Books and articles that have shaped how I think about engineering, AI, and building things. I’ll keep this updated as I go.

  • Clean Code — Robert C. Martin Engineering
    Opinionated but useful. Good foundations for writing code that other people can actually read.

  • Design Patterns — Erich Gamma, Richard Helm, Ralph Johnson, John Vlissides Engineering
    The Gang of Four classic. Dense but worth it — once you see these patterns, you spot them everywhere.

  • The Algorithm Design Manual — Steven Skiena Engineering
    More practical than CLRS. The war stories and catalog of algorithmic problems make it a great reference.

  • Designing Data-Intensive Applications — Martin Kleppmann Engineering
    The best book I’ve read on distributed systems. Changed how I think about data pipelines and system design.

  • Designing Autonomous AI — Kence Anderson AI/ML
    Practical guide to designing AI agents and autonomous systems. Relevant to the LLM tooling work I do daily.

  • How Claude Code Builds a System Prompt — Drew Breunig AI/ML
    Great breakdown of context engineering — how the system prompt is assembled and why it matters.

  • Generative Deep Learning — David Foster AI/ML
    Solid intro to generative models. Good balance of theory and hands-on code.

  • The Manager’s Path — Camille Fournier Leadership
    Essential if you’re going from IC to tech lead. Practical and honest about what each step looks like.

  • Staff Engineer — Will Larson Leadership
    What does impact look like beyond senior? This book lays out the archetypes and trade-offs.

  • The Design of Everyday Things — Don Norman Design
    Foundational HCI book. You’ll never look at a door handle the same way again.

  • Don’t Make Me Think — Steve Krug Design
    Short, practical, and still relevant. Good reminder that simplicity wins.