Compounding Craft: A Weekly System for Music, Writing, and Technical Growth
A practical weekly cadence for building creative and technical skill without burnout: consistent reps, tight feedback loops, and steady compounding over time.
11 articles in this category.
A practical weekly cadence for building creative and technical skill without burnout: consistent reps, tight feedback loops, and steady compounding over time.
A practical guide to navigating nat.io by intent, not chronology: who this site is for, what to skip, and how to get immediate value from the content.
A short, repeatable creative protocol for days when motivation is low: fixed constraints, fixed finish line, and a lightweight reflection loop.
Two people. Same model. Wildly different results. The difference isn't the AI. It's the operating system they run on top of it: prompts that force structure, adversaries, and audits.
Why continuous learning isn't about mastering everything, but about staying curious, sharp, and adaptable in an ever-evolving world.
A 30-year journey of self-directed learning in a credential-obsessed world, exploring how curiosity-driven education creates different but equally valuable expertise.
Your attention is the scarcest resource you have. Just like money, it can be invested, wasted, or compounded. Understanding the economics of attention transforms how we approach learning and skill development.
From learning Mandarin to training neural networks, every skill is fundamentally about translating between different systems of meaning. Understanding this changes how we approach mastery in any domain.
Exploring the dual systems of musical learning - how effective practice requires both deliberate, analytical training (System 2) and intuitive, automatic performance (System 1), with strategies for mastering the crucial transition between them.
In a world obsessed with the latest design tools and frameworks, understanding the fundamental difference between UI and UX—and how to learn both through timeless books—will make you a more effective designer regardless of technological shifts.
Understanding AI isn't just about algorithms and data—it requires an interdisciplinary approach drawing from cognitive science, philosophy, complex systems theory, and more. This guide reveals how combining perspectives from diverse fields can help unravel the mysteries of AI behavior.