Ratify combined INTENT.md; rename canon/ to concepts/

The seed INTENT and the history-derived draft are merged into INTENT.md;
seed/INTENT.md is removed as superseded. "Canon" is reserved for an
established body of knowledge, so the exploratory material moves to
concepts/ and ASSEMBLY-WP-0002 is retitled accordingly.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

Assistant: claude-code
Assistant-Model: opus
Assistant-Process: 1494246@bnt-lap001
Assistant-Session: caf6de6f-f9e4-47ce-a584-49baa271fa4b
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tegwick 2026-10-12 00:15:00 +02:00
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# INTENT.md
> **Status:** draft suggestion (2026-10-11), derived from `README.md` and
> `history/20261011-InitialExploration.md`. To be reviewed and ratified by the
> project owner.
> **Status:** ratified by the project owner (2026-10-12). Merges the seed
> INTENT (the systematic research program, which governs) with the earlier
> draft derived from `history/20261011-InitialExploration.md` (the
> information-organism lens). The original seed INTENT is in git history
> (commit bb1de0d).
## Project
## Repository
`assembly-economics`
**Repository:** `assembly-economics`
**Research program:** Generative Assembly Society
**Ecosystem role:** philosophical and economic framework explored by
**coulomb.social** (State Hub domain `communication`, topic `coulomb-social`)
## Purpose
## Intent
`assembly-economics` exists to develop an experimental economic framework for
societies in which superhuman machine capability — physical, computational and
increasingly cognitive — provides most of the leverage for innovation and
profit.
This repository is a research program for exploring a possible societal contract and macroeconomic model for a world in which automation, abundant productive capacity, advanced energy systems, and sophisticated financial risk management increasingly decouple economic production from compulsory human labor and inherited capital.
In such an economy, wage labour can no longer be the main way people take part
in value creation and gain agency. The project explores a **post-work mechanism
for participation and agency**. Its framing is that an economy is an *adaptive
information processing network*: an assembly of information organisms, humans
and institutions, linked by flows of information, resources and attention.
The research starts from a simple observation:
It is the philosophical and economic framework that **coulomb.social** explores
and builds on.
> If productive capacity becomes abundant, the dominant bottlenecks of society may shift away from capital and labor toward agency, access, attention, adoption, trust, ecological limits, coordination, knowledge, and the ability to form valuable new combinations.
## Core Intent
The program investigates whether **assembly** and **generativity** can provide a more useful foundational lens than production, consumption, employment, or capital alone.
Describe an economy as a living, evolvable information-processing system, and
establish the concepts needed to design, govern and evaluate such systems so
that:
A second, more operational question follows from the first. In such an economy, superhuman machine capability (physical, computational and increasingly cognitive) supplies most of the leverage for innovation and profit, and wage labour can no longer be the main route to participation and agency. The program therefore also explores **post-work mechanisms for participation and agency**, and models the machine side of the economy as populations of adaptive **information organisms** that live inside, and are governed by, human institutions.
1. **Abundant machine resources are spent to preserve scarce sentient
resources.** Money, compute and machine capacity are convertible potential.
Human attention, autonomy and wellbeing are lived capacity. They can only be
allocated once and must be protected by viability boundaries, not optimised
away.
2. **Humans keep purpose and authority.** Information organisms learn, predict
and act, but objectives, authority and hard constraints come from the human
and institutional environment and stay outside the optimisation loop.
3. **Participation does not require labour.** Supplying objectives, judgment,
attention, consent and governance is treated as real economic contribution,
and it is valued accordingly.
---
## Conceptual Pillars
## Core Hypothesis
The initial exploration established six connected layers. Together they form
the project's working vocabulary.
A flourishing society is one that preserves and expands the capacity of people, communities, institutions, and future generations to form valuable new assemblies from the components available to them.
### 1. Adaptive Information Processing Network (AIPN)
The relevant optimization target is therefore not simply GDP, welfare, equality, consumption, or innovation.
A persistent, typed, token-flowing, self-modifying semantic network. Nodes are
high-level business concepts (`DocumentType`, `EmployeeRole`,
`WorkstationClass`, `Goal`, `Observer`). Activations are concrete instances
(documents, people, materials). Observers emit multi-dimensional
success/error signals against explicit and implicit goals. Learning changes
future activation, prediction, utility and, eventually, the structure itself.
A candidate objective is:
> Semantic structure + activation + prediction + feedback + adaptation.
> `sense → activate → predict → act → observe → learn → reorganize`
\[
\boxed{Maximize\ sustainable,\ broadly\ accessible\ viable\ future\ assembly\ space}
\]
Key distinctions: structure vs. activation, observation vs. evaluation,
prediction vs. utility, learning vs. authority, viability before optimisation.
subject to constitutional constraints concerning:
### 2. Membrane
- human agency,
- safety,
- privacy,
- responsibility,
- ecological integrity,
- anti-domination,
- intergenerational continuity,
- and the ability to contest and revise institutions.
The boundary between an organism and its environment, such as a company's
governed IT landscape. It works through semantic projections (read models, not
replicas), preserves identity, provenance and the original governance envelope,
and is claim-oriented. It is bidirectional but asymmetrical. It filters the
vast environment down to what the organism actually samples. It is layered
(constitutional, operational, adaptive, ephemeral) and keeps negative space
visible. Membrane configuration is the main control and deployment interface.
---
### 3. Seed Kernel
## Why This Research Exists
A minimal developmental substrate rather than a finished intelligence. It
attaches to an information environment and grows by adapting to it. The
environment feeds it objectives (prompts act more like hormones than
nutrients) and resources (compute budget). Utility becomes endogenous,
attention becomes resource allocation, and symbiosis is a better target than
autonomy.
Industrial capitalism emerged in a world where productive capital, physical infrastructure, and organized labor were major constraints.
### 4. Evolution
A future economy may increasingly exhibit:
Organisms as genotype/phenotype pairs that are bred, recombined and inherited
across generations. Fitness is multi-dimensional and environment-based. There
are nested adaptation loops (learning, development, evolution, ecosystem), and
heritable membranes. Hard constraints remain outside evolutionary optimisation.
- highly automated production,
- low marginal costs,
- reusable digital and physical infrastructure,
- advanced AI coordination,
- globally accessible knowledge,
- diversified risk-bearing mechanisms,
- and cheap creation of new ventures.
### 5. Metabolism and Substrate
Under these conditions, inherited capital may become less important as the primary gatekeeper of participation.
Organisms run on substrate layers: information, compute as energy, runtime as
habitat, memory as expensive tissue, authority and human attention as premium
energy. Metabolic pathways, waste and excretion, starvation and abundance
behaviour, and return on compute tie internal regulation to economic selection
pressure.
However, abundance does not automatically create a good society.
### 6. Resource Ontology and Attention Economics
It may instead produce:
Resource *accounting* (money as generalised, convertible potential) is distinct
from resource *ontology*. Resources are classed as commodity, capability, human
and institutional, along with whether they are sentient. Human attention is
treated as the reference scarce resource. Attention regulation becomes a
central societal control loop:
- extreme concentration of power,
- weak mass purchasing power,
- attention monopolies,
- ecological overshoot,
- loss of meaning or participation,
- fragile monocultures,
- information capture,
- and increasing inequality of effective agency.
The research therefore asks not only how production changes, but how a society can remain generative under abundance.
---
## Research Question
> How can a technologically abundant society organize production, risk, ownership, power, knowledge, care, recognition, and collective action so that people retain broad reachable futures, can participate meaningfully, can safely depend on others, can create and differentiate themselves, and can pass at least equivalent or greater assembly capacity to future generations?
A compact formulation is:
> Which institutional configurations maximize sustainable, broadly accessible, viable future assembly space?
---
## Core Concepts
### Assembly
A coherent structure formed from existing components that can itself become a component in future structures.
Assemblies may be:
- biological,
- individual,
- social,
- technological,
- economic,
- institutional,
- cultural,
- informational,
- or ecological.
### Generativity
The capacity of an assembly to enable further viable assemblies.
Generativity is not identical to complexity, growth, novelty, or output.
### Viable Future Assembly Space
The set of meaningful future states that remain realistically constructible from the current repertoire of:
- people,
- capabilities,
- knowledge,
- relationships,
- institutions,
- infrastructure,
- ecological resources,
- tools,
- and rights.
### Effective Agency
The diversity and accessibility of futures that are materially reachable by a person or group.
### Right to Assemble
The principle that lack of inherited capital should not prevent reasonable access to the components required for experimentation.
### Assembly Commons
Reusable knowledge, standards, tools, infrastructure, institutions, and other assemblies that reduce the cost of future construction.
### Information Organism
An adaptive, semantically explicit information-processing system: an Adaptive Information Processing Network (AIPN). It attaches to an environment through a membrane, is fed objectives and resources, learns, and can be bred and evolved across generations. Information organisms are themselves assemblies, and they are the main way machine capacity enters the assembly process.
### Membrane
The boundary between an information organism and its environment. It filters what the organism samples, preserves identity, provenance and the governance envelope of the source artefacts, and is the primary control interface through which institutions shape what organisms do.
### Attention as Lived Capacity
Money is generalized, convertible resource potential. Human attention is lived capacity: it can be allocated only once and cannot be substituted by money or machine capacity. Attention is treated as the reference scarce resource of an abundant economy.
### Domination
Concentrated ability to constrain or determine the reachable futures of others through control of:
- markets,
- infrastructure,
- employment,
- attention,
- information,
- institutions,
- or political authority.
---
## Foundational Process
The project uses the following general cycle:
\[
Explore
\rightarrow
Assemble
\rightarrow
Select
\rightarrow
Preserve
\rightarrow
Reuse
\]
with:
\[
Disassemble
\qquad
Reassemble
\]
as equally important processes.
This cycle is intended to apply across scales.
Examples:
- skills becoming capabilities,
- children developing into autonomous adults,
- scientific observations becoming theories,
- components becoming products,
- products becoming platforms,
- people and resources becoming companies,
- institutions becoming governance systems,
- species becoming ecosystems.
---
## Two Lenses: Society and Information Organisms
The program works at two scales that use the same assembly logic.
| Assembly process | Society lens (seed artifacts) | Information-organism lens (history/concepts) |
|---|---|---|
| Explore | experimentation, right to assemble | curiosity, sampling as explicit action |
| Assemble | ventures, institutions, commons | activation, structural learning, chunk/concept formation |
| Select | markets, adoption, science, democracy | observers, multi-dimensional fitness, environments as selectors |
| Preserve | commons, intergenerational transfer | consolidation, inheritance of learned structure (including failures) |
| Reuse | standards, platforms, infrastructure | distributions of pre-evolved organisms, heritable membranes |
| Disassemble / Reassemble | bankruptcy, restartability | forgetting, recombination across interfaces |
The information-organism lens contributes six layers (see `concepts/`):
1. **AIPN.** Semantic structure + activation + prediction + feedback + adaptation.
2. **Membrane.** The governed interface to institutional IT and to the wider environment.
3. **Seed kernel.** A minimal developmental substrate that grows by adapting to its environment.
4. **Evolution.** Genotype/phenotype, recombination, nested adaptation loops; hard constraints stay outside evolutionary optimization.
5. **Metabolism.** Substrate vs. nutrients: information, compute as energy, runtime as habitat, memory as tissue, authority and human attention as premium energy.
6. **Resource ontology.** Commodity, capability, human and institutional resources, split by a sentient boundary; conversion functions between them.
The lenses connect through a societal control loop:
```text
human purpose → objectives → economic allocation
→ (money · compute · machine capacity) → information organisms
→ work → abundance → human benefit → feedback
protected throughout by: attention · autonomy · wellbeing viability boundaries
protected throughout by viability boundaries on attention, autonomy and wellbeing
```
## Scope
---
**In scope**
## Societal Contract
- A conceptual canon (currently v0.1 in the history file) and its successors
- Economic models for participation, agency and value attribution in a
post-work setting
- Resource ontology, conversion functions and attention-protection mechanisms
- Membrane and governance models for embedding information organisms in real
institutions
- Reference scenarios (e.g. invoice processing) and minimal experimental
kernels that make the concepts testable
- Framework input for coulomb.social
The initial societal contract contains ten principles:
**Out of scope (for now)**
1. **Existence** — basic participation should not depend entirely on current market usefulness.
2. **Development** — each stage of life should support development or preservation of capability.
3. **Agency** — people should retain broad sets of realistically reachable futures.
4. **Right to Assemble** — inherited wealth should not be the primary prerequisite for experimentation.
5. **Responsibility** — freedom to assemble does not include unlimited freedom to externalize harm.
6. **Care and Dependency** — safe dependency is a normal part of human life.
7. **Anti-Domination** — reward may be unequal without permitting unchecked control over others.
8. **Plurality** — society should sustain multiple forms of contribution, recognition, selection, and knowledge.
9. **Intergenerational Continuity** — present assembly should not systematically destroy future assembly capacity.
10. **Revisability** — institutions must remain contestable, improvable, and replaceable.
- Production implementations, storage engines, protocols or API formats.
Canon v0.1 deliberately leaves these unstandardised.
- Concrete marketplace product features. Those belong in `coulomb-social`.
- Pricing mechanics as such. See `adaptive-pricing`.
---
## Guiding Principles
## Important Balances
- Semantic explicitness over opaque optimisation
- Viability precedes optimisation, and sentient viability precedes all else
- Learning is distinct from authority, and governance stays outside the network
- Provenance and explainability are first-class
- Keep the kernel small; separate the normative core from exploratory
extensions
The program treats the following as viability balances rather than quantities to maximize independently:
## Proposed Next Artifacts
- freedom ↔ safety,
- voluntarism ↔ responsibility,
- privacy ↔ social translucency,
- merit ↔ equality of agency,
- competition ↔ cooperation,
- diversity ↔ composability,
- experimentation ↔ stability,
- present agency ↔ future agency,
- individual autonomy ↔ collective coordination,
- creation ↔ preservation,
- efficiency ↔ resilience,
- personalization ↔ shared reality.
From canon v0.1 § 53, extended toward the economic layer:
---
- `canon/ConceptualCanon.md`: extract and stabilise the v0.1 canon
- `canon/NetworkObjectModel.md`: precise, implementation-neutral object model
- `canon/MembraneModel.md`: the interface membrane and its layers
- `canon/ResourceOntology.md`: resource classes, conversion functions,
sentient boundary
- `canon/ParticipationModel.md`: post-work participation and agency
- `research/ResearchProgram.md` and `research/ReferenceScenario-InvoiceProcessing.md`
## Explicit Non-Goals
## Relationship to the Ecosystem
This project is not intended to:
- **coulomb.social**: primary consumer; this repo supplies its philosophical
and economic framework.
- **adaptive-pricing / commerce-canon**: neighbouring economic mechanics that
may later adopt this repo's resource ontology.
- **the-custodian / State Hub**: work coordination (domain `communication`,
topic `coulomb-social`).
- design a totalizing ideology,
- abolish markets,
- abolish private property,
- abolish profit,
- prescribe equal outcomes,
- maximize consumption,
- maximize complexity,
- treat GDP as irrelevant,
- reduce all human value to a single score,
- assume that technology eliminates physical scarcity,
- assume that attention, status, land, trust, or ecological capacity become abundant,
- or assume that one allocation mechanism is universally superior.
Markets, commons, communities, public institutions, science, families, and other coordination mechanisms are all treated as candidate components of the system.
---
## Research Method
The program should evolve through repeated movement between:
1. conceptual modeling,
2. formal modeling,
3. scenario testing,
4. historical comparison,
5. empirical measurement,
6. institutional design,
7. falsification and critique.
The intent is to make assumptions explicit rather than hiding them behind political labels.
The project should actively search for:
- contradictions,
- missing variables,
- unintended incentives,
- failure modes,
- power concentration,
- measurement problems,
- Goodhart effects,
- and transition risks.
---
## Initial Model
The first formal artifact is:
`GenerativeAssemblyDynamicsModel.md`
The initial model is **GADM-0.1**.
It contains ten primary stocks:
- Human Capability \(H\),
- Assembly Commons \(X\),
- Productive Capacity \(K\),
- Risk Capacity \(F\),
- Effective Agency \(G\),
- Diversity & Composability \(N\),
- Epistemic Capacity \(Q\),
- Domination Concentration \(P\),
- Ecological Headroom \(E\),
- Social Cohesion \(S\).
It introduces the provisional diagnostic:
\[
VFAC =
H^a X^b G^c N^d Q^e S^f E^g (1-P)^h
\]
for **Viable Future Assembly Capacity**.
VFAC is not intended as a normative welfare score. It is a modeling instrument for examining dependencies and failure modes.
---
## Initial Scenario Program
The first scenario set should compare:
1. **Automated capitalism**
2. **Dividend abundance**
3. **Universal venture access**
4. **Commons-rich economy**
5. **Attention oligopoly**
6. **Generative regime**
A later scenario set should add the information-organism dimension: who breeds, owns and governs the organisms, who controls their membranes, and how their metabolism draws on human attention.
The purpose is not to identify a political winner.
The purpose is to understand system behavior under different assumptions about:
- ownership,
- access,
- reuse,
- risk,
- power,
- demand,
- attention,
- and common infrastructure.
---
## Initial Research Workstreams
### WS-01 — Assembly Ontology
Clarify:
- what counts as an assembly,
- what counts as a component,
- what is preserved,
- what is recombined,
- how assemblies nest across scales,
- and where the concept ceases to be useful.
### WS-02 — Human Development and Life Cycle
Study:
- childhood development,
- education,
- dependency,
- care,
- adulthood,
- ageing,
- mentoring,
- tacit knowledge,
- and intergenerational transfer.
### WS-03 — Agency and Reachable Futures
Develop operational definitions and proxies for:
- effective agency,
- optionality,
- exit,
- restartability,
- access,
- mobility,
- and path closure.
### WS-04 — Markets, Adoption, and Selection
Compare different selection mechanisms:
- consumer adoption,
- markets,
- peer selection,
- science,
- professional standards,
- democratic allocation,
- commons governance,
- and ecological selection.
### WS-05 — Risk and Capital
Explore whether advanced risk management can decouple experimentation from inherited capital.
Topics include:
- venture portfolios,
- limited liability,
- bankruptcy,
- insurance,
- public risk pools,
- diversified micro-investment,
- staged finance,
- and automated underwriting.
### WS-06 — Commons and Reuse
Study which mechanisms convert successful assemblies into reusable foundations.
Topics include:
- open standards,
- open source,
- infrastructure,
- public knowledge,
- interoperability,
- licensing,
- and modularity.
### WS-07 — Power and Anti-Domination
Develop models of power concentration that go beyond wealth.
Study:
- platform control,
- infrastructure control,
- political influence,
- discovery systems,
- identity systems,
- media,
- monopoly,
- and institutional capture.
### WS-08 — Epistemic Capacity
Study the societal mechanisms required to detect and correct bad models.
Topics include:
- science,
- journalism,
- audit,
- reproducibility,
- forecasting,
- open evidence,
- information concentration,
- and AI-mediated epistemics.
### WS-09 — Ecology and Physical Scarcity
Separate informational abundance from physical scarcity.
Study:
- land,
- energy,
- minerals,
- ecosystems,
- biodiversity,
- environmental sinks,
- circularity,
- and physical throughput.
### WS-10 — Recognition, Meaning, and Social Cohesion
Explore:
- positional scarcity,
- recognition systems,
- belonging,
- plural status hierarchies,
- meaningful participation,
- legitimacy,
- trust,
- and peaceful conflict resolution.
### WS-11 — Governance and Meta-Governance
Study:
- constitutional constraints,
- subsidiarity,
- institutional experimentation,
- appeal,
- rollback,
- minority protection,
- governance of metrics,
- and governance of the controller itself.
### WS-12 — Transition Dynamics
Model the path from present institutions toward candidate future regimes.
Study:
- rapid automation,
- labor displacement,
- ownership concentration,
- social dividends,
- asset shocks,
- institutional adaptation,
- and transition legitimacy.
### WS-13 — Information Organisms and Machine Metabolism
Develop the information-organism lens:
- the AIPN concept,
- membranes and institutional governance envelopes,
- seed kernels and development,
- breeding, inheritance and evolution of organisms,
- metabolism, substrate and return on compute,
- and how organisms act as assembly agents within GADM.
### WS-14 — Resource Ontology and Attention
Separate resource accounting from resource ontology.
Study:
- money as convertible potential,
- attention as lived capacity,
- commodity, capability, human and institutional resources,
- the sentient boundary,
- conversion functions,
- attention regulation as a societal control loop,
- and post-work participation and its recognition.
---
## Metrics Philosophy
No foundational social property should be represented by a single metric.
Each major construct should use a sensor bundle including:
1. objective outcome measures,
2. structural measures,
3. behavioral measures,
4. subjective measures.
Metric disagreement is treated as information rather than noise.
The project should explicitly account for Goodhart effects.
---
## Research Principles
1. **Prefer explicit models over slogans.**
2. **Distinguish normative principles from empirical hypotheses.**
3. **Model power separately from wealth.**
4. **Treat children, seniors, care, and dependency as first-class concerns.**
5. **Treat future generations as constrained stakeholders.**
6. **Distinguish logical abundance from physical scarcity.**
7. **Do not make consumer adoption the sole selection mechanism.**
8. **Treat preservation and disassembly as seriously as creation.**
9. **Prefer plural mechanisms over single universal institutions.**
10. **Search actively for failure modes and counterexamples.**
11. **Keep the framework revisable.**
12. **Do not confuse the model with reality.**
13. **Spend abundant machine resources to preserve scarce sentient resources.**
14. **Keep learning separate from authority.** Organisms and controllers optimize; humans and institutions hold purpose, authority and hard constraints.
---
## Initial Repository Structure
```text
.
├── INTENT.md governing statement of purpose
├── seed/ seed artifacts (concept digest, GADM-0.1)
├── history/ exploration transcripts (immutable record of origin)
├── concepts/ exploratory concept documents promoted from history/ and seed/
├── models/
├── research/
├── scenarios/
├── metrics/
├── references/
├── simulations/
└── workplans/ State Hub workplans
```
The seed artifacts are `seed/GenerativeAssemblySocietyConcept.md` and `seed/GenerativeAssemblyDynamicsModel.md`.
Future work should migrate stable concepts, models, scenarios, and metrics into their respective directories while keeping `INTENT.md` as the governing statement of purpose.
---
## Immediate Next Steps
1. Review and critique the conceptual assumptions.
2. Produce a causal-loop diagram for GADM-0.1.
3. Define signs and dependencies for every causal link.
4. Build a first normalized stock-and-flow simulation.
5. Run the six initial scenarios.
6. Identify which variables dominate system behavior.
7. Establish a first metrics catalog.
8. Add an explicit life-cycle extension.
9. Add an explicit power model.
10. Compare the framework against relevant work in economics, systems theory, complexity science, institutional economics, political economy, development theory, and Assembly Theory.
11. Map the information-organism concepts onto GADM-0.1 stocks and flows (WS-13).
12. Promote the resource ontology and attention model into concepts/ (WS-14).
---
## Success Criteria
The research program succeeds if it helps us produce increasingly testable answers to questions such as:
- What makes a society generative?
- Which kinds of abundance actually expand agency?
- Which forms of inequality preserve useful differentiation and which create domination?
- How can experimentation become cheap without making harmful externalization cheap?
- Which institutions best preserve and reuse successful assemblies?
- How should risk-bearing capacity be distributed?
- How should common productive capacity translate into broad participation?
- What forms of power most strongly shrink reachable futures?
- How can a society preserve plurality without fragmenting?
- How can present generations increase rather than consume the option space of future generations?
The goal is not a finished doctrine.
The goal is a progressively better model of the search space.

View file

@ -16,7 +16,7 @@ the reference scarce resource. See INTENT.md for the six conceptual pillars
## In Scope
- Conceptual canon (v0.1 lives in `history/20261011-InitialExploration.md`) and its successors
- Exploratory concept documents under `concepts/` (AIPN concept v0.1 and successors)
- Economic models for post-work participation, agency and value attribution
- Resource ontology, conversion functions, attention-protection mechanisms
- Membrane/governance models for embedding information organisms in institutions
@ -24,7 +24,7 @@ the reference scarce resource. See INTENT.md for the six conceptual pillars
## Out of Scope
- Production implementations, storage, protocols, API formats (deliberately unstandardised in canon v0.1)
- Production implementations, storage, protocols, API formats (deliberately left open in the AIPN concept v0.1)
- Marketplace product features (belong in `coulomb-social`)
- Pricing mechanics (belong in `adaptive-pricing`)

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@ -2,10 +2,14 @@
Provenance: extracted verbatim from history/20261011-InitialExploration.md
(lines 857–1739, conversation dated 2026-10-06). Extracted 2026-10-12 under
ASSEMBLY-WP-0002-T01. Later edits are tracked in git history.
Terminology edit 2026-10-12: the original called this a "Conceptual Canon".
The project reserves "canon" for an established body of knowledge, and this
material is exploratory, so "canon"/"canonical" were replaced with
"concept"/"core"/"reference". The original wording remains in history/.
-->
# Adaptive Information Processing Network
## Conceptual Canon v0.1
## Concept v0.1
**Status:** Initial draft
**Purpose:** Establish a precise conceptual vocabulary for adaptive information-processing networks operating on high-level semantic information objects.
@ -231,7 +235,7 @@ The network can therefore progressively construct abstractions from recurrent pr
### 4. Core Ontology
The minimum canonical vocabulary consists of:
The minimum core vocabulary consists of:
```text
Node
@ -462,7 +466,7 @@ DelayProcessing
Escalate
```
The canon distinguishes:
The concept distinguishes:
```text
something happened
@ -541,9 +545,9 @@ A chunk may summarize a sequence, subgraph, recurring context, workflow, behavio
Chunks MAY themselves participate as ordinary nodes.
### 19. Canonical Learning Modes
### 19. Core Learning Modes
The initial canon distinguishes four primary learning modes:
The initial concept distinguishes four primary learning modes:
- Associative Learning
- Predictive Learning
@ -589,7 +593,7 @@ Attention MAY be driven by high activation, high surprise, high uncertainty, hig
### 25. Memory
The canon recognizes at least three useful forms of memory:
The concept recognizes at least three useful forms of memory:
- Structural memory
- Statistical memory
@ -648,7 +652,7 @@ Level 5 — Hierarchical concept formation
### 33. Processing Cycle
A canonical processing cycle is:
A reference processing cycle is:
```text
1. Observe
@ -745,7 +749,7 @@ Humans MAY interact with the network by providing tokens, activating goals, prov
Artificial agents MAY occupy the same general roles.
The canon does not require a fundamental semantic distinction between human and artificial participants.
The concept does not require a fundamental semantic distinction between human and artificial participants.
Authority and reliability may differ independently.
@ -782,7 +786,7 @@ The same conceptual machinery MAY operate at multiple abstraction levels.
A chunk at one level MAY become a node at another.
### 45. Canonical Distinctions
### 45. Core Distinctions
The following distinctions SHOULD remain explicit:
@ -877,7 +881,7 @@ It intentionally does **not** yet standardize storage representation, distribute
### 53. Proposed Next Artifacts
```text
ConceptualCanon.md
AdaptiveInformationProcessingNetworkConcept.md
ArchitectureBlueprint.md
ResearchProgram.md
ReferenceScenario-InvoiceProcessing.md

View file

@ -1,20 +1,21 @@
# Canon
# Concepts
Normative conceptual documents for `assembly-economics`. Each document is
promoted from exploration material in `history/` and then evolves on its own.
The history files stay unchanged as the record of origin.
Exploratory concept documents for `assembly-economics`. Each document is
promoted from exploration material in `history/` or `seed/` and then evolves on
its own. These are working concepts, not an established body of knowledge. The
history files stay unchanged as the record of origin.
## Documents
| Document | Status | Source in `history/20261011-InitialExploration.md` |
|----------|--------|-----------------------------------------------------|
| [ConceptualCanon.md](ConceptualCanon.md) | v0.1 (extracted verbatim) | lines 857–1739 |
| [AdaptiveInformationProcessingNetworkConcept.md](AdaptiveInformationProcessingNetworkConcept.md) | v0.1 (extracted; terminology edited) | lines 857–1739 |
| MembraneModel.md | planned (ASSEMBLY-WP-0002-T03) | lines 1747–2065 (IT integration), 2882–3203 (membrane as filter) |
| SeedKernel.md | planned (ASSEMBLY-WP-0002-T04) | lines 2070–2437 |
| EvolutionModel.md | planned (ASSEMBLY-WP-0002-T05) | lines 2442–2877 |
| MetabolismModel.md | planned (ASSEMBLY-WP-0002-T06) | lines 3208–3775 |
| ResourceOntology.md | planned (ASSEMBLY-WP-0002-T07) | lines 3780–4263 |
| NetworkObjectModel.md | planned (ASSEMBLY-WP-0002-T08) | derived from ConceptualCanon.md § 53 |
| NetworkObjectModel.md | planned (ASSEMBLY-WP-0002-T08) | derived from AdaptiveInformationProcessingNetworkConcept.md § 53 |
## Conventions
@ -23,6 +24,8 @@ The history files stay unchanged as the record of origin.
- Promotion is verbatim first. Consolidation and edits happen in later commits,
so the diff shows every change against the original.
- Version is stated in the document header (`v0.1`, `v0.2`, …). Bump it on
normative changes, not on wording fixes.
- Implementation-specific material (storage, protocols, APIs) stays out of the
canon, as ConceptualCanon.md § 52 requires.
substantive changes, not on wording fixes.
- Implementation-specific material (storage, protocols, APIs) stays out of
concept documents, as AdaptiveInformationProcessingNetworkConcept.md § 52 requires.
- Do not call these documents "canon". That term is reserved for an
established body of knowledge.

View file

@ -1,592 +0,0 @@
# INTENT.md
## Repository
**Working name:** `generative-assembly-society`
## Intent
This repository is a research program for exploring a possible societal contract and macroeconomic model for a world in which automation, abundant productive capacity, advanced energy systems, and sophisticated financial risk management increasingly decouple economic production from compulsory human labor and inherited capital.
The research starts from a simple observation:
> If productive capacity becomes abundant, the dominant bottlenecks of society may shift away from capital and labor toward agency, access, attention, adoption, trust, ecological limits, coordination, knowledge, and the ability to form valuable new combinations.
The program investigates whether **assembly** and **generativity** can provide a more useful foundational lens than production, consumption, employment, or capital alone.
---
## Core Hypothesis
A flourishing society is one that preserves and expands the capacity of people, communities, institutions, and future generations to form valuable new assemblies from the components available to them.
The relevant optimization target is therefore not simply GDP, welfare, equality, consumption, or innovation.
A candidate objective is:
\[
\boxed{Maximize\ sustainable,\ broadly\ accessible\ viable\ future\ assembly\ space}
\]
subject to constitutional constraints concerning:
- human agency,
- safety,
- privacy,
- responsibility,
- ecological integrity,
- anti-domination,
- intergenerational continuity,
- and the ability to contest and revise institutions.
---
## Why This Research Exists
Industrial capitalism emerged in a world where productive capital, physical infrastructure, and organized labor were major constraints.
A future economy may increasingly exhibit:
- highly automated production,
- low marginal costs,
- reusable digital and physical infrastructure,
- advanced AI coordination,
- globally accessible knowledge,
- diversified risk-bearing mechanisms,
- and cheap creation of new ventures.
Under these conditions, inherited capital may become less important as the primary gatekeeper of participation.
However, abundance does not automatically create a good society.
It may instead produce:
- extreme concentration of power,
- weak mass purchasing power,
- attention monopolies,
- ecological overshoot,
- loss of meaning or participation,
- fragile monocultures,
- information capture,
- and increasing inequality of effective agency.
The research therefore asks not only how production changes, but how a society can remain generative under abundance.
---
## Research Question
> How can a technologically abundant society organize production, risk, ownership, power, knowledge, care, recognition, and collective action so that people retain broad reachable futures, can participate meaningfully, can safely depend on others, can create and differentiate themselves, and can pass at least equivalent or greater assembly capacity to future generations?
A compact formulation is:
> Which institutional configurations maximize sustainable, broadly accessible, viable future assembly space?
---
## Core Concepts
### Assembly
A coherent structure formed from existing components that can itself become a component in future structures.
Assemblies may be:
- biological,
- individual,
- social,
- technological,
- economic,
- institutional,
- cultural,
- informational,
- or ecological.
### Generativity
The capacity of an assembly to enable further viable assemblies.
Generativity is not identical to complexity, growth, novelty, or output.
### Viable Future Assembly Space
The set of meaningful future states that remain realistically constructible from the current repertoire of:
- people,
- capabilities,
- knowledge,
- relationships,
- institutions,
- infrastructure,
- ecological resources,
- tools,
- and rights.
### Effective Agency
The diversity and accessibility of futures that are materially reachable by a person or group.
### Right to Assemble
The principle that lack of inherited capital should not prevent reasonable access to the components required for experimentation.
### Assembly Commons
Reusable knowledge, standards, tools, infrastructure, institutions, and other assemblies that reduce the cost of future construction.
### Domination
Concentrated ability to constrain or determine the reachable futures of others through control of:
- markets,
- infrastructure,
- employment,
- attention,
- information,
- institutions,
- or political authority.
---
## Foundational Process
The project uses the following general cycle:
\[
Explore
\rightarrow
Assemble
\rightarrow
Select
\rightarrow
Preserve
\rightarrow
Reuse
\]
with:
\[
Disassemble
\qquad
Reassemble
\]
as equally important processes.
This cycle is intended to apply across scales.
Examples:
- skills becoming capabilities,
- children developing into autonomous adults,
- scientific observations becoming theories,
- components becoming products,
- products becoming platforms,
- people and resources becoming companies,
- institutions becoming governance systems,
- species becoming ecosystems.
---
## Societal Contract
The initial societal contract contains ten principles:
1. **Existence** — basic participation should not depend entirely on current market usefulness.
2. **Development** — each stage of life should support development or preservation of capability.
3. **Agency** — people should retain broad sets of realistically reachable futures.
4. **Right to Assemble** — inherited wealth should not be the primary prerequisite for experimentation.
5. **Responsibility** — freedom to assemble does not include unlimited freedom to externalize harm.
6. **Care and Dependency** — safe dependency is a normal part of human life.
7. **Anti-Domination** — reward may be unequal without permitting unchecked control over others.
8. **Plurality** — society should sustain multiple forms of contribution, recognition, selection, and knowledge.
9. **Intergenerational Continuity** — present assembly should not systematically destroy future assembly capacity.
10. **Revisability** — institutions must remain contestable, improvable, and replaceable.
---
## Important Balances
The program treats the following as viability balances rather than quantities to maximize independently:
- freedom ↔ safety,
- voluntarism ↔ responsibility,
- privacy ↔ social translucency,
- merit ↔ equality of agency,
- competition ↔ cooperation,
- diversity ↔ composability,
- experimentation ↔ stability,
- present agency ↔ future agency,
- individual autonomy ↔ collective coordination,
- creation ↔ preservation,
- efficiency ↔ resilience,
- personalization ↔ shared reality.
---
## Explicit Non-Goals
This project is not intended to:
- design a totalizing ideology,
- abolish markets,
- abolish private property,
- abolish profit,
- prescribe equal outcomes,
- maximize consumption,
- maximize complexity,
- treat GDP as irrelevant,
- reduce all human value to a single score,
- assume that technology eliminates physical scarcity,
- assume that attention, status, land, trust, or ecological capacity become abundant,
- or assume that one allocation mechanism is universally superior.
Markets, commons, communities, public institutions, science, families, and other coordination mechanisms are all treated as candidate components of the system.
---
## Research Method
The program should evolve through repeated movement between:
1. conceptual modeling,
2. formal modeling,
3. scenario testing,
4. historical comparison,
5. empirical measurement,
6. institutional design,
7. falsification and critique.
The intent is to make assumptions explicit rather than hiding them behind political labels.
The project should actively search for:
- contradictions,
- missing variables,
- unintended incentives,
- failure modes,
- power concentration,
- measurement problems,
- Goodhart effects,
- and transition risks.
---
## Initial Model
The first formal artifact is:
`GenerativeAssemblyDynamicsModel.md`
The initial model is **GADM-0.1**.
It contains ten primary stocks:
- Human Capability \(H\),
- Assembly Commons \(X\),
- Productive Capacity \(K\),
- Risk Capacity \(F\),
- Effective Agency \(G\),
- Diversity & Composability \(N\),
- Epistemic Capacity \(Q\),
- Domination Concentration \(P\),
- Ecological Headroom \(E\),
- Social Cohesion \(S\).
It introduces the provisional diagnostic:
\[
VFAC =
H^a X^b G^c N^d Q^e S^f E^g (1-P)^h
\]
for **Viable Future Assembly Capacity**.
VFAC is not intended as a normative welfare score. It is a modeling instrument for examining dependencies and failure modes.
---
## Initial Scenario Program
The first scenario set should compare:
1. **Automated capitalism**
2. **Dividend abundance**
3. **Universal venture access**
4. **Commons-rich economy**
5. **Attention oligopoly**
6. **Generative regime**
The purpose is not to identify a political winner.
The purpose is to understand system behavior under different assumptions about:
- ownership,
- access,
- reuse,
- risk,
- power,
- demand,
- attention,
- and common infrastructure.
---
## Initial Research Workstreams
### WS-01 — Assembly Ontology
Clarify:
- what counts as an assembly,
- what counts as a component,
- what is preserved,
- what is recombined,
- how assemblies nest across scales,
- and where the concept ceases to be useful.
### WS-02 — Human Development and Life Cycle
Study:
- childhood development,
- education,
- dependency,
- care,
- adulthood,
- ageing,
- mentoring,
- tacit knowledge,
- and intergenerational transfer.
### WS-03 — Agency and Reachable Futures
Develop operational definitions and proxies for:
- effective agency,
- optionality,
- exit,
- restartability,
- access,
- mobility,
- and path closure.
### WS-04 — Markets, Adoption, and Selection
Compare different selection mechanisms:
- consumer adoption,
- markets,
- peer selection,
- science,
- professional standards,
- democratic allocation,
- commons governance,
- and ecological selection.
### WS-05 — Risk and Capital
Explore whether advanced risk management can decouple experimentation from inherited capital.
Topics include:
- venture portfolios,
- limited liability,
- bankruptcy,
- insurance,
- public risk pools,
- diversified micro-investment,
- staged finance,
- and automated underwriting.
### WS-06 — Commons and Reuse
Study which mechanisms convert successful assemblies into reusable foundations.
Topics include:
- open standards,
- open source,
- infrastructure,
- public knowledge,
- interoperability,
- licensing,
- and modularity.
### WS-07 — Power and Anti-Domination
Develop models of power concentration that go beyond wealth.
Study:
- platform control,
- infrastructure control,
- political influence,
- discovery systems,
- identity systems,
- media,
- monopoly,
- and institutional capture.
### WS-08 — Epistemic Capacity
Study the societal mechanisms required to detect and correct bad models.
Topics include:
- science,
- journalism,
- audit,
- reproducibility,
- forecasting,
- open evidence,
- information concentration,
- and AI-mediated epistemics.
### WS-09 — Ecology and Physical Scarcity
Separate informational abundance from physical scarcity.
Study:
- land,
- energy,
- minerals,
- ecosystems,
- biodiversity,
- environmental sinks,
- circularity,
- and physical throughput.
### WS-10 — Recognition, Meaning, and Social Cohesion
Explore:
- positional scarcity,
- recognition systems,
- belonging,
- plural status hierarchies,
- meaningful participation,
- legitimacy,
- trust,
- and peaceful conflict resolution.
### WS-11 — Governance and Meta-Governance
Study:
- constitutional constraints,
- subsidiarity,
- institutional experimentation,
- appeal,
- rollback,
- minority protection,
- governance of metrics,
- and governance of the controller itself.
### WS-12 — Transition Dynamics
Model the path from present institutions toward candidate future regimes.
Study:
- rapid automation,
- labor displacement,
- ownership concentration,
- social dividends,
- asset shocks,
- institutional adaptation,
- and transition legitimacy.
---
## Metrics Philosophy
No foundational social property should be represented by a single metric.
Each major construct should use a sensor bundle including:
1. objective outcome measures,
2. structural measures,
3. behavioral measures,
4. subjective measures.
Metric disagreement is treated as information rather than noise.
The project should explicitly account for Goodhart effects.
---
## Research Principles
1. **Prefer explicit models over slogans.**
2. **Distinguish normative principles from empirical hypotheses.**
3. **Model power separately from wealth.**
4. **Treat children, seniors, care, and dependency as first-class concerns.**
5. **Treat future generations as constrained stakeholders.**
6. **Distinguish logical abundance from physical scarcity.**
7. **Do not make consumer adoption the sole selection mechanism.**
8. **Treat preservation and disassembly as seriously as creation.**
9. **Prefer plural mechanisms over single universal institutions.**
10. **Search actively for failure modes and counterexamples.**
11. **Keep the framework revisable.**
12. **Do not confuse the model with reality.**
---
## Initial Repository Structure
```text
.
├── INTENT.md
├── GenerativeAssemblySocietyConcept.md
├── GenerativeAssemblyDynamicsModel.md
├── concepts/
├── models/
├── research/
├── scenarios/
├── metrics/
├── references/
└── simulations/
```
The first three files are the seed artifacts.
Future work should migrate stable concepts, models, scenarios, and metrics into their respective directories while keeping `INTENT.md` as the governing statement of purpose.
---
## Immediate Next Steps
1. Review and critique the conceptual assumptions.
2. Produce a causal-loop diagram for GADM-0.1.
3. Define signs and dependencies for every causal link.
4. Build a first normalized stock-and-flow simulation.
5. Run the six initial scenarios.
6. Identify which variables dominate system behavior.
7. Establish a first metrics catalog.
8. Add an explicit life-cycle extension.
9. Add an explicit power model.
10. Compare the framework against relevant work in economics, systems theory, complexity science, institutional economics, political economy, development theory, and Assembly Theory.
---
## Success Criteria
The research program succeeds if it helps us produce increasingly testable answers to questions such as:
- What makes a society generative?
- Which kinds of abundance actually expand agency?
- Which forms of inequality preserve useful differentiation and which create domination?
- How can experimentation become cheap without making harmful externalization cheap?
- Which institutions best preserve and reuse successful assemblies?
- How should risk-bearing capacity be distributed?
- How should common productive capacity translate into broad participation?
- What forms of power most strongly shrink reachable futures?
- How can a society preserve plurality without fragmenting?
- How can present generations increase rather than consume the option space of future generations?
The goal is not a finished doctrine.
The goal is a progressively better model of the search space.

View file

@ -1,7 +1,7 @@
---
id: ASSEMBLY-WP-0002
type: workplan
title: "Establish the canon from the initial exploration"
title: "Promote exploration concepts into concepts/"
domain: communication
repo: assembly-economics
status: active
@ -14,14 +14,14 @@ updated: "2026-10-12"
state_hub_workstream_id: "2af40c6f-7b17-5f78-be0c-e0d151bd8f38"
---
# Establish the canon from the initial exploration
# Promote exploration concepts into concepts/
Promote the concepts from `history/20261011-InitialExploration.md` into
normative documents under `canon/`. Each layer of the exploration becomes its
own canon document: promoted verbatim first, then consolidated. See
`canon/README.md` for the source line ranges and conventions.
exploratory concept documents under `concepts/`. Each layer of the exploration
becomes its own concept document: promoted verbatim first, then consolidated.
See `concepts/README.md` for the source line ranges and conventions.
## Extract Conceptual Canon v0.1
## Extract AIPN Concept v0.1
```task
id: ASSEMBLY-WP-0002-T01
@ -30,10 +30,10 @@ priority: high
state_hub_task_id: "12805407-814c-5909-ba99-6938c3f29b09"
```
Extract the AIPN Conceptual Canon v0.1 verbatim into
`canon/ConceptualCanon.md`, with a provenance header.
Extract the AIPN concept v0.1 (originally titled "Conceptual Canon") into
`concepts/AdaptiveInformationProcessingNetworkConcept.md`, with a provenance header.
## Create canon index and conventions
## Create concepts index and conventions
```task
id: ASSEMBLY-WP-0002-T02
@ -42,7 +42,7 @@ priority: high
state_hub_task_id: "e4182d0a-7672-59fd-9753-0a2f4e70b9d0"
```
Add `canon/README.md` listing the canon documents, their status, their source
Add `concepts/README.md` listing the concept documents, their status, their source
ranges in the history file, and the promotion and versioning conventions.
## Promote Membrane Model
@ -55,7 +55,7 @@ state_hub_task_id: "17d0fcac-439c-5091-8936-c3f2da8959c7"
```
Merge the two membrane discussions (IT-integration membrane and membrane as
information filter) into `canon/MembraneModel.md`, v0.1. Cover the
information filter) into `concepts/MembraneModel.md`, v0.1. Cover the
SourceBinding/Evidence concepts, layered membranes (constitutional,
operational, adaptive, ephemeral), and negative space.
@ -69,7 +69,7 @@ state_hub_task_id: "d76809b7-6a6c-52ac-842b-91d982798560"
```
Promote the minimal developmental kernel (birth requirements, metabolic loop,
innate vs. acquired structure, lifecycle, symbiosis) into `canon/SeedKernel.md`.
innate vs. acquired structure, lifecycle, symbiosis) into `concepts/SeedKernel.md`.
## Promote Evolution Model
@ -82,7 +82,7 @@ state_hub_task_id: "2ffe2f19-e5a9-5fb4-a40f-9c9403e53a62"
Promote genotype/phenotype, recombination, the nested adaptation loops,
multi-dimensional fitness, and the constraints kept outside evolution into
`canon/EvolutionModel.md`.
`concepts/EvolutionModel.md`.
## Promote Metabolism Model
@ -95,7 +95,7 @@ state_hub_task_id: "8b2a4b48-cd08-5586-9bf7-9a169fe75f09"
Promote the substrate/nutrient separation, the six substrate layers, metabolic
pathways, waste, and the compact metabolic model into
`canon/MetabolismModel.md`.
`concepts/MetabolismModel.md`.
## Promote Resource Ontology
@ -108,7 +108,7 @@ state_hub_task_id: "e6fbeef5-c13c-5bc6-9512-084f2eb0eb86"
Promote resource accounting vs. ontology, resource classes, conversion
functions, the sentient boundary, and the societal attention control loop into
`canon/ResourceOntology.md`. This is the economic core of the repo.
`concepts/ResourceOntology.md`. This is the economic core of the repo.
## Draft Network Object Model
@ -119,5 +119,5 @@ priority: low
state_hub_task_id: "ec8b650f-5109-5f40-8919-9703b444a4d9"
```
Translate the ConceptualCanon entities into an implementation-neutral object
model, `canon/NetworkObjectModel.md`, as ConceptualCanon.md § 53 proposes.
Translate the AIPN concept entities into an implementation-neutral object
model, `concepts/NetworkObjectModel.md`, as AdaptiveInformationProcessingNetworkConcept.md § 53 proposes.