The Double Diamond model, introduced in 2004, and Design Thinking, popularized in 2008, both emphasized front-loading the process with extensive research and problem definition. This approach was driven by the assumption that building was costly and irreversible, making early exploration crucial. However, the digital age has dramatically shifted these costs. Prototypes can now be created rapidly and affordably, often within an afternoon. This change means the expense now lies not in creation, but in judgment and selection. Traditional artifacts like journey maps and problem statements were insurance against expensive builds that are no longer the primary concern. The cost of AI model queries has plummeted, enabling extensive experimentation. Teams can now build multiple versions of a solution for less than the cost of lengthy debates. This has led to a relocation of the intensive exploration phase to later in the process. Instead of mapping many ideas on walls, teams can now build multiple working prototypes. Ideation workshops and sticky-note exercises, once efficient for generating options when engineering was slow, are now less critical. The real cost is incurred in deciding which of many generated options is valuable. The original Double Diamond assumed a small judgment budget and a large making budget, but this ratio has inverted. The first "diamond" of problem exploration can now be a concise, one-page brief. The second "diamond," focused on solution generation and refinement, now expands significantly. The primary remaining cost is the "judgment budget" – deciding what is good. For industries where building remains expensive and irreversible, like medical devices or hardware, the original front-loading approach still applies, but this is increasingly rare for software. The new model involves a stable outcome, a wide and cheap generation step, and a pre-defined standard of good. This mirrors how software development evolved from extensive specifications to writing tests before coding.