Addition through Subtraction, Nassim Taleb’s Via Negativa Heuristic

More features. More trades. More decisions. More uncertainty. More unexpected side effects.

Consider the converse. Fewer features. Fewer trades. Fewer decisions. Less uncertainty. Fewer side effects.

How can simplifying impact what you’re working on? In “Antifragile: Things That Gain from Disorder“, Nassim Taleb introduces readers to the Latin term via negativa.

The method began as an avoidance of direct description, leading to a focus on negative description, what is called in Latin via negativa, the negative way.

It’s a heuristic for simplifying. Removing things that add unnecessary complexity or uncertainty.

Michelangelo was asked by the pope about the secret of his genius, particularly how he carved the statue of David, largely considered the masterpiece of all masterpieces. His answer was: “It’s simple. I just remove everything that is not David.”

Consider this modernized version in a saying from Steve Jobs: “People think focus means saying yes to the thing you’ve got to focus on. But that’s not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully.”

It’s a heuristic that can be applied across various disciplines.

In product management, Jason Fried implements a framework of enough, where the product (or feature) doesn’t do everything but does what you need.

In trading Index Futures, channeling patience and executing fewer trades can result in greater returns compared to rushing into trades and overtrading.

In playing music, jazz guitarist Pat Metheny discusses the importance of mastering the fundamentals, being able to play solid quarter notes, having the ability to create memorable melodies with fewer notes.

In strength training, Pavel Tsatsouline challenges students to focus on two exercises: Kettlebell Swing and Turkish Get-Up.

Less-is-more.

The less-is-more idea in decision making can be traced to Spyros Makridakis, Robyn Dawes, Dan Goldstein, and Gerd Gigerenzer, who have all found in various contexts that simpler methods for forecasting and inference can work much, much better than complicated ones.