software-engineering

A step-by-step workflow for using AI coding assistants effectively — from understanding a ticket with Rovo to reviewing changes before committing with Claude.

Every era of software engineering is really about one thing: building higher abstractions to hide complexity and let developers focus on solutions, not machines. Here's the full arc from machine code to AI.

A practical breakdown of memory types in AI coding tools — what survives between sessions, what gets wiped, and how to build persistent AI teammates that actually know your codebase.

Understanding how context works in AI coding assistants — what goes in, why it runs out, and how to manage it so the AI stays helpful instead of confused.

A practical comparison of vibe coding and spec-driven development — when to flow freely with AI, when to nail down specs first, and how to combine both without losing your mind.

Every software project exists to solve a real-world problem. But developers aren't domain experts — and that gap is exactly why you need someone who is, sitting with you from day one through delivery.

Coding is just one tool in a developer's toolkit. The real job is solving problems — and that means adapting to any tech stack, understanding the business, and thinking beyond syntax.

Companies are cutting junior roles and investing in AI, but they're destroying the pipeline that creates senior engineers. Why this 'structural collapse' threatens the entire tech industry by 2030.

A practical guide to writing unit tests that help rather than hinder. Learn the AAA pattern, isolation principles, naming conventions, and when to mock — with real code examples.

A personal reflection on my VNG fresher program in 2012 — the 6 months that taught me more real-world engineering than 4 years of university. From Windows to Linux, C# to Java, SQL Server to Redis.