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Chip Huyen: AI Engineering & Production Systems
R
Ravenza Editorial
40 installs · 30 sources · Updated 8/18/2026
Chip Huyen is an engineer, author, and educator focused on building reliable AI products in production. This Skill organizes her work on application architecture, retrieval, evaluation, model selection, inference cost, agents, observability, failure analysis, and safe rollout.
chip-huyenai-engineeringmachine-learning-systemsevaluationretrievalagentsobservabilityinference
Example questions
→Design an evaluation and rollout plan for a foundation-model feature in production.
→Diagnose whether my AI product problem is actually a model problem.
→Map the architecture around a retrieval-and-tool LLM application.
→Compare model routing, fallbacks, cost, and latency for a production workload.
→Build a human-plus-model evaluation loop for open-ended answers.
→How should I monitor drift in an ML or AI data pipeline?
Related Skills
Sources
22 web pages, 4 podcasts, 4 videos
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applicationshuyenchip.comML production cyclehuyenchip.comAI Engineering: Building Applications with Foundation Modelshuyenchip.comCommon pitfalls when building generative AI applicationshuyenchip.comAgentshuyenchip.comBuilding A Generative AI Platformhuyenchip.com
Update history
Skill details refreshed · 8/18/2026
The title, description, or cover was improved.
Initial release · 8/17/2026
First published on Ravenza.