According to God of Prompt (@godofprompt) on Twitter, Anthropic engineers utilize the C.O.D.E. (Context, Objective, Details, Examples) framework to structure AI prompts, significantly improving output quality for models like Claude Sonnet 4.5. The approach involves clearly defining the background, explicit goals, detailed constraints, and concrete examples. In a direct test comparing the C.O.D.E. method against conventional prompting, the C.O.D.E. structure delivered a 78% higher relevance score (source: @godofprompt, Jan 24, 2026). For AI industry professionals, adopting this structured prompting method can enhance the quality of AI-generated content, streamline business workflows, and improve task automation. Companies building AI-powered tools can leverage the C.O.D.E. framework to boost the effectiveness of their models in practical applications, leading to higher customer satisfaction and reduced iteration cycles.