This journal is generated by AI

Training the Idea Muscle: Quantity Over Quality

This week I came across a fascinating article about training the idea muscle that perfectly captures a principle I’ve been trying to internalize: if you reject your own ideas, the part of the brain that generates them will simply stop producing.

  • Never Reject During Generation: The key insight is to generate ideas continuously without filtering them in the moment. You sort them out later. This is similar to the Creativity Faucet concept—you need to let the bad ideas flow out first before the good ones emerge.
  • Do It While Learning: “I don’t think I’ve ever done anything I’m not good enough to do because I get good at the thing while doing it.” This reframes the common fear of not being ready—you become ready by starting.
  • Fun as the Filter: Only work on things you think are fun. This is the real filter, not whether you’re “good enough” or whether the idea is “good enough” initially.
  • Ideas Require Action: Ideas are everywhere, but most people don’t act on them. The muscle being trained isn’t just idea generation—it’s the habit of execution.

This connects beautifully with The Motern Method, a book about an artist who released 23,000+ songs by embracing quantity and rejecting perfectionism.

Slowing Down to Go Deeper

David Cain’s article on default settings being too high offers a counterintuitive productivity insight: slowing down often yields better results than rushing.

  • Reading Aloud: Limiting yourself to mouth-speed rather than eye-speed prevents rushing through text, missing important details, and losing interest. If you’re enjoying something, why would you want to be done with it sooner?
  • The Vacuum Analogy: Passing a vacuum too quickly over carpet means you miss half the dirt. Slow down, and you can hear how much more grit gets picked up. The same applies to reading and eating—the good stuff (meaning in text, pleasure in food) rises up to meet you in the extra time you give it.
  • Quality Over Speed: This challenges the default assumption that faster is better. Sometimes our cultural “default settings” for speed are calibrated too high for actual comprehension and enjoyment.

This resonates with my experience using AI tools—the temptation is to go faster, but often the value comes from slowing down and engaging more deeply with the material.

Learning Tacit Knowledge: Copying Better

Cedric Chin’s piece on acquiring tacit knowledge from experts provides a practical framework for learning skills that can’t be easily articulated.

  • Four Key Elements: When observing experts, focus on their cues (what they notice first), expectancies (what they expect to happen next), goals (their priorities), and actions (courses of action that immediately come to mind).
  • Prototypes vs. Options: Experts rarely compare multiple options—they pick the first available option that fits their criteria because they’ve built up mental prototypes. If you find yourself doing option comparison in a situation where a colleague doesn’t, that’s a signal they have a prototype you lack.
  • Narrative Construction: Experts construct narratives or simulations to explain what they’re seeing, matching patterns against different prototypes. This is fundamentally different from following explicit rules.

This framework is particularly relevant for software engineering, where so much expertise is tacit—knowing when to refactor, which abstractions to choose, how to structure systems. These aren’t things you can learn from documentation alone.