If you mostly live in .NET, the Java platform can look like a parallel universe: JVM, JDK, JARs, app servers, bytecode. The useful shortcut is to map each concept back to something you already know from C# and the CLR. This guide is a translation layer for .NET developers: what the JVM is, how the JDK compares to the .NET SDK, and what your real options are when a C# system needs to work with Java
Dapper vs. Entity Framework When building data-driven applications in .NET, two of the most popular data access technologies are Dapper and Entity Framework Core (EF Core). While both serve the same fundamental purpose—interacting with databases—they take very different approaches. Choosing between them depends heavily on your performance needs, development style, and project complexity. Let’s b
Introduction Picture two doctors updating the same patient record at the same time - one in São Paulo, the other in London. Both are offline. When connectivity returns, whose changes prevail? This is not a hypothetical. It is the everyday reality of distributed systems: multiple nodes, no shared clock, no guaranteed network. The conventional answer has long been locking - one node waits while an
Introduction Some code works. Some code lasts. The difference rarely comes down to typing speed, syntax mastery, or how many nights you're willing to push through. It comes down to how you think about a problem before you write a single line. Big-O notation is a mathematical framework that describes how an algorithm performs as its input grows. In plain terms, it answers one question:
My project is starting to get solid. I really like how it’s starting to look. Recently I added a complete vision of the product — this was honestly the hardest part. I’m trying to keep everything minimalistic. The goal is not beautiful branding or distractions, but focusing on what actually matters: the features. As I mentioned, here are the features: Capture HTTP requests & responses Inspect head
I spent the last few months building BlazOrbit, a component library for Blazor. It's not the first of its kind —MudBlazor, Radzen and Blazorise already exist— so I had to answer a hard question from the start: why does this need to exist? The answer turned out to be a set of architectural decisions I want to share, because each one taught me something about building UI frameworks that I didn't kno
If you're building an AI feature in .NET in 2026, the first framework you hear about is Microsoft Semantic Kernel. It's well-funded, actively maintained, and integrates deeply with Azure. For most projects, that's a fine starting point. But "fine for most" is not "right for all." Over the last few months we've talked to teams who started with Semantic Kernel and ended up looking for something else
If you use ChatGPT, Claude, Grok, Copilot, or Gemini daily, it feels like you're talking to a person. It remembers what you said three messages ago. It references the project details you shared yesterday. It feels like the model has a persistent brain that is learning about you. But it’s a lie. From an architectural standpoint, an LLM is the most "forgetful" piece of software you will ever use. Ev