Why does AI struggle with large and messy codebases? Ambiguity, implicit assumptions, and scale break alignment and reliability.
I propose a map-first workflow called LayeredDSL: a structured YAML metamodel defining domain types, business logic, components, UI, workflows, security, and mapping metadata. Think of it as a single source of truth—AI and developers both work from the same map. Once defined, AI scaffolds or validates code deterministically.
Reduces hallucinations
Ensures traceability and alignment
Enables cross-language and cross-service portability.
I propose a map-first workflow called LayeredDSL: a structured YAML metamodel defining domain types, business logic, components, UI, workflows, security, and mapping metadata. Think of it as a single source of truth—AI and developers both work from the same map. Once defined, AI scaffolds or validates code deterministically.
Reduces hallucinations
Ensures traceability and alignment
Enables cross-language and cross-service portability.
Repo is here: https://github.com/AlessandroAnnini/layereddsl Keen to hear from those building real AI‑driven development systems.