opc-methodology is a structured framework for designing, organizing, and executing AI-driven workflows using prompt-based systems. It focuses on breaking down complex AI tasks into clear stages that improve reliability, reproducibility, and clarity when working with language models. The methodology emphasizes defining objectives, processes, and constraints explicitly, ensuring that AI outputs are guided by structured reasoning rather than vague prompts. It is particularly useful for building consistent workflows in areas such as content generation, automation, and decision support. The framework promotes modular thinking, allowing users to reuse and refine components across different tasks. It also encourages iterative refinement, helping users improve prompt performance through systematic adjustments. Overall, OPC Methodology provides a practical approach to prompt engineering that prioritizes clarity, structure, and repeatability.