Kobie Crawdord

This talk explores the critical role of task quality in the performance of AI models, particularly in agentic tasks. The core thesis is that data quality and task quality are fundamentally intertwined, and improving task quality directly leads to better model training outcomes and performance uplifts. The research validates this by comparing model performance on high-quality versus low-quality tasks, demonstrating a significant difference in learning efficiency.