A few years back, if someone told us that we could describe an application in plain English and some AI tool would generate working code for us, most of us would have laughed and called it science fiction. But today, that has become almost normal. We ask AI tools to create functions, explain errors, generate tests, refactor code, build UI components and sometimes even create entire prototypes. What once felt like magic is slowly becoming part of the everyday workflow of a software developer. This naturally brings up one uncomfortable question — if AI can write code, are software engineers still needed?

The 2025 DORA Report delivers a simple but powerful insight: AI isn’t a magic fix—it’s an amplifier. With over 90% of developers now using AI, productivity is rising, but trust issues remain, with 30% doubting AI-generated code . More surprisingly, AI increases throughput while hurting system stability, leading to more failures and rework—a trend clearly shown in DORA’s impact graph

Artificial Intelligence isn’t just another tool in the software engineering toolbox — it’s reshaping how we write, review, and ship code. What used to be repetitive, mechanical work is now increasingly handled by AI systems, enabling developers and reviewers to focus on design, intent, and architectural quality rather than syntax and boilerplate.

"Ship fast, break less" — If I had a motto for engineering efficiency, this would be it. And if there's one tool that helps teams ship fast and keep things sane, it's the humble Pull Request (PR).

Imagine telling your software: “Hey, just handle this for me.” And then it does. No need to click ten buttons, fill out five forms, or wait around. It just gets it done. That’s not wishful thinking anymore — that’s the promise of agentic AI.

The answer is simple: craftsmanship. There are two parts of learning this craftsmanship: knowledge and work - knowledge about principles, patterns, practices and heuristics that a craftsman needs and practicing the same again and again to get better at it.

SOLID Principles were introduced by Robert C. Martin - The Uncle Bob in the year 2000 on his paper Design Principles and Design pattern. Uncle Bob is one of the weird naming schemes in computer science in line with the Java (The Coffee☕), Python (the snake🐍) and Gang of Four 🧑🏻‍🤝‍🧑🏼🧑🏼‍🤝‍🧑. However the name was coined by Michael Feathers later.

Let try to design and write better code by looking at two 💕 of the important software quality metrics – Cohesion and Coupling. This is applicable for any programming language and help you write high quality code which ensure high reusability and easy maintenance. These high level topics in general talk about how easily our code can be changed and extended. Most people think they are the same – to a certain point it is, but there is a difference