Concepts
The irreducible epistemic atoms underlying the curriculum. 4,828 atoms across 8 types
Use both automated and manual time tracking — neither…
Use automated time-tracking tools alongside manual 30-minute increment logs simultaneously for three consecutive workdays to capture both digital activity and non-digital context that neither method alone reveals.
Pair every important outcome with 1-2 leading indicators…
For each important outcome you care about, identify one lagging indicator (the outcome) and pair it with 1-2 leading indicators (upstream behaviors that predict it), tracking both to validate the predictive relationship.
When the leading indicator improves but the outcome…
When a leading indicator improves but its paired lagging outcome does not follow within the expected timeframe, treat the leading indicator as broken (gamed, confounded, or non-predictive) and replace it.
Pre-commit to prediction failure thresholds (X out of Y)…
Set prediction failure thresholds as numeric ratios (X failures out of Y recent predictions) for each schema before observing prediction outcomes to trigger review when the threshold is crossed.
Measure behavioral agent progress by displacement rate…
Track agent displacement by measuring the percentage of times your designed agent fires instead of the default, not by whether you execute perfectly every time, because replacement is gradual and competes against thousands of prior reinforcements.
Define agent success as 80%+ firing rate, not subjective…
Define agent success as a measurable outcome with a minimum acceptable firing rate threshold (typically 80% over one week for new agents) rather than subjective satisfaction, because subjective assessment systematically inflates reliability perception.
Audit agents with hourly momentary sampling…
Use hourly momentary sampling over 48+ hours rather than end-of-day recall when auditing behavioral agents, because retrospective memory systematically overweights salient successes and underweights invisible failures.
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.
A complete feedback loop needs three elements
For any recurring activity, explicitly define three elements—the specific output being measured, the standard for comparison, and the adjustment rule triggered by deviation—to create a complete minimal feedback loop.
Measure feedback delay in actual time units before…
Before attempting to improve any feedback loop, measure the current delay between action and signal in concrete time units (seconds, minutes, hours, days) rather than accepting vague assessments, because unmeasured delays appear shorter than they actually are through habituation.
Substitute a faster noisy signal for a slower precise one…
Find a faster correlated signal that approximates delayed feedback rather than waiting for the original signal, accepting that speed compensates for increased noise in the approximation.
Daily activities need weekly feedback; strategic…
For daily activities, if feedback latency exceeds one week, or for strategic activities if latency exceeds one month, design a leading indicator or checkpoint that shortens the delay before drift compounds.
Build measurement systems when you design the strategy…
Build measurement dashboards and leading indicators at the same time you design the strategy they measure, not after problems appear, because instrumentation designed during crisis measures symptoms rather than causes.
Validate new feedback mechanisms in the first cycle
For each feedback mechanism you build, verify within the first cycle that the data reveals something unknown, that measurement effort is sustainable, and that you can specify one concrete adjustment based on results—if any component fails, redesign before continuing.
Audit decision-driving metrics every 3 months
When a metric has been used to drive decisions for more than three months without revision, conduct a three-question audit: what behavior does this metric actually incentivize, is the proxy still correlated with the outcome, and what would gaming this metric look like compared to current behavior.
Retire metrics that can't distinguish gaming from genuine…
Retire metrics entirely when they no longer distinguish between gaming behavior and genuine progress, as continued use of a decoupled metric produces wrong information you trust rather than mere absence of information.
Instrument before executing — drift detection requires…
Design measurement infrastructure before executing strategies rather than after problems become visible, because drift detection requires baseline instrumentation that must exist before deviation occurs.
Express error budgets as numbers with time windows — '2…
Express error budgets as time-bounded numeric thresholds (e.g., 'two missed sessions per week' or '30 minutes downtime per month') rather than vague intentions, and track consumption against the budget as a first-class metric.
Budget commitments on two dimensions
Track both time cost (hours per week) and cognitive cost (mental bandwidth on 1-5 scale) for each active commitment when budgeting capacity.
Time audit
Log how you spent your waking hours in thirty-minute blocks for one week, then categorize every block by domain and calculate the percentage of discretionary time each priority actually received.
Monthly priority alignment score
For each of your top three priorities, calculate the percentage of productive hours last month that directly advanced it (not adjacent or preparatory work), then compare this to your stated priority ranking to measure the cost of current misalignment.
When energy data contradicts your narrative about what…
When energy audit results contradict your narrative predictions about which activities energize or drain you, prioritize the measured data over subjective memory in subsequent scheduling decisions.