Descriptive models and artifacts
Descriptive models are structured artifacts that represent what the product must do, how it is built and how it is checked.
A descriptive model is a clear artifact that describes part of the system. It can be a requirements model, domain model, use case model, component model, API catalog, test model or documentation model.
Why models matter for AI
LLMs perform better when the context is structured. A model gives names, boundaries, relationships and rules. This reduces guessing and makes generated outputs easier to validate.
- Models are versioned
- Models are linked to each other
- Models can be validated automatically
- Models can be transformed into the next artifact
Plain answer
AI SDLC artifacts are not documents for storage. They are working inputs for the next AI-assisted step.
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