Model

66 posts filed under Model.

The description fields in your dbt project used to be read by nobody. Now an agent reads them.

The provenance record behind an AI feature fits in a YAML file next to the pipeline code.

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

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

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

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

Companies are writing one job ad for three different jobs and calling it an AI data engineer.

A company at 40 people needs senior data judgment about 2 days a week. Full-time is the wrong container.

A failure that cost one dashboard last year now takes out 40 downstream jobs. The platform grew. The alerts didn't.

Every AI roadmap I review gets the same first check: whether the data could go in a board deck unchecked.

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