The book contains many interesting examples of common biases and logical fallacies, but it’s buried in a lot of bluster and fluff about how smart the author is. While it was likely groundbreaking when it was published in 2004, its ideas have since permeated into the mainstream. Reading it in 2018, the ideas feel neither novel nor original. Thinking Fast and Slow covers the same material with more depth and better writing.

This was my favorite book of 2018. It profoundly impacted the way I approach my work and organize my time. After reading it, I find it easier to maintain concentration and to prioritize important tasks. It was also the final push I needed to un-addict myself from social media.

I love refactoring. Nothing satisfies me more than untangling spaghetti code to reveal its underlying logic in a clear, intuitive way.

I’ve learned that refactoring requires diligence. In my younger and more reckless days, I would rush into a legacy codebase and tear apart the code without any concern for controlled changes. Inevitably, days or weeks later, I would discover that I broke the code by removing a subtle piece that seemed irrelevant but was, in fact, critical for an obscure scenario.

Prior to February 2019, I published all my retrospectives on Indie Hackers:

• Zestful Month 5: Launched, but Still No Customers

In this post, I demonstrate how to retrofit automated tests onto an untested legacy library.

This is part two of a three-part series about how I resurrected ingredient-phrase-tagger, a library that uses machine learning to parse cooking ingredients (e.g., “2 cups milk”) into structured data. Read part one for the full context, but the short version is that I discovered an abandoned library and brought it back to life so that it could power my SaaS business: