Browse All GitHub Copilot Content (392)

Fokko at Work demos the GitHub Copilot and Visual Studio Code 1.138 updates, focusing on sharing Copilot automations, running agent sessions inside local Dev Containers, and improvements to Voice Mode session awareness, with notes on how enterprise policies and pricing plans can affect feature availability.

Jesse Houwing breaks down a nasty PSScriptAnalyzer failure in GitHub Actions where Invoke-ScriptAnalyzer intermittently crashed with a missing Get-Command, then shows how Copilot-assisted investigation, benchmarking, and targeted fixes turned it into a deterministic, faster analyzer with evidence reviewers can rerun.

Allison announces updates to GitHub Copilot’s impact dashboard and reporting APIs, adding 28-day feature engagement metrics so enterprise and organization admins can see which Copilot experiences are being used regularly and where enablement may be needed.

Allison announces expanded GitHub Copilot CLI reporting in the Copilot usage metrics API, adding agentic activity metrics for skills, custom agents, MCP servers, slash commands, and plugins, plus guidance on how counts are calculated and who can access the reports.

Bruno Capuano and Justin Yoo walk through updates to Interview Coach, a .NET sample that uses Microsoft Agent Framework and the GitHub Copilot SDK to build an agent-powered interview practice app with specialist agents, shared MCP tools, and a Blazor UI.

Microsoft Developer shows how to build and customize a hosted agent directly from the GitHub Copilot Chat window using Foundry Canvas, focusing on moving from an initial agent to a more production-ready setup with best-practice checks, generated fixes, observability upgrades, and testing with Agent Inspector.

Hidde de Smet lays out a practical way to judge whether a repo is actually ready for AI coding agents, using GitHub Copilot cloud agent as the concrete example. It focuses on repeatable setup, shared commands, focused tests, CI enforcement, and security boundaries so agent sessions aren’t wasted on missing prerequisites.

Stephen Toub breaks down how GitHub rewrote the Copilot agent runtime from a TypeScript/Node.js/V8 stack into a production Rust runtime, largely using Copilot agents. He explains the architectural drivers (in-process hosting, lower memory, better startup), the incremental port strategy, interop layers, regression patterns, and the measured performance gains.

Aashna Garg and Julia Kasper explain Project HydraFusion in GitHub Copilot, focusing on how orchestrating multiple models per request (instead of selecting a single model) can reduce frontier-model costs, and how the approach is evaluated with demos and benchmarking.

Allison announces general availability of Copilot budget increase requests, letting members request additional AI credits when they hit their limit and enabling org/enterprise owners and billing managers to approve, adjust, or deny requests directly from GitHub settings under usage-based billing.

fiveisprime previews a guided GitHub Copilot experience in VS Code that aims to take developers from an app idea to a deployed Azure application using a structured workflow with explicit checkpoints for scaffolding, local setup, and deployment.

Julia Gong, Ben Liggett, and Ulugbek Abdullaev explain how GitHub Copilot’s inline suggestions in VS Code moved from three separate models (completions, next edit suggestions, and long-distance edits) to a unified “3-in-1” approach, including the diff-patch output format, training strategy, and evaluation methods used to ship it.

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.