Showing category results for CSE

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.

Agentic systems have some discretion in the parameters they sent to tooling, but there are cases, such as experimentation, when you need 100% adherence to a set of parameters.

How we built a minimal, scalable GitOps workflow for edge applications using Azure IoT Operations, Azure DevOps, and a multi-repo strategy. Includes pipeline templates and scripts for real-world deployments.

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.

Introduction to a scaleable and secure turnkey architecture for deploying Copilots connected to Azure AI Search.

A robust agent onboarding process is the backbone of scalable, reliable multi-agent AI systems—enforcing uniqueness, rigorous evaluation, and responsible AI practices at every step.

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.

Using AI‑generated tools like Stagehand with Microsoft's Playwright helps ensure a smooth user experience during modernization efforts such as Hyper Velocity Engineering and monolith-to-microservices migrations.