A Rude Awakening

I woke up one day and there was an announcement within the company I work with that everyone had to start using AI in their work. Claude Code had become so good recently that entire projects that would take about two weeks or more could now be done in an afternoon. While the biggest impact was meant to be seen in the churning out of code, it wasn’t long before the developers started producing frontends that looked pretty well-designed out of the box.

I lead the design team and it seemed like my entire team’s value was being questioned. When someone attacks you, the natural instinct is always to defend yourself. While I pushed back and pointed out the gaps that were in the outputs produced by Claude, (all true by the way), it was also clear to me that there was going to be a point in time when I would be hard-pressed to find issues with the outputs. The writing was on the wall: Adapt, or die!

The Democratisation of Authorship

So I took a step back and tried to figure out what’s actually going on. Engineers were building frontends. Product managers were producing prototypes. Designers were producing code instead of designs alone. There were even marketing people producing websites. But was the output produced good? No. But will they get better over time? Absolutely.

I still remember the day when I first used a printer. I had to get word processing software on my DOS machine, I think it was a program called Word Star. I used that to write out “Welcome to the Fete!” in the largest font that was possible to produce with it. I then printed it out on this dot matrix printer that I got access to at my cousin’s place and I was amazed by the signage that got printed in about 10 minutes! It was exhilarating. Thinking back on it now, the banner looked pretty bad and it wouldn’t pass any graphic artist standards. But I think the excitement was largely driven by the fact that I could do all this myself without going to a specialist banner maker and paying the “big bucks” for a banner that I couldn’t afford as a 7th grader.

I feel we are at a similar point in time today. The authorship of websites, applications and other software has become democratised. The skill barrier that existed before has largely been taken down. With the advent of courses on YouTube, this was already the trend, but there was still a barrier as one had to still learn to use the tools. Today, anyone who can manage to type, or even talk to a computer can now produce a website or an app if they wished to do so. Exciting as it is to see our ideas come alive, let’s be clear that only the baseline has been raised, not the top-line. AI tools at the hands of an expert would produce much better outputs than someone who doesn’t have that domain knowledge. That gap will always remain. But we need to be careful to assess whether that gap is pertinent.

The 8K Television Argument

The most sold resolution of televisions today is 4K. That’s simply because the eye cannot reasonably distinguish between individual pixels at resolutions higher than 4K. So, 8K, while technically superior, is just not worth the premium as it doesn’t qualitatively improve our lives.

The analogy can be seen in enterprises as well. Based on constraints like time and money, the output that “does the job” produced faster will remain more useful than something superior but takes a lot more to produce. This will inevitably be the case with the outputs produced by AI. They will become good enough in most situations.

So, code produced by designers to create websites or apps will meet that standard. These apps will excel on the design end because it’s a designer wielding the tool and will be good enough on the rest of the fronts.

I use coding as an example skill here, but the argument holds for other domains as well. Marketing, sales, finance, operations, product management, etc. will all be fields in which designers can now participate and contribute to in a bigger way than before. But zoom out and you’ll see that the same is possible by people in other fields too. And that, I think is the larger point to pay attention to here — the lines between functional domains is being blurred.

The Question of Taste

I’ve previously maintained that “Taste” is one human quality that can’t be replicated by AI. But I’ve seen what’s possible with AI tools and don’t hold that position anymore. The short version of the reasoning is that taste is a learnt skill. Design schools are doing this every day. And if it can be taught, AI will learn it.

The slightly longer version of that answer: I understand this is an unpopular opinion and it feels like I am threatening our last stronghold. But wouldn’t you rather know and be prepared for the truth than believing in a comforting lie and being shocked when it turns out not to be true? So let me break it down.

I’ve learnt that taste is a skill that is developed by working on three things:

1. Perception: Being more observant to notice the details others miss, like negative space or colour interactions.
2. Discernment: Knowing why something works. Is it the typography or is it a cultural element?
3. Restraint: Knowing what isn’t necessary.

All of these are things that can be taught. When training humans, you explain the science behind human perception and then expose them to hundreds and thousands of examples — essentially pattern recognition and then they are capable of producing tasteful work. If it is pattern recognition, then we’re in the domain of machine learning and AI. It has been proven time and again that the outputs from these generative engines are indistinguishable from those produced by humans. So, if the output from this is indistinguishable from the human generated version, by definition, it cannot be the differentiator.

Therefore even taste delivered by AI will soon (if not already) hit the “good enough” threshold. While some designers will remain and serve the need here, they will be serving an ever diminishing size of market. And when it comes to UX designers specifically, we’ve got the additional threat of interfaces completely disappearing as agents acting on behalf of uses using other applications solely through Application Programming Interfaces (APIs). This is why I wouldn’t stake my flag on this particular quality in the long term.

Beyond the Function

Intelligence, labour and coordination have been human driven since the beginning of the human journey. With AI, that fundamental idea has changed. They can think, execute and coordinate faster and in some ways better than any human ever. This is going to force companies to reorganise themselves differently and not worry about functional domains.

Jobs that were centred around skill, the domain of “how” something is done, will no longer be around. But this isn’t something that should give us pause. Being a painter in the past meant that they’d create their own paints, starting from the raw materials. They’d make their own canvases, frames and a whole slew of other jobs. It was only after all this that they could paint and express what they wanted to. Painters don’t do that today. Most buy their paints and canvases from a store and focus on the challenge of the blank white space.

Organisations of the future will follow a similar path. We don’t need to do the work of learning different tools, processes and skills. That’s going to be abstracted away. So, when creation becomes easy, there’s nothing to celebrate in the act of simply bringing something to life. The harder question is and has always been the “why” behind it all and we now get to focus on that. We need to go from the brush and the canvas to the very reason for painting at all.

So, we’ve got to stop asking how something should be done and start asking what problem you’re really solving and solve that whether it belongs within the “UX Designer” function or not. Put simply, we’ve got to become entrepreneurs, and that’s the real moat.

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