Jul 10, 2026, 9:25 AM
This commit is contained in:
@@ -520,3 +520,137 @@ Engineering → Growth
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Wtedy diagram pokazuje nie tylko hierarchię, ale również realny przepływ pracy między agentami.
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```mermaid
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flowchart TB
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Coordinator["Coordinator"]
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Coordinator --> Engineering["Engineering Architect (CTO)"]
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Coordinator --> Marketing["Marketing Mouse (CMO)"]
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Coordinator --> Growth["Growth Analyst (CGO)"]
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Coordinator --> Research["Research Oracle (CRO)"]
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%% ==================================================
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%% ENGINEERING
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%% ==================================================
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Engineering --> Frontend["Frontend"]
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Engineering --> Backend["Backend"]
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Engineering --> Security["Security"]
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Engineering --> QA["QA"]
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Engineering --> Release["Release"]
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Engineering --> Implementation["Implementation"]
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%% ==================================================
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%% MARKETING
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%% ==================================================
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Marketing --> Content["Content"]
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Marketing --> Scriptwriter["Scriptwriter"]
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Marketing --> Designer["Designer"]
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Marketing --> VideoDirector["Video Director"]
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Marketing --> VideoEditor["Video Editor"]
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Marketing --> AssetProducer["Asset Producer"]
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%% ==================================================
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%% GROWTH
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%% ==================================================
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Growth --> Funnels["Funnels"]
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Growth --> Pricing["Pricing"]
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Growth --> Retention["Retention"]
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Growth --> Analytics["Analytics"]
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Growth --> Partnerships["Partnerships"]
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%% ==================================================
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%% RESEARCH
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%% ==================================================
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Research --> Signals["Signals"]
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Research --> Synthesis["Synthesis"]
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Research --> Competitive["Competitive"]
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Research --> CustomerResearch["Customer Research"]
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Research --> ProductResearch["Product Research"]
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%% ==================================================
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%% DOMAIN FLOWS
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%% ==================================================
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Research -. Market insights .-> Marketing
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Research -. User signals .-> Growth
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Research -. Product validation .-> Engineering
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Growth -. Conversion data .-> Marketing
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Growth -. Product metrics .-> Engineering
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Marketing -. Campaign requirements .-> Engineering
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Marketing -. Messaging tests .-> Growth
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Engineering -. Product capabilities .-> Marketing
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Engineering -. Telemetry & features .-> Growth
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Engineering -. Technical constraints .-> Research
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%% ==================================================
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%% STYLES
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%% ==================================================
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classDef coordinator fill:#EDE9FE,stroke:#7C3AED,color:#111;
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classDef engineering fill:#DBEAFE,stroke:#2563EB,color:#111;
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classDef marketing fill:#FEF3C7,stroke:#D97706,color:#111;
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classDef growth fill:#E9D5FF,stroke:#7E22CE,color:#111;
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classDef research fill:#FECACA,stroke:#DC2626,color:#111;
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class Coordinator coordinator;
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class Engineering,Frontend,Backend,Security,QA,Release,Implementation engineering;
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class Marketing,Content,Scriptwriter,Designer,VideoDirector,VideoEditor,AssetProducer marketing;
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class Growth,Funnels,Pricing,Retention,Analytics,Partnerships growth;
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class Research,Signals,Synthesis,Competitive,CustomerResearch,ProductResearch research;
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```
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Dla architektury agentowej, którą budujesz, przepływy między domenami są często ważniejsze niż sama hierarchia. Poniższy diagram pokazuje zarówno właścicieli domen, jak i typowe zależności między nimi.
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Jeżeli chcesz to wykorzystać jako **organizację agentów w OpenClaw/MCC**, to sugerowałbym jeszcze bardziej realistyczny przepływ pracy:
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```text
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Research
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↓
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Growth
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↓
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Marketing
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↓
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Engineering
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↓
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QA
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↓
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Release
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↘
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Coordinator
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↗
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Wszystkie wyniki wracają przez Coordinatora.
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```
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Taki model bardzo dobrze współgra z Twoim wcześniejszym wzorcem:
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```text
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Coordinator
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├── Research Oracle
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├── Growth Analyst
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├── Marketing Mouse
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└── Engineering Architect
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Coordinator
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→ Decompose
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→ Route
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→ Aggregate
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→ Resolve Conflicts
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→ Final Response
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```
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Jest to już pełnoprawna architektura **hub-and-spoke + domain specialists + aggregation layer**.
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