Notes on dataarchitecture.

Short essays on architecture, cost, hiring and AI: one cartoon, one idea, most days of the week. No tutorials, no listicles.

Your nightly job reprocesses 10TB. Only 50GB changed. You're burning money and adding risk.

You don't always need a data architect consultant. Here's how to know if you do, what to expect, and how to avoid hiring the wrong person.

We spent a decade optimizing compilation times. Now we're staring at an LLM spinner doing the exact same thing.

Nobody sets out to hoard knowledge.

You wouldn't ship a software product without an owner, a roadmap, or a release process. Why do you treat your data differently?

Slow pipelines are a symptom. The disease is poor architectural decisions nobody revisited.

Your second data platform will be overengineered. Fred Brooks predicted this in 1975.

You're paying EUR3K/month for a cloud warehouse. Your Postgres could've handled it.

Your data team doesn't know what their pipelines cost. That's the first problem.

Executives see AI as opportunity. Engineers see it as threat. Neither is talking to the other about it.

Want expert eyes on your data architecture?

No pitch. An honest conversation about whether I can help, and what shape it would take if I can.