Notes On The Steady And Slow Concept

A few weeks ago I sang the praises of intensity recruitment and its power to make things happen in the moment. But since intensity isn’t sustainable, we do well to spend most of our time working steady and slow. If intensity recruitment is about marshaling a high level of engagement, steady and slow is creativity at a low oscillation—just humming along, tinkering, trying things out, and gradually building something up. For artists of all types steady and slow is the optimal state to be in when you want to refine what you did in a state of intensity recruitment. Slow and steady is being okay with being bored, okay with attending to the details, okay with trying out alternate versions, okay with changing one thing to see how it affects the rest, okay with standing back for a moment and assessing what had been improvised/composed in a state higher intensity. 

To return to athletics again: it is well known that elite runners do the majority of their workouts—about 80 percent—at a slow and steady pace. To us amateurs, this seems counterintuitive: How can going slow train you to go fast? We do most of our workouts in the medium to hard effort range. But the research tells us it would be better to go very hard only 20 percent of the time, and very easy 80 percent of the time, and avoid the in-between altogether. (It is said that going slow “builds the aerobic engine.”) The science behind this research explains that what is at stake is exercise’s relationship to recovery. Just as the musician builds skills between practice sessions, the athlete uses easy workouts to actively recover from higher intensity sessions that happen only once or twice a week.


I use steady and slow as a way to modulate the intensity of composing, which in essence is improvising in slow motion. Once I have begun something new, I don’t stop, I don’t edit, and most importantly, I don’t try to understand what has begun. Instead, I keep the composing moment rolling along, whilst trying to not overdo it. For example, if I’ve played something “good enough” I’ll work with that to spur the next steps. Or if I accidentally stumble upon an interesting sound while developing a part, I keep it. I use whatever is closest at hand, trusting that there’s a way to make something work with what I have if I just follow the potentials of the materials. In sum, as with easy running, ideas seem to organically emerge when you go steady and slow. 

Double Resonant Thoughts: Algorithms To Live By (2016) and Thinking In Bets (2018)

“Even the best strategy sometimes yields bad results—which is why computer scientists take care to distinguish between ‘process’ and ‘outcome.’ If you followed the best possible process, then you’ve done all you can, and you shouldn’t blame yourself if things didn’t go your way.”

Brian Christian and Tom Griffiths, Algorithms to Live By  

“What makes a decision great is not that it has a great outcome. A great decision is the result of a good process, and that process must include an attempt to accurately represent our own state of knowledge. That state of knowledge, in turn, is some variation of ‘I’m not sure.’”

Annie Duke, Thinking In Bets