The flood of books on expertise, and mastery has been going on for some time now. From popularizers like Malcolm Gladwell in Outliers, to expertise scholars like Anders Ericsson and his co-editors in The Cambridge Handbook of Expertise and Expert Performance, and including the thoughts of those who have demonstrated expertise and mastery, such as Josh Waitzkin (chess and martial arts) in The Art of Learning, Matthew Syed (Table Tennis) in Bounce, and also those experimenting in methods of becoming expert, such as Cal Newport in So Good They Can’t Ignore You, a wide range of ideas have been gathered together under a single banner.
I’ll explore those and more in future posts, but what has struck me as I’ve studied this area is the prominence of three specific ideas that all those widely ranging accounts seem to share. They are three characteristics that the training and studying approaches of all experts seem to have in common. Regardless of the field of expertise, without fail the training and studying is deep, precise, and persistent. At first sight, those can seem obvious, but let me take each in turn and describe what I think it’s attached to. As you read these, consider what they might look like in the development of expertise in programming, and particularly in chip verification and design. Continue reading