In the era of LLMs, writing code has never been faster or more accessible. However, high-speed code production often masks a fundamental risk: subtle misalignment with the business domain. While AI agents excel at generating plausible text, they lack a durable understanding of context, often filling human ambiguity with statistical guesswork.
This session explores why Domain-Driven Design is not just a legacy modeling technique, but the essential "operating system" for successful AI-assisted development. We will dive into how a disciplined Ubiquitous Language acts as a steering wheel, reducing the space for AI misinterpretation and stabilizing the generation process through clear linguistic constraints.
Furthermore, we will examine the synergy between Living Documentation and Specification-Driven Development. How to treat specifications as a "memory bank", a non-negotiable constitution that guides AI agents, and how Living Documentation preserves deep domain knowledge that code alone cannot capture.
Moving from manual coding to language engineering, we will discuss how to build evolutionary architectures that allow teams to stay in the Problem Space longer, ensuring that the software we generate is not just fast, but meaningful.