This week, GitHub advances developer automation with the Copilot agent’s public preview, introducing actionable workflows and dashboard-driven task management that change how teams approach code generation and review at scale. Microsoft’s Azure AI Foundry simultaneously reaches general availability, bringing new tools for secure model and agent deployments—while also aligning with the expanding Model Context Protocol for multi-agent and cross-platform support. Alongside, .NET 10 lowers barriers to fast scripting and cross-device app-building, streamlining developer productivity. These moves reflect the industry’s pivot toward scalable, standardized AI, more robust cloud services, and tools that fit the realities of cross-platform, hybrid workflows.

This Week’s Overview

GitHub Copilot

This week’s GitHub Copilot updates showcase growing maturity in AI tooling for developers, spotlighting productivity improvements through advanced workflows, customizable automation, and cross-IDE feature growth. VS Code, Xcode, and other environments now offer powerful configuration avenues so teams can tune Copilot to match specific project requirements, with a focus on scalable task automation, end-to-end workflow support, community sharing, and prompt optimization for larger codebases.

Advanced Customizations and Team Alignment

New custom chat modes in Visual Studio Code, as detailed by Harald Binkle, empower developers to instantly toggle AI behaviors for reviewing code, writing tests, designing APIs, or documenting. Storing .chatmode.md files in .github/chatmodes/ ensures precise enablement and team-wide AI behavior standardization, driving consistency on complex projects. In parallel, Microsoft introduced the ‘Awesome GitHub Copilot Customizations’ repo—making it far easier for teams to define, share, and integrate purpose-built instructions, prompts, and chat modes. Teams now centralize standards while maintaining adaptability for unique workflows, aided by practical tips to blend global and domain-specific instructions.

Expanding Agentic Workflows and Task Delegation

Copilot’s transition to a true agent is reflected in the new Agents page (public preview), which allows teams to delegate specific coding tasks—like technical debt reduction or bug fixing—to Copilot and track progress within a unified dashboard. Chris Reddington’s guide demonstrates how agentic workflows let developers convert issues to actionable steps, clarify requirements through chat modes, and securely offload code generation with MCP servers. Offloading routine work dramatically improves overall productivity and innovation capacity.

Enhanced Review, Research, and Web Capabilities

Copilot now significantly eases large pull request reviews, offering more intelligent, prioritizing feedback in PRs with 20+ files—thus lowering reviewer burden. Copilot search is now integrated into GitHub Docs, turning natural questions into instant, contextual answers and streamlining documentation lookup. Additionally, coding agents now feature web browser capabilities via Playwright MCP, facilitating browser automation, data extraction, and live testing—all within Copilot, supporting comprehensive end-to-end automation and research.

Cross-IDE Support and Prompt Optimization

Copilot Vision extends key features to Xcode, including image upload/discussion in chat—crucial for UI reviews in macOS development—alongside enhanced custom instructions and locale-aware support. Prompt engineering best practices are further emphasized: specificity (languages, frameworks, intent) in prompts is proving essential for quality output. Moving from generic to highly tailored prompting is accelerating accurate code generation and faster bug fixes.

AI

Recent developments highlight the growing accessibility, modularity, and social impact of AI in the .NET and Microsoft ecosystem. There’s a strong focus on developer-centric agent orchestration, cross-platform model integration, local AI workflows, and impactful applications in areas like education.

Orchestrating and Standardizing AI Agent Workflows

A new demo shows .NET developers orchestrating multiple AI agents within a Blazor app via the Semantic Kernel Agent Framework. By combining specialized agents (e.g., “Movies” and “Food” assistants) within a concurrency-managed orchestration service, developers enable scalable recommendation/chatbot behaviors. The approach aligns with broader trends—context-driven, modular, and maintainable AI—offering immediately practical blueprints.

Microsoft’s upcoming ‘MCP Dev Days’ will dive deep into the Model Context Protocol, covering live IDE integrations, secure agent server construction, and rapid onboarding. MCP’s standardization will bring uniformity, secure onboarding, and easier model swapping, benefiting both enterprise and open-source projects.

Evolving .NET AI Support and Local AI Workflows

The .NET AI Community Standup covered new AI/ML features in .NET 9, especially native tensor support for C#, with more improvements previewed for .NET 10. These enhancements allow end-to-end ML workflows directly in .NET, simplifying deployments and unlocking advanced, high-performance data tasks for C# developers.

Bruno Capuano’s guide to generating AltText in C# using local Ollama models illustrates practical, privacy-preserving AI running off the dev’s own machine. Leveraging ‘dotnet run app.cs’ for lightweight scripting, this workflow enables fast, offline, and compliant accessibility automation.

Global AI Initiatives and Impact

Microsoft and the Philippine Department of Education are scaling AI-fueled literacy solutions to more classrooms, personalizing learning, tracking student progress, and supporting teachers—especially in underserved areas. The partnership spotlights AI’s power in societal advancement, while presenting engineering challenges in scaling, localization, and security.

Azure

Azure’s July updates reflect sweeping improvements in services, extensibility, and security designed for modern AI- and data-driven cloud applications. Major announcements emphasize modernization, platform openness, and simplified pathways to secure, scalable workloads.

Platform and AI Services Modernize

July’s Azure Updates span secure hybrid deployments (Azure App Service on Stack Hub 25R1), firewall/DNS security, and encryption-in-transit for Azure Files NFS. Azure SQL Database adds streamlined auditing and Hyperscale migration; Cosmos DB now supports refined PostgreSQL pathways. Azure Monitor’s enhanced Metrics Query Editor streamlines diagnostics and visualization. These upgrades meet modern security, scalability, and agility benchmarks.

Azure AI Foundry’s GA Agent Service (now with MCP support) simplifies model integration and agent deployment, introduces new foundation models (with advanced reasoning, video, and lightweight variants), and enables unified agent lifecycle management with improved SDKs and VS Code tooling. The release bolsters deployability, safety, and compliance for regulated AI scenarios.

Performance, Extensibility, and Workflow Automation

Recent performance improvements in Azure Files—including metadata caching, SMB Multi-Channel on Linux, and directory leasing—bring lower latency and higher concurrency, favoring heavy-access and enterprise workloads.

The Azure Developer CLI (azd) extensions framework (alpha) introduces modular, scriptable command add-ons for CI/CD, DevOps, and AI, supporting personalized and reusable CLI workflows. Open extensibility signals a move toward richer, community-driven automation and integrations.

Secure, Scalable AI and Cloud-Native Data

A Forrester study underscores Azure’s leadership in secure, compliant generative AI platform offerings, notably through unified data services and strong risk controls—streamlining adoption for enterprises.

For stateful data use cases, PostgreSQL on Azure Kubernetes Service now leverages fast storage (local NVMe or Premium SSD v2) and CloudNativePG operator for streamlined HA and backup. AI deployment, meanwhile, is further simplified by new Terraform + Vault guides, enabling automated, policy-driven infrastructure and secret management for production AI.

SDK and Library Highlights

The Azure SDK’s June 2025 update brought cross-language leaps: GA for stateful AI agents, robust identity management, Cosmos DB JS SDK improvements (higher throughput, hybrid search), and numerous new and updated libraries across .NET, Python, Java, JS, and Go—simplifying resource management and AI/cloud integration workflows.

Coding

.NET sees continued push toward frictionless, cross-platform development—condensing mobile/web convergence, AI enhancements, and rapid scripting into actionable productivity boosters.

Single-File Apps and Modern Scripting in .NET 10

.NET 10 Preview enables running full C# apps from a single .cs file using dotnet run app.cs. Andrew Lock’s analysis shows how to include in-file NuGet/SDK directives, leverage shebang for Unix-like environments, and notes forthcoming improvements such as multi-file support. This drastically lowers entry barriers for prototyping, sharing, and experimenting without the need for complex project setups.

Blazor, MAUI, and AI-Enhanced Mobile Experiences

Through the .NET MAUI standup, Beth Massi and David Ortinau demonstrate how Blazor web apps can be rapidly adapted for native mobile platforms with full device feature access, while Azure AI Foundry tooling streamlines embedding AI. Community-driven resources and best practices further empower web/mobile/AI hybrid programming.

Security

Security threats continue to rise with remote work, as detailed by Microsoft’s research into North Korean IT worker tactics. Threat actors now exploit job platforms and social engineering to subvert global organizations, leveraging convincing candidate profiles and subtle behavioral red flags.

Practical mitigation: IT managers should strengthen hiring processes beyond routine checks, deploy monitoring for behavioral/network anomalies, and increase workforce awareness around insider risks and social threats—as distributed and hybrid teams are now a prime target for sophisticated, state-sponsored infiltration.