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
A Haystack pipeline can be perfectly wired and still unsafe. The retriever returns documents. Every component did its job. But if untrusted text moved through the pipeline as ordinary context, the trust boundary was lost. That is the problem this post is about. Not bad Python. A valid component connection only says: this value fits the next component It does not say: this value is safe to influen
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
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
Why I Stopped Using MediatR and Built CQRS From Scratch in .NET 10 MediatR is a great library. I'm not here to trash it. But when it moved to a paid model for commercial use, a lot of teams — including mine — had to make a decision. And the more I looked at what MediatR actually does under the hood, the more I realised: this is not complicated enough to justify an external dependency. So I built
Comparison: Haystack 2.0 vs. RAGatouille 0.3 for Building High-Accuracy RAG Pipelines for Developer Docs Retrieval-Augmented Generation (RAG) has become the standard for building LLM-powered tools that answer questions using private or domain-specific data. For developer documentation (dev docs) — which includes technical jargon, versioned APIs, code snippets, and structured reference material —