This article reviews the development and performance of the Extended Linear (ELI) cryocooler models K589 and K591.The focus of this article is the SPRINT development cycle, which emphasizes simulation, risk reduction, and the creation of lean prototypes. Initial simulations used SAGE software to highlight the potential for performance improvements. It provided the groundwork for optimizing the design while keeping dimensions as close as possible to K588/K590. In the next phase, the risk reduction phase focused on mitigating any potential design weak point by performing detailed analysis. These included magnetic flux density evaluations in both DC and AC conditions. The development of lean prototypes has a crucial role in the final phase, allowing rapid iteration and validation of design changes. By streamlining these processes, the SPRINT cycle significantly reduces time-to-market, enabling faster deployment of high-performance cryocoolers in various applications. Additionally, the project life cycle and system engineering principles are explored, highlighting how they contribute to optimizing development speed, product quality and performance. The K589/K591 achieved significant improvements particularly in cooling power while maintaining efficiency. It can reach a steady state working point of 3/4W@120K@71ºC. Those cryocoolers are well-suited for SWaP-constrained applications:It has been optimized to deliver high cooling power with efficient use of energy. By modifying the compressor design the cooler achieves significant cooling performance while maintaining a power-efficient operation.Project life cycle and system engineering play crucial roles in enhancing the effectiveness of a sprint development cycle, particularly in complex projects like this. The project life cycle provides a structured framework that ensures each phase of development is properly complying with the market requirements. By applying system engineering principles, potential issues can be identified and addressed early in the sprint cycle, thus minimizing risks and optimizing the final product. Detailed performance comparisons between the K589/K591 and RICOR’s other linear models are presented, highlighting key variations and their implications for efficiency and reliability.