Best-Practices

Clean code is code that other developers can read and understand quickly. It is not about cleverness. It is about clarity. The best code reads like a well-written paragraph. These 10 rules will make your code better immediately. Each rule includes bad and good examples in both Kotlin and Python. You can apply these today, no matter what language you use. Rule 1: Use Descriptive Names Names should tell you what a variable, function, or class does. If you need a comment to explain a name, the name is wrong. ...

“I feel faster with AI” is not a measurement. It is a feeling. And feelings can be wrong. Some developers report feeling more productive while actually spending more time — because the back-and-forth with AI feels like progress even when it takes longer than writing the code directly. Others underestimate their gains because they do not track the time AI saves on tasks they used to do manually. This article gives you a framework for measuring AI coding productivity with real data. You will learn what to track, how to track it, and how to calculate whether your AI tools are actually paying off. ...

AI writes code fast. That speed creates a new problem: your git history becomes a mess. You end up with massive commits titled “implement feature,” PRs with 50 changed files, and no way to tell which code a human wrote and which code AI generated. Good git hygiene matters more in an AI-first workflow, not less. This article covers practical git patterns for AI-assisted development — from commit structure to PR workflows to attribution tracking. ...

Debugging AI-generated code is a unique challenge. You are looking at code you did not write, understanding logic you did not design, and fixing bugs in patterns you did not choose. Traditional debugging skills still apply, but you need a different approach. Here is the uncomfortable truth about AI debugging: Claude Code almost never fails because it lacks intelligence. It fails because it lacks visibility. You have browser dev tools, console logs, network requests, and actual behavior on your screen. The AI has code files. That is it. ...

Nobody likes writing tests. But everybody likes having them. AI coding tools have gotten surprisingly good at generating tests — and surprisingly bad at certain parts of it. The teams winning with AI in 2026 are not generating the most code. They are building processes to ship reliable code despite the fact that AI introduces roughly 1.7 times more bugs than humans, according to recent studies. Good test generation is a critical part of that process. ...

Most developers write prompts like text messages. Short, vague, and missing context. Then they wonder why AI generates code that misses the point. The difference between a prompt that produces usable code and one that produces garbage is not magic. It is structure. Research shows that well-structured prompts produce code that works on the first try significantly more often. And the sweet spot is shorter than you think — 150 to 300 words. ...

Vibe coding is powerful. It makes you faster. But if you use it for everything, you will build fragile software, miss critical bugs, and slowly lose the skills that make you a good developer. This article is the honest guide. Six situations where you should NOT vibe code — and what to do instead. If you are new to vibe coding, start with What is Vibe Coding? first. This article assumes you already know the basics. ...