Many companies are building their first AI agents right now. Most of them test the agent by chatting with it a few times in the playground and then call it done. In this blog post I explain how to evaluate AI agents in Microsoft Foundry (formerly Azure AI Foundry) in a structured way. At the end you can run an evaluation against a test dataset in the portal or with the SDK, read the results, and set up continuous evaluation for production.
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AI agents are everywhere right now, and many IT pros ask me where they should start. In this blog post I show you how to build your first Microsoft Foundry agent. We go step by step: create a project in the portal, deploy a model, create the agent with instructions and tools, test it in the playground, and finally call it from Python code. You do not need to be a developer to follow along. At the end you have a working Microsoft Foundry agent that you can extend for your own use cases.
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