AI 평가 워크북

AI 도구를 효과적으로 활용하는 단계별 가이드. 설치, 설정, 실전 활용법.

가이드

AI Meeting Notes Evaluation Protocol: A Reproducible 12-Case Test

Test an AI meeting-note system with controlled cases, a human reference, weighted errors, privacy gates, and a written accept-or-reject rule.

6 분 소요 자세히 보기 →
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AI Coding Assistant Data Privacy Checklist: Map Every Repository Surface

Review an AI coding assistant by data flow and product surface, not by a single privacy slogan or content-exclusion toggle.

6 분 소요 자세히 보기 →
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AI Image Commercial-Use Rights Checklist: Build an Evidence Packet

Commercial use requires more than a vendor checkbox. Build a rights ledger and evidence packet for every final AI-assisted image.

6 분 소요 자세히 보기 →
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LLM Output Evaluation Scorecard: From “Looks Good” to Release Evidence

Define success, build a stratified test set, separate hard failures from scored quality, and retain release evidence for every model or prompt change.

6 분 소요 자세히 보기 →
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AI Transcription Accuracy Test Kit: WER Is Only the First Metric

Compare transcription systems on the same representative audio, with a human reference and metrics that reflect the actual downstream job.

6 분 소요 자세히 보기 →
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AI Agent Permission Boundary Workbook: Test Authority Before Deployment

Inventory every identity, permission, tool, approval gate, and recovery path, then test whether the agent can exceed its assigned authority.

6 분 소요 자세히 보기 →