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.

Depth

The expert’s skills are deeply layered. Specifically, they have achieved mastery of aspects of their field that non-experts aren’t even aware exist and each layer builds on the previous one. Take, for example, Josh Waitkin’s description of learning to play chess:

We will start with day one. The first thing I have to do is to internalize how the pieces move. I have to learn their values. I have to learn how to coordinate them with one another.

Early stages

So let’s say that now, instead of launching from the standard starting position, we begin on an empty board with just a king and a pawn against a king. These are relatively simple pieces. I learn how they both move, and then I play around with them for a while until I feel comfortable. Then, over time, I learn about bishops in isolation, then knights, rooks, and queens.

Soon enough, the movements and values of the chess pieces are natural to me. I don’t have to think about them consciously, but see their potential simultaneously with the figurine itself. Chess pieces stop being hunks of wood or plastic, and begin to take on an energetic dimension. Where the piece currently sits on a chessboard pales in comparison to the countless vectors of potential flying off in the mind. I see how each piece affects those around it. Because the basic movements are natural to me, I can take in more information and have a broader perspective of the board. Now when I look at a chess position, I can see all the pieces at once. The network is coming together

Layers upon layers

 Over time, that process becomes increasingly natural to me, until I eventually see the pieces and the appropriate principles in a blink. While an intermediate player will learn how a bishop’s strength in the middlegame depends on the central pawn structure, a slightly more advanced player will just flash his or her mind across the board and take in the bishop and the critical structural components. The structure and the bishop are one. Neither has any intrinsic value outside of its relation to the other, and they are chunked together in the mind.

 This new integration of knowledge has a peculiar effect, because I begin to realize that the initial maxims of piece value are far from ironclad. The pieces gradually lose absolute identity. I learn that rooks and bishops work more efficiently together than rooks and knights, but queens and knights tend to have an edge over queens and bishops. Each piece’s power is purely relational, depending upon such variables as pawn structure and surrounding forces. So now when you look at a knight, you see its potential in the context of the bishop a few squares away. Over time each chess principle loses rigidity, and you get better and better at reading the subtle signs of qualitative relativity.  Soon enough, learning becomes unlearning. The stronger chess player is often the one who is less attached to a dogmatic interpretation of the principles.

This leads to a whole new layer of principles— those that consist of the exceptions to the initial principles. … Learning chess at this level becomes sitting with paradox, being at peace with and navigating the tension of competing truths, letting go of any notion of solidity.

Towards mastery

This is where things get interesting. We are at the moment when psychology begins to transcend technique. Everyone at a high level has a huge amount of chess understanding, and much of what separates the great from the very good is deep presence, relaxation of the conscious mind, which allows the unconscious to flow unhindered. This is a nuanced and largely misunderstood state of mind that when refined involves a subtle reintegration of the conscious mind into a free-flowing unconscious process.

 Most people would be surprised to discover that if you compare the thought process of a Grandmaster to that of an expert (a much weaker, but quite competent chess player), you will often find that the Grandmaster consciously looks at less, not more. That said, the chunks of information that have been put together in his mind allow him to see much more with much less conscious thought. So he is looking at very little and seeing quite a lot. This is the critical idea. … The Grandmaster looks at less and sees more, because his unconscious skill set is much more highly evolved.

 Nothing I have seen in over 25 years in semiconductors and EDA to make me think that the above should not have an analogy in our field. And I know a few people who I believe are well along this path — it’s a core part of what we look for in Verilab. But it’s not widespread across the industry. I think it needs to become much more common.

Precision

Training leading to mastery is finickity, attentive to detail, exacting. It’s precise. Years ago, my wife and I dabbled in partner dancing — Latin American, and Ballroom. One evening, after only a few months practice, the teacher allowed a few couples to stay on after our beginners’ class to get a taste of the intermediate training.   My wife and I, and a few other beginner couples, watched from the side for a while, and then we were allowed onto the floor to work with the more experienced dancers on our Waltz. We were already experienced enough to know the overall couple shape, and the general progress of the dance across the floor. We were also competent enough to avoid colliding with anyone else (although that’s partly because we were slow!) So I thought we were doing OK, but then the teacher glared at me, walked across, and firmly modified the angle between my left hand and my left forearm. I was making a common beginner mistake by holding my arm too low, resulting in a bend between the top of my forearm and the back of my hand. In fact there should be no bend. That tiny change somehow made a positive difference to our overall posture. Or at least, I thought it did. The teacher did nod approvingly for a moment, but then he frowned at something else but moved on to help another couple.

An immediate reaction to a demand for more precision in our practice and training in programming could lead to complaints that “we have a product to get out!” and “the client doesn’t care about that!” I’m not arguing that pragmatism needs to be ignored, but I believe such complaints are counterproductive. If I look at the best engineers I know, they already know how to be pragmatic. A core part of what drives them is precisely to be efficient, minimal, and to satisfy the client needs. But in the elite engineers I work with, there just doesn’t seem to be a dichotomy between precision and pragmatism. They achieve the latter via the former.

Persistence

To be honest, “persistence”, in the sense of not giving up, only scratches the surface of this final component. The persistence must be done while maintaining depth and precision. The best English word for this is probably assiduity. But whatever we call it, it’s worth drawing out the notion and placing it on an equal footing with the other two, because it is, by all accounts, absolutely essential. There certainly are child prodigies, and there is beginner’s luck, but there are few if any experts who have reached their high levels of performance without a lot of work. Here is Cal Newport in So Good They Can’t Ignore You, talking about the accomplished guitarist, Jordan Tice:

Jordan picked up his Martin to play me the new song. It had the driving beat of bluegrass, but the melody, which was inspired by a Debussy composition, happily disregards the genre. When Jordan played, he stared just beyond the fretboard and breathed in sharp, sporadic gasps. At one point he missed a note, which upset him. He backed up and started again, insisting on playing until he finished the full phrase without mistake. I told him I was impressed by the speed of the licks. “No, this is slow,” he replied. He then showed me the pace he’s working toward: It’s at least twice as fast. “I can’t quite make the lead trail yet,” he apologized after it slipped away from him. “I guess I could do it, but I can’t get the notes to pop out yet like I want it.” He showed me how the successive notes in the lead tend to span many strings, complicating fast picking. “It’s really wide.”

In the above we see precision in action. And, characteristic of experts, Tice is training at the edge of his ability. That’s why he misses a note, and why it upsets him. But Newport goes on:

At my request, Jordan laid out his practice regimen for this song. He starts by playing slow enough that he can get the effects he desires: He wants the key notes of the melody to ring while he fills the space in between with runs up and down the fretboard. Then he adds speed— just enough that he can’t quite make things work. He repeats this again and again. “It’s a physical and mental exercise,” he explained. “You’re trying to keep track of different melodies and things. In a piano, everything is laid out clearly in front of you; ten fingers never getting in the way of one another. On the guitar, you have to budget your fingers.” He called his work on this song his “technical focus” of the moment. In a typical day, if he’s not preparing for a show, he’ll practice with this same intensity, always playing just a little faster than he’s comfortable, for two or three hours straight. I asked him how long it will take to finally master the new skill. “Probably like a month,” he guessed. 

Two or three hours a day. For a month. And this particular song was merely his focus “of the moment”. Judging by Tice’s success, that was just one of many, many such focuses of the moment he has tackled over the years. Depth, Precision, Persistence — or, in the words of the literature, “10,000 of deliberate practice”.  You will not become expert without them; with them, expertise may well be within your grasp. Hence the name of this blog — Altum, Accuratum, Assiduum — in which I explore this area, and our own pursuit of mastery in Verilab.