SayPro Documentation of GPT Prompt Outputs and Topic Extraction Results
Purpose:
To systematically record and archive the outputs generated by GPT-powered tools used by SayPro for topic extraction, content creation, policy development, and stakeholder engagement. This documentation supports transparency, quality control, and knowledge management within SayPro’s initiatives.
Key Components:
- Prompt Log
- Record the exact GPT prompt submitted, including date, time, and the user who initiated the request.
- Include the context or purpose of the prompt to clarify its intended use.
- Generated Output Archive
- Save the full text of GPT’s response/output.
- Ensure outputs are stored in a searchable, organized format (e.g., by date, topic, project).
- Attach metadata such as word count, token usage, and version of GPT model used.
- Topic Extraction Results
- Document lists of extracted topics, keywords, or themes generated from prompts.
- Categorize extracted topics according to SayPro’s strategic focus areas (e.g., education policy, stakeholder engagement).
- Include any post-processing or filtering steps applied to the raw outputs.
- Quality Review and Validation
- Include notes on human review of the GPT outputs for relevance, accuracy, and completeness.
- Record any modifications made to the original AI-generated content.
- Identify any limitations or errors found during review.
- Utilization Records
- Document how and where the GPT outputs were used (e.g., reports, policy briefs, engagement materials).
- Note any follow-up actions or decisions influenced by the AI-generated content.
- Access and Security
- Store documentation securely with controlled access to ensure data integrity and confidentiality.
- Maintain version control to track updates or revisions to prompts and outputs.
- Reporting and Insights
- Periodically analyze documented outputs to assess AI tool effectiveness and identify patterns in content generation.
- Use insights to refine prompt design and improve future outputs.
Benefits:
- Ensures traceability and accountability of AI-generated content.
- Supports collaborative review and iterative improvement of materials.
- Facilitates knowledge sharing and reuse of AI outputs across SayPro teams.
- Enhances transparency around AI usage in policy and educational processes.
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