Ready to build AI-powered apps? Discover how .NET developers can create powerful generative AI solutions using C#, ML.NET, and Semantic Kernel. Learn to leverage existing skills to build enterprise-grade chatbots, content generators, and more - Python not required.

I explored Google Gemini and was impressed by its speed compared to ChatGPT! My hands-on experience, from coding .NET regex to using the free API tier in Google AI Studio, is detailed in this article. Even though Gemini's Semantic Kernel integration is new, I easily adapted an OpenAI example. If you're curious about a powerful OpenAI alternative, especially within the Google ecosystem, you need to read this.

Recently, I explored using Semantic Kernel and OpenAI for more accurate page scanning. By converting HTML to markdown and extracting metatags with XPath, I reduced input size and improved efficiency. OpenAI’s new JSON output feature further allowed me to receive structured data, making the process more reliable.

I was recently working on learning more about using Dataframes and Polyglot Notebooks with C# and needed some sample data to work with. At first I started by looking for some examples online, but I wanted to write a blog about my experience and wanted my own sample of data.

Assuming you are skilled in C# and the .NET ecosystem, you may be wondering if you need to learn Python to do data analysis or AI/ML. The short answer is you can do everything that Python does with C# and it will likely perform better and take less time to build in C#.

I was recently working through some automation challenges and looked up c# scripting options. I wasn't really expecting to find any compelling solutions, but the world of .NET is evolving at a rapid rate in the last few years and thought I'd try my luck. I was pleasantly surprised when the dotnet tool dotnet-script came up in my search. I had not seen this tool before and it started me on a path of evaluation.

The results of my recent experiment where I evaluated the new Blazor Server Side Rendering (SSR) to see how well it works for migrating from older MVC or Razor Page project incrementally.

I recently converted one of my example projects that used MVC controller based API, Marten Event Sourcing and Rebus to use Wolverine. This article contains some of my initial impressions of Wolverine in that experience and focuses on Wolverine.http API endpoints.

I have been digging into MartenDb and found a sample of the Event Sourcing features included in MartenDb. In this article I walk through this simple Event Sourcing example and describe what is happening.

In today's rapidly evolving business landscape, traditional linear business models are being disrupted by the emergence of platforms. Platform thinking offers a new paradigm for businesses to unlock their potential, create scalable ecosystems, and drive innovation. In this article, we will delve into the world of platform thinking, exploring its benefits and highlighting why businesses should consider adopting this strategic approach.