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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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id, title, category, status, canonical_id, aliases, duplicate_of, source_trust_level, confidence_score, verification_status, tags, raw_sources, last_reinforced, github_commit, inferred_by
| id | title | category | status | canonical_id | aliases | duplicate_of | source_trust_level | confidence_score | verification_status | tags | raw_sources | last_reinforced | github_commit | inferred_by | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| wiki-2026-0508-ai-overviews-and-sge | AI Overviews and SGE (Search Generative Experience) | 10_Wiki/Topics | verified | self |
|
none | B | 0.85 | conceptual |
|
2026-05-09 | pending | Claude Opus 4.7 (manual cleanup 2026-05-09) |
AI Overviews and SGE
📌 한 줄 통찰
Google 의 search 의 매 query 의 AI-generated answer + cited source. 매 brand 의 매 click 의 lose, 매 citation 의 gain. Direct answer + structured data + Core Web Vitals 의 critical.
📖 핵심
Evolution
- PageRank (1998): link 의 popularity.
- Knowledge Graph (2012): structured entity.
- BERT / RankBrain (2018+): semantic.
- SGE (2023+): generative answer.
- AI Overviews (2024+): permanent UI.
매 component
- AI-generated answer: top of SERP.
- Cited source: 매 link.
- Follow-up question: chat-like.
- Traditional results: below.
Optimization 의 framework
Visual Hierarchy
- 매 H1 / H2 / H3 의 clear.
- 매 1 question / heading.
- 매 short paragraph.
Direct Answer
- 매 H2 (question) 직후 = 1-2 sentence answer.
- 매 expansion = 다음 paragraph.
- "Inverted pyramid" (journalism).
Schema.org
- FAQPage / HowTo / Article.
- Product / Recipe (specific).
- 매 entity 의 explicit.
Core Web Vitals
- LCP < 2.5s.
- INP < 200ms.
- CLS < 0.1.
→ 매 SGE 의 selection signal.
E-E-A-T
- Experience: 매 first-hand.
- Expertise: credential / qualification.
- Authoritativeness: 매 domain authority.
- Trustworthiness: secure, accurate.
→ Google 의 quality rater guideline.
매 query type 의 SGE behavior
Informational ("How to X")
- AI Overview 가 dominant.
- 매 step-by-step format.
Transactional ("buy X")
- AI Overview 가 less.
- 매 product result.
Navigational ("Tesla home page")
- AI Overview 거의 X.
- 매 direct site.
YMYL (Your Money Your Life)
- 매 strict E-E-A-T.
- 매 medical / financial / legal.
- 매 conservative AI Overview.
Zero-click 의 reality
- 매 user 의 click 의 ↓.
- 매 publisher 의 traffic 의 hurt.
- 매 brand visibility 의 citation 의 trade-off.
매 measurement
Search Console
- 매 query 의 AI Overview 의 inclusion.
- 매 impression / position.
3rd-party
- Semrush, Ahrefs, BrightEdge.
- 매 SGE-specific tracking.
Self-monitor
- 매 important keyword 의 manual check.
- 매 weekly / monthly.
💻 Code
FAQ schema (top citation chance)
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "How does AI Overview work?",
"acceptedAnswer": {
"@type": "Answer",
"text": "AI Overview generates a summary answer at the top of search results, citing source URLs."
}
}
]
}
</script>
HowTo schema
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "HowTo",
"name": "How to bake bread",
"step": [
{ "@type": "HowToStep", "name": "Mix flour", "text": "..." },
{ "@type": "HowToStep", "name": "Knead", "text": "..." }
]
}
</script>
매 page structure (AI-friendly)
<article>
<h1>Topic</h1>
<p>Direct answer in 1-2 sentence (lead).</p>
<h2>What is X?</h2>
<p>Brief definition + key points.</p>
<h2>Why is X important?</h2>
<p>Context + benefit.</p>
<h2>How to use X?</h2>
<ol>
<li>Step 1</li>
<li>Step 2</li>
</ol>
<h2>Common mistakes</h2>
<ul>
<li>Mistake 1</li>
</ul>
</article>
Author bio (E-E-A-T)
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Person",
"name": "Jane Doe",
"jobTitle": "Senior AI Researcher",
"alumniOf": { "@type": "Organization", "name": "MIT" },
"url": "https://janedoe.com"
}
</script>
🤔 결정 기준
| Query type | Strategy |
|---|---|
| Informational | FAQ + HowTo schema |
| Product | Product schema + reviews |
| YMYL | E-E-A-T strict |
| Local | LocalBusiness schema |
| News | Article + freshness |
기본값: Direct answer + FAQ schema + Core Web Vitals + E-E-A-T author info.
🔗 Graph
- 부모: SEO
- 변형: AI-Answer-Engine-Optimization · Generative-Engine-Optimization
- 응용: Core Web Vitals Optimization (INP, LCP, CLS)
- Adjacent: Zero-Click-Search · Knowledge Graph
🤖 LLM 활용
언제: Content website 의 SGE traffic 의 capture. 언제 X: 매 internal app. 매 paid-only content.
❌ 안티패턴
- JS-only render: bot blind.
- Fake schema: penalty.
- Click-bait + AI 의 misalign: low citation.
- No author info: low E-E-A-T.
🧪 검증 / 중복
- Verified (concept).
- 신뢰도 B (Google Search Central, Schema.org).
- Related: AI-Answer-Engine-Optimization (overlap).
🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-09 | Manual cleanup — schema code + E-E-A-T + 결정 |