Dotnet

Introduction I’ve been doing a lot of research on AI agents recently, exploring different frameworks, architectures, and models. The speed of innovation is incredible, especially the recently released Large Language Models (LLMs) Claude Opus 4.6 and Claude Sonnet 4.6, and OpenAI’s GPT 5.3 Codex. What I’ve found is that it really helps to try different models and see which one fits your use case best. For example, Claude Opus 4.6 and GPT 5.3 Codex really take the time to understand the codebase before making changes when you use them in agent mode, they analyze the full context, read related files, and plan their edits rather than jumping straight to code generation. However, one good thing I find very helpful is to make multiple iterations with different models and compare the results side by side to see which one is better for your specific use case. This also gives you more insight into how different models approach the same problem, which can be very valuable when you’re building for example an AI agent. It’s also a learning process. ...

Introduction I’ve been experimenting with the Model Context Protocol (MCP) for a while now, and it’s changed how I think about extending AI assistants like GitHub Copilot. Then, Microsoft recently released a stable version of the new MCP trigger for Azure Functions. It made building a cloud-native, serverless MCP server incredibly straightforward. As soon as I saw it, I had an idea: what if I could use this to build a simple, cloud-based tool to save and retrieve notes directly from Copilot? ...

In this blog post, I’ll share my experience building a .NET 8 Azure Function App that retrieves a user profile via the Microsoft Graph API. The function app is designed to run in Azure and return the user profile of the logged-in user via Microsoft Entra-ID. While the technical implementation was exciting, the interesting part of this journey was using GitHub Copilot as a code reviewer through Pull Requests in GitHub. It became generally available on April 4th. I’ll walk you through the process, share my thoughts on Copilot’s feedback, and highlight areas where it shines and where it could improve. ...

Introduction In this blog post, we will explore how to integrate Azure Functions with the OpenAI extension. This integration allows you to use triggers and bindings with the powerful capabilities of OpenAI within your serverless functions. We will walk through the setup, configuration, and deployment of an Azure Functions project that uses the OpenAI extension, using Bicep templates for infrastructure as code. Prerequisites Before we begin, ensure you have the following tools and resources: ...

Are you keen on exploring the fusion of Artificial Intelligence (AI) and minimal APIs in the world of C#? If so, you’re in the right place! In this article, I’ll walk you through the integration of Semantic Kernel, an open-source SDK facilitating Large Language Models (LLMs) integration, into a minimal API built using ASP.NET Core in .NET 8. By using the power of OpenAI’s GPT-3, we’ll go on a journey to create a plugin that crafts narratives based on user input. ...