Browse All Artificial Intelligence Content (850)

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.

Brendan Burns explains why Microsoft was named a Leader in the 2026 Gartner Magic Quadrant for Container Management, and uses the announcement to outline how AKS, Azure Container Apps, Azure Arc, and Fleet Manager are positioned for AI, hybrid, and edge container operations at scale.

Allison announces a public preview that adds GitHub REST API endpoints for enabling and managing GitHub code scanning’s AI Scan for pull requests at both the organization and repository level, making it easier to roll out AI-powered security detections across selected repos without manual UI configuration.

yaronc announces a preview Fabric REST API that exposes item lineage as a dependency graph you can query from code, enabling automated impact analysis, documentation/catalog scenarios, CI/CD checks, and richer context for AI agents that need to reason about upstream sources and downstream consumers.

Rena Liu announces Azure AI Speech LLM 2607 and explains what changes for developers building speech-to-text and real-time voice experiences, including better multilingual and mixed-language recognition, improved punctuation and numeric transcription, lower latency, and a simpler phrase list parameter for domain-specific customization.

Steven Truitt shares a hands-on walkthrough of using Microsoft Discovery as AI assistance to take a small chip-design project from a rough spec through C and HLS, into Verilog RTL, and finally to physical layout and basic timing/power optimization using open-source EDA tooling.

Microsoft Security Research breaks down a large-scale business email compromise campaign that used AI-assisted executive impersonation and fake invoices to push finance teams into fraudulent ACH payments, and maps practical mitigations using Microsoft Defender for Office 365, Defender XDR, and Security Copilot.

Steve Sweetman explains how to govern AI agent spend in Microsoft Foundry by combining request-path token limits, observability (traces, monitoring, evaluations), and finance-grade budgets, then tying those signals to ROI so teams can decide what to optimize, scale, or retire.

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.

Microsoft Developer introduces Toolboxes in Microsoft Foundry as a way to make MCP (Model Context Protocol) integrations more enterprise-ready, with centralized governance, consistent authentication, and reusable configuration across multiple agents and tools.

Microsoft Developer discusses the MCP Triggers & Events experimental extension, showing how agents can poll MCP servers for events and be triggered via webhooks, and what new event-driven agent architectures this enables.

Caitie McCaffrey reviews the current state of the Model Context Protocol (MCP), focusing on the major changes in the 2026-07-28 specification release and what they mean for developers building AI agents and agent-to-agent communication patterns.

Microsoft Developer explains why Dynamic Client Registration becomes a scaling problem for MCP clients, and how switching to Client ID Metadata Documents turns the client_id into a durable, URL-based identity that servers can fetch on demand.

Jeremiah Lowin shows how MCP Apps can render interactive UI (buttons, charts, forms) directly inside AI clients, and walks through building these experiences in Python using FastMCP and Prefab—from basic components to dynamically generated interfaces.

Den Delimarsky explains how MCP authorization evolved, covering the original OAuth profile, protected resource metadata, changes to client registration, and how enterprise-managed authorization fits into the model.

Microsoft Developer demonstrates how to build modern Model Context Protocol (MCP) servers in VS Code, moving beyond simple local tool calls to more production-ready agent integrations with notifications, elicitation, stateless HTTP, and plugin-based distribution.

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.

Jakub Oleksy’s August 2026 GitHub availability report breaks down five production incidents across GitHub Actions, authentication, and Copilot services, including what failed, how GitHub mitigated impact, and what reliability work is planned next (capacity, autoscaling, retries, and regional failover).

Authorised Territory demonstrates how to build domain-specific AI agent evaluators in .NET using Microsoft Agent Framework connected to a local Ollama model, then run automated checks against the agent’s responses to validate both content and output structure.

Nick Brady rounds up July and August 2026 updates for Microsoft Foundry, including GA for Hosted Agents, Voice Live integration, and Toolboxes, plus Model Router pool/region changes and new model releases. It also calls out SDK migrations (Python/JS/Java/.NET) and runtime requirement bumps you should test before upgrading.

willchap describes a practical framework for evaluating scientific AI systems—execution, optimization, and exploration—using three RF engineering design challenges. The post shows how Microsoft Discovery orchestrates agentic workflows that combine analytical reasoning with HFSS simulations, while surfacing assumptions, trade-offs, and decision points for human guidance.

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.

Microsoft Developer demonstrates how to build a no-code AI agent in the Azure AI Foundry Portal: create a Foundry project, deploy a model, connect an MCP server for a cupcake store scenario, then validate the agent using tracing, token usage metrics, and evaluations.

Marco Casalaina breaks down Foundry IQ, Fabric IQ, Work IQ, and Web IQ, explaining them as grounding capabilities that give AI agents the right context. He maps each “IQ” to the underlying data source (knowledge bases, OneLake, Microsoft 365 apps, and the public web) and what it enables.

MinseokSong walks through a reference implementation that uses Microsoft Foundry and an Azure Function to classify incoming support emails, then uses Power Automate to validate the AI recommendation against a SharePoint allow-list, require human approval, and create an Outlook draft (without sending).

christinchen announces the general availability of Azure Copilot’s Troubleshooting Agent, a built-in experience in the Azure portal that helps teams investigate and resolve operational issues faster by combining resource context, supported diagnostics, and recommended actions—while keeping customers in control through identity and RBAC.

The Visual Studio Code Team shares the VS Code 1.138 Insiders changelog, focusing on Agent Host and Agents window improvements like shareable session links, side-by-side agent sessions, repo-first context attachment for issues/PRs, voice mode session awareness, and agent-session cleanup controls.

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.