AI coding agents are exceptionally good at generating boilerplate code, are somewhat effective for business logic, and often produce "AI slop."
Domain-Driven Design was created to manage complexity. Using explicit patterns and a shared language, business logic stays intentional and expressive. Agentic tools default to framework-driven development and anemic models, not Domain-Driven Design.
In this session, we explore how AI coding assistants can amplify good domain design, allowing developers and architects to focus on what matters most: the business logic itself. We begin by live coding ("vibe coding") a solution with minimal guidance, intentionally surfacing common failure modes such as blurred bounded contexts and misplaced business logic. We then introduce a series of Domain-Driven Design "guardrails" that reshape the coding agent's behavior: enforcing clear bounded contexts, leveraging ubiquitous language, encapsulating business logic within expressive models, and maintaining proper separation of concerns. These guardrails become the primary mechanism for steering AI-generated code toward meaningful behavior and evolvable designs.
Attendees will leave with practical, experience-backed techniques applicable to agentic tools such as Claude Code, Copilot, Cursor, and Warp, as well as tool-agnostic patterns for integrating AI coding assistants into a DDD-centric workflow—retaining human ownership of the domain model while leveraging AI for speed and efficiency.