Notes on dataarchitecture.

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

Most data teams know their monthly cloud bill. Far fewer can tell you which euro produced value and which one was pure waste.

The 2026 data tooling is the best it's ever been. The bottleneck in most teams I see is still a leader who can't say, in two sentences, what …

Run your AI feature twice on the same input. If a different answer would be a problem, you've found a deterministic requirement.

Most teams collect everything "just in case," then try to add privacy when an audit looms. By then it's in 40 tables.

An e-commerce client's reporting ran on a spreadsheet one person updated by hand every morning. It broke every quarter, always at month-end.

The best data engineers move for ownership and a manager who can describe the strategy. A 10% bump alone rarely does it.

The team bought more tokens. The agent still gave confident, wrong answers. The bottleneck was never compute.

Nobody chose to keep 7 years of event logs. The default did. You've paid for it every month since.

The cheapest AI safety feature in 2026: "I don't have current data."

The cloud migration finished in March. By July the bill was 3x and nothing was faster.

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.