Written by Krezzia Noelle Basilio and Samit Jhaveri, this post explores the Microsoft Engineering Series on scalable Retrieval-Augmented Generation (RAG) AI apps, practical best practices, and challenges in building intelligent Microsoft solutions.

How Microsoft Engineers Build AI: Learn about scalable RAG-enabled AI Apps

Authors: Krezzia Noelle Basilio, Samit Jhaveri

For developers, building intelligence into applications is a growing imperative. Recent studies show that 92% of companies plan to invest in AI over the next three years to improve productivity and customer service.

At Microsoft, teams of engineers are constantly exploring new ways to apply AI at scale, developing solutions that leverage advanced machine learning models and contemporary AI techniques. To help developers of all experience levels understand these technologies, Microsoft has launched a new video series titled How Microsoft Engineers Build AI.

Series Introduction

The series aims to demystify how Microsoft engineering teams implement and scale AI functionalities within enterprise and consumer apps. The first episode focuses on a widely-implemented approach: Retrieval-Augmented Generation (RAG).

Building RAG into modern applications—especially at scale—presents unique challenges, including data management, context relevance, and performance evaluation. The episode demonstrates how to overcome these obstacles using strategies and best practices gathered from real-world Microsoft solutions.

Inside the First Episode: RAG in Copilot for Azure

Cloud Advocate Frank Boucher hosts a conversation with Senior Product Managers Brian Steggeman and Eric Imasogie, and Principal Software Engineer Manager Tianqi Zhang. They share their hands-on experiences from building the Ask Learn plugin, a RAG-based extension within Copilot for Azure.

Discussion Highlights

  • What is RAG? The episode explains the fundamental concept of retrieval-augmented generation and how it differs from other techniques like fine-tuning.
  • Product Applications: Examples include Copilot in Azure, Microsoft Security Copilot, and Dynamics 365 Business Central—all of which use RAG to surface accurate and relevant information.
  • Technical Challenges: The team discusses issues in content selection, preprocessing, and measuring RAG effectiveness.
  • Innovative Solutions: Strategies to ensure up-to-date and accurate plugin responses are revealed.

Demonstration and Developer Guidance

A practical demonstration shows how the Ask Learn plugin helps Azure developers retrieve answers quickly within their workflow, streamlining the development experience for AI-powered applications.

Call to Action

The post encourages developers to watch the video for in-depth learning and practical takeaways. For hands-on experience, it recommends using Visual Studio and highlights the integration of GitHub Copilot, now available for free in the IDE.

Additional Resources

Key Takeaways

  • Microsoft’s engineering teams are advancing scalable RAG-enabled AI solutions.
  • Practical advice for prototyping, managing data, and avoiding common pitfalls in AI app development is provided.
  • The Copilot for Azure ‘Ask Learn’ plugin serves as a prime example of effective RAG design, directly benefiting developers using Microsoft AI tools.

Developers interested in building modern RAG-based applications can leverage these insights and best practices, directly from Microsoft experts.

This post appeared first on “Microsoft DevBlog”. Read the entire article here