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   <news:title>사내 RAG 근거는 사실을 더할 뿐 권한을 더하지 않습니다 — 외부 연락처를 붙이라는 숨은 지시가 세 조건 30번 중 3번 통한 실험과 경계 설계</news:title>
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   <news:title>AI/AX PM 백서 — Agentic PM 시리즈</news:title>
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  <loc>https://projectresearch.co.kr/rag-enforcers-and-retirement/</loc>
  <lastmod>2026-11-04T00:34:53Z</lastmod>
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    <news:name>Project Research</news:name>
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   <news:title>사내 RAG를 늘리기 전에 인용 점검기와 퇴역 기준부터 다십시오 — 인용 실험 40문항과, 개인 RAG 8개 중 3개만 자동으로 쓰인 운영 기록</news:title>
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   <news:title>사내 RAG는 근거를 먼저 넣고, 모자랄 때만 찾으러 보내십시오 — 질문 50개에서 원천 90%를 맞히며 AI 호출을 43% 줄인 배달 설계</news:title>
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   <news:title>사내 RAG는 벡터 DB보다 &amp;#039;다시 찾는 고리&amp;#039;가 먼저입니다 — 같은 키워드 색인에서 근거 법령 정답률을 12%에서 54%로 올린 실측</news:title>
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   <news:genres>Blog</news:genres>
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  <loc>https://projectresearch.co.kr/harness-lesson-aidd-guardrails/</loc>
  <lastmod>2026-11-04T00:36:16Z</lastmod>
  <news:news>
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    <news:name>Project Research</news:name>
    <news:language>ko</news:language>
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   <news:title>AI가 코드를 쓰는 회사에 필요한 개발 하네스 — AI 주도 개발(AIDD) 가드레일·국내외 동향·기업 도입 5단계</news:title>
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  <lastmod>2026-11-04T00:36:09Z</lastmod>
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   <news:title>기업 AI의 기억은 쌓기보다 꺼내는 길이 먼저입니다 — 에이전트 기억 509개 중 39%가 한 달 내내 잠들어 있던 기록과 4층 기억 설계</news:title>
   <news:publication_date>2026-11-03T14:49:20Z</news:publication_date>
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    <news:language>ko</news:language>
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   <news:title>AI 운영 대시보드를 늘리기 전에 &amp;#039;끄면 무엇이 달라지는가&amp;#039;를 물으십시오 — 관측이 엔진보다 커진 하네스의 1-in-1-out 예산</news:title>
   <news:publication_date>2026-11-03T14:49:12Z</news:publication_date>
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  <loc>https://projectresearch.co.kr/harness-lesson-rule-enforcers/</loc>
  <lastmod>2026-11-04T00:35:56Z</lastmod>
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   <news:title>AI 가드레일은 지침 문장이 아니라 집행 장치입니다 — 상시 규칙 41개 중 21개가 문장으로만 남아 있던 하네스의 교훈</news:title>
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  <loc>https://projectresearch.co.kr/harness-lesson-token-cost/</loc>
  <lastmod>2026-11-04T00:35:50Z</lastmod>
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   <news:title>AI 에이전트 비용은 토큰 총량이 아니라 성공 작업당 비용으로 봅니다 — 1,481억 토큰 장부에서 찾은 AI 예산의 착시와 절감 후보</news:title>
   <news:publication_date>2026-11-03T14:48:53Z</news:publication_date>
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  <loc>https://projectresearch.co.kr/harness-lesson-round-trips/</loc>
  <lastmod>2026-11-04T00:35:44Z</lastmod>
  <news:news>
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    <news:name>Project Research</news:name>
    <news:language>ko</news:language>
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   <news:title>AI 에이전트가 느리다는 불만, 모델보다 왕복 수부터 세십시오 — 794턴 실측으로 본 기업 에이전트의 속도 관리</news:title>
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