AI coding agents are exceptionally good at generating boilerplate code, can be surprisingly effective at producing business logic, and—left unchecked—can produce what is increasingly referred to as “AI slop.”

Domain-Driven Design exists to manage complexity through explicit models and a shared language, keeping business logic intentional and expressive. Agentic tools default to framework-driven development and anemic models, not Domain-Driven Design. The good news is that in an AI-driven development world, DDD provides critical structure and constraints for AI-generated code. In this session, we explore how AI coding assistants can amplify—rather than replace—good domain design, allowing developers and architects to focus on what matters most: the business logic itself.

We begin by live coding (or “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 specific 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.