Source: NN/g latest articles and announcements
When the cost of adding another AI component approaches zero, teams stop architecting and start accumulating—layering agents, tools, and integrations without rationalizing their interactions or dependencies. The result mirrors the "big ball of mud" antipattern from software engineering: systems that work until they don't, where no one fully understands the failure surface and small changes cascade unpredictably. The underlying problem is economic, not technical. The frictionless cost of AI iteration has outpaced the discipline required to keep complex multi-agent systems coherent.