Ai
201 posts filed under Ai.
The Data Platform Scaling Checklist (When to Evolve)
Scaling too late costs you 6 months. Scaling too early costs you 18.
Read →Communication Overhead Kills Data Team Velocity
You doubled your data team. Delivery got worse. Fred Brooks explained why in 1975.
Read →From EUR80K/Month Cloud Bill to EUR45K - The Optimization Sprint
This company cut their cloud data bill from EUR80K to EUR45K in 6 weeks. No functionality lost.
Read →The Five Ideals Applied to Data Teams
Gene Kim wrote The Unicorn Project about a developer trapped in bureaucracy. Data engineers live that story every day.
Read →The Shadow IT Problem - When Fast Beats Right
Shadow IT doesn't start with rogue employees. It starts when the gap between 'I need this' and 'we can deliver this' gets too wide.
Read →The Three Ways Applied to Data Pipelines
Your data team ships pipelines fast. That's the First Way. They're ignoring the other two.
Read →Platform Scaling Without Hiring
Five times the data. Same number of people. No new hires. The only way through? Rethink the architecture.
Read →Data Observability Practical Start
Data observability sounds expensive and complex. Here's how to start in one afternoon.
Read →Incremental Processing Pattern
Your nightly job reprocesses 10TB. Only 50GB changed. You're burning money and adding risk.
Read →Waiting for LLMs vs Waiting for Compilation
We spent a decade optimizing compilation times. Now we're staring at an LLM spinner doing the exact same thing.
Read →