use-case-to-prompt

You can generate AI prompts from a use case by providing a fully reviewed specification to create a structured bundle. This process transforms the use case into implementation, test, and data model prompts, ensuring consistency and traceability across the pipeline.

To ensure traceability between use case steps and generated tests, enforce a deterministic prompt generation process. The generated test prompts require tests to be explicitly named after the use case steps, and postconditions are treated as assertions to align outcomes.

Yes, you can use a single reviewed use case specification to create an end-to-end AI pipeline. The process uses a three-prompt chain to align implementation, tests, and data models, which can be re-used across multiple projects.

Yes, prompt generation from use cases requires a fully reviewed, ready-to-use specification as input. This ensures the resulting implementation, test, and data model prompts are deterministic and align with the overall workflow without ambiguity.

The three-prompt chain for use case implementation works by transforming a single specification into three distinct prompts. It generates structured prompts for code implementation, test generation, and data models while enforcing explicit extensions and treating postconditions as assertions.