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
title: Team Topologies
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [Team Topologies, Skelton Pais, stream-aligned team]
duplicate_of: none
source_trust_level: A
confidence_score: 0.9
verification_status: applied
tags: [team-design, devops, organization, conway-law]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
language: n-a
framework: organizational
---
# Team Topologies
## 매 한 줄
> **"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.
## 매 핵심
### 매 4 Team Types
- **Stream-Aligned**: 매 single value stream (product/feature/customer) 의 own. 매 most teams (~70%).
- **Platform**: 매 internal services (CI/CD, observability, auth) 의 stream-aligned 의 enable.
- **Enabling**: 매 short-term coaching (e.g. "help adopt OpenTelemetry"). 매 disband after.
- **Complicated-Subsystem**: 매 deep specialist domain (video codec, ML inference, payments crypto).
### 매 3 Interaction Modes
- **Collaboration**: 매 high-bandwidth, short-term, exploratory.
- **X-as-a-Service**: 매 platform team의 well-defined API 의 provide.
- **Facilitating**: 매 enabling team의 coach mode.
### 매 Cognitive Load
- 매 team의 cognitive load 의 limit (Miller's 7±2). 매 boundaries 의 set.
- 매 intrinsic / extraneous / germane load 의 distinguish.
### 매 응용
1. Scale-up 50→500 eng — stream-aligned squad 의 split.
2. Platform team 의 internal-developer-platform (IDP) build.
3. ML platform — 매 complicated-subsystem (training infra) + platform (serving).
## 💻 패턴
### Team API (markdown contract)
```markdown
# Team API: Payments Platform
## Mission
Provide reliable payment processing API for stream-aligned teams.
## Services Provided (X-as-a-Service)
- POST /charge (SLO 99.95%)
- POST /refund (SLO 99.9%)
## On-call
PagerDuty: payments-platform-oncall
## Interaction
- X-as-a-Service for stream-aligned teams.
- Collaboration window: Tuesdays 10-11am for new integrations.
```
### Stream-aligned team boundary
```yaml
# team-checkout.yaml
team: checkout-squad
type: stream-aligned
owns:
- service: checkout-api
- service: cart-service
- frontend: /checkout/*
depends_on:
- team: payments-platform (X-as-a-Service)
- team: identity-platform (X-as-a-Service)
oncall: checkout-oncall
```
### Cognitive load assessment
```python
# Quick survey, 1-5 scale per team
load_survey = {
"domain_complexity": 4, # how complex is the business?
"tech_complexity": 3, # how many techs to master?
"context_switches": 5, # how many systems do you touch?
"external_deps": 2, # how many other teams must you coordinate with?
}
score = sum(load_survey.values())
# >15: overloaded, consider splitting or moving deps to platform
```
### Enabling team engagement
```markdown
# Engagement: Observability Adoption
Enabling team: SRE-Coaching
Target: checkout-squad
Duration: 6 weeks
Goal: Adopt OpenTelemetry tracing, define SLOs.
Exit criteria: Team independently maintains SLO dashboard.
```
## 매 결정 기준
| 상황 | Team type |
|---|---|
| 매 customer-facing product slice | Stream-aligned |
| 매 shared infra (k8s, CI/CD) | Platform |
| 매 short-term capability gap | Enabling |
| 매 deep specialist (codec, ML kernel) | Complicated-Subsystem |
| 매 ad-hoc cross-team feature | Collaboration mode (temporary) |
**기본값**: 매 stream-aligned 의 default. 매 platform team의 too-early formation 의 avoid (먼저 stream-aligned 의 pain point 의 ).
## 🔗 Graph
- 부모: [[Conway's Law]] · [[DevOps]]
- 변형: [[Spotify Model]]
- 응용: [[Platform Engineering]] · [[Internal Developer Platform]]
- Adjacent: [[Domain-Driven Design]] · [[Microservices]] · [[SRE]]
## 🤖 LLM 활용
**언제**: 매 50+ engineer org 의 redesign. 매 platform team의 charter 의 draft. 매 cognitive load survey 의 analyze.
**언제 X**: 매 <10 person startup (premature). 매 Conway 의 ignored 매 consulting deliverable.
## ❌ 안티패턴
- **Platform-first**: 매 stream-aligned 매 pain 없이 platform 의 build → unused.
- **Permanent enabling team**: 매 coaching team의 forever 의 stay → "ivory tower".
- **Component team**: 매 horizontal slice (e.g. "frontend team") — 매 stream 의 cut, hand-offs ↑.
- **Too many interactions**: 매 every team의 every team 의 talk → 매 N² coordination cost.
## 🧪 검증 / 중복
- Verified (Skelton & Pais, "Team Topologies" 2019; teamtopologies.com 2026 case studies).
- 신뢰도 A.
## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — Team Topologies 4-type + interaction modes + Team API |