The building and construction sector is a major contributor to global energy demand and carbon emissions, highlighting the growing need for energy-efficient buildings. Simultaneously, the industry is undergoing a significant transformation, driven by increasing demands for digitalization and standardized practices. As AI and digital tools are advancing at an unprecedented pace, there is a risk of losing the vital connection between buildings and human well-being. This paper explores how generative algorithms can address these challenges by balancing technical optimization, such as energy efficiency, with aesthetic principles. The generative design tool developed, called Daedalus, seamlessly integrates with industry workflows, producing Industry Foundation Classes (IFC)—compliant buildings for Building Information Modeling (BIM) standards. The methodology combines site-specific constraints, multi-objective fitness functions and aesthetic parameters while focusing on computational extensibility. This allows for flexible exploration of diverse building configurations, optimizing multiple objectives to detect energy efficient building shapes in terms of orientation, compactness, natural light, and passive climatization. By incorporating the golden ratio and symmetry, the paper investigates a novel approach for generating aesthetic designs. The results demonstrate the tool´s ability to produce varied, site-responsive designs that align with both environmental and design goals. The algorithm is extendable and flexible for further development. Daedalus is designed for both single buildings and ensembles; however, it can be extended for larger urban developments. This work demonstrates how generative design can be utilized to explore energy efficient building shapes. The results contribute to the development of sustainable buildings from the early design stage, providing a robust framework for future research and practical applications in the workflows of tomorrow’s building projects.