This paper advances the Design Science Research (DSR) paradigm by addressing the fundamental challenge of coevolving problems and solutions in dynamic, uncertain, and iterative environments. Although DSR frameworks excel in structured problem-solving, they lack mechanisms to conceptualize problem spaces under high uncertainty. A robust understanding of such spaces remains critical for DSR’s practical relevance. This study introduces an extended conceptualization of the problem space building upon the model proposed by Maedche et al. [1]. We extend the problem conceptualization as a fluid, iterative process in which problems and solutions continuously shape each other through stakeholder-artifact interactions. By integrating theoretical concepts of effectuation and affordances, our model empowers researchers and practitioners to navigate complex, rapidly evolving problem spaces while providing a structured yet flexible approach for iterative problem and solution refinement. We demonstrate the model’s practical application in a real-world DSR project, showcasing its ability to enhance problem-solving in socially and technologically intricate domains. This approach ensures that DSR remains adaptive, responsive, and effective in uncertain contexts.