Algorithms to Live By: How I Used Computer Wisdom to Make Better Choices

Why this book matters: I read Algorithms to Live By when my days felt noisy and every choice seemed expensive. The idea that computer science has practical heuristics for human life felt oddly liberating. The rules are not technical traps - they are mental shortcuts that save time and protect clarity.

The Book in One Line

Treat life's choices like computational problems and use simple, proven heuristics to make better, faster decisions.

5 Key Ideas That Matter

1. The Explore/Exploit Tradeoff
- Explanation: Balance trying new things (explore) with using known good options (exploit).
- Quote: "The optimal strategy is to explore early and exploit later."
- Why it matters: I stopped oscillating between novelty and routine. The rule gave me permission to try more early and settle when a pattern emerged.
→ Takeaway: Schedule experimentation windows, then commit to winners.

2. The 37% Rule (When to Stop Searching)
- Explanation: When choosing among options, sample ~37% then pick the next that’s better than anything seen so far.
- Quote: "If you ask 100 people, you should sample first and then pick."
- Why it matters: I used this to hire and to choose projects - it reduced paralysis.
→ Takeaway: Early sampling beats endless searching.

3. Sorting and Scheduling Heuristics
- Explanation: Simple rules like shortest task first or batching similar tasks improve throughput.
- Quote: "Order matters."
- Why it matters: I reorganised my day to cluster related work, and my clarity skyrocketed.
→ Takeaway: Design your day like a scheduler: reduce context switches.

4. Caching and Memory Management
- Explanation: Keep a small cache of essential routines and let the rest be lazy-loaded.
- Quote: "Don’t try to remember everything."
- Why it matters: I stopped overloading my short-term memory and used small rituals instead.
→ Takeaway: Create tiny habits as caches for important behaviours.

5. Overfitting and Regularisation
- Explanation: Avoid solutions that only work on past data; prefer robust, simple rules.
- Quote: "Simplicity generalises better."
- Why it matters: I stopped chasing perfect plans tuned to flawed pasts.
→ Takeaway: Build simple systems that survive noise.

Real-World Application

I applied the 37% rule to hiring: I would interview a set number of candidates, then hire the next one who clearly outperformed earlier interviews. That saved me from spanning months of searching. For daily work, I used scheduling heuristics to batch deep work and shallow tasks. The result: less decision fatigue and more time for important problems.

What the Book Gets Wrong (or Misses)

The book is brilliant at mapping ideas, but human contexts add emotion and politics. Algorithms assume clean metrics. People bring values and unpredictable motives. Also, some heuristics need cultural adaptation. The solution: use the book as a toolbox, not a rulebook. Apply with empathy and emotional intelligence.

Final Takeaway

Algorithms to Live By gave me practical, memorable rules that reduced my mental load. It shifted me from chaotic choice to designed choice. If you want to map which cognitive patterns steal your clarity and build personalised decision rituals, try QUEST - it helps you apply these algorithmic ideas to your personality, not just the theory.