Reading List

Either reading or listening.

Done

• The C Programming Language
• Go Code
• Effective Go
• The Go Programming Language → link
• On Java - Bruce Eckel
• Blockhain Chicken Farm - stories about tech in China’s countryside
• Crypto 101
• Let’s Go - Alex Edwards
• Understanding Kubernetes
• The Unix Programming Environment
• Fluent Python
• shape up
• Designing Data Intensive Applications
• Patterns.dev
• If You’re In My Office, It’s Already Too Late
• Sapiens - Yula Noah Harari
• Slow Productivity - Cal Newport
• Thinking, Fast And Slow - Daniel Kahneman

• Human errors model and management

• Dig Your Well Before You’re Thirsty
• Making reliable distributed systems in the presence of software errors
• The Book of Shaders
• Ian Goodfellow, Yoshua Bengio, Aaron Courville - Deep Learning (2017, MIT)
• Thinking In Systems: A Primer
• “Elements of Typographic Style” by Robert Bringhurst - “the bible” of typeface design

• Designing Types with FontForge

• “Designing Type” by Karen Cheng
• The Pattern on The Stone - book from 1998 that states some fundamentals of CS in beautiful terms.
• The Rust Programming Language (“the book”)
• Margin of Safety - Seth Klarman

In Progress

• The Scaling Era: An Oral History of AI, 2019-2025

Backlog

• You Have Not Yet Heard Your Favourite Song: How Streaming Changes Music
• Algorithms for Decision Making
• Kenneth O. Stanley and Joel Lehman: Why greatness cannot be planned: the myth of the objective
• Countdown to Zero Day - about stuxnet
• Crossing the Chasm
• Chinese Next-Generation Psychological Warfare: The Military Applications of Emerging Technologies and Implications for the United States
• Programming Elixir 1.6 by Dave Thomas
• Programming Phoenix 1.4 by Chris McCord, Bruce Tate and José Valim

• The Pragramatic Programmer
• A Philosophy of Software Design

• The Hundred Page Machine Learning Book
• Neural Networks and Deep Learning - Michael Nielsen
• Gergely Orosz’s Software Engineer’s Guidebook
• Range: How Generalists Triumph in a Specialized World
• System Design Interview An Insider’s Guide by Alex Xu
• Thinking in Systems - Donella Meadows
• Clean Code: A Handbook of Agile Software Craftsmanship
• Domain-Driven Design with Golang
• Introduction To Algorithms - also recommended by primeagen, beefier/advanced
• INTERPRETABLE MACHINE LEARNING BY CHRISTOPH MOLAR
• Understanding Kubernetes
• The Ultimate Go Notebook
• Structure and interpration of computers

• Swift Book

• Cracking the Coding Interview
• Introduction to Algorithms - Thomas H. Cormen, Charles E. Leiserson
• The System Design Interview
• Phoenix Project
• Skunk Works
• Refactoring - Martin Fowler
• Domain Driven Design - Evans
• Mostly Adequate Guide To Functional Programming
• Algorithms
• Crafting Interpreters
• Communicating Sequential Processes - paper by Tony Hoare
• SOLID by Khalil Stemmler
• Functional and Reactive Domain Modeling
• Domain Modeling Made Functional
• Statecharts
• Something about geology. Rocks are cool.
• Training For Climbing - Eric Hörst
• Gang of Four - for design patterns
• Daily Rituals: How Artists Work
• Every Programmer Should Know
• Effective Python
• SHOE DOG by Phil Knight
• Practical Networking
• Uncle Bob’s Clean Architecture
• Deep Work (or other work by Cal Newport)
• Beej’s Guide to Network Programming
• Building Evolutionary Architectures
• Mountaineering - The freedom of the hills
• Side Hustle - Chris Guillebeau
• 鬼吹燈
• Refactoring UI
• a simple path to wealth
• the little book of common sense investing
• Architecture Patterns with Python
• Simple Sabotage
• “You Are Not Expected to Understand This”: How 26 Lines of Code Changed the World
• Networking for systems administrators
• coding the matrix - linear algebra. Read this before getting into AI programming.
• Make Your Own Neural Network
• Google SRE bible
• Common Sense Guide to Data Structures - recommended by primeagen, basic
• Prestige, Manipulation, and Coercion: Elite Power Struggles in the Soviet Union and China after Stalin and Mao
• Build your own Database - Example code in Go
• THE MASTER ALGORITHM: HOW THE QUEST FOR THE ULTIMATE LEARNING MACHINE WILL REMAKE OUR WORLD BY PEDRO DOMINGOS
• Database Internals
• The Algorithm Design Manual
• The Infinite Game
• What color is your parachute?
• How Big Things Get Made
• From rules to examples: Machine learning’s type of authority
• The Making of the Atomic Bomb by Richard Rhodes
• What Every Programmer Should Know About Memory
• There Is No Antimemetics Division
• The Technological Republic: Hard Power, Soft Belief, and the Future of the West - Alex Karp
• The Last Days of Night
• River of Doubt - Theodore Roosevelt
• Alice in Differentiable Wonderland - really good deep learning book
• apple in china
• Breaking Through: My Life in Science - Katalin Karíko
• If anyone builds it, everyone dies
• the visual display of quantitative information
• building a datacenter for dummies
• king warrior magician lover
• Talking Nets: An Oral History of Neural Networks

On Building SaaS

• The Mom Test by Rob Fitzpatrick
• Badass: Making Users Awesome by Kathy Sierra
• Deploy Empathy by Michele Hansen
• The SaaS Playbook by Rob Walling

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More lists of books to read:

• Flavio Copes reading list
• This tweet thread
• This Reddit post
• Andrej Karpathy’s list of good books
• Computer Science Papers Every Developer Should Read
• books tech people never read (and it shows)