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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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4.8 KiB
id, title, category, status, canonical_id, aliases, duplicate_of, source_trust_level, confidence_score, verification_status, tags, raw_sources, last_reinforced, github_commit, tech_stack
| id | title | category | status | canonical_id | aliases | duplicate_of | source_trust_level | confidence_score | verification_status | tags | raw_sources | last_reinforced | github_commit | tech_stack | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| wiki-2026-0508-nudge-theory | Nudge Theory | 10_Wiki/Topics | verified | self |
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none | A | 0.9 | applied |
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2026-05-10 | pending |
|
Nudge Theory
매 한 줄
"매 choice architecture를 미세 조정하여 freedom of choice를 보존한 채 predictable한 방향으로 행동을 유도.". Richard Thaler · Cass Sunstein의 Nudge (2008) — 2017 Thaler 노벨경제학상. 2026 현재 UX design · public policy · health intervention · LLM safety의 기반 framework.
매 핵심
매 nudge 정의 (Thaler/Sunstein)
- 매 small change in choice architecture
- 매 predictable behavior change 유도
- 매 옵션을 금지하지 않음 (libertarian paternalism)
- 매 economic incentive 거의 없음 (cheap)
매 mechanism
- Default: 매 default option 압도적 영향 (organ donation opt-in vs opt-out — 12% vs 99%).
- Salience: 매 정보 visibility 증가.
- Framing: 매 동일 정보, 다른 표현 (90% lean vs 10% fat).
- Social proof: 매 "X% of users do Y".
- Friction: 매 desired action은 쉽게, undesired는 hard.
매 응용
- UK Behavioral Insights Team — tax letter "9 of 10 pay on time" → 5% 회수율 증가.
- Spotify "Discover Weekly" → 매 default playlist으로 engagement 증가.
- Apple Health — 매 default 7000 step goal로 average +500 step.
💻 패턴
Default opt-in for desired behavior
// BAD: opt-in for 2FA
<Checkbox label="Enable 2FA (recommended)" defaultChecked={false} />
// GOOD: default-on with easy opt-out
<Checkbox
label="Enable 2FA"
defaultChecked={true}
helperText="Recommended. You can disable in Settings."
/>
Friction: confirm destructive action
function DeleteAccountButton() {
return (
<ConfirmDialog
title="Delete account?"
requireType="DELETE my-username" // typed friction
cooldownSeconds={5}
>
<Button variant="danger">Delete</Button>
</ConfirmDialog>
);
}
Social proof nudge
<PricingCard plan="pro" badge="Most popular — 73% of teams choose this" />
Framing — loss aversion
// BAD (gain frame, weaker)
<p>Save $120/year with annual billing</p>
// GOOD (loss frame, stronger; Tversky/Kahneman)
<p>Stop paying $10/mo extra — switch to annual</p>
Salience — progress nudge
function ProfileCompletion({ percent }: { percent: number }) {
return (
<Banner show={percent < 100}>
Profile {percent}% complete — add a photo to reach 100%
<ProgressBar value={percent} />
</Banner>
);
}
Implementation intention prompt
// "When X happens, I will do Y" — proven habit formation
<Onboarding>
<p>When will you exercise?</p>
<Select options={["Morning", "Lunch", "Evening"]} />
<p>Where?</p>
<Input placeholder="Living room, gym..." />
</Onboarding>
매 결정 기준
| 상황 | Approach |
|---|---|
| User benefits from default | opt-out default |
| User must consciously choose | opt-in, no default |
| Discourage harm | friction (confirm, delay) |
| Encourage rare valuable action | salience + reminder |
| Group conformity helpful | social proof |
기본값: transparent default + easy opt-out — 매 dark pattern과의 차별점.
🔗 Graph
- 부모: Behavioral_Economics · Cognitive Bias
- 변형: Choice_Architecture · Habit_Loop
- 응용: Micro-interactions · Gamification
- Adjacent: FOMO (Fear of Missing Out) · Progressive-Disclosure · 매몰_비용_오류_(Sunk_Cost_Fallacy)
🤖 LLM 활용
언제: UX flow 설계, public health/policy, habit-forming product, opt-in/opt-out 결정. 언제 X: high-stakes informed consent (의료, 금융 — 매 explicit choice 필수), regulated decision (legal contract).
❌ 안티패턴
- Dark pattern (sludge): 매 친 user가 아닌 친 vendor — Sunstein 본인이 Sludge (2021)로 비판.
- Hidden default: 매 user 모르게 enable — opt-in의 transparency 무시.
- Manipulation > nudge: 매 deception (e.g. fake countdown) — ethics 위반.
- Over-nudging: 매 모든 화면에 nudge — banner blindness.
- No measurement: 매 A/B test 없이 nudge — direction 불명.
🧪 검증 / 중복
- Verified (Thaler/Sunstein Nudge 2008 / 2021 final ed., UK BIT trial reports, Sunstein Sludge 2021).
- 신뢰도 A.
🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — Nudge theory (Thaler/Sunstein) + UX patterns |