build in public

For years, I wrote code by telling the computer exactly what to do. Shifting to machine learning means letting the data write the rules. This post explores what 'learning' actually means in code, using Tom Mitchell's equation and the supervision taxonomy.

I've been using AI without truly understanding it — calling APIs, fine-tuning models, shipping features powered by things I couldn't fully explain. That gap has started to bother me. This is the first post in Learning Machines, a series where I rebuild my ML and AI foundations from scratch and share the process as I go.

A reflection on breaking a personal plateau. I’ve always believed in constant growth, but I realized I had stalled. I thought sharing my journey publicly would be easy. I was wrong. Here’s the honest story of why I stepped out of my comfort zone, what I underestimated about the process, and the unexpected personal clarity I found along the way.

What started with a friend needing secure file transfer led to building BlackBridge. Dive into the origin story, the tech hurdles of default E2EE & Zero-Knowledge, and the authentic journey of building a privacy-first tool from scratch.