CREATING AN LLM-AS-A-JUDGE THAT DRIVES BUSINESS RESULTS

Summary from the TLDR newsletter

This article discusses how to avoid creating bad evaluation processes. It introduces a technique called 'Critique Shadowing' for streamlining AI evaluation processes. Critique Shadowing involves finding a principal domain expert, creating datasets, and having the domain expert review the data and fix errors before building the LLM judge and performing an error analysis. The process repeats periodically or when material changes occur. The real value of the process is that it tricks people into looking at their data and performing careful analysis.