The petroleum refining industry faces pressure to transform operations toward carbon neutrality while maintaining economic viability. Concurrently, Large Language Models (LLMs) have emerged as powerful tools for knowledge integration and problem-solving across diverse domains. This chapter examines the convergence of these transformative forces, analyzing how LLMs can accelerate the transition toward sustainable refining technologies through prompt engineering methodologies. The analysis explores historical innovation patterns in refining, the emergence of AI-assisted design capabilities, and the potential for accelerating industrial transformation. Key findings indicate that systematic prompt engineering may compress development timelines and enable more comprehensive exploration of solution spaces, though significant limitations regarding validation, technical depth, and epistemological uncertainty must be carefully managed. The framework established here provides the foundation for applying AI-augmented design to complex sustainability challenges while maintaining appropriate rigor and accountability.