Think Better — a collection of one-to-two page chapters explaining metacognitive "thinking tools", organized in three sections:

• See Clearly — Analyze → organize and evaluate data
• Know Deeply — Assess → model and understand systems
• Choose Wisely — Act → develop and decide strategies

Each chapter consists of a title, a BLUF to remember, an introductory paragraph, a brief set of rules and relationships to learn, a few examples, and recommended further readings. Each chapter corresponds to a single summary card in the "Think Better" metacognition deck.

Chapters:

• Analyze → See Clearly — organize and evaluate data
  • Be a Better Bayesian — estimate initial odds for each case, and as new evidence comes in update the odds based on likelihood of observations ("Beliefs should be Knobs, not Switches!")
  • Signal, Noise, and Interference — Signals convey information, noise is random, and adversaries add interference
  • Statistical Savvy — data comes in distributions, defined by experience; learn the concepts of mean, variance, skew, "long tails", outliers, etc.
  • Conservation — some quantities are neither created nor destroyed; identify them, follow their flows, and track down any apparent "leaks"
  • Independence — find the factors that carry the most information and aren't conditional or connected to each other; analyze them and identify the most important ones
  • Square Root Rule — deviations tend to grow like the square root of the number of things (random walk steps, survey sample results, fluctuations in random events, ...)
  • Generalize — solve a whole family of questions at once by using symbols instead of specific numbers
  • Specialize — divide-and-conquer to attack complex situations; plug in specific numbers to confirm solutions
  • Analogize — find parallel patterns in distant domains; rename, reverse, reuse, reframe
  • Anomalies — examine odd outliers as potential portents of change and as exceptions that can refine rules
  • Logic — build systematic Truth Tables of all possible combinations and test their consistency
  • Falsify — test hypotheses and seek counterexamples, not confirmation
  • Structures — graph continuous variables, sort discrete events into bins, and examine all dimensions of situations
• Assess → Know Deeply — model and understand systems
  • Identify Implications — examine the consequences of proposed rules, compare with observations, and design new tests including both positive (presence) and negative (absence) factors
  • Summarize — put the bottom line up front (BLUF), respect the reader, make it memorable
  • Identify Actors — find primary players, locate leverage points, and evaluate extremes (the strongest, widest ranging, fastest changing, most persistent, ...)
  • Group — combine similar entities to hide complexity, simplify modeling, and enhance understanding
  • Split — divide distinct entities to avoid ambiguity, clarify difference, and enhance model accuracy
  • Evaluate Changes — quantify shifts, spreads, slides, swings, accelerating flows, directional drift, etc.
  • Feedback — study causal patterns and self-regulating systems, positive (reinforcing, runaway) and negative (stabilizing, balanced) connections
  • Limits — look for barriers to further change such as nonlinearities, competiting forces, resource depletion, and waste accumulation
  • Interfaces — study connections between systems and sub-system components, such as matter or energy flows across boundaries, mismatches, delays, reflections, etc.
  • Spectra — study system changes across space and time, measure frequencies and repetition rates, look for resonances and interference patterns
  • Coordinates — find the natural directions and dimensions of a system, viewpoints from which situations seem simpler, axes along which things rotate or repeat
• Act → Choose Wisely — develop and decide strategies
  • Allies — build partnerships, identify common ground and shared goals and complementary skills, make friends
  • Game Theory — catalog choices for each side in a competition and play them against each other, evaluate results, and apply rules to optimize; learn concepts like Minimax, Prisoner's Dilemma, Pure and Mixed Strategies, Perfecxt Information, etc.
  • Cognitive Fallacies — recognize and avoid unforced errors such as seeking confirmation, attributing malice, anchoring prematurely
  • Robustness — recognize and avoid non-resilient strategies, remember that models are imperfect simplifications, recognize changes in the situation, accept graceful degradation, anticipate that adversaries will attempt the unexpected
  • Maximize Utility — apply numbers to outcomes (lost income, replacement cost, risk, relative preference order, ...) and optimize
  • Minimax — find the least-bad worst-case and the least-good best-case, and optimize in between
  • Anticipate Dishonesty — ask how likely information is to be true, reliability of the sources, fit with prior data, motivation for deception
  • Model All Actors — identify values, goals, resources, and constraints associated with a situation for each entity that competes and chooses
  • Nonlinearity — be aware of things that grow faster or slower than the changes in their inputs, and relationships that change over time or space
  • Shuffle — consider different orders of events or choices, and see whether transposition preserves or can change outcomes
  • Sort — arrange factors (inputs, outputs, actors, factors, ...) in various orders (increasing, decreasing, similar clusters, dimensions of difference, ...) and seek patterns that might matter