Stop Your GCP Bill Before It Stops You
AI has made it almost too easy to spin up GCP services without thinking through the cost implications. Here's how I built a hard cap that actually cuts off spending - using Google's own recommended pattern.
AI has made it almost too easy to spin up GCP services without thinking through the cost implications. Here's how I built a hard cap that actually cuts off spending - using Google's own recommended pattern.
Someone asked me how I handle ambiguity. Here's my honest answer - and why I'm not entirely sure it's right.
The process of hitting a ceiling, figuring out what's missing, and coming back stronger works the same way whether you're learning handstands or distributed systems.
Around 2021, if you wanted AI in a data workflow, you picked a vertical. Coding assistance. Data validation. Each was isolated. That constraint is gone now — and it changes everything.
Code comments, unit tests, documentation, diagrams — the stuff that chronically didn't get done. Gen AI changed that completely, and the impact on data teams is bigger than most realize.
I spent years building OLAP cubes. Carefully maintained conformed dimensions, aggregation tables, multidimensional models. That infrastructure was real work. Today, it's increasingly obsolete.
I used to tell junior engineers to study for certifications. I don't say that anymore. Here's the advice I gave a co-op student last month: build something and put it on GitHub.