DDD & Domain Modeling: Using AI to Accelerate Design

Insights from Virtual DDD Meetup

During a recent Virtual DDD Meetup, Staffan, cofounder of Qlerify, showcased how Qlerify uses AI to accelerate domain modeling.

From a simple text prompt, AI generated a CRM process featuring roles such as Salesperson and Sales Manager. The tool automatically generated domain events, placed them on a timeline, and mapped out commands and entities. The workflow was then turned into a Domain Model with Bounded Contexts, from which working API code could be produced.

The session sparked engaging discussions, including a surprise appearance by Eric Evans, the father of Domain-Driven Design (DDD), who asked insightful questions about the tool and its approach.

In this article we'll expand on the video with detailed step-by-step instructions you can follow. Whether you’re an architect, a domain expert, or a developer, Qlerify provides an intuitive and collaborative way to define bounded contexts, aggregates, and commands—helping you accelerate domain modeling and implementation

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Takeaways from Eric Evans’ Discussion

Eric Evans, the creator of DDD, joined the discussion and raised thought-provoking questions. Key takeaways included:

• AI-generated models serve as a powerful starting point but require iterative refinement.
• There is potential for “round-trip engineering,” where updates to the codebase reflect back into the domain model.
• While generic subdomains work well with AI, core domains require more human involvement to capture complex business logic

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