How Machines Learn
A grounded explanation of how AI systems learn—and why it's often misunderstood.
Notes on engineering, performance, and developer experience.
Showing all 13 posts
A grounded explanation of how AI systems learn—and why it's often misunderstood.
Reflecting on why machine learning feels more like tacit, embodied expertise than conscious reasoning—and what that means for AI hype.
A practical look at separating business meaning from UI mechanics in React, using a real invoice app refactor as the example
What began as a Frontend Mentor challenge became a deep dive into full-stack architecture. This post unpacks my design decisions, lessons learned, and why overengineering can be a powerful way to learn simplicity.
Java’s data types, wrapper classes, and concurrency helpers look excessive until you see the trade-offs they unlock.
A playful look at Java’s entry point, file conventions, and curly-brace culture, and why the verbosity pays off in large systems.
Legacy syntax, paradigm overload, and a forgiving runtime make JavaScript tough on newcomers, but understanding those quirks helps.
Kickstarting this blog with a few thoughts on what will land here and why it exists.
Why treating programming as a bundle of practiced skills—rather than pure theory—helps developers escape plateaus.
Learn production-ready Docker Compose patterns including environment management, custom images, and multi-service architectures
Create a Node.js application that connects to PostgreSQL and understand how Docker Compose services communicate
Install Docker Desktop and run a complete web application with database using Docker Compose
Learn how Docker Compose solves the 'it works on my machine' problem by letting you run entire applications with one command