Browse All Artificial Intelligence Content (785)

DevClass.com reports on GitHub’s private preview of Stacked PRs, a workflow for breaking large changes into smaller, independently reviewable pull requests that can still depend on each other, with an optional gh stack CLI that’s also intended to work well with AI agents.

PrabhKaur (co-authored with Avneesh Kaushik) lays out an architecture-focused checklist for building AI agents in Microsoft Foundry with security, observability, least privilege, continuous validation, and human accountability built in from the start.

Allison explains a new GitHub Copilot Cloud Agent (CCA) admin capability: enterprise admins can now enable the agent for selected organizations (including via organization custom properties), and manage the policy through the AI Controls page or new REST API endpoints.

Yun Jung Choi explains that Azure MCP tools are now built into Visual Studio 2022 via the Azure development workload, letting developers enable an Azure MCP Server inside GitHub Copilot Chat to provision resources, deploy apps, and troubleshoot Azure services without installing a separate extension.

Cassidy Williams interviews GitHub Staff Software Engineer Brittany Ellich about building a personal “command center” app, focusing on how GitHub Copilot CLI and agent-based workflows supported the process from planning through implementation.

simonjj shares an Azure Developer CLI template that deploys Google’s Gemma 4 (via Ollama) onto Azure Container Apps serverless GPU with an OpenAI-compatible endpoint, protected by an Nginx basic-auth proxy, plus steps to verify the API and wire it into the OpenCode terminal coding agent for private, in-subscription prompting.

Phillip Misner and Stephen Finnigan explain how incident response changes for AI systems: non-determinism and high-volume output shift triage, containment, telemetry needs, and remediation verification, while many IR fundamentals (ownership, escalation, and communication) still apply.

Harshada Hole introduces Visual Studio’s Debugger Agent guided workflow, which uses a live debugging session to help you reproduce bugs, validate hypotheses via breakpoints and call stacks, and iterate to a verified fix with less manual setup.

Fernando Vasconcellos outlines evergreen cloud cost optimization principles and explains how AI workloads change cost patterns, with practical guidance on visibility, governance, rightsizing, and continuous review—framed around managing and optimizing spend on Azure over time.

GitHub shares how staff software engineer Brittany Ellich built a personal “productivity hub” using GitHub Copilot CLI, including an AI chat agent (“Marvin”), unified task lists, and calendar integrations, with the goal of learning by building your own AI tools.

Jesse Houwing summarizes GitHub’s update that GitHub Copilot can now keep inference processing and associated data within US or EU data residency regions, and shows the enterprise/org policy you must enable to restrict Copilot to data-resident models.

Reenu Saluja breaks down the main Azure hosting options for production AI agents and explains when to use each, with a deeper walkthrough of Microsoft Foundry Hosted Agents (deployment, lifecycle management, observability, scaling, and invocation patterns).

sachoudhury explains GitHub Copilot Custom Skills: repo- or user-scoped SKILL.md “runbooks” that Copilot can discover and execute in agent mode to automate multi-step developer workflows (commands, scripts, and report generation).

David Sanchez lays out a practical DevOps playbook for teams adopting AI coding agents (including GitHub Copilot Cloud Agent), focusing on readiness prerequisites, human–agent collaboration patterns, pipeline changes, governance, and security controls needed to keep quality and accountability intact as non-human contributors scale up.

Joseph Katsioloudes introduces Season 4 of GitHub’s Secure Code Game, a hands-on set of challenges where you exploit and fix vulnerabilities in an agentic AI assistant (ProdBot) to learn real-world AI-agent security risks like prompt-based tool misuse, memory poisoning, and sandbox escape.

GitHub shows how GitHub Copilot CLI can speed up onboarding by scanning a repository and returning a plain-English overview of the codebase from the terminal.

stclarke shares a Microsoft AI announcement introducing MAI-Image-2-Efficient, a production-oriented text-to-image model available in Microsoft Foundry and MAI Playground, positioned as faster and cheaper than MAI-Image-2 while maintaining “flagship” quality.

ManishChopra outlines six practical integration patterns for building agents and copilots that query Oracle Database@Azure with sub-millisecond proximity to Microsoft’s AI stack, covering options from Copilot Studio connectors to ORDS/PL/SQL, Azure Functions, and Logic Apps, plus the identity/governance controls typically needed for production.

Ismael Mejía Useche and Pooja Yarabothu introduce the “PostgreSQL Like a Pro” video series, focused on practical ways to run and modernize PostgreSQL workloads on Azure—covering AI agent patterns, AI-assisted migrations in VS Code, and performance/resiliency considerations at scale.

Microsoft Developer features Jonathon Frost from the Microsoft Azure PostgreSQL team, walking through migrating to managed PostgreSQL on Azure (homogeneous and heterogeneous scenarios) and demonstrating AI-assisted Oracle-to-Postgres migration using VS Code with GitHub Copilot.