Event Lifecycle Phases¶
Core Idea¶
Event lifecycle phases is the structural pattern of decomposing a hazard-bearing event into a pre-event / event / post-event trichotomy and treating each phase as the primary unit of intervention design rather than treating the event as a single object. Each phase has a characteristically different tempo (slow / fast / medium), decision logic (probabilistic / urgent / restorative), intervention shape (preventive / responsive / reparative), success metric (events not occurring / events controlled / capacity restored), and political economy (invisible payoff / visible heroics / contested distribution of recovery). The structural commitment is that the same event needs three distinct intervention systems, not one; collapsing them into a single planning frame mis-allocates effort, attention, and budget.
The pattern has four load-bearing parts: a class of hazard-bearing events with a recognisable onset and end; a pre-event regime where the event has not happened but its probability and severity can be reshaped by investments made now; an event regime where the event is unfolding and the action space is constrained, time-pressured, and dominated by previously deployed capacities; and a post-event regime where the event is over but its damage and signal must be processed to restore the system and update the pre-event regime for the next cycle. The three regimes are connected: post-event learning feeds back into pre-event design, pre-event readiness shapes what is possible during the event, and event experience shapes both. The cycle structure is itself load-bearing — today's recovery is tomorrow's preparedness, today's incident is tomorrow's hardening priority — so the post-event phase carries a structural responsibility to feed the pre-event phase through lessons-learned databases, after-action reviews, and control updates, and cutting that feedback severs the system's ability to learn from its own events. Failing to draw the phases distinctly is the most common diagnostic failure.
How would you explain it like I'm…
Before, During, After
Three Plans, One Event
The Pre/During/Post Split
Structural Signature¶
the class of hazard-bearing events with recognisable onset and end — the pre-event regime where probability and severity are still reshapable — the event regime constrained by previously deployed capacity — the post-event regime that repairs and extracts signal — the regime-change at each phase boundary (tempo, decision logic, metric, political economy) — the cycle feedback from post-event learning into pre-event design
A configuration exhibits event lifecycle phases when each of the following holds:
- A class of hazard-bearing events. A recognisable kind of event with an onset and an end imposes consequences on a system: a disaster, a breach, an acute illness, an outage.
- A pre-event regime. A phase in which the event has not happened but its probability and severity can be reshaped by investments made now — preventive in shape, probabilistic in logic, slow in tempo, with an invisible payoff.
- An event regime. A phase in which the event is unfolding, the action space is constrained and time-pressured, and outcomes are dominated by previously deployed capacities — responsive, urgent, fast, with visible heroics.
- A post-event regime. A phase in which the event is over but its damage and signal must be processed to restore the system — reparative, restorative, medium-tempo, with a contested distribution of recovery.
- Regime-change at the boundaries. The decisive invariant: each phase has a characteristically different tempo, decision logic, intervention shape, success metric, and political economy, so the same event requires three distinct intervention systems, not one. Applying one phase's logic to another is a category error.
- A cycle feedback. Post-event learning feeds back into pre-event design — today's recovery is tomorrow's preparedness — making the post-event-to-pre-event handoff a structural responsibility whose severance disables learning.
The components compose so that the dominant predicted pathology is mis-allocation toward the visible, heroic event phase at the expense of the invisible pre-event and unrewarded post-event phases — and the corrective is separate per-phase budget lines plus protection of the cycle feedback.
What It Is Not¶
- Not
temporal_dynamics. Temporal dynamics describes how a system evolves continuously over time; this prime imposes a discrete trichotomy (pre/event/post) with a regime-change at each boundary and treats each phase as a distinct intervention-design unit. - Not
state_and_state_transition. That is the bare abstraction of states and the transitions between them; this prime is the specific, normatively-loaded hazard trichotomy with characteristic tempo, decision logic, and political economy per phase. - Not
failure_mode_and_effects_analysis_fmea. FMEA enumerates and rates failure modes for pre-event mitigation; event lifecycle phases spans all three regimes and is about allocating across them, not analysing the hazard itself. FMEA is a pre-event tool within this frame. - Not
recurrence. Recurrence is the bare fact of a pattern repeating; this prime's cycle is a designed feedback responsibility (post-event learning feeding pre-event design), not merely an observation that events recur. - Not
antifragility. Antifragility is gain from disorder; this prime is value-neutral phase-decomposition — it organises intervention across phases without claiming the system benefits from the hazard. - Common misclassification. Treating a hazard as a single object and evaluating it under one decision framework. Applying probabilistic cost-benefit to a minute-scale rescue, or urgent heroics to a decade-scale mitigation, is a category error; catch it by asking which phase an intervention belongs to and whether its logic and horizon match.
Broad Use¶
- Disaster management: the textbook trichotomy — mitigation / response / recovery — made institutional by national agencies and the international Sendai framework, each phase with its own funding streams, profession, and characteristic failure modes.
- Cybersecurity: hardening / incident response / post-incident review, where pre-event work is invisible until it pays off, the response is high-tempo and visible, and the post-event phase is where organisational learning happens or fails to.
- Medical care: prevention / acute care / rehabilitation, organising public-health budgets, clinical specialties, and reimbursement.
- Software reliability: reliability engineering / on-call response / post-mortem and follow-up, with the blameless post-mortem existing because the post-event phase designs the next pre-event phase.
- Climate policy: mitigation / adaptation / loss-and-damage, the global negotiation tracks splitting along exactly these phase boundaries because each has a different politics, beneficiaries, and time horizon.
- Workplace safety: hazard reduction / emergency response / return-to-work, with different institutions owning each phase.
- Conflict and security: prevention / crisis response / post-conflict reconstruction, with chronic coordination failures at the seams.
Clarity¶
Naming the phases forces explicit attention to three questions that event-as-single-object framing conflates: what investments are we making now to bend the probability or severity of the event? what capacities will we have to deploy when the event is unfolding? what processes will let us repair and learn after the event ends? Each has a different time horizon, a different stakeholder, and a different evidence base, and treating them as one question lets the differences disappear. The clarifying separation is between the three regimes' decision logics — probabilistic on a decade horizon, urgent on a minute horizon, restorative on a month-to-year horizon — which cannot be evaluated under a single decision-analysis framework without producing nonsense. The framing also surfaces a recurring pathology with a structural cause: organisations over-invest in response (visible, heroic, politically rewarded) and under-invest in pre-event and post-event work (invisible, prosaic, politically thankless), and once the phases are named, this imbalance becomes a defensible point of intervention rather than a quiet institutional drift. Distinguishing the phases is what lets an analyst say, precisely, that an organisation is mis-allocated toward the heroic middle phase at the expense of the bookending ones.
Manages Complexity¶
The pattern manages complexity by separating decision regimes. A pre-event decision — which sea wall to fund — involves probability, discount rates, and political feasibility on decade horizons; an event decision — where to send the rescue helicopter — involves urgency, information scarcity, and chain of command on minute horizons; a post-event decision — how to allocate reconstruction grants — involves equity, evidence of harm, and contested accountability on month-to-year horizons. Trying to evaluate all three under a single framework produces nonsense; treating them as separate regimes that communicate at well-defined handoffs is the structural intervention. A second compression is that the phases cycle, so the post-event phase has structural responsibilities to feed the pre-event phase, and naming the cycle makes the feedback an explicit design object rather than an afterthought. The intervention catalogue is phase-keyed and portable: each phase has its own set of moves, evidence base, and success metric; the handoffs between phases are designable seams where chronic failures concentrate; and the political-economy asymmetry across phases predicts where budget imbalances will form. The compression is that a disaster planner, a security team, a clinician, and a reliability engineer all run the same three-regime decomposition with the same handoff-and-cycle structure under different names, so a practice matured in one substrate — the blameless post-mortem, say — transfers as a phase-specific discipline to another.
Abstract Reasoning¶
Recognising the pattern enables reasoning about phase-specific intervention catalogues (each phase has its own moves, evidence, and metrics, and an intervention proposed for the wrong phase is usually wasted), about handoff design (most chronic failures live at the seams — pre-event readiness not communicated to response teams, response decisions not captured for post-event learning — and the seams are designable), about political-economy asymmetry (the visibility of each phase varies dramatically, producing predictable budget imbalances that naming makes actionable), about phase-specific failure modes (pre-event fails by invisibility, event response fails by brittleness, post-event fails by amnesia), and about cross-phase optimisation (a more expensive sea wall can reduce response and recovery costs, while a cheap one shifts cost to the other phases). The non-obvious move the prime licenses is to refuse to evaluate a hazard under a single decision framework and instead to ask, separately for each regime, what its decision logic, time horizon, stakeholder, and success metric are — because applying one phase's logic to another (probabilistic cost-benefit to a minute-scale rescue, or urgent heroics to a decade-scale mitigation) is a category error. The reasoning generalises across hazard-management substrates, though it is bounded to them: the trichotomy is an institutional framework tightly bound to human hazard-management practice, with normative content in what counts as "mitigation," "response," and "recovery," so the prime is framed rather than purely structural and applies where there are intentional actors managing a recognised hazard. An open structural question is whether the trichotomy specifically is load-bearing or whether the deeper prime is "an event has structurally distinct phases with different intervention logic," since four-phase variants appear in some institutional frameworks; the evidence currently leans tri-phase, with the trichotomy as the most common specialisation of phase-decomposition-with-regime-change-at-the-boundaries.
Knowledge Transfer¶
The decomposition ports across hazard-management substrates as a recognisable family. From disaster mitigation to cybersecurity: the insight that under-investment in mitigation produces predictably larger response costs transfers directly to security spending, with the vocabulary of return-on-mitigation, scenario exercises, and pre-positioned capacity porting cleanly. From blameless post-mortem to workplace safety: the discipline that the post-event phase is sacred and must be insulated from individual blame to produce honest signal is being borrowed by industrial-safety culture. From three-phase budgeting to climate: the insistence that funding lines be drawn separately for the three phases is what the climate-finance debate rediscovered under the loss-and-damage banner. From drill-as-investment to medicine: the insight that drills are pre-event investments, not training events, transfers to clinical simulation and trauma-team readiness. The role mappings transfer directly — pre-event regime ↔ mitigation / hardening / prevention / reliability engineering; event regime ↔ response / incident response / acute care / on-call; post-event regime ↔ recovery / post-incident review / rehabilitation / post-mortem; handoff ↔ readiness-to-response / response-to-recovery seam; cycle ↔ recovery-feeds-preparedness loop. The transferred and non-obvious lesson is the predictable mis-allocation: every hazard-managing organisation tends to over-invest in the visible, heroic event phase and under-invest in the invisible pre-event and unrewarded post-event phases, and the corrective — drawing separate budget lines per phase and protecting the post-event-to-pre-event feedback — is the same move whether the substrate is hurricanes, breaches, epidemics, or outages. A practitioner who has internalised the prime can therefore walk into an unfamiliar hazard-management organisation, name the three regimes, locate the chronic failures at the seams, and predict the budget imbalance from the phases' differing visibility — and can import a matured phase-specific practice, such as the blameless post-mortem, from whichever substrate first developed it.
Examples¶
Formal/abstract¶
Disaster management supplies the prime's canonical, institutionally codified instance: the mitigation / response / recovery trichotomy. The class of hazard-bearing events is natural disasters — hurricanes, floods, earthquakes — each with recognisable onset and end. The pre-event regime (mitigation) is where probability and severity are still reshapable: building codes, sea walls, floodplain zoning, drills. Its decision logic is probabilistic on a decade horizon (which mitigation yields the best expected loss reduction per dollar), its tempo slow, its payoff invisible — a disaster that does not happen leaves no monument. The event regime (response) is constrained by previously deployed capacity: the action space is where-to-send-the-helicopter, the logic urgent on a minute horizon, the tempo fast, the work visibly heroic. The post-event regime (recovery) repairs and extracts signal: reconstruction grants, after-action reviews, the logic restorative on a month-to-year horizon with contested distribution. The decisive structural fact is the regime-change at the boundaries — three different tempos, decision logics, metrics, and political economies, so the same hurricane needs three distinct intervention systems, and evaluating all three under one cost-benefit framework produces nonsense. The cycle feedback is load-bearing: recovery's lessons-learned should feed the next mitigation cycle, and severing that handoff disables organisational learning. The prime predicts the dominant pathology: over-investment in the visible, heroic response phase and under-investment in invisible mitigation and unrewarded recovery — corrected by separate per-phase budget lines and protected feedback. Mapped back: the hurricane is the hazard-bearing event; mitigation, response, and recovery are the three regimes with their characteristic tempos and logics; the recovery-to-mitigation loop is the cycle feedback; and the predicted budget skew toward the heroic middle phase is the prime's signature mis-allocation.
Applied/industry¶
Two applied instances run the identical six-element skeleton, and a matured practice from one transfers to the other. First, site reliability engineering: the hazard-bearing events are production outages. The pre-event regime is reliability engineering — error budgets, capacity planning, chaos testing — slow and invisible until it pays off. The event regime is on-call incident response, measured by mean-time-to-acknowledge and mean-time-to-recover, high-tempo and visible. The post-event regime is the blameless post-mortem, whose entire purpose is to design the next pre-event phase — the cycle feedback made an explicit, sacred ritual. The phases have distinct logics: a mitigation decision (invest in redundancy) is probabilistic over months, a response decision (roll back or fix forward) is urgent over minutes, a post-mortem decision (which follow-up to prioritise) is restorative over weeks. Second, cybersecurity: hardening / incident response / post-incident review map onto the same three regimes, with the same predicted pathology — security teams over-fund visible incident-response capability and under-fund invisible hardening and the unglamorous post-incident review where organisational learning lives or dies. The transferable move is concrete: the blameless post-mortem, matured in SRE, is precisely the discipline of insulating the post-event phase from individual blame so it produces honest signal, and it is being borrowed wholesale by security teams and even industrial-safety culture. The prime's diagnostic — name the three regimes, locate chronic failures at the seams (pre-event readiness not communicated to responders; response decisions not captured for learning), and predict the budget imbalance from the phases' differing visibility — applies unchanged. Mapped back: outages and breaches are the hazard-bearing events; reliability-engineering/on-call/post-mortem and hardening/IR/review are the three regimes; the post-mortem-to-engineering loop is the cycle feedback; and the over-investment in the visible response phase is the same mis-allocation the prime predicts across every hazard-managing organisation.
Structural Tensions¶
T1 — Phase-Specific Logic versus Single Decision Framework (scopal). The prime's load-bearing claim is that each phase has its own decision logic — probabilistic on a decade horizon, urgent on a minute horizon, restorative on a month-to-year horizon. The tension is between honouring three regimes and the analytic convenience of one unified framework. The characteristic failure mode is the category error: applying probabilistic cost-benefit to a minute-scale rescue, or urgent heroics to a decade-scale mitigation decision. The diagnostic: for any proposed intervention, ask which phase it belongs to and whether its logic, horizon, and metric match that phase — an intervention evaluated under the wrong phase's framework is usually wasted.
T2 — Visible Event Phase versus Invisible Bookend Phases (political economy). The three phases differ sharply in visibility: response is heroic and rewarded, mitigation invisible until it pays off, recovery thankless. The tension is between where effort is rewarded and where it is most cost-effective. The failure mode the prime predicts is structural mis-allocation: over-investing in the visible response phase and starving the invisible pre-event and unrewarded post-event phases. The diagnostic: compare per-phase budget lines against per-phase expected loss reduction — if spending tracks visibility rather than leverage, the organisation is skewed toward the heroic middle, and the corrective is separate, protected budget lines per phase.
T3 — Phase Interiors versus Handoff Seams (coupling). Each phase can be well-run internally while the system fails at the seams between them — pre-event readiness not communicated to responders, response decisions not captured for recovery. The tension is between optimising phase interiors and designing the handoffs. The failure mode is seam neglect: investing in each phase as a silo while chronic failures concentrate at the transitions no one owns. The diagnostic: locate the handoffs explicitly and ask who owns each seam — most chronic hazard-management failures live at the boundaries, which are designable but routinely left as gaps between separately-managed phases.
T4 — Cycle Feedback versus Severed Loop (temporal). The phases cycle: post-event learning is supposed to feed pre-event design — today's recovery is tomorrow's preparedness. The tension is between treating the post-event phase as a terminus and treating it as the design input to the next pre-event phase. The failure mode is amnesia: completing recovery without feeding lessons back, so the system cannot learn from its own events and repeats them. The diagnostic: check whether a structural channel (after-action review, lessons-learned database, blameless post-mortem) actually carries post-event signal into the next mitigation cycle — if the loop is severed, each event is the system's first event again.
T5 — Cross-Phase Cost-Shifting versus Per-Phase Optimisation (scalar). Phases are coupled in cost: a more expensive sea wall (pre-event) can reduce response and recovery costs, while a cheap one shifts cost downstream. The tension is between optimising each phase's budget locally and optimising total lifecycle cost. The failure mode is local thrift that raises global cost: under-funding mitigation to hit a pre-event budget, then paying far more in response and recovery. The diagnostic: evaluate interventions against total cost across all three phases, not the phase that bears the spend — a phase-local saving that pushes larger costs into other phases is a false economy the per-phase framing hides.
T6 — Trichotomy versus Finer Phase Decomposition (grain). The prime specialises into three phases, but some institutional frameworks use four or more, raising the question of whether the trichotomy itself is load-bearing or a convenient grain. The tension is between the clean three-regime decomposition and hazards whose structure does not fit it. The failure mode is forcing a hazard into pre/event/post when it has a distinct fourth regime (a long warning phase, a chronic-impact tail) that the trichotomy buries. The diagnostic: ask whether each regime in the actual hazard has a genuinely distinct tempo, logic, and metric — if a phase boundary hides two different decision logics, the trichotomy is too coarse and the decomposition should follow the regime changes, not the institutional default.
Structural–Framed Character¶
Event lifecycle phases sits on the framed side of the structural–framed spectrum, with an aggregate of 0.7. A genuine relational skeleton underlies it — a discrete pre/event/post decomposition with a regime-change at each boundary and a cycle feedback — but the prime is realised as an institutional hazard-management framework whose categories cannot be stated without human practice.
Two diagnostics push hardest toward framed, both at the maximum. The prime is institutional in origin (institutional_origin 1.0): the mitigation/response/recovery trichotomy is a disciplinary framework codified by national disaster agencies and the international Sendai framework, not a relation read off the world; its very vocabulary is the output of a specific professional and policy lineage. And it is human-practice-bound (human_practice_bound 1.0): "mitigation," "response," and "recovery" presuppose intentional actors managing a recognised hazard, with budgets, professions, and a political economy attached to each phase — there is no physical or biological substrate where the phases exist absent someone designing interventions across them. The remaining diagnostics add a partial lift without crossing to the maximum: the vocabulary leans toward risk- and disaster-management terms (vocab_travels 0.5), the phase labels carry mild normative load about what counts as good mitigation or successful recovery (evaluative_weight 0.5), and invoking the prime partly IMPORTS the hazard-management framing rather than merely recognising a pattern already present (import_vs_recognize 0.5). The underlying state-and-transition skeleton is real — that is what keeps it from a pure 1.0 — but the inherited institutional framework is heavy enough to place it firmly on the framed side, exactly as the 0.7 aggregate records.
Substrate Independence¶
Event-lifecycle phases is a moderately substrate-independent prime — composite 3 / 5 on the substrate-independence scale. Its domain breadth sits at 3: the pre-event / event / post-event trichotomy as institutionalised intervention units recurs across disaster management (mitigation / response / recovery), cybersecurity (hardening / incident response / review), medicine (prevention / acute / rehabilitation), software reliability (engineering / on-call / post-mortem), climate policy (mitigation / adaptation / loss-and-damage), workplace safety, and conflict (prevention / crisis / reconstruction) — genuinely distinct fields, but every one is a human-institutional hazard-management substrate in which agencies, professions, and funding streams organise around the phases. There is no physical or biological instance: the phases are intervention categories defined by what an organisation does before, during, and after, which is what caps the breadth. Its structural abstraction is the weakest component at 2: the trichotomy is barely more than a temporal ordering relative to a hazard event, and it carries heavy institutional commitments (each phase presupposing a profession, a budget, and a politics) rather than a medium-neutral relation. The transfer evidence is the strongest at 4: the phase boundaries, their characteristic seam-failures, and the post-event-designs-the-next-pre-event loop are demonstrably recognised across disaster, cyber, medical, and climate practice, with named frameworks (Sendai, NIST, ICS) in each. The institutional ceiling and thin abstraction hold the composite at a defensible 3.
- Composite substrate independence — 3 / 5
- Domain breadth — 3 / 5
- Structural abstraction — 2 / 5
- Transfer evidence — 4 / 5
Relationships to Other Primes¶
Parents (1) — more general patterns this builds on
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Event Lifecycle Phases is a kind of, typical State and State Transition
A specific, normatively-loaded specialisation: the states are pre-event/event/post-event, the transitions onset and termination, and each state carries its own intervention logic, time horizon, stakeholder, and political economy that the bare abstraction does not supply. The file: 'a specific, normatively-loaded specialisation of that skeleton'.
Children (1) — more specific cases that build on this
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Incident Response is a kind of Event Lifecycle Phases
The file states it outright: incident_response IS "that middle phase specifically, examined from within" — the acute phase of the pre/event/post trichotomy that event_lifecycle_phases (valid candidate, CAND-R25-015-02, already a Phase-C link) spans. event_lifecycle_phases allocates effort ACROSS the three regimes; incident_response is the acute regime's internal structure. Clean part-of/child-of (a phase within the lifecycle), explicitly the "broader frame incident response sits inside." High conviction. Distinct from controlled_reentry (the adjacent return phase, not a parent) which Phase-C correctly kept separate.
Path to root: Event Lifecycle Phases → State and State Transition
Neighborhood in Abstraction Space¶
Event Lifecycle Phases sits in a moderately populated region (50th percentile for distinctiveness): it has near-neighbors but no dense thicket of synonyms.
Family — Staged Processes & Drift (32 primes)
Nearest neighbors
- Temporal Dynamics — 0.74
- Stage Gate Process — 0.73
- Funnel Analysis — 0.71
- Conservation Event — 0.70
- Identity-Preserving Modification — 0.70
Computed from structural-signature embeddings · 2026-06-14
Not to Be Confused With¶
The nearest neighbour, temporal_dynamics, is the contrast most worth drawing because the two share a vocabulary of time and change yet differ in structure and purpose. Temporal dynamics is the general study of how a system's state evolves continuously over time — trajectories, rates, oscillations, equilibria — and it is descriptive and substrate-neutral. Event lifecycle phases imposes a discrete structure on top of a hazard's timeline: a pre/event/post trichotomy with a regime-change at each boundary, where the discontinuity in tempo, decision logic, success metric, and political economy is the whole point. The invariants differ. Temporal dynamics' invariant is the evolution law that holds across time; this prime's invariant is the qualitative break at each phase boundary that makes the same event require three distinct intervention systems. A practitioner who reaches only for temporal dynamics will model the hazard as one continuous process and miss the central prescription — that a single decision framework applied across the phases is a category error, because the regimes are not points on one continuum but three different worlds with three different logics.
A second genuine confusion is with state_and_state_transition, which shares the prime's discreteness and is its structural skeleton. State-and-state-transition is the bare abstraction: a system occupies one of several states and moves between them by transitions. Event lifecycle phases is a specific, normatively-loaded specialisation of that skeleton — the states are pre-event, event, and post-event; the transitions are onset and termination; and crucially, each state carries a characteristic intervention logic, time horizon, stakeholder, and political economy that the bare abstraction does not supply. The added content is exactly what makes the prime useful and also what makes it framed rather than purely structural: "mitigation," "response," and "recovery" are institutional categories with normative freight, not value-neutral states. The distinction matters because state-and-state-transition would let an analyst model the three phases as interchangeable nodes in a graph, missing the prime's load-bearing claim that the phases are asymmetric in visibility and reward, which is what predicts the chronic mis-allocation toward the heroic middle phase.
A third confusion worth separating is with failure_mode_and_effects_analysis_fmea, which a risk practitioner may treat as covering the same ground. FMEA enumerates a system's possible failure modes, rates them by severity and likelihood, and prioritises mitigations — but it lives almost entirely in the pre-event regime, and its object is the hazard's internal structure, not the allocation of effort across a lifecycle. Event lifecycle phases spans all three regimes and is about balancing intervention systems across them, treating FMEA as one tool deployed within the pre-event phase. The invariants differ accordingly: FMEA's is the ranked catalogue of failure modes; this prime's is the regime-change across phases and the cycle feedback from post-event learning into pre-event design. Conflating them leads to the exact pathology the prime warns against — pouring analytic effort into pre-event hazard analysis while leaving the response and recovery regimes, and the seams between them, undesigned.
For a practitioner the through-line is to recognise what each neighbour omits. Temporal dynamics omits the qualitative breaks at the phase boundaries; state-and-state-transition omits the asymmetric intervention logic and political economy that distinguish the phases; FMEA omits everything outside the pre-event regime. The prime's contribution is precisely the union of what they leave out: three regimes with distinct logics, an asymmetry that predicts budget skew, and a cycle that makes post-event learning a design responsibility rather than an afterthought.
Solution Archetypes¶
No catalogued solution archetypes reference this prime yet.