Evaluating AI agents for NL-to-SQL generation across Azure Databricks AI/BI Genie, GitHub Copilot CLI, and Microsoft Agent Framework. We achieved ~75% accuracy with schema documentation and runtime validation, while discovering that business logic errors represent a fundamental limitation requiring domain expertise.
How to build an observable MCP Server with discoverable tools and agents.
A step-by-step guide to enable search in the semantic kernel agents using bing grounding in Azure Foundry AI Agent using A2A.
When setting up an experiment is complex, agents can automate the process to make it faster and more reliable.
How we built a production-ready MCP server with OAuth 2.1 authentication and On-Behalf-Of flow for Microsoft Graph, navigating a rapidly evolving specification.
Learn how to streamline AI development by using Microsoft Devtunnels to connect local services with Azure Machine Learning evaluation pipelines, eliminating deployment delays while maintaining comprehensive cloud-based validation.
This blog details how the Azure AI Evaluation SDK can be used to assess the performance of a small language model for function calling, such as Phi-4-mini-instruct, and view the results in Microsoft Foundry.
This blog post shares real-world experiences from Microsoft's ISE team using GitHub Copilot to accelerate AI development workflows, demonstrating how AI tools can significantly speed up tasks like creating documentation, class diagrams, data visualizations, and demo scripts when used by experienced developers.
Practical patterns for designing scalable, high-performing multi-agent systems—grounded in real implementation experience.
How to leverage Testcontainers for integration testing
