Innovative design serves as both a precursor and a foundational component in advancing future industries. It is also a key driver in fostering new quality productive forces. To promote innovative design, it is essential to uphold philosophical guidance, abandon the reverse thinking of imitation and follow-up, and shift from isolated technological innovation toward systemic innovation. This approach enhances the independent innovation capacity in critical areas. This study integrates the development trajectory of human civilization to precisely identify the evolutionary patterns of design, and applies systems science theory to analyze the intrinsic logical differences between modern and innovative design. The study finds that innovative design is rooted in an open system that integrates human, machine, and environmental elements. It possesses the capacity to adapt to complex and dynamic contexts. By drawing on a comprehensive knowledge system that fuses explicit and tacit knowledge, it stimulates disruptive innovation at its source. To this end, drawing on the essential reduction method of phenomenology and the process of expert knowledge acquisition, this study establishes a first-principles framework of knowledge phenomenology: knowledge generation‒transition from tacit to explicit‒transition from explicit to tacit‒integration of tacit and explicit knowledge. Based on this foundation, a forward-oriented innovative design framework is proposed: design problem space‒explicit knowledge space‒tacit knowledge space‒innovative solution space. Furthermore, using reverse decoupling based on the function‒behavior‒structure design theory, a predictive framework for disruptive technological innovation is developed: technological problem space‒knowledge base identification‒application scenario prediction‒convergent technology forecasting. This framework enables the integrated advancement of disruptive innovation design as a systems engineering process. Taking humanoid robots as an example, the study establishes a disruptive innovation design framework for humanoid robots and preliminarily validates the rationality of this systems engineering approach. Furthermore, from the three dimensions of science, technology, and industry, this study analyzes the global competitive landscape of future industries and proposes three development recommendations: establishing a research system driven by the bidirectional coupling of artificial intelligence and basic research, strengthening technological research and development in key areas, and improving the knowledge resource sharing platform. To efficiently advance innovative design, three measures can be implemented: establishing and improving forward-oriented design methods for specialized areas; developing categorized technology roadmaps; and strengthening the industrial application of design outcomes, thereby better stimulating national innovation potential and supporting the high-quality development of future industries.