This idea holds considerable promise, and supports many similar ideas I have found in practice to work well on skilling up in arbitrary domains of interest.
Currently that domain is Leetcode problems, which are about as concrete and deliberate practice-friendly as you can get, as a mind sport with a clear end goal (solve the problem) and 2 primary quality markers (CPU used by your solution, memory used by your solution.
To really make it into a proper loop I do my LC kata according to when they come up in my Anki decks, which isn’t deliberate practice but it’s closer than I think most part-time study regimens can get. An interesting phenomenon about doing a lot of practice in a concrete domain is that, for most new problems which I can’t yet get on the first shot, there is a very clear “first gate” stopping point where my brain throws up its hands and says “Bridge missing, consult solutions”. And indeed this first gate to understanding is usually much more difficult to overpower solely by myself, taking hours instead of minutes if I can open it at all. To say nothing of possible second, third etc gates that often appear afterward… I suspect these are distributed log-normally. I sometimes wonder if I’m depriving myself of potential unseen mental gains by usually deciding to just look at the solution and mark the Anki card as “again” instead of pushing through.
Incidentally I did some research in undergrad on control theory, the mathematical discipline underlying feedback loops, although like a lot of higher level math I haven’t found a decent way to transmit my intuition around e.g. Lyapunov stability into something that accelerates human or machine learning. I do get the sense there’s a there there.
This idea holds considerable promise, and supports many similar ideas I have found in practice to work well on skilling up in arbitrary domains of interest.
Currently that domain is Leetcode problems, which are about as concrete and deliberate practice-friendly as you can get, as a mind sport with a clear end goal (solve the problem) and 2 primary quality markers (CPU used by your solution, memory used by your solution.
To really make it into a proper loop I do my LC kata according to when they come up in my Anki decks, which isn’t deliberate practice but it’s closer than I think most part-time study regimens can get. An interesting phenomenon about doing a lot of practice in a concrete domain is that, for most new problems which I can’t yet get on the first shot, there is a very clear “first gate” stopping point where my brain throws up its hands and says “Bridge missing, consult solutions”. And indeed this first gate to understanding is usually much more difficult to overpower solely by myself, taking hours instead of minutes if I can open it at all. To say nothing of possible second, third etc gates that often appear afterward… I suspect these are distributed log-normally. I sometimes wonder if I’m depriving myself of potential unseen mental gains by usually deciding to just look at the solution and mark the Anki card as “again” instead of pushing through.
Incidentally I did some research in undergrad on control theory, the mathematical discipline underlying feedback loops, although like a lot of higher level math I haven’t found a decent way to transmit my intuition around e.g. Lyapunov stability into something that accelerates human or machine learning. I do get the sense there’s a there there.