Creativity of Code: Interdisciplinary Design in the Age of AI

This post was originally published on LinkedIn.

Design is more than visual aesthetics. It’s the creation and construction of solutions according to a deliberate plan. In the 1960s, Bruce Archer aspired to create a science of design; and in his Systematic Method for Designers, he very early on identified the disconnect between engineer and [construction] architect - fundamental differences in value and logic.

Whilst Bruce later regretted trying to converge humanities, science, and design; and proposed design as an equal third triad, I think he was onto something. As AI eats and regurgitates parts of design, his original vision is more relevant than ever.

Design as a Discipline (1979); the intersection between science, humanities, and design - his later vision.

Looking more broadly, The Interaction Design Foundation describes design thinking as an iterative, non-linear process that teams use to understand users, challenge assumptions, redefine problems and create innovative solutions to prototype and test. Beyond this, we can recognise service design, organising business resources to improve experiences, or business design, which merges design thinking with strategic planning.

Developers as Designers

As someone deeply involved in data science, architecture and software engineering, I often feel developers and data scientists aren’t fully recognised for their creative contributions. Recently, the term design technologist emerged, describing professionals who bridge design and engineering, typically through rapid prototyping. Yet, this label only scratches the surface. After conversations with Diana Wolfe, and I was inspired to put some of my strong feelings into words, and structure my thoughts.

All technologists inherently practice design: from shaping enterprise and architectural patterns to sculpting clean code and defining clear naming conventions. They frequently envision entire systems mentally, sculpting them with precision toward elegant solutions within complex technical constraints. Despite this creative labour, their artistry often remains invisible - like the vast bulk of an iceberg hidden beneath the water.

Crucially, developers don’t just build software for machines; they focus deeply on end-user experiences. They prototype, iterate, gather feedback (either directly, or mediated through the help of business analysts, and user experience professionals), and rigorously align their outputs with design principles. Software architects similarly combine analytical prowess and creativity to ensure systems are scalable, secure, maintainable, and genuinely user-centric. If we accept design as shaping the world around us, developers are undeniably designers - with technology as their medium, their clay.

The Disconnect Between Strategy and Delivery

Thinking beyond the intersection of design professionals and technologists, we can also see historically there’s been a persistent disconnect between technologists (developers and architects) and strategy or advisory teams. Developers often focus on practical implementation, feasibility, and scalability, while strategists primarily look to market trends, long-term vision, and transformational goals. Without a shared language or mutual understanding, this misalignment can cause friction, inefficiencies, and diluted results.

Today, as AI becomes integrated into virtually every workflow; creative, strategic, and technical; bridging this gap is more vital than ever. We’re no longer in the raw innovation stage but in a phase of widespread AI diffusion. AI adoption is limited by organizational constraints, not technological maturity. Artists now generate music and visuals with tools like Suno and DALL·E. Developers rely increasingly on AI assistants like GitHub Copilot. Across all disciplines, collaboration with AI tools - and each other - becomes essential.

Subject Matter Expertise in the AI Era

To effectively leverage AI, subject matter expertise remains indispensable. The notion of “vibe engineering,” captures this blend of deep professional skill and AI-assisted enhancement - not just vibe coding. Developers who embody this approach use AI to generate clean, maintainable, and scalable code - but the final quality, elegance, and suitability of the output depend on human judgment.

Similarly, creative professionals increasingly employ AI tools to ideate, prototype, and accelerate their work. Yet the strategic, aesthetic, and emotional direction they provide is irreplaceable. Effective AI adoption is not merely about mastering new tools; it’s about redefining how experts from different domains recognise and interact with one another’s unique strengths and forms of creativity - whether technical, artistic, or strategic.

Beauty in Code and Craft

Well-written code isn’t just functional, it can be beautiful. Vikram Chandra compares coding to literature: both require clarity, structure, and expressive depth. Elizabeth Treahy sees parallels between clean code and fashion or fine art, where elegance and beauty lie in simplicity. The influential book Beautiful Code compiles insights from leading developers, reinforcing the idea that their craft involves genuine artistry.

Donald Knuth introduced the concept of “literate programming,” arguing that code should be composed with readability in mind - not merely executed by machines, but appreciated by human readers. Likewise, the Zen of Python articulates this aesthetic philosophy concisely, highlighting simplicity, clarity, and elegance as essential qualities of good design.

Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. Flat is better than nested. Sparse is better than dense. Readability counts. Special cases aren’t special enough to break the rules. Although practicality beats purity. Errors should never pass silently. Unless explicitly silenced. In the face of ambiguity, refuse the temptation to guess. There should be one— and preferably only one —obvious way to do it. Although that way may not be obvious at first unless you’re Dutch. Now is better than never. Although never is often better than right now. If the implementation is hard to explain, it’s a bad idea. If the implementation is easy to explain, it may be a good idea. Namespaces are one honking great idea — let’s do more of those!

Bridging Silos for Innovation

Today’s innovation requires genuine interdisciplinary collaboration. Developers engineer elegant systems; designers infuse emotional resonance; strategists guide vision and direction. However, these roles often remain compartmentalised, each overlooking the creativity inherent in the others.

Historically, great breakthroughs - such as those in computational biology or quantum computing - can result from integrating ideas from biology, physics, and mathematics. This wasn’t a one-off, we need to continue to share our distinct modes of thinking with each other. Organisations must proactively cultivate environments that promote interdisciplinary dialogue, mutual respect, and knowledge-sharing. That integrated approach is how we can be successful.

Recognising Creativity Everywhere

I’m writing this blog because creativity isn’t confined to the arts; every human can be creative. Scientists and mathematicians routinely employ imagination alongside rigorous logic. Abstract reasoning, elegant problem solving, and the spark of innovation are universally human traits, irrespective of domain.

Let’s consciously acknowledge and celebrate creativity wherever it arises. Let’s actively foster cross-functional teams, develop shared vocabularies, and promote mutual appreciation across disciplines. When we genuinely collaborate, leveraging diverse forms of creativity, we create systems and societies, that are more functional, meaningful, beautiful, and human-centred.

Bruce Archer once attempted to unify humanities, science, and design into a coherent whole. While he later stepped back from the ambitious convergence he envisioned, suggesting design be recognised as a distinct equal alongside humanities and sciences, he captured something fundamental: the value in seeing the interconnectedness and creativity across all human pursuits. He was onto something powerful.

In embracing his vision today, in the AI-driven world, perhaps we finally realise the interdisciplinary dream Archer once glimpsed - a world where creativity, logic, art, science, and technology seamlessly support and amplify one another, making something greater than any domain alone.

Let’s recognise creativity wherever it lives. Let’s foster cross-functional teams, shared language, and mutual appreciation.