Principles
2,201 principles · page 33 of 46
Assign a concrete next action to each blocker to eliminate…
Assign a concrete next action to each blocker to eliminate cognitive intrusion even before the blocker is fully resolved.
Generate explanations of new material by asking 'why…
Generate explanations of new material by asking 'why is this true?' and 'how does this connect?' rather than summarizing what was said.
Focus failure analysis on system-level causal chains ('what…
Focus failure analysis on system-level causal chains ('what in my process allowed this') rather than character judgments ('what's wrong with me') to extract actionable improvements.
Break progress externalization into the smallest sustainable
Break progress externalization into the smallest sustainable unit—a single daily entry requiring under 60 seconds—because elaborate tracking systems collapse under maintenance overhead while simple systems persist.
Design physical and digital workspaces to afford only…
Design physical and digital workspaces to afford only the cognitive operations required for current work, removing all objects and applications that compete for attention, because every irrelevant stimulus in the perceptual field consumes neural processing resources that could support task focus.
Document not only what tools you use but the complete…
Document not only what tools you use but the complete routing rules, processing workflows, decision principles, and evolution history of your knowledge management system, because undocumented systems cannot be debugged, improved, transferred, or rebuilt after failure.
Test AI interactions for cognitive extension versus…
Test AI interactions for cognitive extension versus replacement by assessing whether you understand more after the interaction and could reconstruct the reasoning independently, because partnership requires mutual capability growth while delegation produces dependence.
Externalize mental models by writing them down as named…
Externalize mental models by writing them down as named, versioned artifacts to convert invisible cognitive habits into inspectable infrastructure.
Treat surprises and violated expectations as diagnostic…
Treat surprises and violated expectations as diagnostic signals that reveal which operating schemas need inspection, since mismatches between prediction and reality expose invisible assumptions.
Maintain competing schemas for the same domain to counteract
Maintain competing schemas for the same domain to counteract confirmation bias, since single schemas automatically classify contradictory evidence as noise before conscious evaluation.
Use AI as a schema inspection tool by articulating…
Use AI as a schema inspection tool by articulating your reasoning in text and asking it to identify unstated assumptions, since AI operates on text rather than emotional charge and can detect patterns you cannot see from inside.
Conduct schema audits by writing down actual operating…
Conduct schema audits by writing down actual operating rules, sourcing their origin, testing them against success and failure cases, and rating confidence against evidence.
Periodically verify that your documented schemas match…
Periodically verify that your documented schemas match current operational reality by directly observing the system rather than consulting representations.
When two people's schemas of the same situation diverge…
When two people's schemas of the same situation diverge, treat the divergence itself as information about complexity the territory contains that neither schema fully captured.
For any schema you plan to act on, explicitly inventory…
For any schema you plan to act on, explicitly inventory three omissions—things the real territory contains that your schema does not—to counteract the natural tendency to treat a single mental model as complete.
Define explicit usefulness boundaries for each schema…
Define explicit usefulness boundaries for each schema specifying where it stops working and what alternative framework to switch to at those boundaries.
Practice defusion from schemas by explicitly labeling…
Practice defusion from schemas by explicitly labeling them as 'my schema of X' rather than 'what X is' to create psychological distance between yourself and the representation.
Ask trusted observers to identify assumptions they see…
Ask trusted observers to identify assumptions they see you operating from that you may not be aware of, since defensive routines make your own schemas invisible to you while remaining obvious to others.
Track your revealed preferences by comparing stated criteria
Track your revealed preferences by comparing stated criteria with actual decision patterns, using the gap as a measurement of schema blindness.
Deliberately choose what resolution you need…
Deliberately choose what resolution you need for your current purpose rather than attempting to maximize resolution across all dimensions, since cognitive resources are finite and higher resolution everywhere produces overload.
Before learning new domain content, explicitly surface…
Before learning new domain content, explicitly surface and externalize your current implicit schema for that domain — this creates structure for new information to integrate with rather than overwrite.
When making schemas explicit, externalize competing…
When making schemas explicit, externalize competing interpretive frameworks simultaneously rather than sequentially to enable genuine comparison instead of allowing the fastest schema to pre-empt alternatives.
When two schemas conflict, search for their common…
When two schemas conflict, search for their common ancestor—the deeper value or goal both serve—to determine the appropriate routing rule rather than selecting a winner.
Track which schemas win repeatedly across situations…
Track which schemas win repeatedly across situations to identify your dominant paradigms, then subject those dominant schemas to the most scrutiny since their accumulated precision-weighting makes them hardest to overturn when evidence contradicts them.
Treat rapid certainty as evidence that a single schema…
Treat rapid certainty as evidence that a single schema dominated without competition, since genuine deliberation between competing schemas produces slower processing and felt uncertainty.
Surface default schemas by deliberately entering contexts…
Surface default schemas by deliberately entering contexts where they break, because comfort renders them invisible while discomfort reveals them.
Design explicit falsification tests for your schemas…
Design explicit falsification tests for your schemas by specifying what evidence would change your mind, because unfalsifiable beliefs cannot be distinguished from dogma.
Label the physical sensation of schema shock to engage…
Label the physical sensation of schema shock to engage prefrontal processing before defensive responses execute, creating space for accommodation rather than protection.
Separate schema accuracy from identity worth by explicitly…
Separate schema accuracy from identity worth by explicitly stating that model failures are properties of the model not properties of the self, because schema-identity fusion converts intellectual updating into threats to self-concept.
When formal and intuitive schemas produce conflicting…
When formal and intuitive schemas produce conflicting assessments, investigate the disagreement rather than defaulting to either one, because the conflict signals either a pattern your formal criteria missed or a bias your intuition hasn't examined.
Periodically formalize your strongest intuitive schemas…
Periodically formalize your strongest intuitive schemas by articulating their implicit rules and testing them against evidence, converting speed into inspectability without losing the original pattern recognition.
Surface your implicit person-schemas through explicit audit…
Surface your implicit person-schemas through explicit audit (default assumptions about motivation, attribution patterns, entity vs. incremental beliefs) rather than treating your perceptions of others as transparent observations of how they really are.
When organizational vocabulary encodes undesired schemas…
When organizational vocabulary encodes undesired schemas, replace the words deliberately and consistently despite initial awkwardness, because linguistic change drives institutional schema change.
Conduct blameless post-mortems that ask what the team…
Conduct blameless post-mortems that ask what the team believed about the system rather than who caused the failure, because schema-focused investigation produces structural learning while person-focused investigation produces defensiveness.
Before assuming you understand someone's reasoning…
Before assuming you understand someone's reasoning, articulate your reading of their underlying model and verify it with them directly.
Listen for what someone mentions first, repeats, dismisses…
Listen for what someone mentions first, repeats, dismisses, and treats as obvious — these reveal the structure of their schema more reliably than the content of their arguments.
When you cannot accurately predict what someone will say…
When you cannot accurately predict what someone will say next from their stated position, your model of their schema is incomplete — update it before arguing further.
Design AI prompts to explicitly frame the task context…
Design AI prompts to explicitly frame the task context, provide structural examples, and specify output constraints — these shape the model's temporary processing schema more reliably than abstract instructions.
Test a schema by applying it to edge cases…
Test a schema by applying it to edge cases and counterfactuals — schemas that fail at boundaries or cannot handle hypotheticals have structural gaps that will produce errors under pressure.
Document the structural assumptions underlying major…
Document the structural assumptions underlying major decisions so that when reality changes, you can identify which assumptions broke rather than defending the entire decision framework.
When team members persistently disagree despite shared…
When team members persistently disagree despite shared information, map each person's schema explicitly before debating conclusions — most sustained conflicts trace to invisible schema divergence.
Treat early-stage schema errors as cheap and late-stage…
Treat early-stage schema errors as cheap and late-stage schema errors as catastrophic — invest in schema validation early when correction costs are lowest.
Version your schemas with dates and track revisions…
Version your schemas with dates and track revisions explicitly — visible history of past changes normalizes schema updating and counters cognitive inertia.
Document the purpose each category serves so…
Document the purpose each category serves so you can evaluate whether it still serves that purpose when circumstances change.
Break complex classification tasks into hierarchical levels…
Break complex classification tasks into hierarchical levels where each level captures information at different granularities, from global patterns down to fine distinctions.
Make category boundaries explicit through written scope…
Make category boundaries explicit through written scope notes that specify what belongs and what doesn't, not just labels.
Preserve information through graduated scales during…
Preserve information through graduated scales during deliberation, then compress to binary only at the final point of action when a decision must be executed.
Match classification granularity to your ability…
Match classification granularity to your ability to discriminate and your need to differentiate — scales finer than you can reliably distinguish add complexity without information.