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runleonarun authored Jul 19, 2023
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Expand Up @@ -18,7 +18,7 @@ By now, everyone knows the wonders of the GPT models for code generation and pai

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As a one-person Analytics team at [Sage](http://www.hellosage.com/) I had to create our dbt pipelines from the ground up. This meant 30+ of facts and dimensions into a Staging Layer, plus all of the following layers of augmented models and Mart tables. After the fact, we are talking about 3500+ lines of YAML that I was NOT excited to get started on. Fortunately for me, this was February 2023 and ChatGPT had just come out and boy, was I glad to use it. After a good dose of “prompt engineering” I managed to get most of my documentation and tests written out, only needing a few extra tweaks.
As a one-person Analytics team at [Sage](http://www.hellosage.com/) I had to create our dbt pipelines from the ground up. This meant 30+ tables of internal facts and dimensions + external data into a Staging Layer, plus all of the following layers of augmented models and Mart tables. After the fact, we are talking about 3500+ lines of YAML that I was NOT excited to get started on. Fortunately for me, this was February 2023 and ChatGPT had just come out and boy, was I glad to use it. After a good dose of “prompt engineering” I managed to get most of my documentation and tests written out, only needing a few extra tweaks.

Writing this article as of July 2023, and now powered by GPT-4 and not GPT 3.5, it is already easier to get the same results I did, so here are my learnings that I hope everyone can replicate.

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