Now that I have a working ereader again (finally!), I can finally start tackling a long list of e-books I have collected. Here’s what’s queued up for the rest of 2025 and, let’s be honest, probably well into 2026.

This post is primarily for myself—a convenient reference when I’m figuring out what to read next. But if it helps you discover a useful book or two, that’s a nice bonus!

If you’re interested in the books that have already shaped my journey, check out my post on Books That Shaped My Journey.

Design and User Experience

Design for Inclusivity: A Practical Guide to Accessible, Innovative and User-Centred Design by Roger Coleman, John Clarkson, and Julia Cassim

Offers tools and techniques for designing accessible products and services.

Lean Analytics by Alistair Croll and Benjamin Yoskovitz

Focuses on finding the One Metric That Matters for startups, covering six business models and five growth stages.

Lean UX by Jeff Gothelf and Josh Seiden

Applies Lean principles to user experience design with a focus on rapid experimentation and validation.

Lean Enterprise by Jez Humble, Joanne Molesky, and Barry O’Reilly

Examines how large organizations can innovate at scale using Lean and Agile principles.

Machine Learning and AI

Building LLM Powered Applications by Valentina Alto

Covers prompt engineering, fine-tuning, and RAG for building production LLM applications.

Designing Machine Learning Systems by Chip Huyen

Based on Stanford CS 329S course. Teaches a holistic approach to building reliable, scalable, and maintainable ML systems. Covers the entire lifecycle of ML systems in production.

Applied Text Analysis with Python by Benjamin Bengfort, Rebecca Bilbro, and Tony Ojeda

Covers natural language processing and text analysis with Python and machine learning.

DevOps and Infrastructure

The DevOps 2.0 Toolkit by Viktor Farcic

Focuses on automating continuous deployment pipelines with containerized microservices.

Mastering Ubuntu Server by Jay LaCroix

A comprehensive guide to Ubuntu Server administration and deployment.

Software Development Practices

The Art of Lean Software Development by Curt Hibbs, Steve Jewett, and Mike Sullivan

Introduces Lean software development practices in an incremental approach.

Software Engineering at Google by Titus Winters, Tom Manshreck, and Hyrum Wright

Documents Google’s engineering practices, culture, and tools.

The Complete Software Tester by Kristin Jackvony

Covers manual testing, automation, API testing, and security testing practices.

Artificial Intelligence Methods for Optimization of the Software Testing Process by Sahar Tahvili and Leo Hatvani

Explores AI applications in software testing optimization.

Performance and Optimization

How to Make Things Faster by Cary Millsap

Explains performance optimization methodologies for systems and applications.

Tools and Utilities

Mastering Regular Expressions by Jeffrey Friedl

A comprehensive guide to regular expressions across multiple programming languages.

Grep Pocket Reference by John Bambenek and Agnieszka Klus

A concise reference guide for the grep utility and text searching.

Pro Git by Scott Chacon and Ben Straub

The comprehensive guide to Git version control.

Programming Languages

Everyday Go by Alex Ellis

Covers practical Go development including testing, distribution, and monitoring.

Cloud Native Go by Matthew A. Titmus

Teaches building reliable distributed services using Go.

Python 3 for Science and Engineering Applications

Textbooks covering Python for scientific computing and engineering applications.

Data Engineering

Fundamentals of Data Engineering by Joe Reis and Matt Housley

Examines the data engineering lifecycle from ingestion to storage and governance.

Data Pipelines Pocket Reference by James Densmore

A practical guide to building and maintaining data pipelines.

Data Science in Production by Ben Weber

Covers deploying machine learning models to production environments.

Architecture and Design Patterns

Fundamentals of Software Architecture by Mark Richards and Neal Ford

Provides an overview of software architecture principles and patterns.

Design Patterns: Elements of Reusable Object-Oriented Software by Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides

The classic “Gang of Four” book documenting 23 fundamental design patterns.

Algorithms

Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein

The comprehensive algorithms textbook covering design and analysis.

Grokking Algorithms by Aditya Bhargava

An illustrated introduction to algorithms and data structures.

40 Algorithms Every Programmer Should Know by Imran Ahmad

Covers practical algorithm implementations in Python.

Security

Designing Secure Software by Loren Kohnfelder

Covers security principles, threat modeling, and secure coding practices.

Cognitive Science and Programming

The Programmer’s Brain by Dr. Felienne Hermans

Applies cognitive science research to understanding how programmers read and comprehend code.

It’s an ambitious list—for sure more ambitious than realistic for just a few months. But I plan to work through these gradually over the coming year (or two). Some will be quick reads, others will be reference materials I’ll return to over time.

Related: See the books that have already shaped my journey into software engineering.

What’s on your reading list? I’d love to hear your recommendations!