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Software engineering is evolving rapidly with AI coding assistants like GitHub Copilot and ChatGPT, giving rise to the era of “vibe coding,” where machines handle repetitive code and humans focus on judgment, design, and impact. This article explores the pressing questions every engineer faces today: If AI can handle much of the coding, where should we focus our effort? Should we become broad generalists or go deep into narrow areas? How do curiosity-driven explorations, like diving into Domain-Driven Design, fit into an outcome-focused industry? How should we adjust our learning to keep up with AI? And ultimately, how can engineers remain valuable, even irreplaceable, in this new landscape?

As developers, we love exploring new frameworks and patterns, but sometimes that curiosity backfires. Simple projects can quickly spiral into complex, over-engineered systems that are hard to maintain. In this article, I explore why this happens and share practical strategies for keeping code clean, focused, and maintainable without sacrificing functionality or quality.

Excited to share this blog post on a process-driven approach to system design and software architecture. Rather than starting with architecture as a fixed blueprint, I explore how a structured, flexible design process leads to decisions that are evidence-based, context-aware, and built to evolve. From understanding requirements and exploring options to evaluating trade-offs and defining architecture, this approach prioritizes clarity, adaptability, and long-term success in software systems.

Senior-level system design interviews can feel overwhelming, even for experienced engineers. They test not only how well you design systems, but how clearly you think, communicate, and adapt in real time. After going through several of these interviews and learning a few lessons the hard way, I put together five practical tips that can help you approach them with more structure, confidence, and impact.