🦄 ai that works: Policies to Prompts, evaluating the enron email dataset against SEC regulations
🦄 ai that works
A weekly conversation about how we can all get the most juice out of todays models with @hellovai & @dexhorthy
Policy to Prompt: Evaluating the Enron Emails Dataset against SEC regulations
One of the most common problems in AI engineering is looking at a set of policies / rules and evaluating evidence to determine if the rules were followed.
In this session we'll explore turning policies into prompts and pipelines to evaluate which emails in the massive enron email dataset violated SEC and Sarbanes-Oxley regulations.
Pre-reading
To prevent repeating the basics, we recommend you come in having already understanding some of the tooling we will be using:
Discord
Cursor (A vscode replacement)
Programming languages
Application Logic: Python or Typescript or Go
Prompting: BAML (recommend video)
Meet the Speaker 🧑💻
Meet Vaibhav Gupta, one of the creators of BAML and YC alum. He spent 10 years in AI performance optimization at places like Google, Microsoft, and D. E. Shaw. He loves diving deep and chatting about anything related to Gen AI and Computer Vision!
Meet Dex Horothy, founder at Human Layer - a YC company. He spent 10+ years building devops tools at Replicated, Sprout Social and JPL. DevOps junkie turned AI Engineer.