1) Simple CRUD or data-centric systems If the core problem is straightforward data storage and retrieval with minimal business rules: Admin dashboards Basic inventory apps Simple reporting tools DDD adds layers (aggregates, repositories, domain services) without real benefit. 👉 Better fit: Transaction scripts, layered architecture, or even low-code. 2) Stable domains with little change DDD shines when: Rules change frequently Language evolves Domain knowledge deepens If the domain is mature and unlikely to change (e.g., fixed regulatory forms, static catalogs), DDD’s modeling effort doesn’t pay off. 3) Small teams or short-lived projects DDD requires: Shared language Modeling workshops Ongoing refinement For: 1–2 developers Proof-of-concepts Hackathons MVPs with uncertain future …the coordination cost exceeds value. 4) When the domain complexity is low but technical complexity is high Example: Real-time streaming...