개요

원천: OpenAI Research Blog 날짜: 2026-04-15 지역: US 계층: L1,L2 신뢰도: 0.88

핵심 내용

Prompt Engineering for Multi-Agent Systems: Context Window and Memory Implications

출처: OpenAI Research Blog 날짜: 2026-04-15 지역: US 계층: L1,L2 | 깊이: detailed 신뢰도: 0.88 | 논제 정합: 0.59

핵심 지표

Effective multi-agent prompting requires 50K+ token context per agent, 5 agents=250K tokens base load

요약

Context inflation per agent drives O(n²) memory cost multiplication in multi-agent orchestration

Vibe Coding Economy 정합성

P5의 Prompt Engineering for Multi-Agent Systems: Context Window and Memory Implications에서 메모리 수요 증폭 메커니즘 제시

마스터 논제 점수: 0.59

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원본: us_015 | 출처 URL: https://openai.com/research/prompt-engineering-multi-agent-context-2026.md

Vibe Coding Economy 정합성

마스터 논제 점수: 0.59

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원본 ID: P5_us_015