Solving for learning: why

About twelve months ago my life changed. I left shift work and began working for a startup. As a part of this adventure I’ve made a deliberate effort to hone the writing, product and technical skills that my role allows me to exercise—yes, I am actively interpreting this trio as the foundation for a moat.

What I do now is unlike anything I’ve done before. New organisation and market structures; new tempos; new people; new expectations; new incentives; new ways of working; new purposes; new skills; new ideas. Another name for this scenario? An apprenticeship.

This is the perspective shift that I’ve been thinking about over the last couple days. And here’s why: in Robert Greene’s Mastery, the explicit and all-important, overarching purpose of an apprenticeship is learning.

“…the goal of an apprenticeship is not money, a good position, a title, or a diploma, but rather the transformation of your mind and character—the first transformation on your way to mastery.”

In an apprenticeship, everything should be orientated towards the accumulation of knowledge, experience, skills, growth, expertise—any synonym for learning you can think of. There’s a simple answer for why this should be the case: most things we want can be acquired as a consequence of deliberate, long-term periods of compounded learning.

Take a peak at the Bill Walsh’s and Steve Jamison’s, The Score Takes Care of Itself. As the title indicates, the entire premise of the book is that emphasising process over outcome leads to a better outcome than focusing on outcomes alone.

The book uses professional sports—American football, specifically—as its backdrop. Professional sports is a notoriously finite game on the organisational level: there can only be one champ. It’s also a cut-throat finite game on the individual level: most professional athletes have only careers and the competition for those careers is ferocious.

I suspect cementing learning as the key focus of an apprenticeship is best done in the context of an infinite game—where the point is not to win the game but to keep the game going. A good example of this is the idea that “people like Olympic athletes get where they get by mediocratizing rather than optimizing what they do”. This comes from Venkatesh Rao’s Mediocratopia blogchain:

“This kind of improvement replaces quantitative improvement (optimization) with qualitative leveling up, or dimensionality increase. Each time you hit diminishing returns, you open up a new front. You’re never on the slow endzone of a learning curve. You self-disrupt before you get stuck. So you get a learning curve that looks something like this (yes, it’s basically the stack of intersecting S-curves effect, with the lower halves of the S curves omitted)”

“Opening a new front.” “Self-disrupting.” This is solving for learning, and while it can result in finite game wins it will also lead to continual progression in the infinite game of life. The process and outcome of continual learning ultimately results in higher engagement with reality and higher satisfaction with it, too. Most things can be derived from that.

For contrast, consider the opposite of solving for learning: apathy. Apathy is disengagement, disinterest, uncaring. Apathy doesn’t pay attention, doesn’t ask questions, doesn’t wonder, doesn’t experiment—doesn’t do much of anything at all. The apathetic don’t do much and presumably don’t enjoy the experience of being very much, either (no comment on the systemic structures that reliably generate individual and/or collective apathy).

I guess that the real purpose of solving for learning in an apprenticeship phase is that it ingrains habits and perspectives that result in a quality of experience that is much higher than if we solved for something else.