Rules
1,053 rules · page 2 of 22
Use verb and pattern tags (#deciding, #recurring-blocker)…
Favor verb-based and pattern-based tags (#deciding, #recurring-blocker) over abstract category tags (#productivity, #management) to capture actionable relationships.
Delete singleton tags, keep tags connecting 5+ notes…
When a tag appears on only one note, delete it during review; when a tag connects five notes from three different months, preserve it as earning its maintenance cost.
Gather atomic notes first, then arrange — do not start…
When attempting to structure an argument or presentation, gather existing atomic notes on the topic first, then arrange them into a sequence that produces a natural train of thought, rather than starting with an outline.
Ask AI for multiple sequences of your notes, not one best…
Present AI systems with your atomic notes and ask for multiple possible sequences (chronological, causal, problem-solution) rather than asking for a single best structure, using AI to discover sequences rather than impose them.
Split notes at 800 words or 3 topics — decomposition…
When a note exceeds 800 words or covers three distinct topics, decompose it into 2-4 separate atomic notes and rewrite the connections between them to reveal causal chains invisible in the original structure.
Before splitting a note, decide
When splitting a compound note during refactoring, make explicit decisions about which idea is the core claim, what was supporting evidence versus separate argument, and how the pieces causally relate before completing the split.
Let AI detect structural debt — make refactoring decisions…
Use AI to audit your knowledge base for structural debt (compound notes, duplicates, orphans, broken connections) but perform the actual refactoring decisions yourself to gain the cognitive benefit.
Sequence gaps during refactoring are specs for new notes…
When refactoring reveals that notes in a sequence jump or break, treat those gaps as specifications for new atoms to write rather than as sequence failures.
Uncertain about atomicity during capture? Write it now…
When unable to determine if a note contains one idea or two, write it as-is during capture, then return during a dedicated review session to attempt decomposition without the pressure of real-time capture.
Improve one thing every time you touch a note — kaizen…
Each time you review or link a note, make one small improvement (sharpen title, add missing context, split tangled claim) rather than scheduling separate cleanup sessions.
Speak to capture during movement — voice is 3-4x faster…
Use voice capture for thoughts occurring during movement, driving, or exercise, as speaking is 3-4x faster than mobile typing and preserves complete thought structure before decay.
One gesture from thought to capture — every extra step…
Design capture tools to minimize decisions between intent and recording, targeting one gesture or keystroke from any application context.
Anchor one capture trigger to an existing habit — six…
Start with one capture trigger anchored to your most natural existing habit, run it for six weeks minimum before adding a second trigger.
Track which inbox items truly needed real-time response…
Track which inbox items actually required real-time response rather than batch-window response to gather evidence about whether continuous processing is truly necessary for your role.
The flinch away from writing a thought down IS the signal…
When a thought triggers resistance to capture (a 'flinch' away from writing it down), use that resistance feeling as the capture trigger rather than a reason to skip—thoughts that produce hesitation are the highest-value capture targets.
In power-dynamic conversations, defer notes — capture…
During conversations where power dynamics make visible note-taking signal service role rather than equal participation, defer capture until immediately after the conversation ends—step outside within 2 minutes and externalize the three most important points while still in short-term memory.
Keep raw inbox captures out of AI retrieval scope
Index only processed permanent notes in AI-searchable systems while keeping unprocessed inbox captures outside retrieval scope, because AI systems cannot distinguish epistemic status and will retrieve raw captures with equal confidence to verified knowledge.
Ask four diagnostic questions during weekly review…
During weekly reviews, ask four metacognitive questions—what did I capture well, what did I almost lose, where did I over-capture noise, and what am I avoiding—to monitor system health rather than just processing lists.
Digitize analog notes weekly — handwriting for capture…
For analog captures intended for long-term use, implement a pipeline that photographs or transcribes key entries into digital storage during weekly review—preserving handwriting's cognitive benefits during capture while enabling digital searchability and AI-readability for retrieval.
Keep taking personal notes alongside AI transcription…
When using AI meeting transcription, continue taking personal compressed notes during the conversation rather than relying solely on transcripts—then review AI summary against your notes afterward to identify gaps and improve real-time capture calibration.
Random skipped captures = friction problem; clustered…
Classify each skipped capture by checking whether failure frequency is random across topics (friction problem requiring tool improvement) or clustered in specific domains (resistance problem revealing avoidance patterns).
Ask 'What would become true if I wrote this down?'…
For each thought you resist capturing, immediately ask and write down 'What would become true if I had written this down?'—usually revealing that externalization would trigger a downstream commitment chain you're avoiding.
Capture emotions now, interpret them later in review…
Defer emotional interpretation to review sessions when multiple entries enable pattern recognition, rather than explaining emotions during initial capture.
For each surprise, write
For each captured surprise, write one sentence answering 'What did I apparently believe that turned out to be wrong?' to convert observations into explicit model gaps.
Capture small mundane surprises — they reveal systematic…
Capture small, mundane surprises rather than filtering for 'important' ones, because small surprises reveal systematic blind spots that large surprises obscure.
Document 2-3 pre-mortem failure modes with every…
For significant decisions, add a fifth field documenting pre-mortem risks (2-3 specific ways the decision could fail) to preserve concerns that hindsight bias will erase.
Measure your biological prime time with hourly ratings…
When measuring your biological prime time, set hourly check-ins for at least 10 workdays and rate mental clarity, motivation, and physical energy on a 1-5 scale to identify your peak 2-3 hour window.
Offer alternative times instead of justifying your focus…
When defending peak attention hours against meeting requests, offer alternative times outside your blocked window rather than explaining or justifying the block itself.
Batch shallow work outside your peak hours, not throughout…
Batch all shallow work—email, Slack, administrative tasks, routine meetings—into time blocks outside your measured biological prime time rather than distributing them throughout the day.
Write a one-minute ready-to-resume note before every task…
Before switching from any unfinished task, write a one-minute ready-to-resume note specifying: where you stopped, what remains unresolved, and the next concrete action you will take when returning.
Put your phone in another room during deep work…
Place your phone in a different room, drawer, or timed lockbox during deep work blocks, not merely flipped over on your desk, to eliminate both visual cues and immediate retrieval affordances.
Disable app notifications that produced no valuable action…
For every app on every device, apply the 30-day action criterion: if no notification in the past month caused an action you're glad you took, disable notifications for that app immediately.
Limit immediate notifications to 5 sources — batch…
Classify notification sources into three tiers—Tier 1 immediate (5 or fewer total), Tier 2 batched (checked on schedule), Tier 3 eliminated (disabled entirely)—and configure each source according to its tier within 24 hours of classification.
Remove badge counters from all apps except your top 5…
Remove notification badge counters for all apps except Tier 1 immediate-response sources to eliminate visual triggers that create psychological open loops independent of notification content.
Insert 5-minute transition buffers between all calendar…
Insert five-minute transition buffers between all calendar blocks—meetings, deep work sessions, any context shifts—using those minutes to close the previous context and orient to the next rather than scheduling back-to-back commitments.
Write for three minutes after charged interactions before…
After emotionally charged interactions—difficult conversations, stressful emails, frustrating exchanges—take three minutes to write what happened, what you felt, and what (if anything) needs to happen next before switching to analytical work.
Name the emotion driving task-switch urges — three-second…
When experiencing the urge to switch tasks during focused work, pause for three seconds to name the internal state driving the urge (boredom, uncertainty, anxiety), then consciously return to the task without suppressing the emotion.
When a task bores you through under-challenge, inject…
When a task produces boredom through severe under-challenge (skill level exceeds task demands by 3+ points on a 10-point scale), inject complexity by adding constraints, combining tasks, or converting execution into teaching rather than forcing continued engagement through willpower.
Match curiosity type to task type — open questions…
Frame exploratory work with broad open-ended questions to recruit I-type curiosity (pleasurable anticipation), and frame convergent problem-solving with specific gap-closing questions to recruit D-type curiosity (need-state tension), matching curiosity type to the cognitive demands of the task.
60-90 minute boxes for creative work, 15-25 minutes…
Use time-boxes of 60-90 minutes for creative and strategic work requiring divergent exploration before convergence, and 15-25 minute boxes for administrative work where compression forces efficiency, matching box duration to the cognitive signature of the task type.
Take soft-fascination breaks (walking, nature)…
Structure breaks between time-boxes with activities providing soft fascination (nature, walking, distant gaze) rather than hard stimulation (social media, news, email) to enable genuine deactivation of the attentional goal and prevent false breaks that drain the same resource you're trying to restore.
Stop and take a real break when output quality degrades…
When cognitive output quality begins degrading (increased rewrites, slowed pace, rising error rate), stop work and take a 10-15 minute break with genuine disengagement even if the task is incomplete, because work produced during depletion has lower quality than work produced after restoration despite shorter total time.
When stuck on a creative problem, switch to walking…
When stuck on a problem requiring creative or non-obvious solutions, stop active work on it and switch to low-demand activity (walking, showering, routine tasks) to activate incubation effects, as the break enables cognitive processing that continued deliberate effort cannot produce.
Measure meditation success by detection speed, not drift…
Begin focused-attention meditation with 10-minute daily sessions targeting detection speed (time between drift and noticing) rather than drift frequency (number of wanderings), because faster noticing is the trainable skill while reduced wandering is a late-stage outcome requiring months of practice.
Note, release, return — treat each wandering-catch cycle…
When your mind wanders during meditation, execute a three-step micro-protocol: (1) mentally note what pulled attention away without elaborating, (2) release it without judgment, and (3) return to the chosen anchor, treating each completed cycle as one successful repetition of attention training rather than recovery from failure.
Pre-decide everything before a deep work session…
Eliminate decision points during deep work startup by pre-deciding tool configuration, document access, notification state, and physical materials before the session begins.
End deep work sessions with a 2-5 minute shutdown ritual…
End every deep work session with a 2-5 minute shutdown ritual that reviews accomplishments, documents next steps, and closes all open cognitive loops before transitioning to other activities.
Keep separate Deep and Shallow task lists — schedule Deep…
Maintain two separate task lists—Deep (requiring sustained focus) and Shallow (executable while mildly distracted)—and schedule Deep items during measured peak attention windows while batching Shallow items for post-peak periods.