Requirements-centric SDD that adapts the Unified Process for AI: use cases owned by requirements engineers, with code, tests, and docs regenerated around them.
Reviewed 2 days ago · Jul 18, 2026
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Metrics updated Jul 19, 2026 · collected automatically from the GitHub API
Adapts the Unified Process's four phases (Inception, Elaboration, Construction, Transition) to AI-native development. Use cases and entity models — not code — are the durable artifacts, specifying system behavior and maintained by requirements engineers for the life of the system. AI agents generate and regenerate code, tests, and documentation from them, with comprehensive tests protecting behavior across regenerations. Delivered as a Claude Code plugin marketplace: a stack-agnostic aiup-core plus technology-specific implementation plugins.
/requirements — create the requirements catalog (aiup-core)/entity-model — create the entity model with ER diagrams/use-case-diagram — generate a PlantUML system use case diagram/use-case-spec — write a detailed use case specification/reverse-engineer — brownfield entry point: recover AIUP artifacts from an existing codebase/implement — generate the implementation from a use case (stack plugin: aiup-vaadin-jooq or aiup-angular-jpa)/browserless-test, /playwright-test, /spring-boot-test, /vitest-test) lock in behavior before regeneration/reverse-engineer recovers entity models and use case specs from existing code before iteration beginsaiup-angular-jpa), and a companion IntelliJ plugin linking @UseCase-annotated tests to their UC-XXX specsSKILL.md skills installable through Tessl into Codex, Cursor, Copilot, Gemini CLI, and OpenCodeA database management UI for Spring Boot (Java) that retrofitted the AI Unified Process artifact set — vision.md, requirements.md, entity_model.md, and fourteen use-case specs — onto a codebase started in 2022.
Reviewed 13 hours ago
AIUP is the outlier among the frameworks tracked here: it comes from the requirements-engineering tradition (Jacobson-style use cases, the Rational Unified Process’s phase model) rather than from developer tooling. Its explicit critique of other SDD tools is that their specs describe the code — an elaborate prompt discarded once the feature ships — whereas AIUP use cases describe system behavior and outlive any implementation, with tests as the consistency engine that makes regeneration safe. The thing to watch is whether behavior-first specs maintained by requirements engineers survive contact with long-running maintenance better than developer-owned specs do; the public evidence base (two small example apps in the org) is still thinner than the methodology’s enterprise framing.