Operationalize your Prompt Engineering Skills with Azure Prompt Flow
In today’s AI-driven world, prompt engineering is a game-changing skill for developers and professionals alike. With Azure Prompt Flow, you can harness the power of open-source LLMs to solve real-world operational challenges! This article guides you through using Azure’s robust tools to build, deploy, and refine your own LLM apps—from chatbots to data extraction tools and beyond. Whether you're just starting or looking to sharpen your AI expertise, this guide has everything you need to unlock new possibilities with prompt engineering. Dive in and take your tech journey to the next level!Beyond the Model: Empower your AI with Data Grounding and Model Training
Discover how Microsoft Foundry goes beyond foundational models to deliver enterprise-grade AI solutions. Learn how data grounding, model tuning, and agentic orchestration unlock faster time-to-value, improved accuracy, and scalable workflows across industries.The Future of AI: The Model is Key, but the App is the Doorway
This post explores the real-world impact of GPT-5 beyond benchmark scores, focusing on how application design shapes user experience. It highlights early developer feedback, common integration challenges, and practical strategies for adapting apps to leverage the advanced capabilities of GPT-5 in Foundry Models. From prompt refinement to fine-tuning to new API controls, learn how to make the most of this powerful model.Journey Series for Generative AI Application Architecture - Model references and evaluation models
In the previous content, we integrated the entire SLMOps process through Microsoft Olive. The development team can configure everything from data, fine-tuning, format conversion, deployment, etc. through Olive.config. In this article, I hope to talk about model reference and evaluation.Journey Series for Generative AI Application Architecture - Foundation
At Build last year, Microsoft CTO Kevin Scott proposed Copilot Stack to provide problem-solving ideas for Generative AI applications. Based on the Coplit Stack, community have developed many frameworks in the past year, such as Semantic Kernel, AutoGen, and LangChain. These frameworks are more biased toward front-end applications, and enterprises need a better engineering solution. This series hopes to give you some ideas based on Microsoft Cloud and related frameworks and tools.
