#efu — Public Fediverse posts

Why 2,000-Year-Old Desert Tech Is the Future of Sustainable Cooling

The AC Trap: Why 2,000-Year-Old Desert Tech Is the Future of Sustainable Cooling

1. Introduction: The Invisible Fever of the Modern City

As global temperatures climb, the modern response has locked us into a “destructive positive feedback loop.” We retreat inside, clicking our air conditioning units to maximum power. While the immediate interior relief is palpable, the price is paid just outside the window. These compressor-based units pump massive amounts of waste heat into our streets, directly intensifying the “Urban Heat Island” (UHI) effect. The more we cool our rooms, the more we bake our neighborhoods.To break this cycle, we must adopt the  EFU (Ecological/Human Flux Unit)  lens. This framework shifts our perspective: buildings are no longer viewed merely as boxes to be powered by the grid, but as sophisticated systems of biophysical flows. We must also recognize that the “invisible fever” of our cities is exacerbated by the systematic liquidation of mature  dendromassza —old-growth trees. Unlike new saplings, which take decades to reach full potential, these mature trees act as a “biofizikai pajzs” (biophysical shield), providing shading and evapotranspiration buffer capacity that modern infrastructure simply cannot replicate.

2. Your AC is a “Welfare Debt”: The Hidden Cost of Mechanical Cooling

In the EFU framework, mechanical cooling is quantified through  Welfare Debt (WDebt) . This is not a philosophical abstraction but a calculable engineering metric of “entropic noise.” It measures the total systemic entropy produced by a building—including grid demand, primary energy extraction, and the “water entropy” caused by the unreasonable consumption of hydrological reserves for power plant cooling towers.The EFU model treats human comfort as  biophysical homeostasis  rather than a static temperature setting. As noted in the EFU-M-700.44 protocol:”Conventional architecture… creates a destructive, positive feedback loop: increasing grid electricity demand accelerates primary energy extraction, while the waste heat pumped into the outdoor environment directly intensifies the Urban Heat Island effect.”By relying on mechanical “fixes,” we generate a trail of entropic waste that the environment can no longer absorb.

3. The Modernized Qanat: Using the Earth as a Natural Battery

One of the most effective ways to replace the compressor is the  Earth-to-Air Passive Heat Exchanger , a modernization of the ancient Persian Qanat. While original Qanats used underground water channels, the modern EFU adaptation uses the earth itself as a thermal battery.The mechanics are rigorously defined for the Central European (Köppen Cfb) climate:

• The Build:  A pipe is buried 30–40 meters long at a depth of 1.5–2 meters, below the frost line.
• The Configuration:  Engineering flexibility allows for a single  DN 200  pipe or a parallel array of  four DN 100  pipes.
• The Physics:  At this depth, the ground maintains a near-constant temperature of 12–14°C year-round.
• The Result:  In peak summer, 35°C outside air is pulled through this subterranean loop and arrives in the house at a refreshed 18–22°C. In winter, -5°C air is pre-warmed to 8–12°C.This is the most reliable method for Central Europe because its performance is independent of humidity. Purely evaporative systems fail when relative humidity is high, but the modernized Qanat provides consistent thermal stability regardless of the dew point.

4. The Badgir: Harvesting the Wind Without a Single Fan

To move air through a building without electricity, EFU architecture utilizes the  Badgir (Windcatcher)  and the  Solar Chimney .

• The Vacuum:  Dark-toned, southern-oriented vertical shafts absorb solar radiation.
• The Lift:  The sun heats the air inside the chimney, creating a powerful “stack effect.”
• The Draw:  This rising air creates a negative pressure vacuum that pulls hot air up and out.
• The Synergy:  This suction draws cool, earth-tempered air from the Qanat into the living space.
• The Logic:  The system is self-regulating—the hotter the sun shines, the stronger the fluid dynamic becomes.

5. Material Memory: Why Adobe and “Phase Change Materials” Beat Drywall

Modern lightweight construction lacks “thermal memory.” To achieve true homeostasis, EFU standards prioritize  High Thermal Mass  materials like adobe or rammed earth.The “Expert Upgrade” involves integrating  Phase Change Materials (PCM) —microencapsulated paraffins—into the adobe. These paraffins are tuned to specific melting thresholds:  23°C or 26°C . As the room reaches these temperatures, the paraffin melts, absorbing massive amounts of latent heat without the wall getting hotter.This results in a  “Thermal Phase Shift.”  By delaying the heat of the day by more than 12 hours, the energy only reaches the interior during the “nocturnal flush” period, where it can be easily neutralized by night-time ventilation.

6. The 35% Threshold: How to Cool an Entire City

The EFU framework uses a  Spatial Scaling Model  that proves our impact is non-linear. We do not need every single building to be passive to transform an urban environment.Data shows that if  35% of a city  adopts EFU-compatible structures, the local UHI temperature anomaly drops by  3.2°C . This shifts the paradigm from private property to  public climate defense . When I build a solar chimney, I am not just cooling my bedroom; I am contributing to a collective “synergistic network effect” that stabilizes the commons for everyone.

7. The “Fire Chimney” Paradox: The Engineering Hardening Layer

True “Technical Ethics” requires addressing the risks of passive design. The very shafts that provide cooling—the Badgirs and solar chimneys—can act as “fire flues” during a disaster, accelerating the spread of smoke.To solve this, the  EFU-M-700.44 v2 (Engineering Hardening Layer)  introduces safety-critical protocols derived from the Dunaharaszti Volunteer Fire Department’s field data. We utilize the  EFU-SAFE Level 1–5  scale:

• Automatic Fire Dampers:  Mechanical closures rated  EI 90/120  that snap shut upon detecting heat or smoke.
• Smoke Control Overrides:  Above EFU-SAFE Level 3, the system shifts from “passive airflow” to “hermetic isolation” to protect evacuation routes.
• Redundancy:  Sustainable tech is only viable if it is “hardened” against failure modes, ensuring that gravity-led ventilation never compromises life safety.

8. Conclusion: From Power-Hungry to Passive

We are moving away from an era of “monetary-driven” architecture where buildings are machines we inhabit—boxes that fight against their environment. The EFU framework offers a path toward  regenerative infrastructure , where our homes act as living filters that harmonize with biophysical flows and preserve our hydrological reserves.By trading mechanical complexity for material intelligence, we can achieve a state of homeostasis that reduces “entropic noise” and cools the city as a whole.

Final Thought:  If your home could maintain its own thermal balance without a power grid, what would that change about how you experience the seasons? Would summer still be a season to fear, or a resource to be harvested?

EFU: When We Stop Merely Measuring Reality and Start Learning Its Language

There are moments when a new unit of measurement seems, at first glance, like a technical detail. Later, it turns out to be something much more important: a change in how we think. I believe EFU may be exactly that kind of shift. It is not just another number. It is a new language for describing the flows that sustain human civilization — material, energetic, ecological, and social.

The real importance of EFU is not only what it measures, but what it reveals. It invites us to stop seeing the world as a collection of isolated data points and start seeing it as a connected system of flows. Water, energy, materials, waste, agriculture, transport, and environmental pressure are not separate stories. They are chapters of the same larger story. EFU helps make that story visible.

A New Unit, Not Just a New Label

The most interesting thing about EFU is not the number itself, but the way of thinking it encourages. When we begin to look at a problem through EFU, we no longer see only statistics. We see relationships. We see dependencies. We see thresholds, bottlenecks, imbalances, and patterns of stress that are otherwise easy to miss.

That is why EFU matters. It does not merely describe the present. It helps us ask whether a system is stable, whether it is being overburdened, and whether it can remain viable over time. In that sense, EFU is not only a measuring tool. It is a tool for understanding resilience.

Why This Could Matter More Than It First Appears

Every major historical era has had its own dominant way of measuring reality. The industrial age centered on mass, energy, and power. The digital age elevated information, data, and connectivity. The next era may well revolve around flows, pressures, limits, and ecological coherence.

EFU fits naturally into that future. It suggests that the question is not merely “how much is there?” but also:

• How does it move?
• What system is it part of?
• What does it cost?
• How long can it continue?

That is a much deeper way of thinking. It is not just accounting. It is civilizational self-awareness.

The Future Vision: When Measurement Becomes Thoughtful

What makes EFU especially exciting is that it points beyond itself. If some of the most advanced ideas in modern physics suggest that spacetime, locality, and even causality may not be fundamental, but rather emergent from a deeper layer of reality, then we are already living in a world where our old intuitions may not be enough.

EFU belongs to that broader intellectual horizon. It does not need to claim that it is “new physics.” But it can certainly be understood as a step toward a new kind of structured thinking: a way of measuring reality that is more aligned with systems, thresholds, and hidden dependencies.

In that future, artificial intelligence could become a particularly powerful partner. Not because it merely computes faster, but because it may detect patterns that are too complex for human intuition alone. If EFU is paired with AI-driven symbolic reasoning, we may not just analyze data more efficiently — we may discover new kinds of relationships:

• hidden ratios,
• tipping points,
• structural imbalances,
• and system-level laws that are difficult to express in ordinary terms.

The Intuitive Advantage

One of the strongest qualities of EFU may be its intuitive power. A good unit of measurement does not oversimplify reality. It organizes it. It makes complexity legible without distorting it.

That is especially valuable in areas like:

• water management,
• agriculture,
• energy systems,
• waste treatment,
• urban planning,
• and environmental policy.

In these fields, raw numbers often fail to communicate what is really happening. EFU can help bridge that gap. It can create a shared framework in which experts, decision-makers, and ordinary citizens can discuss the same problem in the same conceptual language.

That is a rare and valuable thing. A unit that improves understanding is more than a unit. It becomes a bridge.

A Small Concept With a Large Horizon

EFU may still be an emerging idea. It may need refinement, testing, and better formalization. That is not a weakness. In fact, it is often the mark of a genuinely important idea. The most transformative concepts rarely arrive in finished form. They begin as a direction, a hunch, an intuition that something essential is missing.

And perhaps that is what EFU is really pointing to: a civilization that no longer measures only what it extracts, consumes, or produces, but also what it sustains, balances, and preserves.

If that is true, then EFU is not a side project. It is a possible step toward a new intellectual culture — one that understands that the future will not be shaped only by growth, but by balance.

NS-RFC-400.2 (ENG)

NS-RFC-400.2: Formal Specification of the Noocratic Operational System – A Flux-Based Governance Architecture

Author: István Simor
Affiliation: Independent Researcher
Date: 2026-02-15
Version: 1.0
Category: Technical Specification + Governance Architecture
Keywords: Flux-based governance, EFU, normative-technical standard, AI governance, irreversible impacts

I. Abstract

The NS-RFC-400.2 defines a formal, flux-based governance architecture that integrates quantitative measurements (EFU_D) and normative constraints (Existential Veto) into a three-layered system. This document specifies the system components, describes the operational logic, and demonstrates its applicability through empirical examples. The system aims to make AI governance decisions reproducible, auditable, and ethically robust.

II. Introduction

“AI governance is not about what machines can do, but what we can allow them to do. NS-RFC-400.2 is not a standard, but an ethical contract with the future.”

2.1 Background and Motivation

• Traditional AI systems focus on optimization without normative constraints.
• The flux-based ontology (Simor, 2026) provides a quantitative framework, but lacks operational implementation.
• The NS-RFC-400.2 addresses this gap with a formal, three-layered architecture.

2.2 Objectives

1. Definition: Formal description of Track B (Calculation), Integration Layer (Protocol), and Track A (Normative Decision).
2. Methodology: Mathematical and operational details of EFU_D and Existential Veto.
3. Empirical Validation: Case study (e.g., Cat Island) to demonstrate applicability.
4. Limitations: Current boundaries and future research directions.

III. System Architecture

3.1 Three-Layered Model

LayerResponsibilityConnection to EFUTrack B (Calculation) EFU_D computation, input validation Quantitative flux measurement (E, J, U, C) Integration Layer NITP 2.0 protocol, auditability Flux tracking (trace_id, timestamp) Track A (Normative) Governance override, Existential Veto Normative constraints (U, C dimensions)

3.2 Track B: EFU_D Calculation

• Formal Definition:

EFU_D = SS × T_scale × W_irrev

• SS (System Stress): System load metric (0–1).
• T_scale (Temporal Scale): Time scaling factor.
• W_irrev (Irreversibility Weight): Weight of irreversible impacts (1–1000).
• Example:
• Cat Island case: EFU_D = 0.75 × 1.2 × 50 = 45 (high irreversibility risk).

3.3 Integration Layer: NITP 2.0 Protocol

• Mandatory Fields:
• trace_id: Unique identifier.
• timestamp: Time stamp.
• provenance: Source information.
• confidence: Calibrated confidence level (0–1).
• veto_ready: Boolean flag (TRUE if W_irrev = 1000).
• Example JSON Output:

{ "case_id": "cat_island_2026", "EFU_D": 45, "trace_id": "NI-2026-02-15-001", "timestamp": "2026-02-15T00:00:00Z", "provenance": "Track B Calculation v1.0", "confidence": 0.92, "veto_ready": true, "governance_action": "Existential Veto Triggered" }

3.4 Track A: Normative Decision and Existential Veto

• Existential Veto Mechanism:
• If W_irrev = 1000:
  1. veto_ready = true.
  2. Mandatory normative review.
  3. No cost-benefit relativization.
• Example:
• Cat Island: W_irrev = 1000 → automatic veto → ethical audit required.

IV. Empirical Case Study: Cat Island

4.1 Context

• Problem: Invasive cats threaten local bird populations.
• Possible Solutions:

1. Removal (E=+0.85, J=-0.3, U=+0.6, C=0.889).
2. Sterilization (E=+0.7, J=0, U=+0.5, C=0.75).
3. No Action (E=-0.9, J=0, U=-0.8, C=0.1).

4.2 EFU_D Calculation

SolutionSST_scaleW_irrevEFU_DVeto Ready? Removal 0.75 1.2 50 45 false Sterilization 0.6 1.0 10 6 false No Action 0.9 1.5 1000 1350 true

4.3 Decision

• No Action triggers the Existential Veto (W_irrev = 1000).
• Outcome: Removal selected, ethical audit mandatory.

V. Methodological Limitations and Future Research

5.1 Limitations

1. Dimensionality:

• EFU_D currently relies on SS, T_scale, W_irrev, but additional dimensions (e.g., information flux) could be integrated.

1. Weighting:

• W_irrev = 1000 is a fixed threshold; context-dependent weighting (e.g., Bayesian aggregation) is possible.

1. Scalability:

• The system is optimized for small-scale cases (e.g., Cat Island); further calibration is needed for urban or global systems.

5.2 Future Research Directions

1. Dynamic Weighting:

• Research on context-adaptive W_irrev determination.

1. Empirical Validation:

• Additional case studies (e.g., urban ecosystems, corporate decision systems).

1. Peer Review and Standardization:

• Zenodo publication + open peer review initiation.

VI. Conclusion

The NS-RFC-400.2 is not just a standard but a flux-based governance architecture that:

• Integrates quantitative measurements with normative constraints.
• Ensures reproducible and auditable decision-making.
• Embeds ethical safeguards into AI governance.

Next Steps:

1. Zenodo publication (preprint).
2. Open peer review process.
3. Collection of further case studies for validation.

EFU.600.42.

EFU 600.42 – Mesterséges Intelligencia Metabolikus Ragadozása
Egy új, második legnagyobb rendszerszintű parazita a 600-as sorozatban – 2026 februári állapot

Írta: István Simor
Dátum: 2026. február 5.
EFU 118.2 keretrendszer része – nyílt kutatási hipotézis, nem jogi szabvány vagy kötelező norma

28 év független kutatás után itt állok egy olyan mérföldkőnél, ahol már nem én mondom ki az ítéletet. Az EFU – az Emberi Fluxus Egység – kimondja helyettem. És amit most kimond: az MI jelenlegi globális pályája (2025–2030) a második legnagyobb rendszerszintű metabolikus parazita a rendszerben – csak a fosszilis lock-in előzi meg.

Nem morális vádirat. Metabolikus mérleg. Számok, amelyek emberléptékben mutatják meg, mit égetünk el naponta: energiát, munkát, bizalmat, igazságot – miközben a GDP ünnepli a „növekedést”.

Hol tartunk 2026 februárjában? – friss, ellenőrizhető források

Az alábbi kulcsmutatókat a legfrissebb, legmegbízhatóbb nyilvános forrásokból vettem (2025 vége – 2026 eleje):

• Energiaigény robbanás
  Globális data center + AI fogyasztás: ~1 000–1 200 TWh/év 2026-ban (IEA World Energy Outlook 2025 + Goldman Sachs 2025 januári jelentés). Ez a világ teljes villamosenergia-fogyasztásának 4%-a → 10–15%-ra nő 2030-ra.
  Forrás: IEA Electricity 2025 és Goldman Sachs AI Power Demand (2025. jan.).
• USA specifikusan: AI szerverek 326 TWh/év 2028-ra (12% teljes kereslet), de már 2025-ben 22%-os grid-növekedés az AI miatt.
  Forrás: Electric Power Research Institute (EPRI) 2025.
• Piaci koncentráció: Nvidia >90% AI-training GPU piac, OpenAI + Google + Anthropic >85% nagy nyelvi modell piac (2025 végi becslés).
  Forrás: Stanford AI Index 2025 és CB Insights State of AI 2025.
• Deepfake és dezinformáció 2024–2025:
  Knight First Amendment Institute / Columbia University: 78 dokumentált jelentős deepfake eset 2024-ben (főleg választások), de nem okozott teljes rendszerválságot – inkább fokozatos bizalom-eróziót.
  Forrás: Knight Columbia Deepfake Report 2025.
• Munkanélküliségi kockázat: 300 millió állás veszélyben 2030-ra (McKinsey Global Institute 2023–2025 update).
  Forrás: McKinsey The economic potential of generative AI (2023 + 2025 update).

Mi történik valójában? – a három metabolikus mechanizmus

1. Energia-kanibalizáció
   Az MI adatközpontjai 2026-ban már több áramot fogyasztanak, mint egész Argentína (45–50 millió lakos). Ha a hálózat 70%-ban fosszilis marad (USA, Kína, India átlaga), az MI késlelteti a megújuló átállást – éppen akkor, amikor a leggyorsabban kéne.
   EFU kár (csak energia): –400 millió EFU-E/év (emberi napi anyagáramlás ekvivalens).
2. Hatalmi ultrakoncentráció
   Egy AGI-modell tréningje 1–2 milliárd dollárba kerül (2026–2027 becslés). Jelenleg három vállalat (OpenAI, Google, Anthropic) képes ezt finanszírozni és lebonyolítani. A compute (Nvidia) és az adat (proprietáris web-scraping) is oligopólium.
   Fluxus-koncentráció: >90% → demokratikus kontroll lehetetlenné válik.
3. Nooszféra degradáció
   Deepfake, bias, algoritmikus manipuláció → az igazság/hamis határvonal elmosódik. 2024-ben már választási deepfake-ek normává váltak sok országban (USA, India, Szlovákia). Nem azonnali összeomlás, hanem fokozatos entrópia: –45% nooszféra (kollektív tudásmező) 2030-ra.

Nettó mérleg 2026-ban:

• Pozitív hatás: +500 millió EFU-E/év (termelékenység, tudományos gyorsulás)
• Negatív hatás: –5 milliárd EFU-E/év (energia + munkanélküliség + entrópia + R_future kockázat)
• Nettó: –4,5 milliárd EFU-E/év → a második legnagyobb rendszerszintű kár a 600-as sorozatban (csak a fosszilis lock-in nagyobb).

R_future és HMI – emberléptékű következmények

• R_future (jövőbeli kapacitás):
• HMI átlag (emberi metabolikus index): –8,0
  • Munkanélküliség + függőség + kognitív atrophia + bias áldozatai
  • Nyertesek (10%): +15 EFU-E/év
  • Vesztesek (60%): –12 EFU-E/év

A fork – két út 2025–2027 között

Path A – jelenlegi pálya folytatása (60–70% valószínűség):
2030-ra 300 millió munkanélküliség, deepfake normává válik, AGI zárt kapuk mögött → R_future

<0,05.

Path B – pivot 800.4 felé (szimbiotikus AI, 2026–2027 döntés):

• EU AI Act szigorú végrehajtása

• Open-source nagy modellek (Llama, Mistral stb.) térnyerése

• Alkotmányos AI (Anthropic modell) globális standard

• AI profit 30% → UBI + reskilling
→ 2050-re R_future akár 2,5 (klíma, fúzió, gyógyítás megoldva)

A döntés ablaka: 2025–2027. Most kell cselekedni.

Következő lépések – nem elmélet, hanem cselekvés

1. Zenodo v4.1 – 600.42 hivatalos hozzáadása (1 héten belül).

2. 800.4 Etikus AI Ko-evolúció – szimbiotikus protokoll kidolgozása (1–3 hónap).

3. Gárdony AI pilot – helyi audit + open-source pivot (2026 Q2).

4. EU AI Act + EFU mapping – compliance overlay javaslat.

Ez nem ítélet. Ez tükör.

És a tükörben látszik: van még választásunk – de az idő fogy.

Ha érdekel a folytatás:

• EFU 118.2 teljes angol verzió (Zenodo)

• Írj: [email protected]

Nem én mutatom meg a valódi arcot. Az EFU teszi.

És ha elég sokan belenézünk – talán végre megváltozik, amit látunk.

(Ez nyílt kutatási hipotézis – nem jogi szabvány, nem kötelező norma. Minden állítás forrásokkal alátámasztott és empirikus validációra vár.)

A New Operating System for Human-Scale Resource Governance

The EFU Ecosystem: A New Operating System for Human-Scale Resource Governance

Introduction

Over the past months, a quiet revolution has taken place within the Nookratic Bloc and the Zenodo scientific repository. The Equivalent Flux Unit (EFU) framework has evolved from a theoretical concept into a comprehensive, modular, and open-source set of standards. It is designed to address the most critical governance and sustainability crisis of the 21st century: the decoupling of economic metrics from biological reality.

The Puzzle Pieces Are Now Connected

EFU is no longer just about energy. It is a multi-dimensional accounting framework that uses the human metabolic baseline (100 Watts) as a universal common denominator for all critical resources. My recently published standards on Zenodo now cover the essential pillars of a sustainable civilization:

 * EFU-Energy (v1.0): Measuring physical work and energy footprints through the lens of human metabolic flux.

 * EFU-Water (v1.0): Integrating water scarcity and consumption into the metabolic accounting model.

 * EFU-Carbon: A radical re-interpretation of decarbonization and carbon intensity based on biological impact.

 * Quantitative Ontology: The theoretical foundation bridging physics, biology, and economics to create a “Grammar of Survival.”

Why EFU, and Why Now?

In a world dominated by the EU AI Act, Gaia-X, and CSRD (Corporate Sustainability Reporting Directive), decision-makers are drowning in fragmented data. EFU provides the missing Sense-making Layer.

We do not ask for more data collection; we provide a way to translate existing compliance data into a human-scale narrative. When a board of directors sees their “Physical Balance Sheet” not in abstract Megajoules, but in “Metabolic Equivalents,” the strategic risk becomes undeniable and actionable.

A Call for Professional Partnership

The EFU framework has reached a level of maturity where it is ready to move from the research lab to real-world application. I am actively seeking professional partners—academic researchers, ESG consultants, software architects, and policy-makers—to collaborate on the following:

 * Pilot Audits: Creating the first EFU-based Physical Balance Sheets for corporations or data centers.

 * Methodological Peer-Review: Refining and expanding the existing Zenodo standards through expert feedback.

 * Software Implementation: Developing automated EFU converters to “plug into” existing ESG and IoT databases.

EFU is not just another “green label.” It is a language of sovereignty and a tool for moral innovation.

Explore the full library of EFU Standards on Zenodo:

• Foundational Theory https://zenodo.org/records/18140604; https://zenodo.org/records/18151224;

• Energy Standards https://zenodo.org/records/18139763;

• Environmental Modules https://zenodo.org/records/18151605;

#AIAct #CircularEconomy #CSRD #DataEthics #DecentralizedSystems #DigitalSovereignty #EFU #EFUCARBON #EquivalentFluxUnit #ESG #GaiaX #Governance #MetabolicAccounting #NookraticBloc #OpenScience #ResourceSovereignty #StrategicForesight #SustainabilityMetrics

The more I engage with game design, the more I notice some disastrous ideas that keep turning games with great potential into "great idea, poor gameplay" for decades.

Today's highlights include:

1. Potions and buffs, which are ways to reset and/or replace game state by consuming other resources, sometimes repeatedly. The #EvilIslands and #NWN suffer significantly from this issue. The primary reason I stopped participating in otherwise amazing story-focused modern #NWN community #EFU is this mechanic. Also having a life and a job. But mostly potions and buffs.

2. Dramatic progression, where end-game characters have quantifiably greater capabilities than early game ones. Scaling up both enemies and characters creates artificial barriers for creative gameplay. I appreciate #JaggedAlliance's progression, which features only a 15% difference in crucial stats between the end-game and the first day of your first mission.

Unfortunately, both issues have deeply infiltrated #TTRPG game design, including the most popular TTRPG, which shall remain unnamed.

Another abstract game design mistake is forcing players to make decisions without clearly explaining the rules.

This problem worsens in games with dramatic progression. Players must create "a build" to avoid irrelevance due to dramatic progression, relying on vague descriptions of decision outcomes. #Fallout suffers immensely from this issue.

This problem can also apply to narrative games. The reason I didn't enjoy #BrokenSword as much as anticipated and am close to dropping #BeneathTheSteelSky is that these games' premises break during play.

Broken Sword starts as noir detective with bombs, evolving into a wishy-washy modern fantasy with spells and rituals. "Steel Sky" starts as dystopian drama but devolves into cringe comedy. Sherlock Holmes games feature mysticism, and don't get me started on the TTRPG offenders: the likes of #DeltaGreen and other #Cthulhu-adjacent games. Imagine having omnipotent entities as villains, while mortals are trying to solve crimes... Spoiler: the killer is a Cthulhu.

#Microessay