Skip to content
How to ThinkIn the Age of AI

Rules

1,053 rules · page 11 of 22

Rule

Train body-scanning to detect somatic markers early…

Train interoceptive awareness through systematic body-scanning practices to detect somatic markers early enough to intervene before automatic responses execute.

1 lesson
Rule

Start triggers conservatively — 3-5 daily activations…

Start behavioral triggers with a more conservative threshold than feels right, aiming for 3-5 activations per day rather than 30, to build trust through relevance before expanding sensitivity.

1 lesson
Rule

Classify trigger firings as true/false positives for one…

Log each trigger firing for one week as true positive or false positive, then adjust the threshold only after accumulating empirical data rather than based on single instances.

1 lesson
Rule

When false positives exceed 30%, add guard clauses…

Add qualifying guard clauses to behavioral triggers when false positives exceed 30% of total activations, inserting context checks that must pass before the main action executes.

1 lesson
Rule

Scale guard clause complexity to false-positive cost…

Match the number of qualifying conditions to the cost of false positives—use minimal guards for low-cost triggers and multiple defensive checks for high-consequence triggers.

1 lesson
Rule

When triggers fail to fire, increase signal strength…

When a trigger consistently fails to fire, increase its signal strength through modality shift, physical obstruction, temporal isolation, implementation intentions, or redundant cueing rather than attempting to 'remember better.'

1 lesson
Rule

Place triggers at the exact decision fork where behaviors…

Position physical trigger cues at the exact decision fork where competing behaviors diverge, not merely in the same room, because triggers must intercept choice at the moment it occurs.

1 lesson
Rule

Audit your real movement patterns before placing triggers…

Audit your actual movement patterns through physical space before placing any environmental triggers, because triggers placed on aspirational paths rather than real paths will never fire.

1 lesson
Rule

Encode the full action protocol in your notification text…

For each digital trigger, encode the complete action protocol in the notification text itself ('Daily Review — 3 wins, 1 lesson, tomorrow's top 3') rather than generic labels, to eliminate decision-making at activation.

1 lesson
Rule

Ask 'Did you write for 30 minutes?' not 'Did you finish…

Design social accountability around process questions ('Did you write for 30 minutes?') rather than outcome questions ('Did you finish the chapter?') because process accountability triggers action while outcome accountability triggers anxiety.

1 lesson
Rule

One week of zero firing = mandatory redesign — change…

When a trigger has not fired successfully in one week despite being needed, redesign it immediately by changing at least one of: salience, timing, modality, or context specificity.

1 lesson
Rule

Accountability reporting must be near-zero effort…

Make social accountability reporting require near-zero effort (single emoji, shared spreadsheet checkbox, photo) rather than written explanations, because reporting friction kills trigger reliability.

1 lesson
Rule

Remove any trigger that produces action less than 80%…

Set your trigger signal-to-noise ratio threshold at 80% actionability minimum — remove any trigger that produces action fewer than 80% of times it fires.

1 lesson
Rule

Monthly trigger audit

Conduct monthly trigger audits by evaluating each trigger against four questions: Is it still firing? Do you respond when it fires? Is the behavior still relevant? Is calibration still correct?

1 lesson
Rule

Design triggers for your worst cognitive day…

Design triggers to work at your minimum cognitive state (tired, distracted, depleted) rather than your maximum state, because triggers must function when you need them most.

1 lesson
Rule

Classify every decision as one-way or two-way door before…

Before beginning deliberation on any decision, classify it as one-way door (irreversible/high-stakes) or two-way door (reversible/low-stakes) and allocate analysis time proportionally—minutes to hours for two-way doors, days to weeks for one-way doors.

3 lessons
Rule

Use a weighted decision matrix when options exceed 3…

For decisions involving three or more options and four or more criteria, externalize the comparison into a weighted decision matrix rather than relying on intuitive averaging, because working memory cannot hold all dimensions simultaneously.

1 lesson
Rule

Assign criterion weights before scoring options — knowing…

When building a decision matrix, assign criterion weights before scoring any options to prevent unconscious adjustment of weights toward your pre-existing preference.

1 lesson
Rule

Score by criterion across options, not by option across…

Score one criterion at a time across all options rather than one option at a time across all criteria, to force apples-to-apples comparison and reduce halo effects.

1 lesson
Rule

Every decision framework needs five explicit components

For each decision framework you build, explicitly include five components: evaluation criteria, sequence of evaluation, time budget, kill conditions (automatic disqualifiers), and decision rights (who decides, who is consulted).

1 lesson
Rule

For reversible decisions, act at 50-60% information…

For reversible decisions, act when you have 50-60% of desired information because experiential learning from outcomes typically exceeds information gain from additional deliberation.

1 lesson
Rule

After irreversible commitments, schedule external reviews…

After making irreversible commitments, schedule reviews with someone uninvolved in the original decision and define success/failure criteria in advance, because escalation of commitment will corrupt your post-decision assessment.

1 lesson
Rule

Before committing to a one-way door, search for ways…

When facing a one-way door decision, actively search for ways to restructure it into a two-way door through trial periods, exit clauses, smaller pilots, or phased rollouts before committing to the heavyweight deliberation process.

1 lesson
Rule

Two-way door decisions with sub-week reversal costs get 24…

For two-way door decisions where reversal costs under one week of effort, set a decision deadline of 24 hours or less regardless of how the decision feels emotionally.

1 lesson
Rule

Define rollback metrics and automated reversal triggers…

When implementing feature flags, canary deployments, or A/B tests, treat the deployment decision as a two-way door by defining rollback metrics and automated reversal triggers before deployment.

1 lesson
Rule

For two-way doors with persistent disagreement, invoke…

When disagreement persists on a two-way door decision after expressing positions, invoke 'disagree and commit'—explicitly state disagreement, commit to supporting the chosen path, and move forward immediately without seeking consensus.

1 lesson
Rule

Apply the 37% rule to search decisions — explore…

When hiring or making other search-based decisions from a known pool size, spend the first 37% of candidates or options in pure exploration (reject all, calibrate threshold), then commit to the next candidate that exceeds the best seen in the exploration phase.

1 lesson
Rule

Reduce options to 5-7 before evaluating — choice overload…

For decisions where options number more than 7, either reduce the option set to 5-7 before evaluation or use elimination criteria to filter before detailed comparison, because choice overload degrades both decision quality and satisfaction above this threshold.

1 lesson
Rule

Design pre-commitments when calm to constrain behavior…

Design pre-commitment rules during cold cognitive states (well-rested, calm, not under deadline pressure) to constrain behavior during hot cognitive states (stressed, depleted, emotionally activated), never vice versa.

1 lesson
Rule

Decision journal entries need six fields captured before…

When recording a decision in a journal, capture six mandatory elements before outcome is known: date/time, one-sentence decision, reasoning chain, expected outcome (falsifiable), confidence percentage, and current mental/physical state.

1 lesson
Rule

Review decisions in three steps

When reviewing decision journal entries, follow the three-step sequence: (1) re-read original reasoning with outcome hidden, (2) predict outcome based only on original reasoning, (3) uncover actual outcome and compare all three—this sequence defeats hindsight bias.

1 lesson
Rule

After 30+ journal entries, calculate your calibration…

Across 30+ decision journal entries, calculate your calibration by grouping decisions by stated confidence level (e.g., all 70% predictions) and checking whether that percentage actually occurred—use this ratio to adjust future confidence statements.

1 lesson
Rule

Evaluate decision process separately from outcome — 'was…

When reviewing decision outcomes, evaluate process quality independently from result quality by asking 'given what was knowable at decision time, was the reasoning sound?' rather than 'did it work out?'

1 lesson
Rule

Decide at 70% information — waiting for 90%+ almost always…

Apply the 70% information threshold: if you have 70% of the information you wish you had, decide immediately—waiting for 90%+ almost always costs more than the improved decision quality returns.

1 lesson
Rule

Review all installed defaults quarterly — outdated…

Schedule quarterly reviews of every default you have installed in your systems and processes, because contexts change and outdated defaults silently steer toward yesterday's goals without conscious detection.

1 lesson
Rule

Before purchasing, name what else the money could buy…

Before committing to any purchase decision, explicitly name what else that money could buy in different categories (not just competitor products), because mental retrieval naturally limits alternatives to within-category competitors and misses the highest-value cross-category tradeoffs.

1 lesson
Rule

Calculate optimization breakeven time — if payback exceeds…

When evaluating whether to optimize an existing system, calculate breakeven time by dividing optimization effort by weekly time savings—if payback exceeds the system's expected remaining lifespan, redirect effort to the actual constraint instead.

1 lesson
Rule

Delegate any decision reversible within one week at low…

Apply the irreversibility test to every delegation candidate: if the decision can be reversed at low cost within one week, delegate it regardless of its perceived importance; if reversal is expensive or impossible, retain it for your direct judgment.

1 lesson
Rule

Every delegation needs three written components

For every delegated decision, specify three mandatory components in writing: the single accountable owner (one person not a committee), the constraints within which they have full authority, and the explicit conditions that trigger escalation back to you.

1 lesson
Rule

For 6+ person decisions, collect independent written…

When a decision requires input from six or more people with distributed expertise, use independent written assessment before any group discussion—have each person write their recommendation anonymously, compile responses, then discuss—to prevent anchoring and social hierarchy from suppressing better information.

1 lesson
Rule

Use consent-based decisions for speed+buy-in — proceed…

For operational decisions requiring both speed and buy-in, use consent-based decision making: present a proposal and proceed unless someone articulates a specific reasoned objection (how it would prevent achieving goals), rather than seeking consensus (positive agreement from everyone).

1 lesson
Rule

Consensus is for existential decisions only — founding…

Reserve consensus decision-making exclusively for existential decisions where the group cannot survive executing an outcome some members fundamentally oppose—founding documents, core values, irreversible strategic pivots—because consensus is the slowest inclusive framework and should match its cost to decision stakes.

1 lesson
Rule

Classify decisions as speed-dominant or accuracy-dominant…

Before any analysis begins for a decision, explicitly classify it as speed-dominant (reversible, low cost of wrong, high cost of delay) or accuracy-dominant (irreversible, high cost of wrong, low cost of delay), then let that classification dictate process—fast decisions get 15 minutes and bias toward action, slow decisions get structured analysis.

1 lesson
Rule

Score process and outcome independently on a 2x2…

Evaluate decision quality separately from outcome quality by scoring process and results independently, placing decisions in a 2x2 matrix to distinguish deserved success, bad luck, dumb luck, and deserved failure.

1 lesson
Rule

Run four diagnostic questions in 60 seconds to select…

Before selecting a decision framework, run four diagnostic questions in sequence: (1) How reversible? (2) How many competing criteria? (3) What time horizon of consequences? (4) What is the cost of analysis itself?—using the answers to converge on the appropriate framework class within 60 seconds.

1 lesson
Rule

Add 'Did I use the right framework?' to every decision…

In post-decision review, explicitly add the meta-question 'Did I use the right framework for this decision?' and note framework-decision mismatches (comprehensive analysis on trivial reversible choices, satisficing on irreversible high-stakes decisions) to build your personal routing table.

1 lesson
Rule

Categorize weekly decisions as routine or novel — build…

Audit your work week by categorizing each decision as 'routine' (similar decision made before, could use framework) or 'novel' (requires fresh thinking), then for the five highest-frequency routine decisions, draft simple frameworks (default answer, two-option heuristic, or pre-commitment rule) and implement all five within one week.

1 lesson
Rule

After recurring activities, spend 60 seconds recording…

Add a 60-second structured observation step immediately after recurring activities, recording one sentence about output and one about potential changes, to convert open-loop repetition into closed-loop learning.

1 lesson