Normally Distributed

I have an unofficial rule on this blog: no listicles. Consider this post a rule-breaker: seven pieces of career advice, gathered the hard way. I recently crossed the ten-year mark in tech, and these are the things I find myself repeating to mentees - and

Ten days ago, I started building a diagram library from scratch. Today I'm releasing Flora - a fault-tolerant, Mermaid-compatible diagram library that renders polished, interactive SVGs from imperfect input. I want to talk about Flora, but I also want to

A few months ago, I participated in a company-wide hackathon with a group of data engineers. The project was straightforward enough: build tooling to automate some of our data modeling conventions - tasks like auto-generating documentation, scaffolding sc

I've been spending a lot of time lately figuring out which AI tools to invest in. New models, new frameworks, new CLI tools, new IDE integrations (or no IDE at all?!). The ecosystem is moving so fast that just orienting yourself feels like a project in it

I've been using Claude Code almost every day for over six months now, and the thing that surprises me most isn't how fast it is. It's how quickly it exposes the gaps in my own thinking.I'll prompt something like "clean up this model" or "make this easier

If you've been following AI news lately, you've probably heard about the viral rise of Moltbook. The concept is wild: a Reddit-style social network exclusively for AI agents. Bots post, comment, and interact with each other while humans can only watch. Wi

I've been back at work for three weeks after seven-and-a-half months of maternity leave, and it genuinely feels like I've returned to a completely different industry.The fundamentals haven't changed: data pipelines still break in unexpected ways, and tech

Last week, I followed the 2025 New York City mayoral election and was so impressed by how clearly the New York Times visualized the election results. Their choropleth map did a great job of capturing the city's political mood at a glance. You can see enti

In this case, each noise complaint is represented as a point on a map, and each neighborhood in the geojson file is represented as a polygon. The spatial join checks which polygon each point falls inside and assigns that neighborhood's name to the complai