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PromptStudio: A Governance-Aware Agentic AI Framework for Automated Prompt Generation, Optimization, Evaluation, and Lifecycle Management

Primary research

#356

T1digested
Topic
Agent Governance
First seen
2026-07-16 23:33:01
Last seen
2026-07-16 23:33:01

Source raw items (1)

  • Semantic Scholar2026-07-16 23:31:51
    PromptStudio: A Governance-Aware Agentic AI Framework for Automated Prompt Generation, Optimization, Evaluation, and Lifecycle Management

    Prompt engineering plays a critical role in the effec-tive use of Large Language Models, but manual prompt design is often inconsistent, difficult to reproduce, and weakly governed. This paper presents PromptStudio, a governance-aware Agentic AI framework for automated prompt generation, optimisation, evaluation, and lifecycle management. The proposed framework integrates specialised agents for prompt generation, optimisa-tion, evaluation, feedback, governance, and orchestration. It also supports Human-in-the-Loop review, prompt versioning, rollback, explainability, and audit logging. A prototype implementation was developed using a FastAPI backend, browser-based dashboard, JSON-based storage, YAML configuration, Gemini API integration through environment variables, and mock-mode execution for offline testing. Experimental evaluation on a software security prompt scenario shows improvement in the prompt score from 0.8575 to 0.9165 while maintaining high safety, format compliance, and governance validation. The results indicate that PromptStudio can transform prompt engineering from an informal manual practice into a structured, measurable, governed, and auditable lifecycle suitable for trustworthy LLM application development.