Evals Skills for AI Agents (github.com)

Latitude has announced a comprehensive suite of skills designed to assist developers in building and evaluating applications using large language models (LLMs). This collection offers a structured workflow that helps streamline the process of identifying failure patterns, constructing evaluations, and ensuring that these evaluations work effectively. The skills are sequentially structured, allowing developers to take a systematic approach from initial annotation of production logs to creating golden datasets for regression testing, ensuring that applications remain robust and reliable. This development is significant for the AI/ML community as it underscores the importance of observability and evaluation in the deployment of AI technologies. By providing practical skills like issue discovery, evaluation type selection, and judge alignment, Latitude empowers developers to enhance their understanding of LLM performance and accountability. The inclusion of meta-skills for pre- and post-evaluation checks ensures that evaluations maintain quality and relevance, ultimately helping teams detect and correct issues before they impact users. This methodology supports the ongoing drive for reliable and trustworthy AI systems in a rapidly evolving tech landscape.