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-working-backwards
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title: Working Backwards
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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: [PR-FAQ, Amazon Working Backwards, Press Release First]
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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: [product-management, amazon, framework, decision-making]
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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: PR-FAQ Document
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---
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# Working Backwards
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## 매 한 줄
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> **"매 customer 부터 거꾸로"**. Amazon이 1990s 말 정착시킨 product development framework — 매 internal press release 와 FAQ 를 먼저 작성한 뒤 거기서 spec 를 도출. 2026 현재 Amazon, Coupang, 토스 등 product-led org 의 standard discipline.
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## 매 핵심
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### 매 5개 customer question
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1. **Who is the customer?** 매 구체적 segment.
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2. **What is the customer problem or opportunity?**
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3. **What is the most important customer benefit?** (선택 X — 1개)
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4. **How do you know what customers need or want?** (data, interview, signal)
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5. **What does the customer experience look like?** (end-to-end flow)
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### 매 PR-FAQ 구조
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- **Press Release** (1 page): headline, sub-headline, summary, problem, solution, leader quote, customer quote, how to get started.
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- **External FAQ** (1-2 page): customer-facing 의 anticipated Q.
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- **Internal FAQ** (3-5 page): build cost, risk, business model, dependency, metric.
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### 매 응용
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1. New product 0→1 (Kindle, AWS S3 의 origin docs는 PR-FAQ).
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2. Major feature launch 의 alignment.
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3. Roadmap prioritization (PR-FAQ readable → ship-worthy).
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## 💻 패턴
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### PR-FAQ template (Markdown)
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```markdown
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# [Product Name] launches [date]
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**[Punchy 1-line headline]**
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[Sub-headline: 1-2 sentence customer benefit]
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**SEATTLE — [Date]** — Today, [company] announced [product]. [Product]
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solves [problem] for [customer segment] by [solution mechanism].
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> "[Customer quote — specific, emotional, concrete benefit]"
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> — [Persona name, role]
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> "[Internal leader quote — vision]"
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> — [Leader, title]
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To get started, customers can [single clear CTA].
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---
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## FAQ — External
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**Q: How is this different from [competitor]?**
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A: ...
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**Q: How much does it cost?**
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A: ...
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## FAQ — Internal
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**Q: What's the build cost & timeline?**
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A: ...
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**Q: What's the customer #1 success metric?**
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A: ... (single number, owned)
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**Q: What's the biggest risk and how do we mitigate?**
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A: ...
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**Q: What dependencies does this have?**
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A: ...
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**Q: What's the kill criterion?**
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A: ... (numeric trigger to stop)
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```
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### Five-Whys driving from PR back to spec
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```
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PR claim: "Latency under 200ms p99"
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Why? → Customer task abandons at >300ms (data: session log)
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Why? → Cognitive flow break
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Why? → Page reflow during quote refresh
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Why? → Server-side rendering on every poll
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Why? → No client-side delta caching
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→ Spec: implement WS-based delta + client cache. Owner: X. Metric: p99<200ms.
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```
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### PR-FAQ readiness rubric
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```
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| Criterion | Score 1-5 |
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|----------------------------------------|-----------|
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| Headline passes "would I click" test | |
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| Customer quote sounds like real user | |
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| #1 benefit is concrete & measurable | |
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| Internal FAQ has kill criterion | |
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| Dependency list complete | |
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| Metric is single number with owner | |
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Total ≥ 24/30 → ship-worthy review.
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```
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### Inverted backlog prioritization
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```python
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# 매 score = (PR clarity) * (customer benefit magnitude) / (build cost * risk)
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def working_backwards_score(pr_clarity, benefit, cost, risk):
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return (pr_clarity * benefit) / (cost * risk + 1e-6)
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backlog = sorted(items, key=lambda i: -working_backwards_score(**i))
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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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| 0→1 new product | Full PR-FAQ before any code |
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| Major feature in existing product | Mini PR-FAQ (1 page total) |
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| Bug fix / small improvement | Skip — JIRA ticket OK |
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| Stakeholder misalignment | PR-FAQ as alignment artifact |
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| Roadmap prioritization | Compare PR-FAQ readability head-to-head |
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**기본값**: any project >2 engineer-weeks → PR-FAQ first.
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## 🔗 Graph
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- 변형: [[Press Release First]]
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- Adjacent: [[Lean Startup]]
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## 🤖 LLM 활용
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**언제**: PR draft 초안, FAQ Q-set 생성, customer quote persona 생성, 다른 PR-FAQ 와의 consistency check.
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**언제 X**: 매 actual customer voice 의 substitute X — 매 real interview 가 source of truth.
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## ❌ 안티패턴
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- **Solution-first PR**: 매 problem 정의 없이 feature listing — 매 reverse 의 본질 무시.
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- **Vague metric**: "improve experience" 의 X — 매 single number + owner.
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- **No kill criterion**: 매 internal FAQ 에 numeric stop trigger 필수.
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- **PR after build**: 매 retroactive PR — 매 Working Backwards 의 X. 매 build 전에 작성.
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- **Buzzword quote**: customer quote 가 marketing speak — real user transcript 기반.
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## 🧪 검증 / 중복
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- Verified (Bryar & Carr "Working Backwards" 2021, Amazon shareholder letters 1997-, Coupang internal docs).
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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 — PR-FAQ template + readiness rubric |
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