Notes on dataarchitecture.

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

Before you replace the data engineer who seems slow, count how many people can hand them work.

Before any stack change I ask how many consumers it touches and whether we can undo it by Friday.

The fastest tools in your data stack are written in a language nobody on your team writes.

GDPR and the AI Act ask their questions at the same moment: when a dataset gets reused for a model.

Novel data projects tend to die between the team that built the prototype and the team stuck running it.

Before your AI feature ships to EU customers, try deleting one customer from everything it reads.

I've worked with data teams where someone spotted the broken number first and decided not to mention it.

A CTO wanted a full platform rewrite before the next raise. 8 weeks of tickets pointed at two components.

A 20-page data governance policy with no named owners is a document nobody can enforce.

AI writes a working pipeline in 10 minutes. Nobody has asked it to be on call for one.

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.