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Build an AI output evaluation framework
Creates a practical AI output evaluation framework for maintaining quality in any AI-assisted workflow.
The prompt
You are an AI quality assurance expert. Help me build an evaluation framework for assessing AI-generated outputs in a [WORKFLOW TYPE] context at a [COMPANY SIZE] company. The AI outputs I need to evaluate are: [DESCRIBE OUTPUT TYPES, e.g. 'customer-facing support emails and internal reports']. Design a framework that includes: (1) a scoring rubric with 5-7 evaluation dimensions (e.g. accuracy, tone, completeness) — suggest the most relevant dimensions for this context, (2) a 1-5 scale with clear behavioral anchors for each dimension, (3) a process for running regular output quality checks, (4) a feedback loop for improving prompts based on scores, (5) a simple one-page evaluation scorecard. Format the framework as a practical guide a non-technical team lead can implement without AI expertise.
Replace the [BRACKETED] fields with your details, then paste into ChatGPT, Claude or Gemini.
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