Microsoft/visual-studio

2 posts

microsoft

How Microsoft Engineers Build AI: Learn about scalable RAG-enabled AI Apps (opens in new tab)

Microsoft’s new *How Microsoft Engineers Build AI* video series explains how its teams develop AI applications at scale. The first episode focuses on retrieval-augmented generation (RAG), using Copilot for Azure’s Ask Learn plugin as a practical example. It shows how RAG can combine proprietary data with large language models to deliver accurate, contextually relevant answers. ## Building AI Applications with RAG - RAG is presented as a practical way to improve AI applications without relying solely on model fine-tuning. - It retrieves relevant information from a knowledge base and provides that context to an LLM when generating responses. - The approach is useful for applications that need current, domain-specific, or proprietary information. ## The Ask Learn Plugin - Microsoft engineers explain how they built the Ask Learn RAG plugin for Copilot for Azure. - The plugin helps Azure developers find answers quickly within their existing workflow. - The project involved product managers and engineering leaders sharing development challenges, design decisions, and best practices. ## Challenges in Developing Reliable RAG - Selecting the right source content is essential for producing useful answers. - Data must be preprocessed effectively before it can be retrieved. - RAG systems require careful performance evaluation to measure accuracy and relevance. - Keeping responses accurate and up to date requires ongoing improvements to content and retrieval methods. ## Broader Microsoft Applications - The episode discusses RAG implementations across: - Copilot in Azure - Microsoft Security Copilot - Dynamics 365 Business Central - These examples demonstrate how RAG can support different products and business scenarios. The episode is intended as a practical introduction for developers building RAG-based applications, covering prototyping, data management, evaluation, and common pitfalls. Developers can explore the series alongside Microsoft Learn resources and Azure AI development tools such as Visual Studio and GitHub Copilot.

microsoft

Developing with Accessibility in Mind at Microsoft (opens in new tab)

Global Accessibility Awareness Day highlights the importance of building inclusive digital products. The post recommends integrating accessibility testing throughout development using Accessibility Insights for Web and Visual Studio’s Integrated Accessibility Checker. Combining automated scans with manual testing helps developers identify both common and deeper accessibility problems. ## FastPass for Rapid Automated Testing - Accessibility Insights for Web uses axe-core to detect common, high-impact accessibility issues. - FastPass can identify problems in under five minutes, often revealing failures within a couple of minutes. - Developers can use it while writing UI code to find and fix issues early. - The tool also includes WCAG 2.2 guidance and testing support in its Assessment feature. ## Visual Studio’s Integrated Accessibility Checker - Available since Visual Studio 2022 version 17.5, the checker scans desktop applications within the IDE. - It detects common accessibility issues and reports them directly in Visual Studio. - The feature is powered by the Axe-Windows engine, also used by Accessibility Insights for Windows. ## Manual Testing with Quick Assess - Automated tools cannot detect every accessibility issue, so manual inspection remains necessary. - Quick Assess provides 10 assisted tests for issues beyond automated detection. - Tests include explanations of why each issue matters, along with remediation resources and examples. - Examples include checking heading levels and reviewing individual instances for easier validation. ## Building Accessibility into Development - Accessibility testing should be part of the product life cycle rather than a final checklist. - Developers can use FastPass’s Tab Stops test to evaluate keyboard navigation and focus order. - Poor focus order can make interfaces difficult to use for people relying on screen readers, magnifiers, or those with reading disorders. - Small, consistent testing practices can significantly improve the experience for users with disabilities. The recommended approach is to start with automated checks, supplement them with Quick Assess and keyboard-based manual testing, and continue improving accessibility throughout development.