refactor(topics): 멀티 에이전트용 지식 재편 — _Common(공통 기본기) + Domain_* 구조
에이전트 8종(대화형/프로그래머 C·S/디자이너/설계자/기획자/QA/PD/PM)에게 [공통 기본 능력 + 롤별 Specialty] 2층으로 지식을 주입하기 위한 재분류. 문서 내용·포맷은 무수정, 폴더 이동만 (6,372개 문서 수 보존 확인). - Topic_Programming → Domain_Programming (내부 구조 보존) - Topic_Graphic → Domain_Design - Topic_Business → Domain_Product - Topic_General → Domain_General - _Common 신설: Math(구 Topic_Math_Specialty), Reasoning(구 General/From_Thinking & Reasoning), Reasoning_Creativity(구 General/From_창의성), Communication(Poetic_Blog_Writing + From_writing) - 타 도메인의 From_* 폴더는 유지 (출처 표기일 뿐, 이미 도메인에 맞게 분류된 문서) - 빈 폴더 정리 (memory/procedures) - 에이전트→폴더 매핑은 workspace의 .astra/agent-knowledge-map.json (9개 에이전트) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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id: wiki-2026-0508-team-topologies
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title: Team Topologies
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [Team Topologies, Skelton Pais, stream-aligned team]
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duplicate_of: none
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source_trust_level: A
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confidence_score: 0.9
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verification_status: applied
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tags: [team-design, devops, organization, conway-law]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: n-a
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framework: organizational
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---
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# Team Topologies
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## 매 한 줄
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> **"매 4 fundamental team types + 3 interaction modes 의 fast flow 의 organize"**. Matthew Skelton & Manuel Pais (2019) 의 framework — Conway's Law 의 deliberately inverse-leverage. 2026 모던 SaaS scale-up 매 default playbook.
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## 매 핵심
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### 매 4 Team Types
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- **Stream-Aligned**: 매 single value stream (product/feature/customer) 의 own. 매 most teams (~70%).
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- **Platform**: 매 internal services (CI/CD, observability, auth) 의 stream-aligned 의 enable.
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- **Enabling**: 매 short-term coaching (e.g. "help adopt OpenTelemetry"). 매 disband after.
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- **Complicated-Subsystem**: 매 deep specialist domain (video codec, ML inference, payments crypto).
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### 매 3 Interaction Modes
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- **Collaboration**: 매 high-bandwidth, short-term, exploratory.
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- **X-as-a-Service**: 매 platform team의 well-defined API 의 provide.
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- **Facilitating**: 매 enabling team의 coach mode.
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### 매 Cognitive Load
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- 매 team의 cognitive load 의 limit (Miller's 7±2). 매 boundaries 의 set.
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- 매 intrinsic / extraneous / germane load 의 distinguish.
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### 매 응용
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1. Scale-up 50→500 eng — stream-aligned squad 의 split.
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2. Platform team 의 internal-developer-platform (IDP) build.
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3. ML platform — 매 complicated-subsystem (training infra) + platform (serving).
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## 💻 패턴
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### Team API (markdown contract)
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```markdown
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# Team API: Payments Platform
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## Mission
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Provide reliable payment processing API for stream-aligned teams.
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## Services Provided (X-as-a-Service)
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- POST /charge (SLO 99.95%)
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- POST /refund (SLO 99.9%)
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## On-call
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PagerDuty: payments-platform-oncall
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## Interaction
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- X-as-a-Service for stream-aligned teams.
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- Collaboration window: Tuesdays 10-11am for new integrations.
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```
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### Stream-aligned team boundary
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```yaml
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# team-checkout.yaml
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team: checkout-squad
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type: stream-aligned
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owns:
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- service: checkout-api
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- service: cart-service
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- frontend: /checkout/*
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depends_on:
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- team: payments-platform (X-as-a-Service)
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- team: identity-platform (X-as-a-Service)
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oncall: checkout-oncall
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```
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### Cognitive load assessment
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```python
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# Quick survey, 1-5 scale per team
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load_survey = {
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"domain_complexity": 4, # how complex is the business?
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"tech_complexity": 3, # how many techs to master?
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"context_switches": 5, # how many systems do you touch?
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"external_deps": 2, # how many other teams must you coordinate with?
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}
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score = sum(load_survey.values())
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# >15: overloaded, consider splitting or moving deps to platform
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```
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### Enabling team engagement
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```markdown
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# Engagement: Observability Adoption
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Enabling team: SRE-Coaching
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Target: checkout-squad
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Duration: 6 weeks
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Goal: Adopt OpenTelemetry tracing, define SLOs.
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Exit criteria: Team independently maintains SLO dashboard.
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```
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## 매 결정 기준
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| 상황 | Team type |
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|---|---|
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| 매 customer-facing product slice | Stream-aligned |
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| 매 shared infra (k8s, CI/CD) | Platform |
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| 매 short-term capability gap | Enabling |
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| 매 deep specialist (codec, ML kernel) | Complicated-Subsystem |
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| 매 ad-hoc cross-team feature | Collaboration mode (temporary) |
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**기본값**: 매 stream-aligned 의 default. 매 platform team의 too-early formation 의 avoid (먼저 stream-aligned 의 pain point 의 ).
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## 🔗 Graph
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- 부모: [[Conway's Law]] · [[DevOps]]
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- 변형: [[Spotify Model]]
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- 응용: [[Platform Engineering]] · [[Internal Developer Platform]]
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- Adjacent: [[Domain-Driven Design]] · [[Microservices]] · [[SRE]]
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## 🤖 LLM 활용
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**언제**: 매 50+ engineer org 의 redesign. 매 platform team의 charter 의 draft. 매 cognitive load survey 의 analyze.
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**언제 X**: 매 <10 person startup (premature). 매 Conway 의 ignored 매 consulting deliverable.
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## ❌ 안티패턴
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- **Platform-first**: 매 stream-aligned 매 pain 없이 platform 의 build → unused.
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- **Permanent enabling team**: 매 coaching team의 forever 의 stay → "ivory tower".
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- **Component team**: 매 horizontal slice (e.g. "frontend team") — 매 stream 의 cut, hand-offs ↑.
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- **Too many interactions**: 매 every team의 every team 의 talk → 매 N² coordination cost.
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## 🧪 검증 / 중복
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- Verified (Skelton & Pais, "Team Topologies" 2019; teamtopologies.com 2026 case studies).
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- 신뢰도 A.
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — Team Topologies 4-type + interaction modes + Team API |
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