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Technology

Brex’s Prompt Engineering Guide

github.com

[This is] based on lessons learned from researching and creating Large Language Model (LLM) prompts for production use cases. It covers the history around LLMs as well as strategies, guidelines, and safety recommendations for working with and building programmatic systems on top of large language models, like OpenAI’s GPT-4.

Why I Stopped Worrying and Learned to Love Denormalized Tables

glean.io

I quickly learned that writing one giant query with a bunch of joins or even bunch of Python helper functions could get me stuck. My transformation functions weren’t flexible enough, or my joins were too complicated to answer the endless variety of questions thrown my way while keeping the numbers correct.

Instead, the easiest way to be fast, nimble, and answer all the unexpected questions was to prepare a giant table or dataframe and limit myself to it. As long as I understood the table’s contents, it was harder to make mistakes. I could group by and aggregate on the fly with confidence.