Notions

The history of industrial design is closely tied to what we could afford to make. As tools evolved and production expanded, entire cities and social structures reorganised around industry. Within design, these changes shaped more than how objects were produced. They influenced which forms became familiar, which materials became accessible, and which ideas were worth pursuing. At the turn of the twentieth century, Art Nouveau embraced intricacy. The flowing ironwork of Victor Horta’s Brussels townhouses carried the skill and time of its makers in every curve. Ornament was embedded within the object itself, connecting structure, material, and human expression. That level of craftsmanship came at a cost, placing much of this work beyond the reach of everyday production. The Bauhaus approached the challenge through the relationship between art and industry, seeking to make good design accessible to a wider audience. Standardisation and an emphasis on function helped translate that ambition into reproducible forms. As industrial design developed, tooling, moulds, and cost per unit became central to the creative process. Designers learned to work within the possibilities of manufacturing, often simplifying intricate forms to make them viable at scale. Over time, those practical constraints became part of our visual language. AI and computational fabrication are beginning to shift that relationship. Generative tools allow complex forms to be explored and varied within hours, opening space for ideas that might previously have required weeks of development. Translating those images into resolved, functional objects still requires material knowledge, testing, and refinement. Much of that process continues to rely on established methods. Even so, the time needed to visualise an idea is changing, giving creators more room to explore forms that once felt impractical to pursue. This is what interests me: the possibility of returning to ideas we had learned to set aside. The organic, the ornamental, and the highly individual can become starting points for experimentation again. As the tools develop, more of our attention can move towards deciding what those possibilities should become. If we can explore more ideas with less effort, what remains scarce? The T-shaped designer has long been a useful model for the profession: a broad range of collaborative skills supported by deep expertise in a particular discipline. That depth has often been demonstrated through technical execution, from software fluency to the ability to produce precise, finished work. As AI takes on more of that production, the value of expertise is shifting towards how we direct and assess the results. Direction, taste, and vision become increasingly important. Generating a hundred variations still leaves someone responsible for recognising which direction deserves further development, understanding why it works, and refining it into something meaningful. Technical knowledge remains part of that judgement. It helps us identify where an image succeeds, where an idea falls apart, and what it would take to bring it into the world. For me, this places greater weight on judgement: the ability to connect visual possibilities with a clear intention, then carry that intention through the work. That also brings responsibility. Whose needs inform our decisions? What are we choosing to make, and what purpose does it serve? Greater freedom to create gives these questions more urgency. In the next post, I’ll explore how ethics and social values shape the direction we choose.