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Designers are increasingly challenged by a constant change of context and the interaction of layers of data from a huge variety of sources, from natural-artificial to human-machine. This research aims at mapping the interrelations of energy problems, bio- and artificial intelligence, and human-machine interaction to reflect and rethink the future of solar design. This paper first discusses its theoretical approach that stands at the convergence of light-harvesting systems, their aggregation and intelligence. Afterwhich, this paper explores their translation into iterative processes between designer and artificial intelligences, which is defined as rule/agent-based and machine learning systems; in particular, the relationship between Cellular Automata, Genetic Algorithm, and Generative Adversarial Networks (GANs) is discussed. Finally, it introduces a design project [email protected]_ - showing the proposed combinatorial pipeline and some preliminary results.