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gbrain: sync converted org-mode brain files

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2026-05-26 03:00:48 +00:00
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projects/passepartout/strategy/moats.org
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@@ -3,7 +3,7 @@
:ID: aa6d062e-a520-5d14-8773-00687ed9c689
:ID: 2f783eb4-638e-5afa-9b59-6224d086a712
:END:
#+title: Competitive Barriers — Moats and Infrastructure Lock-in
#+title: Moats
#+filetags: :passepartout:economics:moats:competition:lock-in:switching:
Re-evaluated: time is not the primary moat. A Phase 4+ [[id:28c46769-c14b-42aa-ac7a-69d310157f8f][Passepartout]] fed on Wikipedia + Wikidata can build a general ontology in two weeks. The organic growth advantage collapses for general knowledge.
@@ -11,8 +11,9 @@ Re-evaluated: time is not the primary moat. A Phase 4+ [[id:28c46769-c14b-42aa-a
**Actual moats (weaker than initially assumed):**
1. **Domain-specific gate rules** — thin. A few hundred lines of Lisp data. Write once, trivial to copy. Not a real moat.
2. **Empirical decision history** — every HITL decision is a Merkle fact. A fresh instance has none. Makes *your* instance more valuable but doesn't prevent competition — it's a switching cost, not a barrier to entry.
3. **[[id:45258a2d-1675-562c-9024-5d1eb2f1ea56][Evaluation harness (regression suite)]]** — thousands of test cases accumulated from every bug fix. Cannot be ingested from public data. Strongest residual moat.
4. **Infrastructure integration** — specific Docker compose layouts, Traefik patterns, Authentik configs encoded as gate rules. A competitor's infrastructure is different.
3. **Curated empirical parameter database (provenance store)** — force field parameters, solvation model coefficients, scoring function weights, training dataset descriptors, and validity envelopes accumulated over years of use. Each entry carries a source citation, confidence interval, and validation history. A competitor starting fresh has no curated parameters, no accumulated validation comparisons against experiment, and no community-sourced validity envelopes. This is a data moat that compounds with every deployed instance: each instance contributes new validated parameters and benchmark comparisons to the collective provenance store via the social protocol, making the network's cumulative empirical knowledge increasingly difficult to replicate. See [[id:45258a2d-1675-562c-9024-5d1eb2f1ea56][evaluation harness]] for how the same network effect applies to regression test cases.
4. **[[id:45258a2d-1675-562c-9024-5d1eb2f1ea56][Evaluation harness (regression suite)]]** — thousands of test cases accumulated from every bug fix. Cannot be ingested from public data. Strongest residual moat.
5. **Infrastructure integration** — specific Docker compose layouts, Traefik patterns, Authentik configs encoded as gate rules. A competitor's infrastructure is different.
**Strongest competitor strategy:** Not copying your gate rules — offering the same architecture as a service with their own pre-seeded general knowledge and a consulting engagement to customize gate rules. The AGPL prevents closing the architecture but does not prevent offering it as a service with a customization layer.