Browse All Artificial Intelligence Content (1146)

Visual Studio Code shows how to give GitHub Copilot more context by sharing your running website through VS Code’s Integrated Browser, so Copilot can reference what you’re seeing while you work.

Fokko at Work walks through selected new features in Visual Studio Code 1.129 related to GitHub Copilot, using short demos and calling out that availability can vary based on enterprise policies and pricing plans.

Waldek Mastykarz explains how to evaluate agent skills that call APIs without paying for test traffic or mutating production data. He outlines why direct evals against real endpoints create cost, state, and non-determinism problems, then shows a proxy-based approach using Dev Proxy to emulate APIs while keeping production URLs unchanged.

Hidde de Smet audits a local SKILL.md “skills” library spread across Claude Code, a shared .agents catalog, and GitHub Copilot’s VS Code setup, showing how silent failures (missing files, duplicates, stale references) accumulate over time and how to stocktake them with a checklist and a couple of shell one-liners.

olivialiu-micro explains how SQL Server 2025 enables governed outbound calls to external AI services while keeping control inside the database security model, including permissions, enablement switches, authentication options, and built-in auditing for REST invocation and external model objects.

Lee Stott invites AI engineers to a Microsoft Foundry Discord round table on scaling agent apps beyond demos, focusing on how Foundry Toolbox, Skills, and Tool Search reduce tool sprawl, prompt bloat, and auth plumbing by centralizing tools behind a governed MCP endpoint with runtime discovery.

Rafia Aqil explains Microsoft’s IQ Platform (Work IQ, Fabric IQ, and Foundry IQ) and how it adds business and organizational context to AI systems. The post breaks down Fabric’s OneLake-based data layer, ontology-driven meaning, and Foundry IQ’s managed services for RAG, memory, ranking, and citations.

Pablo Lopes announces a free, open-source course that guides developers through modernizing a legacy ASP.NET app to .NET 10 using the GitHub Copilot modernization agent, including assessment and planning artifacts, an execution workflow, and a final deployment to Azure App Service.

Microsoft Developer walks through what’s new in Data API builder (DAB) 2.0, focusing on how it sits between an app and a database to expose APIs without writing custom CRUD endpoints. The overview highlights new secrets management, broader authentication options, improved authorization controls, and integration points.

Yesenia Yser and Toby Kohlenberg explain why AI agents need to be treated as first-class security principals, with tightly scoped roles, controlled tool access, and end-to-end auditability to prevent quiet permission creep and hard-to-investigate incidents.

Lily Ma explains why synchronous MCP tool calls break down for long-running work, and shows a practical Azure Functions + Durable Functions pattern you can use today while the MCP Tasks extension rolls out across clients and SDKs.

jordanselig explains the new stable Enterprise-Managed Authorization (EMA) extension for MCP and how it differs from a centrally governed OAuth setup using Microsoft Entra ID and Azure App Service Authentication. The post includes a working sample, a local EMA lab, and practical security details for deploying an Entra-governed MCP endpoint.

Noa Kuperberg breaks down how billing works for the Azure Copilot Observability Agent in Azure Monitor, including what gets metered, which operations are billable, where users can see per-response usage, and how to track costs in Azure Cost Management alongside standard Azure Monitor charges.

GitHub hosts a live Rubber Duck Thursday session exploring the new GPT-5.6 models (Luna, Terra, Sol) inside the GitHub Copilot App, focusing on what changes when you switch models and how that affects Copilot’s behavior during real-time usage.

Authorised Territory demonstrates how to add console telemetry to a .NET AI agent harness by wiring up a trace provider and emitting traces using OpenTelemetry, with a local Ollama model (gpt-oss) used as the LLM runtime.

Manasa Ramalinga lays out a practical reference map for governing enterprise AI and autonomous agents, focusing on how to turn responsible AI policy into enforceable controls, runtime visibility, and audit-ready proof using Microsoft’s governance, security, and observability services.

jordanselig shares a reference implementation for giving an AI agent both short-term conversation history and durable, user-scoped memory on Azure App Service, using Redis for bounded session history and Cosmos DB vector search for recall, with keyless auth via managed identity and a one-command azd + Bicep deployment.

Giles Odigwe announces the production release of Agent Skills for Python in Microsoft Agent Framework, explaining how to package reusable domain expertise (instructions, resources, and scripts) that agents can load on demand, with governance features like approvals, filtering, caching, and controlled script execution.

Davide Mauri shares a practical first tip for developers who are new to Microsoft Azure and want to start building a full-stack AI application while keeping costs under control, pointing viewers toward Azure’s Budget Bytes guidance and related Azure services.

John Edward explains why AI agents that look great in demos often break down in production, and what teams need to engineer around the model to make agents reliable at scale.

Rachel Kang explains new Visual Studio features for working with GitHub Copilot models: pinning favorites in the model picker, comparing model capabilities (like context window size and vision support), and tracking context window and plan usage so long-running chats don’t catch you off guard.

Waldek Mastykarz explains how to design AI coding-agent evaluations (AX evals) that produce real signal instead of misleading scores, focusing on representative prompts, precise pass/fail/skip criteria, judge calibration, and enough repeated runs to separate variance from actual improvements.

Krishna Roy shows how to load test Copilot Studio agents by simulating real multi-turn conversations over Direct Line (HTTP + WebSockets) with Locust, then running the same workload in Azure Load Testing. The post covers measuring TTFB vs full turn completion, handling turn.complete, file uploads, and secret handling with Key Vault.

Pamela Fox shows how to build an MCP server that returns more than plain text: image thumbnails as binary tool results and an interactive MCP app (a carousel) rendered inside VS Code, so GitHub Copilot can search, inspect, and present curated image results.

Allison summarizes the June 2026 GitHub Copilot update for Visual Studio 2026, focusing on new usage tracking and alerts, a trust validation layer for MCP servers, and Copilot features that tie into pull request workflows and C++ modernization.

Allison announces updates to GitHub Copilot for JetBrains, including BYOK custom endpoint support, expanded plugin-based customizations, Claude provider support for custom agents, and local sandboxing in public preview, plus UX and reliability improvements across chat, model selection, and CLI sessions.

Allison announces a public preview feature where GitHub code scanning surfaces AI-powered security detections directly on pull requests, helping teams catch issues in languages and frameworks that don’t have native CodeQL coverage. The update explains what’s included, how it runs, enablement requirements, and how billing works via AI credits.

Simona Liao, Wendy Breiding, and Yun Jung Choi introduce Visual Studio 18.8’s built-in Agent Skills, a set of reusable Copilot capabilities for common .NET and Azure tasks. The post explains where to find and enable skills, why they’re off by default, and highlights starter skills for API work, performance reviews, Azure deployments, and Kusto queries.

Michael Washington explains how he built AI Story Builders, an open-source app that uses structured story data, embeddings, and RAG, plus a knowledge-graph layer, to help authors generate more coherent fiction and query story context more reliably.

arindamc shows how to build a “row-to-intelligent-action” pipeline in Microsoft Fabric: capture Azure SQL changes via CDC into Fabric Eventstreams, reshape them with DeltaFlow, enrich each micro-batch in Spark Structured Streaming using AI Functions for PySpark, and publish Business Events for real-time routing and dashboards.

Visual Studio Code shows how to run language models locally in VS Code using the Ollama extension, including configuring custom models, bring-your-own-key providers, and utility model settings, with an emphasis on keeping processing private on your machine.

Allison announces a public preview feature in the GitHub Copilot app: the /security-review slash command, which runs an on-demand security review of your in-flight code changes and returns prioritized findings with suggested fixes you can apply and re-check without leaving Copilot.

Lee Stott tours Microsoft’s open-source course on taking AI agents from prototype to production using Microsoft Agent Framework and Microsoft Foundry, covering agent design, multi-agent orchestration, evaluation, deployment, data sovereignty, and tool governance with concrete commands and code patterns.

jisunchoi explains how to replace “multi-model chaos” with a governed AI gateway on Azure using Azure API Management, covering cost controls (token quotas and budget-based model downgrades), security hardening (managed identity + private endpoints), observability with Application Insights, and a Terraform-based deployment you can integrate with GitHub Copilot.

Bruno Capuano and Pablo Nunes Lopes host a .NET + AI Community Standup covering recent updates around agent development in .NET, running models locally, and using GitHub Copilot in modernization scenarios, with pointers to Microsoft Learn resources for getting started.

ofer announces a new OneLake Architectural Guidance whitepaper and summarizes five repeatable enterprise patterns for building a unified, governed data foundation in Microsoft Fabric, aimed at analytics modernization and AI readiness, including data access unification, medallion architecture, governed data mesh, platform simplification, and external data sharing.

abhimittal shows how to use Azure API Management (APIM) as an AI gateway in front of Azure AI Foundry to capture per-model token usage for governance. The post walks through an inbound policy that authenticates with managed identity, emits token metrics to Azure Monitor/Application Insights, and adds edge protection with Azure Front Door + WAF.

Microsoft Developer demonstrates a real-time 3D digital twin of a wind farm built in Microsoft Fabric, combining LiDAR-derived terrain geometry, live turbine telemetry from a Fabric Eventhouse, and a natural-language interface that can identify underperforming turbines and estimate cost impact.

Helen Hou-Sandí explains how GitHub addressed an accessibility issue in pull requests where status checkmarks were hard to distinguish, and how the team used GitHub Copilot to quickly investigate unfamiliar code and ship a design fix that improves the PR review experience.

kinfey shares a reference implementation for running long-lived autonomous coding agents from Microsoft Teams, using MCP as the control plane and Azure Container Apps dynamic sessions as a Hyper-V-isolated sandbox. The post focuses on multi-agent orchestration, deployment reliability under platform timeouts, and practical security guardrails like auth, allowlists, private ingress, and managed identities.