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My first thought when reading your comment was "How could you possibly fit everything there is to learn into 4 hours a day?", but I think the disconnect is in two different conceptions of what a job is - For most people, a job is something where you are hired to do a specific task for a specific wage, using specific skills that you learn once and then apply many times. "Make this button green." "Move the navbar 20px to the right." "When this button is clicked, send off an RPC to the server, and when it's complete, update the table with the relevant data." These types of tasks lend themselves well to an "instruction manual" approach to skill acquisition: you read the manual, you apply it to your job, you memorize the parts that you use frequently, and you're done. Once you know everything in the manual, there's little point in studying further, because you know everything in the manual. A smaller (but growing) minority of jobs require you to solve a vaguely-defined problem, where there is no manual because nobody's solved it before, and often times the problem hasn't even been posed in a tangible form. "Find out who wrote everything on the web." "Evaluate whether we should invest $5M into this venture capital fund." "Identify our next billion-dollar business." "Make cryptocurrency useful." These jobs lend themselves to a "toolbox" approach. There is no manual, but if you have a wide enough breadth of experience, you've picked up a large variety of tools that you might be able to apply to the problem. So if you're tasked with figuring out who wrote what on the web, one approach might be ask the authors by having them add HTML markup, and then parsing and following that. Another approach might be to identify author bylines through machine-learning and then cross-reference them with a database of peoples' names that appear on the web. A third approach might be to identify pictures next to the byline and run facial recognition on them. You don't know which approach will be most useful until you're given the problem and actually try a few, but the bigger your toolbox, the more likely you are to find one that works. The financial returns to these types of jobs tend to scale exponentially with their complexity, because the number of people who can solve them decreases exponentially. That's why it's beneficial to have as big a toolbox as you possibly can if you want to play in these markets. |