In software engineering, "overhead" is the enemy. We spend our careers refactoring code to shave off milliseconds and optimizing cloud spend. So, when the news broke that saying "please" and "thank you" to AI costs OpenAI tens of millions of dollars in compute power, many engineers had a predictable reaction: Cut the fluff. Give me the code. But if you are a lead trying to ramp up AI usage in your team, you’ve likely run into a specific type of resistance. Some engineers dismiss the tools because they feel like "toys" or because the initial outputs feel mediocre. What they might be missing is that in the world of LLMs, politeness isn't social etiquette—it's a technical shortcut to better data. 1. Tone as a "High-Tier" Context Filter LLMs don't have feelings, but they are masters of pattern matching. They were trained on human data where professional, polite language is statistically linked to high-quality sources: academic ...
Right now, I find myself fighting a three-front war. Front one is keeping a 20-year-old behemoth of a B2B application alive. We are talking about decades of legacy ASP.NET and VB.NET where two decades of tweaks, patches, and "temporary fixes" have become permanent, load-bearing pillars of the architecture. Every time I touch it, it feels like playing Operation with oven mitts on—spending 90% of my week untangling logic just so a simple bug fix doesn’t cause a ripple effect that crashes a critical service. Front two is modernizing the architecture. I am actively trying to implement a rudimentary Strangler Fig pattern—slowly carving out legacy functionality and pushing it into a clean, testable shared library project so we can actually run proper unit tests and stop the bleeding. Front three is modernizing the team. While keeping the lights on and quietly rebuilding the engine, I am also pushing a retraining effort to get my peers up to current framework versions and embracing ...