Hamel Husain is a machine learning engineer with 25+ years of experience who built part of the foundation beneath GitHub Copilot - his CodeSearchNet project was early LLM research later used by OpenAI for code understanding. Today he runs Parlance Labs, consults with AI teams across 35+ products, co-authored O'Reilly's 'Evals for AI Engineers', and teaches thousands of engineers how to move beyond vibes and actually measure their AI systems.
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.