SDLC stages and practices
AI SDLC splits work into practices: concept, stakeholder requirements, specification, use cases, architecture, testing and documentation.
Each stage contains practical tasks that can be repeated on any product. The goal is to make delivery predictable: same input type, same template, same validation criteria.
- Product concept and success metrics
- Stakeholder requirements
- Requirements specification
- Use case identification and specification
- Domain model
- Traceability matrix
- Architecture model
- Testing model
- Documentation model
These practices make AI useful for real work, because the platform knows what should be created and what quality means at each step.
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