SemanticMind
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SCM case studies · Case study 2 · Original output

Change and regeneration

Change is applied in the semantic foundation and then derived into affected projections and artefacts.

NoteThis projection is a real, unaltered AI output. It was generated by GPT-5.6 Sol based on the semantic model and demonstrates that the method produces working, inspectable results — not only a concept, but a verifiable artefact.

Change and regeneration

When a business rule, responsibility or information requirement changes, the change is first made in the semantic reality — not as an isolated edit of a single document, diagram or program.

AI can then help to:

  • analyse business impact
  • identify affected projections and artefacts
  • propose change alternatives
  • adjust technical implementation
  • update documentation and tests
  • check consistency between business meaning and runtime

Change is no longer treated as disconnected patches across tools. It is organised as the controlled evolution of a shared semantic foundation, with human judgement and approval before release.

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