vscode-pet command, and invites the community to submit name ideas during a one-week window.

Juan Montes profiles Kinaxis’ Maestro platform and how it uses Azure (including AKS, Databricks, Azure OpenAI, Cosmos DB, and Azure AI Content Safety) to run large-scale supply chain scenario modeling, forecasting, and agentic AI experiences. The piece also touches on Kinaxis’ internal use of GitHub Copilot for an agentic, PR-driven development workflow.

Sam Morrow discusses GitHub’s Model Context Protocol (MCP), covering what his team is shipping across MCP server and client implementations, plus the spec areas he’s most excited about and what’s coming next.

Allison announces generally available enterprise managed permissions for GitHub Copilot agent operations, letting admins centrally decide which actions are blocked, require human approval, or run without prompting across supported Copilot clients.

Allison announces agentic autofix for GitHub Code Quality, letting teams select up to 25 findings and assign them to GitHub Copilot in one action. Copilot applies fixes on a branch, validates the changes, and opens a pull request for review, with usage governed by existing enterprise policy and AI credits.

Waldek Mastykarz explains how to pick a “minimal viable model” for AI coding work by running your own evals instead of defaulting to the most expensive option. Using GitHub Copilot Chat in VS Code, he compares model quality scores and per-run costs across real upgrade scenarios to show why “smarter” can be worse value.

Allison announces updates to GitHub Copilot for JetBrains, including enterprise-managed sandbox policies, cross-file cursor jumps for next edit suggestions, global project context in chat, and enterprise policy diagnostics. The release also adds a preview integration that connects Copilot CLI terminal sessions to IDE context and improves reliability across MCP and agent sessions.

bharadwajr explains how the Azure team built GEM (Great Experiences Matter), an AI-enabled “feedback-to-fix” loop that aggregates customer feedback at scale, turns it into prioritized insights, and creates actionable Azure DevOps work items with an auditable evidence trail and human review.

Allison announces GitHub Enterprise Server (GHES) 3.22 general availability, highlighting updates for enterprise administration and collaboration, including Copilot CLI support for disconnected environments, enterprise teams, improvements to repository rulesets and required reviewers, and UI enhancements for issues and pull requests.

Justin Yoo walks through a practical profiling workflow for distributed .NET apps, showing how to identify which process owns a slow user interaction, use Visual Studio CPU profiling to rule out CPU-bound work, and then measure hidden async waiting that doesn’t show up in CPU samples.

GitHub explains how to make GitHub Copilot work better in a real project by giving it durable context about your repo. It covers adding custom instructions under .github, defining repeatable “skills” for tasks like testing, using custom agents for bigger workflows, and connecting MCP servers such as Playwright.

Maddy Montaquila explains how a “Aspire-ified” .NET app can give a coding agent more context and control, including a single command to start containers, processes, and the debugger, plus the ability to manage resources and view logs from one place.

Andrea Griffiths and Meagan Cojocar demonstrate GitHub Copilot Cloud Agent running inside Slack and Microsoft Teams, showing how teams can create issues, review diffs, preview HTML, and analyze repository data directly from chat, plus what admins need to enable it safely in enterprise environments.

John Savill recaps the major Microsoft AI updates from August 2026, including new and updated models, routing and content-understanding changes, and a set of Copilot and Azure Copilot improvements that affect how teams use AI features across developer and enterprise environments.

This week in the Weekly GitHub Copilot Roundup, the model lineup expanded (GPT-6 Astra GA, plus Gemini 3.8 Flash and Claude Fable 5.1) while deprecations and policy updates made it clear that model choice is now an admin and billing decision as much as a developer preference. At the same time, Project HydraFusion signaled a shift from picking one model to routing work across multiple models, with early experiments showing how orchestration can balance quality, latency, and spend. Governance also tightened across agent workflows, with content exclusions reaching the Copilot app and CLI, clearer identity constraints for cloud agents in Actions, and new budget expiration controls. On the workflow side, VS Code kept making agent sessions more reviewable, and Copilot code review entered a new phase with optional approvals that can satisfy branch protection rules if you choose to enable them.

Allison’s weekly Copilot changelog highlights new model options (Claude Fable 5.1 and Gemini 3.8 Flash), stronger content protection via honored content exclusions in Copilot app/CLI, and VS Code 1.136 updates aimed at managing agent sessions and getting pull requests ready to merge.

Allison announces general availability of OpenAI’s GPT-6 Astra in GitHub Copilot, highlighting its strength on long-horizon, agentic coding tasks, how it’s billed under usage-based pricing, and where developers and admins can enable and select the model across supported IDEs and clients.

sbaynes shares a short update on HydraFusion in GitHub Copilot, highlighting a shift from picking a single model to orchestrating multiple models that plan, build, critique, and complete coding tasks, with a claim of up to 67% lower cost for comparable outcomes.

Jesse Houwing explains why GitHub Copilot cloud agent sessions can’t be spawned from GitHub Actions using GITHUB_TOKEN, and how GitHub’s accountability model (identity, billing, and auditability) shapes what “agentic workflows” can do today. He then lays out practical orchestration patterns that work, with concrete YAML examples.

GitHub introduces Project HydraFusion and shares benchmark results claiming higher verified task quality and lower estimated cost versus Claude Opus 5 on Terminal-Bench 2.1. The short also points developers to try HydraFusion as a selectable model via the /experimental feature in GitHub Copilot CLI.