Alex Barksdale enhanced the DataDog/documentation repository by developing and refining documentation for LLM Observability features, focusing on datasets and experiment management. Over two months, Alex introduced project-based organization and CSV support for dataset workflows, clarifying how engineers and data scientists define and run experiments with multiple evaluation methods. Using Markdown and Python, Alex updated API documentation to improve discoverability and usability, and later expanded guidance to cover dataset versioning, retention, and access to historical versions. This work deepened the documentation’s clarity and reproducibility, supporting robust data governance and enabling more reliable experiment tracking within the LLM Observability workflow.