Test-Driven AI Agent Definition (TDAD): Compiling Tool-Using Agents from Behavioral Specifications
We present Test-Driven AI Agent Definition (TDAD), a methodology that treats agent prompts as compiled artifacts: engineers provide behavioral specifications, a coding agent converts them into executable tests, and a second coding agent iteratively refines the prompt until tests pass. Deploying tool-using LLM agents in production requires measurable behavioral compliance that current development practices cannot provide. Small prompt changes cause silent regressions, tool misuse goes undetected, and policy violations emerge only after deployment. To mitigate specification gaming, TDAD introduces three mechanisms: (1) visible/hidden test splits that withhold evaluation tests during compila...
| Authors | Tzafrir Rehan |
|---|---|
| Primary category | cs.SE |
| Published | 9 March 2026 |
| Last updated at source | 9 March 2026 |
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