Concepts
The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types
Plan-Do-Check-Act (PDCA) cycle
a four-step scientific process for iterative improvement consisting of Plan (identify gap and hypothesize change), Do (implement change on small scale), Check (measure results), and Act (adopt, modify, or abandon change based on results)
Bottleneck-first optimization
the practice of identifying and improving only the constraint in a system, since improvements at non-constraint steps do not change system output
Compounding
the multiplicative accumulation of small, consistent improvements that build upon each other to produce exponential growth over time, where each iteration enhances the effectiveness of subsequent iterations through system interactions and retained gains
Marginal gain
a small, measurable improvement (typically 1%) made to a specific component or dimension of a system that, when accumulated across many such improvements, produces exponential growth through compounding effects
Optimization
the process of improving a system, process, or outcome by systematically adjusting inputs or parameters to maximize performance within constraints, where each successive improvement requires exponentially more effort to achieve proportionally smaller gains due to diminishing returns.
Stopping rule
a pre-defined criterion or condition that determines when an optimization effort should cease, consisting of three components: a threshold (what constitutes sufficient improvement), a metric (how to measure progress toward that threshold), and a trigger (what action to take when the threshold is met).
Randomization
the process of randomly assigning inputs to different versions in an A/B test to distribute confounding variables evenly across groups so that any systematic difference in outcomes can be attributed to the treatment rather than background conditions
Confounding
the technical term for what goes wrong when you change multiple variables simultaneously, where a confounding variable correlates with both your change and your outcome, making it impossible to determine which one actually caused the result
Variable isolation
the discipline of changing one thing at a time so that observed effects can be attributed to specific causes
Ablation study
a formalization of variable isolation in machine learning that systematically removes or disables individual components of a model and measures how performance changes to determine each component's contribution
Local optimum
a performance configuration within a fitness landscape that represents the peak of improvement potential within the current framework, where further incremental changes yield no measurable improvement because all directions are downhill.
Framework
the set of unquestioned assumptions, architectural principles, and operational constraints that define the boundaries within which a personal agent operates, determining what actions feel available and what features appear relevant to the agent's performance.
Kaizen
the disciplined practice of continuous, incremental improvement within an existing framework, characterized by small, measurable gains that compound over time to produce significant cumulative value.
Kaikaku
the radical reform of an existing framework through wholesale replacement, characterized by high-stakes, rare events that produce substantial improvements (30-50%) and establish a new baseline for subsequent kaizen.
Speed optimization
the systematic process of reducing the time and friction required for a personal agent to execute, thereby increasing execution frequency and enabling the agent to operate at lower motivation thresholds while maintaining or improving output quality
Overhead
the non-execution time in an agent's operation that includes setup, navigation, context-switching, waiting, and searching, which does not directly contribute to the agent's output but is necessary for the process
Accuracy
the degree to which an agent's output corresponds to the intended outcome, measured by the hit rate of actions taken and decomposed into bias (systematic error) and noise (random error)
Reliability optimization
the process of redesigning agents to fire consistently under varying conditions by building structural support mechanisms such as fallback paths, backup triggers, and minimum viable execution modes
Scope optimization
the practice of expanding or narrowing the situations and actions an agent handles until the agent's boundary matches its purpose
Scope creep
the gradual, uncontrolled expansion of project or agent scope beyond its original boundaries that leads to increased costs, delays, and reduced effectiveness
Energy optimization
the discipline of achieving results with minimal expenditure — cognitive, emotional, or physical
Emotional energy
the cost of feeling — managing anxiety, suppressing frustration, performing social roles, and processing interpersonal dynamics
Physical energy
the cost of doing — maintaining posture, managing fatigue, regulating sleep debt, and sustaining the metabolic processes that fuel both cognition and emotion
Integration tax
the cumulative cost of all transitions, handoffs, translations, and context switches between agents in a system, which can exceed the execution cost of the individual components