Principles
2,201 principles · page 39 of 46
Identify and improve keystone meta-schemas whose function…
Identify and improve keystone meta-schemas whose function cascades across multiple domains rather than optimizing domain-specific schemas in isolation.
Map default behaviors across cognitive domains to identify…
Map default behaviors across cognitive domains to identify the meta-schemas running automatically in your cognitive operating system's idle loop.
Limit real-time recursive metacognitive depth to two…
Limit real-time recursive metacognitive depth to two or three levels before externalizing to avoid working memory saturation and the illusion of depth without genuine inspection.
Increase the marginal value of each new piece of knowledge…
Increase the marginal value of each new piece of knowledge by connecting it to existing knowledge, as connected information compounds quadratically while isolated information accumulates linearly.
Externalize knowledge as discrete atomic units rather…
Externalize knowledge as discrete atomic units rather than continuous narrative to enable recombination and connection across contexts.
Progressively refine captured information through multiple…
Progressively refine captured information through multiple encounters rather than attempting perfect formulation on first capture.
Use typed relationships with semantic labels rather…
Use typed relationships with semantic labels rather than generic connections to reduce ambiguity and enable automated reasoning over knowledge structures.
Limit relationship type taxonomies to 5-7 categories…
Limit relationship type taxonomies to 5-7 categories that match actual cognitive distinctions rather than pursuing ontological completeness.
Force relationship classification at link creation time…
Force relationship classification at link creation time to detect spurious connections before they accumulate as noise in the system.
Measure knowledge depth by calculating edge-to-node ratios…
Measure knowledge depth by calculating edge-to-node ratios within conceptual clusters rather than counting individual facts or node quantities.
Build conceptual triangles by explicitly connecting nodes…
Build conceptual triangles by explicitly connecting nodes that share a common parent, converting sparse star topologies into dense mesh structures that support multiple retrieval paths.
Conduct periodic orphan audits with rapid binary…
Conduct periodic orphan audits with rapid binary triage—connect, delete, or incubate for 30 days—treating connection speed as a system health metric.
Invest maintenance effort proportional to node connectivity…
Invest maintenance effort proportional to node connectivity rather than treating all notes equally, concentrating review cycles and revision work on high-degree nodes that hold graph structure.
Distinguish organic hubs that earn centrality through…
Distinguish organic hubs that earn centrality through genuine conceptual relationships from artificial index hubs that create cosmetic connectivity without semantic weight.
Identify structural gaps in your knowledge by detecting…
Identify structural gaps in your knowledge by detecting clusters that should be connected but have no bridge nodes, revealing blind spots where cross-domain synthesis is missing.
Test bridge node validity by generating novel predictions…
Test bridge node validity by generating novel predictions or insights in both connected domains—if the connection produces only similarity recognition without actionable transfer, demote it to metaphor status.
Build knowledge graphs with T-shaped topology—deep clusters…
Build knowledge graphs with T-shaped topology—deep clusters connected by bridge nodes—rather than uniform density or disconnected islands, optimizing for both depth and strategic breadth.
Use spatial visualization to reveal structural properties…
Use spatial visualization to reveal structural properties of your knowledge graph that sequential text-based interfaces necessarily hide.
Trace the shortest path between two seemingly unrelated…
Trace the shortest path between two seemingly unrelated concepts to reveal the hidden chain of relationships connecting them.
Discover your actual domains of expertise by identifying…
Discover your actual domains of expertise by identifying naturally formed clusters of densely interconnected concepts rather than imposing predetermined categories.
Trust the structural patterns in your knowledge graph over…
Trust the structural patterns in your knowledge graph over your self-narrative about what you know, because graph structure reflects actual cognitive investment while self-assessment is systematically distorted.
Measure domain depth by examining both the size of concept…
Measure domain depth by examining both the size of concept clusters and the density of connections within them, where high density indicates structural comprehension beyond mere fact accumulation.
Diagnose specific knowledge deficiencies by identifying…
Diagnose specific knowledge deficiencies by identifying where edges should exist between concepts you already have but have not articulated the relationship.
Distinguish between missing edges (concepts…
Distinguish between missing edges (concepts you have but haven't connected), sparse nodes (concepts with insufficient connections), and missing nodes (concepts absent from your graph) because each requires different remediation strategies.
Prioritize filling knowledge gaps that are adjacent…
Prioritize filling knowledge gaps that are adjacent to your densest clusters because these represent concepts within your zone of proximal development where learning will be most effective.
Integrate new knowledge immediately through connecting…
Integrate new knowledge immediately through connecting it to existing nodes rather than accumulating unprocessed material, because the integration act forces retrieval and spaced repetition of surrounding concepts.
Design external systems to survive the death of the tools…
Design external systems to survive the death of the tools that currently access them by storing knowledge in durable, open, human-readable formats with explicit connections.
Conduct regular structural reviews of your knowledge graph…
Conduct regular structural reviews of your knowledge graph to detect and repair decay (dead links, missing connections, orphan nodes) before trust degradation makes the system unusable.
Start graph exploration with overview (shape), then zoom…
Start graph exploration with overview (shape), then zoom to filtered regions (relationships), then examine specific nodes (details), rather than beginning with targeted search.
Couple AI systems with explicitly structured personal…
Couple AI systems with explicitly structured personal knowledge graphs rather than unlinked text collections to enable graph traversal and structural reasoning beyond semantic similarity.
Offload structural representation and storage to external…
Offload structural representation and storage to external knowledge graphs to reallocate biological cognitive capacity toward synthesis, evaluation, and creative recombination.
Active coupling with an external knowledge graph extends…
Active coupling with an external knowledge graph extends cognitive reach only while you maintain, traverse, and trust the system; a graph you built but no longer use is an artifact, not an extension.
To extract information from a contradiction, articulate both
To extract information from a contradiction, articulate both beliefs explicitly, validate the evidence for each, identify the contextual variable that determines when each applies, then formulate a synthesis that accounts for both.
When models in an ensemble disagree, treat the disagreement…
When models in an ensemble disagree, treat the disagreement as a diagnostic signal indicating regions of uncertainty rather than a flaw requiring forced consensus.
Contradictions that resolve through clarification of terms…
Contradictions that resolve through clarification of terms or context indicate surface-level issues; contradictions that cascade through multiple dependent beliefs indicate deep structural tensions.
During a holding period, maintain active awareness…
During a holding period, maintain active awareness of the contradiction by writing notes when it surfaces rather than ignoring it or forcing resolution.
Resist forced cognitive closure under time pressure…
Resist forced cognitive closure under time pressure, fatigue, or social accountability demands, as these conditions systematically increase premature resolution of deep contradictions.
Audit values-behavior gaps by comparing stated values…
Audit values-behavior gaps by comparing stated values against behavioral evidence (calendar, spending, time allocation) over 30+ days, treating discrepancies as diagnostic data rather than moral failures.
When behavior contradicts stated values, investigate…
When behavior contradicts stated values, investigate the actual reward structure driving the behavior rather than increasing willpower or restating the value more emphatically.
Frame values-behavior gaps as blocked action problems rather
Frame values-behavior gaps as blocked action problems rather than character defects, asking what environmental or psychological barriers prevent valued behavior.
When two opposing beliefs are both evidentially supported…
When two opposing beliefs are both evidentially supported, find the vantage point (usually a higher level of abstraction or a contextual variable) from which both become explicable as partial truths within a larger frame.
Test integration quality by verifying that each component…
Test integration quality by verifying that each component schema still generates distinct predictions post-integration; if all schemas produce identical outputs, you have homogenized rather than integrated.
When two legitimate values generate ongoing tension without…
When two legitimate values generate ongoing tension without resolution, design oscillation rhythms rather than forcing a permanent choice.
Before attempting to resolve a contradiction, determine…
Before attempting to resolve a contradiction, determine whether additional information could produce a stable answer—if not, you face a polarity requiring management rather than a problem requiring solution.
Design early warning indicators for when you've drifted too…
Design early warning indicators for when you've drifted too far toward one pole of a permanent tension, triggering course-correction before downsides accumulate into crisis.
When aggregate data contradicts disaggregated data, identify
When aggregate data contradicts disaggregated data, identify the lurking variable that defines scope boundaries before declaring a genuine contradiction.
When expert advice from different domains contradicts…
When expert advice from different domains contradicts, extract the implicit scope conditions (risk profile, time horizon, optimization target) before applying either recommendation.
Evaluate decisions as members of a class rather…
Evaluate decisions as members of a class rather than as isolated instances to avoid narrow framing that rejects positive expected value.