Product Evals in Three Simple Steps
Label some data, align LLM-evaluators, and run the eval harness with each change.
Eugene Yan9 min read
engineering
10 stories
Advice for New Principal Tech ICs (i.e., Notes to Myself)
Based on what I've learned from role models and mentors in Amazon
Eugene Yan13 min readAI Engineer 2025 - Improving RecSys & Search with LLM techniques
Recsys & search are converging with LLMs via semantic IDs, data augmentation, and unified foundation models.
Eugene Yan1 min readAn LLM-as-Judge Won't Save The Product—Fixing Your Process Will
Applying the scientific method, building via eval-driven development, and monitoring AI output.
Eugene Yan5 min readNVIDIA GTC 2025 - Building LLM-Powered Applications
Chip Huyen and I share what we've learned, best practices, and insights at NVIDIA GTC 2025.
Eugene Yan1 min readMy Minimal MacBook Pro Setup Guide
I just upgraded my personal laptop from a 2019 Intel MacBook Pro to an M4 MacBook Pro. Like all my new devices, instead of restoring from a backup, I try to Marie Kondo my digital life and start from a clean slate. This also lets me reexamine my existing tools and explore new options.
Eugene Yan5 min read39 Lessons on Building ML Systems, Scaling, Execution, and More
ML systems, production & scaling, execution & collaboration, building for users, conference etiquette.
Eugene Yan9 min readBuilding the Same App Using Various Web Frameworks
FastAPI, FastHTML, Next.js, SvelteKit, and thoughts on how coding assistants influence builders' choices.
Eugene Yan8 min readAI Engineer 2024 Keynote - What We Learned from a Year of LLMs
Special double-feature closing keynote from the 6 authors of the hit O'Reilly article on Applied LLMs.
Eugene Yan3 min readNetflix PRS 2024 - Applying LLMs to Recommendation Experiences
Challenges and lessons from deploying LLM experiences: evals, scalability, guardrails.
Eugene Yan2 min read
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