Blog

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.

Real senior Python interview questions from a top outsourcing company in Vietnam — covering data structures, memory management, async concurrency, database optimization, and code quality.

Most developers struggle not because they lack technical skill, but because they can't communicate clearly upward. Here's a practical framework for talking to your manager with precision and confidence.

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.

Learn how NestJS modules work: feature modules, shared modules, global modules, dynamic modules, and how the module system organizes your application architecture.

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.