Chip Huyen is a Vietnamese-American computer scientist, author, and educator who turned a rejection letter from Stanford into a three-year around-the-world journey, two bestselling Vietnamese travel books, and eventually a second application that got her in. She went on to teach at Stanford, build ML infrastructure at NVIDIA and Netflix, co-found Claypot AI, and write two of the most-read technical books on machine learning systems in production - 'Designing Machine Learning Systems' (2022) and 'AI Engineering' (2025). Her newsletter and blog are required reading for anyone building serious AI products.
Mihail Eric is a Palo Alto-based ML engineer, researcher, educator, and serial founder who has spent a decade bridging cutting-edge AI research and production systems. A Stanford CS alumnus who studied under Christopher Manning and Percy Liang, he built some of Amazon Alexa's earliest large language models, co-founded YC-backed Storia AI, founded Confetti AI (acquired by Towards AI), and now teaches 'The Modern Software Developer' at Stanford while running a newsletter for 17,000+ AI practitioners.
Shreya Shankar is a PhD candidate at UC Berkeley's EPIC Lab building AI-powered data systems that are reliable and cost-efficient. A Stanford-trained engineer who worked at Google Brain and Meta, she bridges academic research and industry practice through DocETL (an open-source LLM data processing system with 3.5K+ GitHub stars used by 30+ S&P 500 companies), an O'Reilly book on AI evals co-authored with Hamel Husain, and a Maven course that has reached 4,500+ professionals. She is on the CS faculty job market and gave a faculty candidate talk at Carnegie Mellon in March 2026.