Best-Practices

LLMs: The Things We’ve Been Overlooking “What temperature are you using?” If someone asks, what do you say? “The default.” “0.7.” “I don’t know — does it matter?” Most answers fall into one of those three. And if you try to justify the answer, you run out of words fast. That’s how we use LLMs. We call the APIs every day — stuff prompts into messages, send them off, get responses. But when the question becomes “What does Temperature actually do?”, “How is Top-P different from Temperature?”, “Does Prompt Caching just work if you turn it on?”, “Will hallucinations go away with a better model?” — the answers get fuzzy. ...

Introduction: Why Clean Code Still Matters in the AI Era We’re flooded with AI tools that promise to do the coding for us. But after experimenting with them, I noticed a recurring pattern: AI writes code in a vacuum. It doesn’t see the “messy” reality of my project three files away. I realized that the faster the AI generates code, the faster my codebase can turn into a nightmare if I’m not careful. This brought me back to the basics. Why did we start talking about Clean Code in the first place? As Uncle Bob famously noted in his book years before ChatGPT existed: ...

Why Artificial Intelligence Fails to Reach the Frontlines AI automation software ships at a breakneck pace, yet most industries outside software development aren’t experiencing the transformation. After conversations with people across manufacturing, and traditional business sectors, the pattern is clear: the gap between AI capability and actual adoption is substantial. Three core problems explain why. Digital Transformation Comes First Executives get excited about AI transformation (AX), but most organizations haven’t completed basic digital transformation (DX). AI needs data. If your business processes exist on paper, in people’s heads, or in disconnected silos, AI cannot assist your business. ...

Engineering Is The Art of Trade-offs Before diving into this, I should mention that my career isn’t particularly long yet. My thoughts on technology are still evolving, and they might be immature at times. But there’s one clear truth I’ve learned from facing various challenges in the field: there’s no “perfect answer” in software engineering. Trade-offs: More Than a Zero-Sum Game We often think of engineering trade-offs as simple opportunity costs. ...