What We Learned from a Year of Building with LLMs

About the Authors

Eugene Yan designs, builds, and operates machine learning systems that serve customers at scale. He’s currently a Senior Applied Scientist at Amazon where he builds RecSys for millions worldwide and applies LLMs to serve customers better. Previously, he led machine learning at Lazada (acquired by Alibaba) and a Healthtech Series A. He writes and speaks about ML, RecSys, LLMs, and engineering at eugeneyan.com and ApplyingML.com.

Bryan Bischof is the Head of AI at Hex, where he leads the team of engineers building Magic—the data science and analytics copilot. Bryan has worked all over the data stack leading teams in analytics, machine learning engineering, data platform engineering, and AI engineering. He started the data team at Blue Bottle Coffee, led several projects at Stitch Fix, and built the data teams at Weights and Biases. Bryan previously coauthored the book Building Production Recommendation Systems with O’Reilly, and teaches data science and analytics in the graduate school at Rutgers. His Ph.D. is in pure mathematics.

Charles Frye teaches people to build AI applications. After publishing research in psychopharmacology and neurobiology, he got his Ph.D. at the University of California, Berkeley, for dissertation work on neural network optimization. He has taught thousands the entire stack of AI application development, from linear algebra fundamentals to GPU arcana and building defensible businesses, through educational and consulting work at Weights ...