trcc Philosophy Guidlines

I display Creative Computation in Design as a Driver of Innovation

Universities are places of free thinking, learning and innovating. In design education, these potencials are often obscured by a superficial understanding of design, that focuses solely on the surface and whats “visible” or “visual”. Teaching Creative Coding is a contribution to a meaningful and system-level arts and design education.

I Teach the Basics

Almost all programming languages work the same way: Functions, loops, conditional statments and variables are the fabric of any software system. Understanding how these elements work together is the key to unlock the world of designing and systems. That’s why my teaching circulates around these elements. In my curriculum I call them “The Four Pillars”.

Processing and p5.js

A great programming language for Creative Coding has to fulfill three requirements: It must be easy to get started with, it must contain everything important to develop complex and real life applications and it has to offer a wide range of media outputs. Both Processing and p5.js fulfill these requirements better than any other framework.

Self-imposed Limits

Self-imposed limitations are positive, helpful, stimulating to ideas, and full of elegance.

Building Tools

I teach to build simple tools to break dependencies and create alternatives.

Slow is beautiful

If something is slow because it is difficult, it means that I am learning. Friction an slowness are indicators for personal growth.

Demystify Technology

Learning to code means to open the blackbox and practice design on the systems level. Code is the ideal language, to investige, formulate and design systems.

Personal Development First

Learning creative coding is difficult. Just like learning to play the piano. Both can fill a lifetime. Both are deep crafts. Learning a deep craft is a process of becoming. Who we become is the main outcome. The visual output is important too, but for me it’s secondary.

I help my students climb the wall

The first steps must be gentle. In the beginning, when a student feels resonance with the craft, they are vulnerable. This early resonance is like a spark without tinder – bright but fleeting.

I help my students climb the wall. I brace against it, cup my hands to form a stirrup, so the students can step up. Their view, once blocked by the wall, now opens to the wide landscape of the craft.

At that moment, my work is done and I feel deeply fulfilled. But I will always remain a learner myself. My students are my greatest teachers, and their stories are my greatest inspiration.

On Artificial Intelligence

The output of AI is mostly boring, empty and dysfunctional. Its best results are mediocre, its worst results are terrible. The greatest students strive to understand what they are building. They focus on the system and not (just) the output.

We craft resilient and beautiful systems through deep understanding, a well-defined purpose, simplicity, dependecy-awareness and great documentation. But AI bloats systems. In software, in design, in society, everywhere. It makes them complicated, often impossible to debug and fix. A naive view on AI creates one single and unbreakable dependency. It’s like mayrring an LLM.

Nevertheless, in my teaching, I do not actively disencourage my students to use AI. I think it’s important that they make their own experiences and creating spaces for experience and personal development, that’s most important for me in my work.