✨Test-Driven AI Agent Definition (TDAD): Compiling Tool-Using Agents from Behavioral Specifications
📝 Summary:
TDAD is a methodology that compiles AI agent prompts from behavioral specifications using automated testing. This iterative process refines prompts to ensure measurable compliance, preventing regressions and policy violations for reliable production deployment.
🔹 Publication Date: Published on Mar 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08806
• PDF: https://arxiv.org/pdf/2603.08806
• Project Page: https://www.alphaxiv.org/abs/2603.08806
• Github: https://github.com/f-labs-io/tdad-paper-code
✨ Datasets citing this paper:
• https://huggingface.co/datasets/f-labs-io/SpecSuite-Core
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For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#AIAgents #PromptEngineering #TestDrivenDevelopment #AISafety #AIResearch
📝 Summary:
TDAD is a methodology that compiles AI agent prompts from behavioral specifications using automated testing. This iterative process refines prompts to ensure measurable compliance, preventing regressions and policy violations for reliable production deployment.
🔹 Publication Date: Published on Mar 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08806
• PDF: https://arxiv.org/pdf/2603.08806
• Project Page: https://www.alphaxiv.org/abs/2603.08806
• Github: https://github.com/f-labs-io/tdad-paper-code
✨ Datasets citing this paper:
• https://huggingface.co/datasets/f-labs-io/SpecSuite-Core
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#AIAgents #PromptEngineering #TestDrivenDevelopment #AISafety #AIResearch