Software Engineering

Engineers should already have been concerned for customer's needs. There is no need to redefine.

I set aside Claude Code, and I pick up the old-fashioned MDN documentaiton and a Vite environment to learn more about radial gradients!

I detail the journey to get a local Wifi point accessible by an HTTPS website.

This post explores the idea of how useful MCP and LLM technology is for the software engineer.

Discover how to turn AI from a crutch into a superpower—learning to harness it wisely, stay creative, and keep the magic of problem-solving alive in software engineering.

I built a simple Stripe-integrated timesheet app in just 4 hours using AI for boilerplate and my own creativity for polish, proving that AI is great for speed but real software quality still needs a human touch.

I learned to overcome vibe coding while solving mixed-content issues for a freelance project, using AI for guidance but ultimately teaching myself how to deploy with GitHub Actions and DigitalOcean.

I was surprised to learn that 3D software doesn’t share a universal coordinate system, and a client miscommunication taught me the importance of understanding right- vs. left-handed orientations and converting between them for accurate 3D printing.

I discovered that relying on AI alone couldn’t build my 3D slicer, and by stopping to understand raycasting, math, and problem-solving fundamentals, I learned that true progress comes from combining AI assistance with real comprehension.

Looking into documentation, I find a few aspects about OffscreenCanvas to use when processing graphics.

I learned firsthand how AI hype can overshadow reliability when I raised concerns about unchecked hallucinations in a product, and it reminded me that true creativity and critical thinking require questioning technology and not blindly trusting it.