feat(programs): open Domain Knowledge Program v1 — 7-stage production line + per-domain KPI
The real bottleneck is domain MODELLING. Phase B is organized as one program with sub-programs per domain, each run through the SAME 7-stage production line. No new runtime framework, no new module (ADR-009, Freeze v1.0) — only program data + a derived reporting view. - Customer enters by INDUSTRY, not regulation: Industry -> Domain Model -> Requirement Sources -> Requirements -> Capabilities -> ... -> Completeness. - 7-stage checklist identical for every domain (Domain Model / Requirement Sources / Capability Registry / Transition Patterns / Playbooks / Reference Scenarios / Completeness) with per-stage ownership. README generalized to the framework. - Each domain lists typical_requirement_sources + typical_certifications -> pre-onboarding capability HYPOTHESIS (the ETO insight; feeds Company 2A as inferred, never confirmed). - Backlog v1 (by customer value): 1 Industrial Automation, 2 Environmental, 3 Automotive, 4 Medical, 5 Energy. Five domain-definition shells (environmental restructured to the unified shape, law-first preserved). - Per-domain KPI is DERIVED from the real corpus (computed-not-stored; sources modelled / transition patterns / playbooks / reference scenarios), NOT a curated number. Reference suite renders maturity bars: Industrial Automation 43% (3/7 sources) leads, Environmental 0% (work ahead). Backlog (value) and KPI (corpus state) are deliberately separated. - ADR-009: Domain Knowledge Program framework. Honest known refinement: regulation-ID normalization (CRA vs Cyber Resilience Act) aliased in the KPI. 7 program-contract tests (backlog order + industry-first + derived-not-stored), check-loc 0. Knowledge data + ADR + reference harness = non-runtime -> no deploy (ADR-001). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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# Domain Knowledge Programs — from architecture to domains
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# Domain Knowledge Program — the production line for every domain
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**The architecture is stable. From here the value comes from DOMAINS, not more software.**
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The runtime architecture (scope, regulatory map, capability delta, optimization, playbooks, intake,
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production, completeness) is frozen. A new regulatory domain is a **data + knowledge** project that
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extends every existing view automatically — no new runtime framework (see ADR-008, Freeze v1.0).
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**The architecture is stable. From here the value comes from DOMAIN MODELLING, not more software.**
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The real bottleneck is no longer architecture or controls or even „knowledge" — it is **domain
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modelling**. Phase B is therefore organised as ONE program with sub-programs per domain, each run
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through the SAME production line. No new runtime framework (ADR-008/009, Freeze v1.0).
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## The production line (reusable for EVERY domain)
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## The customer enters by INDUSTRY, not by regulation
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A customer never says „explain ISO 9001". They say „I build packaging machines" / „I'm an automotive
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supplier" / „I build parking systems". So the pipeline starts at the industry:
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```
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Regulatory Corpus → Obligations → Capabilities → Transition Patterns → Playbooks → Reference Scenarios → Completeness
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Industry → Domain Model → Requirement Sources → Requirements → Capabilities → … → Reality / Verification
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```
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Each domain delivers the SAME artifacts. Once they land, the existing engines automatically extend:
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Scope · Gap · Capability Delta · Optimization · Playbooks · Reference Scenarios · Regulatory Completeness.
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## The 7-stage checklist (identical for EVERY domain)
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## Law-first (a deliberate ordering)
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Start from the **law**, not from a management system. A management system (e.g. ISO 14001) is NOT
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the domain — it is one possible source state. The customer asks *„welche Anforderungen gelten für mein
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Produkt?"*, not *„wie komme ich von ISO 14001 weg?"*. So the order is:
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```
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Recht → Obligations → Capabilities → (Managementsystem) → Delta
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```
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A management-system→corpus transition pattern is built LAST, once BOTH sides are known.
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## Ownership per stage (coordinate via the board, do not duplicate)
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| Stage | Artifact | Owner |
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| # | Stage | Owner |
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|---|---|---|
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| B1 Corpus + Obligations | legal sources, obligations registry | **Legal Knowledge / Obligation Registry** |
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| B2 Capability Model | new capabilities in the Master Capability Registry | **Compliance Execution** |
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| B3 Transition Patterns | source-state → corpus delta patterns | **Reasoning (Knowledge Acquisition)** |
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| Playbooks | implementation playbooks per capability | **Reasoning** |
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| Reference Scenarios | canonical regression + expected outcomes | **Reasoning** |
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| Completeness | corpus-status registry per domain | **Reasoning / curation** |
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| 1 | **Domain Model** (industry → what world is this?) | Reasoning / curation |
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| 2 | **Requirement Sources** (which regulations/standards/specs apply) | Legal Knowledge |
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| 3 | **Capability Registry** (capabilities the sources require) | Compliance Execution |
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| 4 | **Transition Patterns** (source-state → domain delta) | Reasoning |
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| 5 | **Playbooks** (how to implement each capability) | Reasoning |
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| 6 | **Reference Scenarios** (canonical regression + expected outcomes) | Reasoning |
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| 7 | **Completeness** (auditable coverage per domain) | Reasoning / curation |
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## Programs (planned)
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This is the scaling mechanism: every new domain reuses the same production line; the existing engines
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(Scope, Gap, Capability Delta, Optimization, Playbooks, Reference, Completeness) extend automatically.
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| Program | File | Status |
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|---|---|---|
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| Environmental Knowledge Program | `environmental.yaml` | started (B1 handed off) |
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| Automotive Knowledge Program | _planned_ | — |
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| OT / IEC 62443 Knowledge Program | _planned_ | — |
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| Functional Safety Knowledge Program | _planned_ | — |
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## A domain knows its typical sources → pre-onboarding HYPOTHESIS (the ETO insight)
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Each program is a machine-readable definition (`*.yaml`) consumed by the reference suite to track its
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progress; future sessions flip stage `status` as artifacts land, and the Completeness engine reports
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the domain flipping `unsupported → validated` automatically.
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Each domain definition lists `typical_requirement_sources` and `typical_certifications`. So before
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onboarding, BreakPilot can say „this process world is *probably* present" — as a **hypothesis, not a
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truth**. We don't want to know whether an automotive supplier has ISO 9001 (everyone does); we want
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to know **which company capabilities are therefore probably already present** (feeds Company 2A as
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`inferred`, never `confirmed`).
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## Per-domain KPI — reproducible, not marketing
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Progress per domain is **derived from the Regulatory Completeness Engine + the actual corpus**
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(computed-not-stored): identified requirement sources · modelled capabilities · transition patterns ·
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playbooks · passed reference scenarios · consciously declared corpus gaps. Rendered as a bar
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(`Industrial ███████░░░ 70 %`). These are reproducible quality metrics — no curated numbers.
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## Domain Knowledge Program v1 — backlog (by current customer value)
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| Rank | Domain | File | Typical sources |
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|---|---|---|---|
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| 1 | **Industrial Automation** | `industrial_automation.yaml` | CRA · MaschinenVO · EMV · RED · Data Act · IEC 62443 · NIS2 |
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| 2 | Environmental | `environmental.yaml` | Wasser · Chemikalien · Luft · Energie · Abfall · Produktverantwortung |
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| 3 | Automotive | `automotive.yaml` | IATF · TISAX · UNECE R155/R156 · ASPICE · OEM-Lastenhefte |
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| 4 | Medical | `medical.yaml` | MDR · IEC 62304 · ISO 14971 |
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| 5 | Energy | `energy.yaml` | je nach Zielmarkt |
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The work shifts decisively from software development to knowledge production; the competitive
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advantage now comes from the quality and breadth of the modelled domains.
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