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How to Count a Person Exactly Once

Naruto's shadow clones filling a forest clearing

It's still just one Naruto.

Last week on Obi The Explorer, I covered a data pipeline built on Fivetran that turns every Typeform survey into a single reusable set of models, rather than a fresh CSV and a fresh script every time. You can read all about it here. Everything was rosy until a survey came through and exposed weaknesses in the modelling. This post explains why counting people isn't the same as counting answers, what had to change in the models to fix it, and how getting it right ended up mattering well outside the warehouse.

Why We Stopped Rebuilding Survey Analysis From Scratch Every Time

Phil Connors reporting from Gobbler's Knob in Groundhog Day

Our own Groundhog Day.

At my current company, we run patient feedback surveys, clinical intake forms, and stigma studies through Typeform. Think teams across multiple markets and functions. The same way any company interested in providing its customers with the best possible experience would. For the uninitiated, Typeform is a form builder that lets businesses collect data people want to share. It's easy to use, customisable, and it's great. (Not a sponsorship wink wink).

  • in dbt, AI, Data
  • 7 min read

The Seven Gates We Put Between an AI Agent and Our dbt Models

How our data team stopped trusting a coding agent to remember the process.

TL;DR: An AI agent will write you a dbt model that compiles, passes every test, and is wrong. Adding more instructions doesn't fix this, because the real gap is memory, not knowledge. We moved the process out of the agent's head and into the repo: seven phases, each a gate that must be verifiably passed before the next can start. Below is the whole workflow, what triggered it, and what it's caught so far.

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