Concepts

Sourced concept cards — productivity, psychology, systems, AI.

• Adapted ICE Score — The ICE Score (Impact, Confidence, Ease) is an idea prioritization framework. This adaptation replaces Confidence with Clarity and Ease with Difficulty for solo use without user data.
• AI Identity Threat — AI doesn't destroy jobs first — it erodes the tasks that gave those jobs meaning. This phenomenon, documented by MIT, undermines professional identity before employment itself is threatened.
• Codifiability Threshold — What determines whether a task shifts to automation is not its difficulty, but its codifiability — can its rules, patterns, or sequences be extracted and taught to a machine? Four technological breakthroughs have successively raised this threshold.
• Commitment Device — A commitment device is a constraint you voluntarily impose on yourself in advance to neutralize your own future weakness of will — before temptation strikes.
• Context Engineering — Building explicit data and context 'pipes' to achieve results no one-shot prompt can produce. Context engineering goes beyond prompt engineering.
• Definition of Done — A task is done when a verifiable, objective condition is met — not when you've 'made progress on it'. This explicit criterion closes mental loops and reduces lingering unfinished work.
• Desire as Unhappiness — Every desire is a contract signed with yourself to be unhappy until you get what you want. Not a call to suppress desire — but to recognize it as chosen suffering.
• Ego Depletion — Willpower is a resource that gets spent with each decision. But the science on the exact mechanism is more nuanced than widely believed.
• Explicitation — The key new skill for working with AI: defining each thought with near-surgical precision. AI can't interpret vague judgments — it needs explicit criteria.
• Gall's Law — Every complex system that works evolved from a simple system that worked. No complex system designed from scratch ever works.
• Goodhart's Law — When a measure becomes a target, it ceases to be a good measure. Optimizing for an indicator corrupts it.
• Happiness as Skill — Happiness isn't an inherited state or a destination — it's a learnable personal skill. It's cultivated through subtraction: removing the sense that something is missing.
• Identity Shedding — Questioning and abandoning pre-packaged identities that filter perception. To think honestly, speak without identity. If all your beliefs align into a coherent package, be very suspicious.
• Implementation Intentions — Deciding in advance 'when X, I will do Y' multiplies task completion rates by 2 to 3 compared to a simple intention. The context triggers the action automatically.
• Judgment Over Time — The ideal economic position: being paid for decision quality, not time. With leverage, 10% better judgment can produce 1000x more results.
• Learning Through Play — Mastering a technology through intrinsically motivating projects before applying it to business. The beginner's advantage: no old habits to unlearn.
• Long-Term Games — All returns in life come from compound interest. Trust and reputation compound over decades — play with the same honest people repeatedly.
• Parkinson's Law — Work expands to fill the time available for its completion. Without a defined time constraint, a task takes as long as you let it.
• Permissionless Leverage — Code and media are forms of leverage that require no one's approval — zero marginal cost, infinite scale. The only reason one person can have the impact of a thousand-person company.
• Poiesis vs Praxis — Aristotle distinguished two modes of human action: poiesis (producing a result) and praxis (acting for the meaning of the act itself). AI automates poiesis. What resists is praxis — but the boundary shifts with every technological breakthrough.
• Poiesis, Praxis, Phronesis — Aristotle's three modes of human action. AI automates poiesis (making). Praxis (acting with meaning) resists. Phronesis (judging under uncertainty) becomes the central skill of the agent economy.
• Positive Friction & Dark Patterns — Positive friction is an obstacle voluntarily added by the user to protect themselves from their own biases. Dark patterns are the opposite: friction deliberately deployed against the user.
• Price Inelasticity — When demand doesn't respond proportionally to price — a 2% drop in oil supply can trigger a 20-30% price increase. Applies equally to human skills facing AI substitution.
• Silent Workforce Reduction — AI doesn't only eliminate jobs through announced layoffs — it reduces headcount through directed attrition: not replacing departures, with one position gradually absorbing the work of several.
• Small World Network — In a well-structured network, any node is reachable from any other in ≤6 hops — thanks to hubs that create shortcuts between distant clusters.
• So-So Technology — A 'so-so' technology automates human work without creating enough new roles to compensate. Acemoglu & Restrepo's (2019) concept to distinguish technologies that enrich the economy from those that simply redistribute value toward capital.
• Specific Knowledge — Knowledge that cannot be taught but can be learned — it emerges from the intersection of temperament, environment, and personal obsession. No one can compete with you on being you.
• Test Architecture — When AI generates code, the real human skill is designing rigorous test systems. Humans no longer review code — they design the trials that code must pass.
• The Agentic Era — The shift from task-by-task LLMs to autonomous agents executing complete workflows. 2026 is the inflection point — this scale change invalidates classical automation studies.
• The AI Thinking Pivot — AI doesn't change how we work — it changes how we think about work. It's not a process evolution, it's a mental paradigm shift.
• The Curse of Knowledge — Once you know something, you can no longer imagine not knowing it. You systematically overestimate what others understand without even realizing it.
• The Feynman Technique — To truly understand something, try to explain it simply. The gaps in your explanation reveal the gaps in your understanding.
• The KISS Principle — Keep It Simple, Stupid. A system should be as simple as possible — unnecessary complexity is a liability, not a sign of sophistication.
• Utility vs Meaning — Not all tasks are equal in the face of AI. Some have utility value — they can be optimized, delegated, automated. Others have meaning value — they are intrinsically human and resist automation. Two economies are separating.
• Work as Play — The identification signal of Specific Knowledge: what feels like play to you but looks like work to others. Real winners are so addicted they keep playing even when rewards diminish.