After two decades of building enterprise applications on the Microsoft stack, I’ve witnessed every major evolution of .NET—from the original Framework through the tumultuous transition to Core, and now to the unified platform that .NET 9 represents. What strikes me most about this release isn’t any single feature, but rather how it crystallizes Microsoft’s vision […]
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.NET 9: A Solutions Architect’s Guide to the Modern .NET Ecosystem
After two decades of building enterprise applications on the Microsoft stack, I’ve witnessed every major evolution of .NET—from the original Framework through the tumultuous transition to Core, and now to the unified platform we have today. .NET 9, released in November 2024, represents the maturation of a platform that has finally delivered on the promise […]
Read more →.NET AI Performance Optimization: Reducing Latency and Costs
Last year, I inherited a .NET AI application that was struggling. Response times averaged 2.3 seconds, costs were spiraling, and users were complaining. After three months of optimization, we cut latency by 87% and reduced costs by 72%. Here’s what I learned about optimizing .NET AI applications for production. Figure 1: .NET AI Performance Optimization […]
Read more →ML.NET for Custom AI Models: When to Use ML.NET vs Cloud APIs
Six months ago, I faced a critical decision: build a custom ML model with ML.NET or use cloud APIs. The project required real-time fraud detection with zero latency tolerance. Cloud APIs were too slow. ML.NET was the answer. But when should you use ML.NET vs cloud APIs? After building 15+ production ML systems, here’s what […]
Read more →Building Production AI Applications with .NET 8 and C# 12
When .NET 8 and C# 12 were released, I was skeptical. After 15 years building enterprise applications, I’d seen framework updates come and go. But this release changed everything for AI development. Let me show you how to build production AI applications with .NET 8 and C# 12—using actual C# code, not Python wrappers. Figure […]
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