Dependency management is one of those topics that quietly shapes the quality of every C# codebase. Get it right, and your system stays testable, readable, and flexible. Get it wrong and you inherit hidden coupling, brittle tests, and painful refactors. In this post, I break down the most common dependency patterns in .NET, from the ones you should reach for by default to the ones that should make you pause, and a few you should avoid unless you have no other choice.
Software development principles like SOLID, DRY, KISS, and YAGNI are essential tools, but they are not laws of nature. In real projects, blindly following every rule can sometimes add more complexity than value. This post explores practical situations where bending or even breaking these principles leads to simpler, faster, and more effective outcomes, especially when speed, learning, or constraints matter more than long-term elegance.
Switching priorities mid-sprint is something most developers face sooner or later, yet few of us are taught how to do it well. In this post, I break down a practical, experience-driven approach to pausing one project, ramping up on another, and returning without chaos, tech debt, or burned bridges. If you have ever been pulled into an urgent initiative while critical work was still in progress, this guide is meant to help you stay effective, communicate clearly, and protect both your code and your sanity.
Refactoring a legacy codebase can feel like a never-ending battle against spaghetti code and mounting technical debt. But diving in blindly isn’t the answer. The most effective way to improve a system? Focus on the pain points your users actually experience. In my latest blog post, I break down a strategic approach to refactoring that prioritizes real user impact over chasing every technical issue, saving time, delivering value, and making systems genuinely better.
