Stop focussing on what’s right and design for when things go wrong

When I was studying, one of my lecturers said something that’s stuck with me throughout my whole career. They said “If you’re going to get into this game, you’ll need to get very comfortable with being uncomfortable, most of the time”. What they were referring to was that for a good portion of a design process, you may not know what ‘the final outcome’ looks like.

Add to this the commercial aspect of a deadline and it can become quite a daunting place to find yourself, but then I don’t think any designer got into this game for an easy ride.

The right answer is easier to find than ever

Any decent AI tool can plan a donation journey these days, in seconds. A sitemap, a user flow, the content each step needs, a page structure that follows best practice. Not long ago, that would have taken a few days of workshops, sketches and laying things out in Figma.

That’s genuinely useful, and I’m not criticising it. But it raises an awkward question for anyone who designs for a living: if the machine can get it right, what’s my role?

My thought? Stop focussing so hard on what’s right and turn your attention to what happens when things go wrong.

“Right” is an expectation

AI is good at ‘right’ because ‘right’ is well documented. More importantly, no one praises you or remembers you for getting things right under normal situations; it’s just expected. Millions of checkouts, sign-up forms and service pages have been built, tested, written about and copied. The patterns get averaged, and the average is pretty good these days.

Every agency, freelancer and in-house team has access to the same competent answer. When everyone arrives at the same well-organised donation flow, nobody stands out anymore. The average is built from what usually happens; in reality, people don’t behave like ‘usual’ all the time.

“Wrong” is a moment of hope

Ask the same tool what to do when things break, and things get interesting. AI will technically get things ‘correct’, but emotionally they may well be absent, and not really understanding of the context or situation of either the visitor or the brand.

AI struggles most with the moments that don’t follow a script. Some pages need a single action to dominate, like a crisis line or an emergency appeal. Knowing a call to action should be prominent is easy; making it unmissable without dominating over everything else comes down to a designer’s instinct.

Then there’s the person who doesn’t know what to do. They don’t know what they need, or don’t have the words for it. They aren’t on a journey. They’re stuck.

None of these has a tidy pattern-library answer. They need judgement, empathy and an understanding of the specific people involved. And that understanding comes from talking to them.

It matters more when you’re helping people

Most of our work is for charities, not-for-profits and purpose-driven businesses. A large share of the people visiting those sites arrive at a hard moment. They’re worried, grieving, in debt, unwell, or trying to help someone who might be in one of these situations.

For an online shop, a dead end costs a sale. For a charity, it can cost someone the help they came for, that could be their life. A person in crisis who hits an empty results page doesn’t ‘refine their search’, they leave, and often they blame themselves.

As designers, we embrace the challenge, understanding the uncomfortable truths, and finding unique solutions that answer those challenges; but that’s not something we should expect our audiences to also enjoy. Not knowing what the solution is, and learning to trust you’ll find a solution through your intuition, experiences and process isn’t something we should be expecting people to do at a time of need or failure.

So for us, things going wrong isn’t an anomaly, it’s a core use case. We need to know we’re getting it right when things are going wrong.

Recognition builds trust

People want to be seen and understood. Nobody wakes up thinking of themselves as a “user”, the brands and organisations who are succeeding, recognise this. Their designs make the most important thing to people, obvious.

That kind of care can’t easily be generated. It comes from qualitative, human-to-human research: sitting with people, hearing the words they use, noticing where they hesitate. Of course AI can help you make sense of that research, in the same way it’s helped me write this article, but it can’t do the listening and observation for you, nor can it make the judgement calls you’ll make in the moment, in context.

In summary

AI-assisted design workflows are going to produce a lot of competent, well-structured websites that all behave with familiarity. That’s not a bad thing, we shouldn’t be putting cognitive load on our customers and visitors. The work that truly connects, though, builds trust and becomes memorable, will be the work that knows what to do when things aren’t going right, the work that actually feels like it recognises the visitor’s situation. That’s where human experience is still invaluable and priceless.

As designers, we’ve learned to be comfortable being uncomfortable, however the people we design for shouldn’t be expected to learn the same.

So worry less about getting it right, and get really good at understanding what to do when things go wrong. That’s where people feel seen, and where your work stands out from the mediocre noise.