When you use GenAI for coding, you’re now a Code Director.
With GenAI in the production seat, you have to take a step back from hands-on and start directing vision.
I used Gemini Canvas to build, debug, enhance, deploy an API service, and implement a JavaScript function on my blog within a couple hours—I'm not a developer, but a UX Product Designer for 29 years.
A couple of things in play here:
- 👉 Extremely simple features and simple apps are the sweet spot for GenAI Coding
- 👉 The hands-on engineering/coding role gets abstracted into both a UX Design and Director roles
I knew the basics of Git, Netlify, and code injection, but I had zero ability to wire it all up line by line, let alone troubleshoot the defects (including terminal commands on the Mac).
GenAI guided me through configuring each step, auto-generating fixes every time I brought them up (whether specific errors or something didn’t behave as expected), and I was able to guide it to extend the functionality without disturbing the existing features.
The takeaway is while I knew what I wanted the end user experience to be (UX Design), there was no need for me to touch any lines of code (although I did tweak some CSS).
In order for me to affect change, I had to know how to direct the AI and then let it figure out what code to make or change.
It’s like Art Direction, but with code—Code Direction! ✨
My mindset was all purpose-driven and outcome-based so design decisions flowed from that.
Not too different from how I’ve been operating as a Designer for years 😀
As far as the usefulness of GenAI for coding entire apps?
It currently seems plausible for these simple, self-contained functions (although I’m experimenting building a watchOS app with Cursor in the same vein).
I can’t see it scaling in its current state, given all the dependencies in our everyday software. However, when it does scale, it will be another abstraction of what it means to design and engineer software.
