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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Antigravity Agent
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---
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id: wiki-2026-0508-strategic-thinking
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title: Strategic Thinking
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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: [Strategic Thinking, Strategy, Engineering Strategy]
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duplicate_of: none
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source_trust_level: B
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confidence_score: 0.85
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verification_status: applied
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tags: [strategy, decision-making, engineering-leadership]
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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: na
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framework: na
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---
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# Strategic Thinking
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## 매 한 줄
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> **"매 long-horizon, multi-step, 매 trade-off 의 reasoning — 매 goal → diagnosis → guiding policy → coherent actions"**. Richard Rumelt, *Good Strategy / Bad Strategy* (2011) 의 kernel. 매 engineering context — 매 architecture choice, tech debt, hiring, platform investment.
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## 매 핵심
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### 매 Rumelt kernel
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1. **Diagnosis**: 매 challenge 의 명확한 정의 — what is actually hard?
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2. **Guiding Policy**: 매 approach — how we'll address it.
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3. **Coherent Actions**: 매 mutually reinforcing concrete steps.
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### 매 strategic vs tactical
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- **Strategic**: months-years, irreversible, enables/blocks options.
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- **Tactical**: days-weeks, reversible, executes within strategy.
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- **Type 1 vs Type 2 decisions** (Bezos): 매 one-way door (strategic) vs two-way door (tactical).
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### 매 frameworks
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- **OKRs**: Objective + Key Results.
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- **Wardley Map**: 매 capability evolution chain (genesis → custom → product → commodity).
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- **Five Forces** (Porter): 매 industry structure.
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- **First Principles** (Musk): 매 axiom 부터 reason.
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- **Pre-mortem** (Klein): 매 future failure 의 imagine.
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### 매 응용
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1. Engineering org strategy (build vs buy, monolith vs micro).
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2. Career planning (5-year arc).
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3. Technical roadmap prioritization.
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## 💻 패턴
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### Pre-mortem template (Markdown ADR)
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```markdown
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# ADR-042: Migrate to Kubernetes
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## Diagnosis
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Current ECS deployment cannot scale to multi-region; deploys take 40min.
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## Pre-mortem (it's 2027, this failed)
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- Team didn't learn k8s; constant outages.
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- Cost 3× higher than ECS.
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- Migration took 18 months instead of 6.
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## Mitigations
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- Hire 1 SRE with k8s background before start.
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- Pilot with 2 non-critical services for 3 months.
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- Define rollback criteria.
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```
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### Wardley Map (text DSL — onlinewardleymaps.com)
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```
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title Engineering Platform 2026
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component User [0.95, 0.50] label [0, -10]
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component Web App [0.85, 0.55]
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component Auth [0.75, 0.70]
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component LLM Inference [0.55, 0.30] label [0, 10]
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component GPU Cluster [0.30, 0.40]
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component Datacenter [0.10, 0.30]
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User -> Web App
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Web App -> Auth
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Web App -> LLM Inference
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LLM Inference -> GPU Cluster
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GPU Cluster -> Datacenter
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```
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### First-principles decision (LLM-augmented)
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```python
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# Use Claude Opus 4.7 for option exploration
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from anthropic import Anthropic
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client = Anthropic()
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def explore_options(problem: str, constraints: list[str]) -> str:
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msg = client.messages.create(
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model="claude-opus-4-7",
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max_tokens=2000,
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thinking={"type": "enabled", "budget_tokens": 8000},
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messages=[{"role": "user", "content":
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f"Problem: {problem}\nConstraints: {constraints}\n"
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"From first principles, list 5 distinct approaches with key trade-offs."}],
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)
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return msg.content[-1].text
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```
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### Decision matrix (weighted)
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```python
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options = {
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"Postgres": {"perf": 7, "cost": 9, "team_skill": 9, "scale": 6},
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"DynamoDB": {"perf": 9, "cost": 5, "team_skill": 4, "scale": 9},
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"CockroachDB":{"perf": 8, "cost": 6, "team_skill": 5, "scale": 8},
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}
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weights = {"perf": 0.3, "cost": 0.2, "team_skill": 0.3, "scale": 0.2}
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scores = {k: sum(v[c]*weights[c] for c in weights) for k, v in options.items()}
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print(sorted(scores.items(), key=lambda x: -x[1]))
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```
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### OKR structure
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```yaml
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objective: Make platform self-serve for new teams
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key_results:
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- 90% of new services deploy without platform team involvement (currently 20%)
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- Onboarding time < 1 day (currently 3 weeks)
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- NPS from internal devs > 50
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```
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### Type-1 vs Type-2 framing
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```markdown
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| Decision | Type | Reversibility | Rigor needed |
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|---|---|---|---|
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| Choose primary DB | 1 | Low | High — involve all leads |
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| Choose CI provider | 2 | Medium | Medium |
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| Choose linter ruleset | 2 | High | Low — just decide |
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```
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### Strategy doc skeleton (Will Larson style)
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```markdown
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# Strategy: Platform Reliability 2026
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## Context
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Outages weekly, MTTR 4hrs, eng team rotates on-call.
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## Diagnosis
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Lack of observability + flaky integration tests + no SLO discipline.
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## Guiding Policy
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Invest in observability and SLO culture before adding features.
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## Actions
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1. Adopt OpenTelemetry across all services (Q1).
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2. Define SLOs for top 10 services (Q1).
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3. Error-budget-based release gating (Q2).
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4. Hire 2 SREs (Q2).
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## Non-goals
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- Multi-region active-active (defer to 2027).
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- New feature work pause: NO — 70/30 split.
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```
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## 매 결정 기준
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| 상황 | Approach |
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|---|---|
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| Long-horizon org/tech direction | Rumelt kernel + Wardley map |
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| Capability evolution planning | Wardley map |
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| Multi-option comparison | Weighted decision matrix + ADR |
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| Risk-laden irreversible decision | Pre-mortem + Type-1 framing |
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| Quarterly execution | OKRs |
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| Novel/uncertain space | First principles + LLM exploration |
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**기본값**: 매 strategic decision → ADR + diagnosis + pre-mortem.
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## 🔗 Graph
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- 부모: [[Decision Making]]
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- 응용: [[Architecture Decision Record]]
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- Adjacent: [[Systems_Thinking|Systems Thinking]] · [[Mental_Models|Mental Models]]
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## 🤖 LLM 활용
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**언제**: option exploration, pre-mortem brainstorming, devil's advocate, summarize long context for diagnosis.
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**언제 X**: 매 final commit decision — accountability 의 human; 매 confidential strategy — privacy concern.
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## ❌ 안티패턴
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- **Goals as strategy**: "be #1" 의 strategy X — 매 goal. 매 diagnosis + policy 의 missing.
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- **Strategy as wishlist**: 매 incoherent action list, 매 trade-offs 의 unstated.
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- **Pre-mortem 의 skip**: 매 surprise failure mode.
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- **Analysis paralysis on Type-2 decisions**: 매 reversible 의 just decide.
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- **Wardley map as drawing exercise**: 매 decision 으로 connect X — 매 useless.
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## 🧪 검증 / 중복
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- Verified (Rumelt *Good Strategy/Bad Strategy* 2011; Larson *An Elegant Puzzle*; Wardley *Wardley Maps* 2018).
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- 신뢰도 B (synthesis from multiple authorities).
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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 — strategic thinking frameworks for engineering |
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