Engineering practice at DataChef: code review, testing, and how we keep quality high.
Machine Learning
I recently developed the LinkedIn matcher widget on DataChef Academy. It reads a visitor's job title, headline, and seniority, and recommends the courses most relevant to them, instantly. No meetings to loop in a human curator. No stale spreadsheet of "who gets recommended what." Just paste
AI Coding Assistant
There's a particular kind of engineering conversation I genuinely enjoy. Not the kind where someone brings a problem they already have the answer to and just wants you to nod along. I mean the kind where someone says something that makes you stop and reconsider what you thought
claude
Claude is a tool. It helps us think faster and write code faster. But the developer is still in charge. The goal is simple: better code, clear thinking, and full responsibility. This document explains
Spec-Driven-Development
Something has fundamentally shifted in how we build software. A year ago, if you told us we'd ship a production web application, 8 major features, 11 releases, 17,000 lines of TypeScript across a full
Software Engineering
Transitioning from a web development background to data engineering, I've encountered a significant cultural shift. One of the most striking differences is the apparent lack of established software engineering practices within many data engineering t...