# Microsoft Foundry Published articles for Microsoft Foundry. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Build an interview coach app with the GitHub Copilot SDK DevFeed: [Build an interview coach app with the GitHub Copilot SDK]() Original publisher: [Read original article]() Author: Justin Yoo Published: 2026-09-15T16:00:11Z Content type: tutorial Language: en Sources: [Developer Blogs]() Topics: [GitHub Copilot](), [SDK](), [Model Context Protocol](), [.NET](), [Blazor]() Tags: [agent-framework](), [ai](), [blazor](), [github-copilot](), [github-copilot-sdk](), [mcp](), [microsoft-agent-framework](), [microsoft-foundry](), [model-context-protocol](), [net](), [sdk]() ### AI overview This tutorial demonstrates how to build an interview coach application with the GitHub Copilot SDK in .NET. The sample uses a Blazor chat interface, Copilot instructions and callable tools, and Model Context Protocol services for document handling and interview records. It emphasizes giving Copilot application-specific tools rather than access to shell commands or source files. ### Source excerpt An interview coach has to do more than ask questions. It needs to read a resume, follow up on an incomplete answer, and save enough context to give useful feedback at the end. Some of that work is conversation. Some of it requires calling an application service. The GitHub Copilot SDK lets you use the [...] The post Build an interview coach app with the GitHub Copilot SDK appeared first on Microsoft for Developers. ## Unlocking the Power of AI for Every Developer in Visual Studio with Bring your Own Model DevFeed: [Unlocking the Power of AI for Every Developer in Visual Studio with Bring your Own Model]() Original publisher: [Read original article]() Author: Tanmayee Kamath Published: 2026-08-24T22:39:41Z Content type: release Language: en Sources: [Visual Studio Blog]() Topics: [AI Chat]() Tags: [ai](), [github-copilot](), [microsoft-foundry](), [model](), [release](), [visual-studio]() ### AI overview Visual Studio 18.10 Insiders introduces a preview of Bring Your Own Model, enabling developers to connect supported model providers or Microsoft Foundry deployments in the new Agent preview. ### Source excerpt The best AI in Visual Studio is the AI you can bring with you. Developers don't work in a single-model world anymore. You might reach for one model for everyday coding, another for a domain-specific problem, and an approved model for work that must stay within your organization's governance boundaries. So, the question we hear [...] The post Unlocking the Power of AI for Every Developer in Visual Studio with Bring your Own Model appeared first on Visual Studio Blog. ## From dotnet run to Foundry Hosted Agent in 3 lines of C# DevFeed: [From dotnet run to Foundry Hosted Agent in 3 lines of C#]() Original publisher: [Read original article]() Author: Bruno Capuano Published: 2026-08-24T19:00:00Z Content type: tutorial Language: en Sources: [.NET Blog]() Topics: [hosted-agents](), [Microsoft Agent Framework](), [Azure](), [C#](), [.NET](), [NuGet](), [Entra ID](), [Containers](), [telemetry]() Tags: [agent](), [agents](), [ai](), [azd](), [azure](), [blog](), [c-sharp](), [csharp](), [dotnet](), [entra-id](), [framework](), [hosted-agents](), [hosting](), [infrastructure](), [microsoft](), [microsoft-agent-framework](), [microsoft-foundry](), [net](), [nuget](), [observability](), [post](), [production]() ### AI overview This tutorial shows how to deploy a Microsoft Agent Framework console agent as a Foundry Hosted Agent using one NuGet package, three lines of C#, and two commands. Foundry provides managed Azure infrastructure, scaling, identity, session state, observability, and lifecycle management. ### Source excerpt You built an agent with Microsoft Agent Framework and it works great on your machine. Now what? Turns out deploying it to production takes 1 NuGet package, 3 lines of C#, and 2 commands. Let's do it. The post From dotnet run to Foundry Hosted Agent in 3 lines of C# appeared first on .NET Blog. ## Browser automation with Pydantic AI + Playwright DevFeed: [Browser automation with Pydantic AI + Playwright]() Original publisher: [Read original article]() Author: Pamela Fox (noreply@blogger.com) Published: 2026-08-20T21:57:18Z Content type: tutorial Language: en Sources: [Pamela Fox]() Topics: [Playwright](), [Pydantic](), [Browser Automation](), [Artificial Intelligence](), [Azure OpenAI](), [Entra ID](), [Authentication](), [OAuth 2.0](), [OpenTelemetry]() Tags: [agents](), [ai](), [api-keys](), [authentication](), [automation](), [azure-openai](), [browser](), [microsoft](), [microsoft-foundry](), [openai](), [playwright](), [python]() ### AI overview This tutorial explains how to combine Pydantic AI with Playwright to build agents that browse websites programmatically. It covers connecting Pydantic AI to Microsoft Foundry models through an OpenAI-compatible endpoint, using Entra token-based authentication, and applying Playwright for browsing, manual QA, and design iteration. ### Source excerpt When we build agents, we often want to give them the ability to browse the web: open webpages, navigate from one page to the other, and read the content of a webpage. By combining Pydantic AI with the Playwright capability from Pydantic AI Harness, we can build agents that browse the web safely and programmatically. Using Pydantic AI with Microsoft Foundry models Pydantic AI is an open-source model-agnostic framework from Pydantic for building LLM-based applications and agents. It's type-safe and supports OpenTelemetry, making it a great choice for robust production applications. We can use Pydantic-AI with Microsoft Foundry models using either API keys or Entra token-based authentication. When possible, we always recommend the keyless route, so that's what we'll demonstrate here. We use the azure-identity package to authenticate with Entra, using either local or managed identity, and get back a token provider callback function for that credential: from azure.identity.aio import AzureDeveloperCliCredential, get_bearer_token_provider credential = AzureDeveloperCliCredential() token_provider = get_bearer_token_provider(credential, "https://cognitiveservices.azure.com/.default") Then we use the OpenAI package to configure the model connection: from openai import AsyncOpenAI client = AsyncOpenAI( base_url=os.environ["AZURE_OPENAI_ENDPOINT"] + "/openai/v1", api_key=token_provider, ) model = OpenAIChatModel( model_name=os.environ["AZURE_OPENAI_CHAT_DEPLOYMENT"], provider=OpenAIProvider(openai_client=client), ) Let's explain the options used above: base_url: We point this at the OpenAI-compatible endpoint for our Foundry model. This endpoint works for Azure OpenAI models (like gpt-5.4, which this project deploys), and for cross-provider Foundry models that support the OpenAI v1 API, like Kimi-K2.7-Code. The base URL looks like "https://AZURE_OPENAI_SERVICE_NAME.openai.azure.com/openai/v1". api_key: We pass in the token provider callback function that generates OAuth2 token ## Hugging Face Models on Foundry Managed Compute DevFeed: [Hugging Face Models on Foundry Managed Compute]() Original publisher: [Read original article]() Author: Manoj Bableshwar; Osi Published: 2026-07-07T15:20:06Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [Microsoft](), [AI Development](), [Artificial Intelligence](), [Cloud](), [SDKs](), [Open Source](), [C#](), [JavaScript](), [Python](), [anthropic](), [deepseek](), [OpenAI]() Tags: [agentic-ai](), [agents](), [ai](), [azure](), [c-sharp](), [deployment](), [eval](), [gpu](), [javascript](), [microsoft](), [microsoft-foundry](), [monitoring](), [observability](), [open-source](), [orchestration](), [platform](), [python](), [sdks](), [security]() ### AI overview Microsoft Foundry Managed Compute is presented as a managed GPU platform for deploying open-source and custom models within Foundry. It uses model-oriented configuration while Microsoft manages GPU topology, runtime updates, and security patches across supported runtimes. The platform shares endpoints, SDKs, authentication, observability, and billing with Foundry's other deployment options, while integrating open-source models with Foundry Agents. ### Source excerpt Microsoft Foundry is a platform for building and operating agentic AI applications. Foundry starts with the widest model selection on any cloud -- models from Microsoft, OpenAI, Anthropic, Meta, Mistral, DeepSeek, Hugging Face, and others, spanning frontier, open-source, and custom weights -- all accessible through a single endpoint and a single set of SDKs in Python, C#, JavaScript, and Java. ## PyCon US 2026 DevFeed: [PyCon US 2026]() Original publisher: [Read original article]() Author: Vedha Ranganathan Published: 2026-05-14T00:18:13Z Content type: article Language: en Sources: [Microsoft Python Engineering]() Topics: [Microsoft](), [GitHub](), [Azure](), [Microsoft Agent Framework](), [Meta](), [AI search]() Tags: [2026](), [azure](), [blog](), [developers](), [github](), [meta](), [microsoft](), [microsoft-agent-framework](), [microsoft-foundry](), [post](), [python](), [search]() ### AI overview Microsoft and GitHub announce their presence at PyCon US 2026 in Long Beach, including a booth, hands-on labs, and information about a Pylance integration with Meta's Pyrefly type checker that is in early preview. ### Source excerpt PyCon US 2026 The post PyCon US 2026 appeared first on Microsoft for Python Developers Blog.