Seven simple steps for log analysis in AI systems
Artificial Intelligence
2026-04-23 v2 Computation and Language
Machine Learning
Abstract
AI systems produce large volumes of logs as they interact with tools and users. Analysing these logs can help understand model capabilities, propensities, and behaviours, or assess whether an evaluation worked as intended. Researchers have started developing methods for log analysis, but a standardised approach is still missing. Here we suggest a pipeline based on current best practices. We illustrate it with concrete code examples in the Inspect Scout library, provide detailed guidance on each step, and highlight common pitfalls. Our framework provides researchers with a foundation for rigorous and reproducible log analysis.
Cite
@article{arxiv.2604.09563,
title = {Seven simple steps for log analysis in AI systems},
author = {Magda Dubois and Ekin Zorer and Maia Hamin and Joe Skinner and Alexandra Souly and Jerome Wynne and Harry Coppock and Lucas Sato and Sayash Kapoor and Sunishchal Dev and Keno Juchems and Kimberly Mai and Timo Flesch and Lennart Luettgau and Charles Teague and Eric Patey and JJ Allaire and Lorenzo Pacchiardi and Jose Hernandez-Orallo and Cozmin Ududec},
journal= {arXiv preprint arXiv:2604.09563},
year = {2026}
}