Palace/Note

Overview

learningreasoninginvestingaihabitseconomicsmental-modelssynthesis

Overview

This wiki has become a system for thinking, not just a shelf of summaries. Its recurring concerns are now clear: how people learn, how reasoning goes wrong, how good decisions survive uncertainty, how systems create incentives, and how ideas from different domains can be turned into practical operating models.

What This Wiki Covers

The vault currently draws on 76 source pages and clusters around fourteen recurring areas:

  • Learning science and skill acquisition: advice-on-upskilling, a-mind-for-numbers, the growth-mindset sources, and the surrounding pages on memory, chunking, retrieval, mindset, deliberate practice, grit, and failure tolerance.
  • Breadth vs depth and generalist advantage: range-why-generalists-triumph and the-polymath-peter-burke — kind vs wicked learning environments, sampling period, match quality, fox/hedgehog forecasting, institutional specialization, and when early narrowness wins or backfires. See also the tactical reading list a-reading-list-for-generalists-dylan-bowman focused on dispositional traits, unrelenting strategy, project leadership, and organizational navigation for generalists (heavy on Paul Graham and Ben Kuhn); its top recommendation humans-are-not-automatically-strategic-anna-salamon is now integrated with the core concept that humans are not automatically strategic and its 8 explicit heuristics; also learning-by-writing-holden-karnofsky on the writing-centered investigation loop.
  • Judgment and decision-making under uncertainty: thinking-fast-and-slow — System 1 vs System 2, heuristics and biases, inside/outside view, planning fallacy, prospect theory, framing, outcome bias, and the two selves; connects to Munger, Taleb, Marks, and Epstein clusters.
  • Reading method and bookcraft: Adler and Van Doren's How to Read a Book cluster on active reading, the four levels of reading, analytical reading, syntopical reading, and the adaptation of reading strategy to different genres.
  • Writing, articulation, and AI-era leverage: Dan Koe, Codex workflow essays, and instruction-system pages on how durable context improves both human and agent work.
  • Trading, investing, and uncertainty: Howard Marks, Taleb, Munger, Mark Douglas, CFI's beginner trading primer, and multiple trading essays on edge, sizing, cycles, randomness, and survival.
  • Critical thinking and fallacies: Elizabeth Cox's historical fallacy series, practical critical-thinking guides, the Socratic method, inferencing, and newer pages on reasoning types and causal mistakes.
  • Reading comprehension and vocabulary building: inferencing, context clues, word-part clues, specialized terminology, figurative language, and study tools for turning encountered words into memory.
  • Digital literacy and online judgment: the newer web, search, misinformation, privacy, AI, and app-platform cluster on how digital systems work, how they shape attention, and how to keep agency inside them.
  • Diagnosis and continuous improvement: what-are-5-whys, problem-framing, kaizen, design-thinking, and the synthesis on diagnosis before solution.
  • Habits and behavior change: atomic-habits and the cluster on identity, environment, friction, tracking, and compounding.
  • AI, AGI, and national-security framing: situational-awareness and its connected pages on intelligence explosion, superalignment, and agentic workflows.
  • Multidisciplinary mental models and psychology: Munger, Farnam Street, inversion, incentives, misjudgment, trust, and first- vs second-order thinking.
  • Political economy and capitalism: talking-to-my-daughter-about-the-economy and its concept pages on market society, labor, banking, money creation, inequality, crises, and the politics built into markets.
  • Personal synthesis and operating models: pages that try to turn clusters of material into reusable playbooks rather than isolated recaps.

The Emerging Shape

Several clusters now reinforce each other instead of living alone.

Learning science, habits, and deliberate practice form one stack: how skills are built, stabilized, and turned into automatic behavior. The breadth-vs-depth cluster (Burke + Epstein) now sharpens that stack — kind-vs-wicked-learning-environments explains when deliberate practice and chunking transfer, and when sampling and far transfer matter more. Kahneman adds the judgment layer beneath both: system-1-vs-system-2, wysiati, and substitution-heuristic explain why confident intuition fails in wicked domains even when practice was excellent in kind ones. Critical thinking, fallacies, and reasoning-type pages form a second: how beliefs get tested, where inference fails, and how to inspect claims before acting on them. Trading, investing, and uncertainty form a third: how to make decisions when noise, incentives, psychology, and ruin risk all matter at once — now with experimental mechanisms behind probability-blindness and decision-quality-vs-outcome.

The newer political-economy material widens the wiki in a useful direction. It adds a systems layer beneath older topics like leverage, incentives, labor, value, and power. Questions that once appeared mainly as personal strategy now sit inside a clearer picture of the structures shaping them.

The digital-literacy cluster adds a different kind of systems layer. It turns the internet from background infrastructure into an object of thought: how pages are served, how search ranking and personalization shape discovery, how verification must leave the page, how surveillance changes behavior, how AI changes the cost of fluent error, and how app platforms govern software distribution.

Best Entry Points

Current Totals

  • Sources: 76
  • Entities: 45
  • Concepts: 222
  • Synthesis pages: 10