The article outlines the concept of "What Good Looks Like" (WGLL) as a framework for establishing clarity and quality within teams and organizations. The author shares a personal experience of taking over teams with low confidence and trust issues after layoffs. Faced with inconsistency and misalignment, the teams struggled to define what "good" meant. The introduction of a clear template for a data processing project served as a starting point, establishing a baseline for quality. This template not only defined inputs and outputs but also provided a reference point that could be replicated across various projects and processes. Ambiguity in work creates hidden costs, manifesting as delays and misinterpretations that accumulate over time. As teams grow, differing interpretations of quality lead to inefficiencies. The author emphasizes the importance of making good visible through concrete artifacts like templates and checklists. This visibility helps streamline reviews and onboarding, as everyone starts from a shared understanding. However, establishing a baseline is just the beginning. WGLL should act like a ratchet, continuously raising standards with each improvement, ensuring that the organization evolves rather than reverting to old habits. Ultimately, the effectiveness of WGLL depends on its specific application to different contexts. Vague standards can bleed into unrelated areas, leading to confusion. Each domain requires tailored definitions of "good" to avoid ambiguity. As organizations scale, WGLL must transition from informal conversations to formalized processes that become the default way of working. This transformation involves integrating templates, documentation, and automation, making it easier to uphold quality standards without relying on memory or individual interpretations.