Browse All Artificial Intelligence Content (868)
Microsoft Developer explains practical ALM patterns for taking Copilot Studio agents from experimentation to production, focusing on repeatable deployments, environment isolation, and governance-friendly configuration using solutions, environment variables, and connection references.
Microsoft Developer presents a session on building agentic user interfaces across Copilot and the Power Platform, with demos that connect Copilot and Power Apps and a look at newly released MCP app UI capabilities for creating custom, purpose-built interfaces.
Microsoft Developer kicks off the Agent Academy Hackathon, explaining how to participate and what kinds of AI agents you can build with Copilot Studio, along with links to the Agent Academy learning path and hackathon registration.
Microsoft Developer explains why AI agents that look good in demos can fail in production, and outlines a practical approach to testing agents built with Microsoft Copilot Studio—covering prompts, grounding, actions, and orchestration under real user behavior.
Microsoft Developer walks through building employee experience AI agents with Microsoft Copilot Studio, showing how to connect knowledge grounding with real workflows using MCP-based integrations and Power Platform automation across several practical workplace scenarios.
syedarshad walks through a practical workflow for testing AI agents with LangSmith, using Azure OpenAI as the target model. The guide shows how to build an evaluation dataset, run LLM-as-judge scoring (correctness and hallucination checks), and interpret per-example and aggregate results with tracing and experiment views.
Leon Welicki explains how Power Platform is positioning existing Power Apps (canvas, model-driven, and code apps) for “agentic” workflows, including how agents integrate into apps, how Microsoft 365 Copilot can surface app fragments via MCP, and how developer tools like GitHub Copilot plug into the same managed platform.
Microsoft Developer introduces agent flows in Microsoft Copilot Studio, focusing on how to build agentic automations that stay reliable for business-critical processes by combining deterministic, structured steps with AI-driven judgment where it’s needed.
NandiniMuralidharan shows how to connect browser-harness to Playwright Workspaces so an AI coding agent can drive a real, cloud-hosted Chromium browser over CDP, enabling parallel, isolated sessions for tasks like scraping and interacting with JavaScript-heavy sites.
Satya Nadella shares an update on Microsoft’s multi-model agentic security system, which uses 100+ specialized agents across frontier and custom models to find exploitable bugs, topped the CyberGym benchmark, and helped identify and fix 16 vulnerabilities ahead of Patch Tuesday, with a private preview now available.
Taesoo Kim announces MDASH, Microsoft Security’s multi-model agentic scanning harness, and explains how it uses specialized AI agents to find, validate, and prove vulnerabilities end-to-end. The post shares benchmark results, details 16 Patch Tuesday CVEs found in Windows networking/auth components, and includes two technical deep dives.
Taesoo Kim introduces MDASH, Microsoft’s multi-model agentic scanning harness, and explains how it’s being used to find and validate real Windows vulnerabilities end-to-end. The post breaks down the pipeline stages (prepare/scan/validate/dedup/prove), shares benchmark results, and details 16 Patch Tuesday CVEs plus two technical deep dives.
stclarke summarizes Microsoft and Red Hat’s Red Hat Summit 2026 updates for Azure Red Hat OpenShift, focusing on running modern apps and production AI with enterprise governance. It highlights OpenShift Virtualization for VM-to-Kubernetes migration, identity and confidential computing features, GPU-backed AI workloads, and expanded regional availability.
Allison announces improvements to GitHub Copilot code review comments in pull requests, aimed at making feedback easier to scan and act on with severity labels and grouped suggestions to reduce repetitive noise.
Allison announces that April usage reports are now available so GitHub Copilot admins and individual users can estimate how activity maps to AI credits ahead of the June 1 move to usage-based billing, including known gaps and data-quality issues in the report.
Jingwei Wang introduces “Open in VS Code” from Azure Copilot in the Azure Portal, a guided workflow that takes AI-generated Terraform configurations into an Azure-hosted VS Code environment so teams can validate, configure state backends, and deploy to Azure with fewer handoffs.
Natalie Guevara announces updates to GitHub Copilot’s individual plans ahead of the June 1, 2026 move to usage-based billing, including new “flex allotments” for Pro and Pro+ and a new Max plan for higher-volume usage.
samkemp announces Foundry Local 1.1.0, adding on-device live speech transcription, text embeddings for semantic search/RAG, and an Open Responses API client for streaming, tool calling, and vision. The post also covers WebGPU as an optional plugin, smaller JavaScript packages, and broader .NET compatibility for the C# SDK.
Sandra Ahlgrimm explains how to customize GitHub Copilot’s modernization task lists so teams can modernize legacy Java apps safely: set constraints, split risky upgrades into smaller reviewable steps, validate the current state first, and ensure Copilot surfaces CVEs without making silent changes.
Lee Reilly explains how he used GitHub Copilot CLI—especially /delegate—to build “GitHub Dungeons”, a GitHub CLI extension that turns any repository into a terminal roguelike. The post covers the core idea (seeded by commit SHA), how Copilot’s agent workflow fit into iteration, and the BSP approach used for dungeon generation.
Microsoft Developer hosts Agent Academy Live, a one-day virtual event focused on building production-ready AI agents with Microsoft Copilot Studio, with practical sessions on real-world agent patterns, governance, and architecture, followed by a hands-on hackathon.
kinfey explains why AI agents running model-generated code need stronger isolation than standard containers, then walks through deploying a GitHub Copilot SDK agent on AKS using Kata Containers (kata-vm-isolation) plus layered hardening like seccomp, NetworkPolicy egress allowlists, and deny-by-default tool permissions.
Nick Brady’s April 2026 digest covers Microsoft Foundry updates for model access, local inference, agent observability, and SDK changes across Python, JavaScript/TypeScript, .NET, and Java, with concrete guidance on quota tiers, tracing via OpenTelemetry, and monitoring/evaluation features for production agents.
vikas_gautam introduces PII Shield, a privacy proxy that sits in front of LLM calls to detect and anonymize PII (with optional reversal) so raw identifiers don’t leak through prompts, gateways, logs, or observability pipelines.
vyomnagrani explains why Microsoft built Azure AI Foundry Agent Service on Azure Container Apps, focusing on what changes when AI agents move from prototypes to production: bursty execution, long-running workflows, secure tool execution, isolation, state persistence, and the operational requirements for running agent fleets reliably at scale.
stclarke summarizes the April 2026 Copilot Studio updates, focusing on scaling AI agents with stronger governance, clearer analytics visibility, and more capable workflows. It also covers new integration options like apps-in-agents, MCP-enabled tools (preview), evaluation automation APIs, and multi-agent collaboration features.
osmancokakoglu announces the winners of the AI Dev Days Hackathon and summarizes the projects and the Microsoft stack they used, including Azure AI Foundry, Azure OpenAI models, and the Microsoft Agent Framework, plus common Azure services and DevOps practices used to ship production-grade agentic apps.
Sandra Ahlgrimm demonstrates an end-to-end database migration for a Java application, moving from Oracle DB to PostgreSQL using the GitHub Copilot app modernization extension in IntelliJ, including dependency and configuration updates, bug fixes during setup, and manual verification before and after the migration.
Kedasha Kerr explains what open source is and walks beginners through finding beginner-friendly repositories on GitHub, evaluating whether a project is well maintained, and making a first contribution using a fork-and-pull-request workflow (with an example prompt for GitHub Copilot Chat).
Shireesh Thota summarizes the main architecture trends from Cosmos DB Conf 2026, focusing on how teams are building AI-native apps on Azure Cosmos DB with flexible data models, serverless scale, and first-class semantic/vector search, plus practical patterns for agent memory, cost visibility, and multi-user security.
Jesse Houwing breaks down why GitHub Copilot is moving from Premium Request Units to token-based, usage-based billing, and what that means for model selection, cost predictability, and newer features like Agent Mode, Cloud Coding Agent, and Copilot Code Review—especially for organizations managing budgets and policies.
John Savill explains why enterprises need a data virtualization layer and how to build one using Microsoft Fabric OneLake, including a single namespace approach, shortcuts, mirroring, governance, and semantic models to make data easier to use for analytics and AI.
This roundup tracks a clear shift from agent capability to agent governance: more context, more observability, and more policy controls across Copilot, VS Code, and the CLI. On the platform side, Microsoft tightened the path from prototype to production with .NET agent building blocks, Azure AI Foundry deployment patterns, and data governance improvements that make RAG and operations easier to standardize. We also cover the less flashy work that keeps systems dependable at scale, including Fabric and Databricks operational updates, GitHub migration and ruleset changes, and security research that keeps token theft, privilege escalation, and supply chain risk in focus.
SagarPatra explains how enterprise QA teams can use GitHub Copilot to reduce the mechanical overhead of writing and maintaining automated tests, while keeping trust through human review, governance, and intentional test design that supports reliable regression cycles.
Authorised Territory demonstrates how to build an end-to-end durable workflow for an AI agent pipeline using the .NET Microsoft Agent Framework, running the Durable Task Scheduler Emulator in Docker Desktop and streaming workflow events in real time, with a local Ollama LLM.
Allison announces that Grok Code Fast 1 will be deprecated across GitHub Copilot experiences on May 15, 2026, and outlines what Copilot Enterprise admins need to do to ensure alternative models are available for users.
Allison announces an update to the GitHub Copilot usage metrics API that adds a breakdown of Copilot code review suggestions by comment type, helping enterprises and organizations understand what kinds of review feedback Copilot generates and how often developers apply it.
John Savill runs through the Azure updates for 8th May 2026, covering changes across compute, storage, Kubernetes, databases, and Azure AI services, including retirements and new capabilities that may affect existing deployments.
shwetayadav explains how index-based Terraform for_each keys can trigger destructive disk churn on Azure, and shows a safer migration approach using stable keys plus terraform state mv, with a reusable GitHub Copilot skill to generate deterministic state-move commands.
Yoshio Terada shares a real-world Java modernization story: migrating a Java 5 / Struts 1.3 monolith to Java 21 and Spring Boot in about two days using GitHub Copilot’s app modernization tooling, with a strong focus on planning, custom instructions, and verification to keep AI-driven changes reliable.