The Stack

reading list

Books, research papers, talks, and references I use for AI systems, production engineering, and interview preparation. Inspired by Chip Huyen's Books page.

Research Papers

Papers I keep coming back to on cloud-native databases, distributed streaming, and large-scale systems.

Books

AI Engineering

O'Reilly · 2025

Practical reference for building applications on top of foundation models — model selection, evaluation, deployment, and product patterns.

AI/MLSystems

Designing Machine Learning Systems

O'Reilly · 2022

System-design view of ML in production: data pipelines, features, training loops, model monitoring, reliability, and iteration under real constraints.

ML SystemsData Engineering

Machine Learning Interviews

Chip Huyen · 2021

Interview preparation covering ML fundamentals, system design, practical judgment, and hiring-process expectations for ML engineering roles.

Interview PrepML

Videos & Courses

Chip Huyen's Talks

YouTube

Practical talks on ML systems design, feature stores, and building production-grade AI applications at scale.

ML Systems

The Missing Semester

MIT CSAIL

Practical crash course on shell tools, version control, debugging, profiling, and metaprogramming — all the stuff CS degrees skip.

ToolingLinux

Destroy All Software

Gary Bernhardt · Screencasts

Deep dives into Unix, programming principles, testing, and software design. Densest 10 minutes of learning per dollar on the internet.

DesignTesting

YouTube playlist

Videos from my curated YouTube playlist.