Why Designers Should Welcome AI Prototypes

“I have mocked up something with Claude Design.” It’s a phrase that can send shivers through a UI designer. It feels like the modern equivalent of “Make my logo bigger” or “I want everything above the fold.” And I can understand why.I have encountered designers who are pushing back hard on clients and colleagues creating their own prototypes with AI. But, I think these prototypes can be a gift to designers, provided we help people understand what they are looking at.Why designers are right to be concernedLet’s start by acknowledging that the pushback is often entirely reasonable. When someone has a prototype they can click through, it can look as if the finished product is only a few small tweaks away. The buttons work, the screens look polished, and it all seems rather convincing.Unfortunately, looking finished and being ready to launch are very different things. The prototype may need accessibility work, testing with real users, integration with other systems, and a good deal of attention from designers and devs before it’s ready for the world.If the person who made it assumes all of that has already been taken care of, the designer is left explaining why the “nearly finished” project still needs time and money. I can see why that conversation might make you want to hide under your desk.But, in my experience, fighting a trend like this rarely gets us very far. Clients and colleagues are going to create prototypes whether we like it or not, so we might as well help shape how those prototypes are used.A useful glimpse inside someone else’s headOne of the hardest parts of working with stakeholders has always been understanding what they are imagining. They have expectations about the website or application they want, but those expectations often stay in their heads until we show them a design.Then they know it isn’t quite right, even if they struggle to explain why. We make changes, show them another version, and sometimes find ourselves heading into yet another round of revisions without being much clearer about what they wanted in the first place.A prototype they have created themselves gives us something to discuss from the beginning. They have already spent time exploring ideas and iterating with AI, so we can see the features, content, and interactions they had in mind instead of trying to extract every detail from a vague brief.I would treat that prototype as a functional specification. It can show what someone believes the product should do and give us a starting point for agreeing on scope. It won’t capture every requirement or eliminate changes, but it can expose assumptions earlier and help avoid the sort of scope creep that begins with “I thought that was included.”Of course, a stakeholder’s idea of what users need is still an assumption. We should test those assumptions rather than treating every screen as an instruction to be followed. A functional specification is a starting point for a conversation, not a substitute for user research or design judgment.Change the conversation around the prototypeThe language we use can help set expectations. When someone shares their prototype, try calling it a functional specification prototype and thank them for the work they’ve put into it. They’ve given you something much more useful than a meeting where everybody waves their hands and says they’ll know what they want when they see it.You can then explain what happens next. The prototype shows the proposed functionality and gives the team a shared reference, while the design still needs to be reviewed, tested, refined, and prepared for development. Agree on what is in scope and what remains open before anyone starts planning the launch party.Ask questions about the choices they made. Why did they put that feature there? What were they hoping the user would do next? What happens if the user can’t provide the information the form asks for? These questions help you understand their thinking and uncover problems without making the person feel as if they’ve been sent to the headteacher’s office.If the text is too small or the color contrast looks questionable, you could ask, “Did you ask the AI to check for accessibility? That would be worth doing, and we can review it together.” Of course, an AI check can help identify issues, but it doesn’t replace a proper accessibility review or testing with people who use assistive technology.You can direct criticism at the AI, too. “Claude has a habit of adding those little eyebrow labels above headings, and they aren’t always needed,” is a rather easier conversation than “Why on earth did you put that there?” You’re helping your colleague get more from the tool, while keeping the discussion focused on the design.Give people better tools to work withWe can go further than reviewing whatever the AI produces. We can make it easier for people to produce a better starting point in the first place.If you work in-house, make your design system available to colleagues who are prototyping, so they can give the AI the styles and components it needs to work within your organization’s visual language. Agency designers may not always have access to a client’s system, but where one exists, it is worth asking for it.A collection of components alone won’t do the whole job, though. The AI also needs guidance on when and how to use them. When should it use a checkbox rather than a radio button? When is a dropdown appropriate? What should an error message say, and where should it appear? The more of that thinking you can document, the less you have to rely on the AI guessing.You can provide skills containing UI guidance, too. These might be written for your organization, or you could look at an existing option such as Impeccable, which provides design guidance for supported AI coding tools. Check whether a skill works with the tool your colleagues use before sending them off to install it.And don’t forget the context around the design. Information about your organization, its tone of voice, its audience personas, and the problems people are trying to solve can all help the AI produce something more relevant. A polished interface built around the wrong audience is still going to cause you a headache, however lovely the buttons look.So where does that leave designers?I suspect some of the resistance comes from a reasonable question. If product owners, marketers, and clients can all create prototypes, what happens to the UI designer?For a start, somebody needs to create and maintain the design system, the usage guidance, and the skills that help people produce better work. Those things need to be adapted as the organization and its users change, and designers are well placed to shape them.Then there is the work of making an interface genuinely good. Designers can spend less time translating a vague brief into a first set of screens and more time questioning assumptions, testing with users, improving accessibility, and refining the details. That might mean simplifying a confusing journey or adding the small design delighters that make an experience feel considered.I am not suggesting that every AI prototype will be adequate, or that every team will suddenly give designers more time to polish. But, I do think we have a better chance of influencing the outcome if we engage with the work people are already doing.So, the next time a colleague brings you an AI prototype, thank them and ask them to talk you through it. You might still have to explain why the launch isn’t next Tuesday, but at least you’ll have something concrete to talk about.

I used to go to a lot of conferences. Then COVID happened, and I just... stopped. At first it felt like a win. No early trains. No hotel breakfasts. No lanyard. I could watch the talks online in my slippers.It took me a long time to notice what I'd actually lost. And it wasn't the talks.The best part of a conference was never on stageThink back to the last good conference you went to. I bet the thing you remember isn't a slide. It's a conversation.For me, it goes back to my first conference, @media 2005. At one point they did a sort of live blogroll, asking people who wrote well-known web standards blogs to stand up. They called out PPK (Peter-Paul Koch, whose blog I read every single day) and the guy sitting next to me stood up. The poor man spent the rest of the break being peppered with questions by me.I don't remember a single talk from that day. I remember that conversation. That's what conferences gave us: the chance to turn to the person next to us and ask.Those conversations did something your colleagues can't. Your colleagues are great, if you have them. But they work in the same organization, under the same pressures, with the same blind spots. They can't tell you how things work somewhere else. And a lot of in-house UX people don't have colleagues doing what they do anyway. They're a team of one, or a team of a few.Conferences and local meetups gave us that outside view almost by accident. Now most of us don't go. Budgets got cut. Travel got harder to justify. Meetups quietly fizzled out. And nothing really replaced them.And then the job changed under our feetWhat really worries me is that this is happening at exactly the moment we need each other most.AI has changed how we work, and it's still changing. Someone senior wants everything faster. We're relearning research, design and content in real time. And there's almost no established best practice yet, because it's all so new.I'll be honest. I don't know if I'm doing it right. I'm experimenting with new ways of working all the time, and some of them are brilliant and some are a waste of an afternoon.Take prototyping. I've stopped using Figma for it and now build prototypes in code with Claude instead. It made sense at the time. But Figma has changed a lot since then, and I honestly don't know if I made the right call. I don't have time to try every new way of working. What I'd really like is to ask someone who stuck with Figma how it's going for them. And I don't have anyone to ask.I suspect you're in the same boat. That's a strange position for a whole profession to be in. Everyone reinventing the same wheel, alone, at speed.What I've learned from running a communitySince July 2024 I've run Agency Academy, a community for agency owners and freelancers. We meet on a call every week and chat in Slack between calls.What surprised me is where the useful advice comes from. It's rarely me. It's another member who solved the exact problem last month.Unsurprisingly, for a room full of agency owners and freelancers, the topic that comes up most is winning new work. I thought I had a good handle on that in my own business. Then members started sharing what was working for them. Regular meetups with old clients. Hyper-specific SEO landing pages. Ideas I'd have dismissed as a waste of time if I'd read them in a blog post.But I didn't read them in a blog post. I heard them from people in the same position as me, who'd tried them and could tell me exactly how it went. That's very hard to ignore.That's the hallway conversation, except it happens every week, not once a year.So I'm starting one for in-house peopleIt's called UX Insiders, and I'm launching it in partnership with Smashing Magazine. It's for designers, researchers, UX leads and anyone championing UX inside an organization. Universities, charities, government and companies of every size.Here's how it works:A weekly call every Tuesday, 3:30 to 4:30pm UK time. Bring a problem, a question or a win.A private Slack for the questions that can't wait until Tuesday.Every call recorded with a summary, so you can catch up when you can't make it.It's in-house only, so people can talk openly about their organization without worrying who's listening. You apply first, just so I can check you work in-house. It takes about a minute.Founder places cost £49 a month billed annually (£588 a year) + VAT, for the first 25 members. That's less than most conference tickets before you've booked a train or a hotel, and it lasts all year. It can usually come out of the same training budget too, and you can pay by invoice.Nothing is charged until we launch on Tuesday 5 January. If fewer than 15 people sign up by Friday 11 December, it doesn't go ahead and nobody pays a penny.Apply for a founder placeRun an agency or freelance?Then Agency Academy is your place. Same format: a weekly call every Thursday and a Slack full of people who get it. Members even pass work to each other, which has a habit of paying for the membership.Since I'm offering founder pricing on UX Insiders, it only seemed fair to do something for Agency Academy too. Until the end of October, you can join for £59 a month + VAT, or £49 a month + VAT if you pay annually (£588 a year). That's down from £79 a month, and you keep that rate for as long as you stay.Join Agency Academy at the October priceEither way, find your peopleEven if neither of these is for you, please don't do this job alone. Find a meetup. Start a Slack with three people you trust. Book that conference. The answers we're all looking for right now aren't in a book yet and aren’t being answered by AI . They're in each other's heads.And if you're on the fence about UX Insiders, hit reply and tell me what's holding you back. I read every reply, and your questions will shape how this thing works.

We are doing it all wrong… again.I'm getting serious déjà vu at the moment as I watch organizations attempt to rollout out AI, and to be honest, it is frustrating the shit out of me.Back in 2014, I wrote a book called Digital Adaptation where I talked about the shortcomings in how organizations were approaching digital transformation. This was the time when organizations were finally waking up to the fact that their website wasn't just another brochure and that digital had become essential to all elements of their operation.Digital transformation was never really a technology problem. The technology was the easy part, and most of it was already sitting there waiting to be used. The hard part was that users had changed how they behaved, and organizations were being dragged along behind them, trying to keep up with expectations set by Amazon and Google rather than by anyone in the boardroom. Catching up meant changing culture, processes, and the way people worked, which turns out to be a lot harder than buying a new content management system.AI adoption is the same problem all over again. Yes, there is a shiny new technology involved. But, the thing that will decide whether it works in your organization is people. Not just your users, but your staff too.We appointed a chief electricity officer once, tooIn the book I compared digital teams to the "chief electricity officer" that some companies appointed when electricity first arrived. It made sense for about five minutes, until everyone realized electricity was something every part of the business used and putting one person in charge of it was a bit daft.Today organizations are busy appointing Chief AI Officers and setting up central AI committees. I understand the impulse. It feels responsible, and it gives the board someone to point at when things go wrong. But, AI is going to end up woven into almost every job in the building, and no central team understands the daily work of finance, customer service, and the warehouse well enough to decide how AI should fit into each of them.IT built it, so staff ignored itWe saw what happens when that distance exists with digital. IT designed systems for people they had never met, and when those systems did not work, staff routed around them using their own off-the-books workarounds. The same thing is happening with AI, except the workaround is now a personal ChatGPT account on a phone under the desk.The CEO has had a revelation. Everyone else hasn't.However, not everything is the same. When I wrote the book, it was really aimed at helping digital teams convince management that change was required. Now the direction has flipped. Often it is the CEO who has become the convert, and the rest of the organization is lagging behind.I spoke to the CEO of a cargo airline recently who had binned a reporting project that had been "in production" forever without ever actually being finished. That was because, within days of trying AI, the CEO had working dashboards built with Claude. That is a nice illustration of another point from the book, by the way. Big projects that try to specify everything up front rarely finish, and building, testing, and iterating beats them almost every time.Understandably, that CEO is now evangelical. The problem is that a dashboard for the CEO means nothing to the person processing shipping paperwork. Everyone needs their own revelation about their own role, and you cannot hand somebody a revelation in an all-staff email.Why your staff are right to be nervousThis is where AI differs from digital, and where I see most rollouts fall apart, because your staff are nervous about AI, and understandably so.Is this about replacing me?AI makes every individual employee wonder whether the CEO's enthusiasm is about replacing them. When leadership announces an AI initiative, a lot of staff hear "we are working out how many of you we need." Now, you can reassure them as much as you want, but they have read the same headlines you have.What's in it for me?Then there is the question of what is in it for them. If staff are still going to be sitting at their desks for eight hours but are now expected to produce more, the honest answer is nothing. They take on the learning curve and the risk, and the organization keeps the benefit. I would be reluctant too.Decades of habit don't vanish overnightWe also underestimate what we are asking when we tell people to give up ways of working they have built over decades. That procedural knowledge is a big part of how people see themselves as good at their jobs, so being told a tool can now do it is hardly a neutral message.They are already using it anywayAnd on top of all that, with some people, adoption is already happening without management permission. Plenty of staff are using AI right now to make their lives easier. With these people, the job is less about getting approval and more about catching up with what they already do and making it safe.So what do you actually do about it?Start with the people who already careFirst, start with the enthusiasts rather than the resisters. Every organization has a handful of people who are already experimenting. Bring them together, give them space to share what is working, and let their combined enthusiasm do the heavy lifting.In the book I described an internal conference where staff showed colleagues what they had built, and it did more for adoption than any memo from the top. That works just as well for AI.Make it safe to mess upSecond, make it safe to experiment. That was a big theme in the book, and it matters even more now. Lots of people are afraid to try something different in case they get it wrong, and if your organization has a culture of fear, no amount of memos or shiny new tools will persuade them to play. Playing with new tools is how we learn, so people need to know that a failed experiment will not count against them.Give people time to playFeeling safe is only half of it, though. People also need the time and space to experiment. Most of the staff I meet are so stretched that trying something new feels like a luxury they cannot afford. So, if you want people to explore AI, you have to give them the hours to do it rather than expecting it to happen somewhere between back-to-back meetings.Aim it at the boring bitsThird, frame AI around the parts of the job people hate. Nobody is emotionally attached to reformatting reports or chasing timesheets. At that same airline, a technical writer was convinced AI would replace her, and she became one of its biggest advocates the moment it made the tedious parts of her work faster.Skip the one-size-fits-all trainingFourth, be wary of generic training. I have seen organizations run one-size-fits-all AI sessions aimed at their most resistant staff, and the result was exactly what you would expect. People typed in vague requests, got vague answers, and left convinced AI was rubbish. Garbage in, garbage out.Interfaces matter more than you thinkFifth, pay attention to the user interface. My wife ignored AI entirely until she used Grokbot, which presented it as a team of helpers. Same technology, completely different reaction, which is a reminder that adoption is a design problem as much as anything.Sort out governance (without a committee)Sixth, sort out governance rather than forming another committee. Lock down only the data that genuinely needs protecting, with permissions set at the data layer, and then trust your staff to do the right thing with everything above that. Most people want to do a good job and have no interest in leaking customer data. What they need is a lightweight governance framework that sets out a few clear principles and who is responsible for what, and the responsibility matrix from the book applies almost unchanged here.Don't lock it down until it's uselessFinally, do not lock things down so tightly that AI becomes useless. Yes, sensitive information needs protecting. But, I keep seeing organizations where AI is so restricted that nobody can do anything of real value with it. I am working with a UX team at the moment who want to use AI to build a user research repository, and their Copilot license is so restrictive it will not let them. They are not allowed to bring in any other AI tools without going through a complicated committee process, so the whole idea is stuck, despite management telling them they should embrace AI.Over-locked AI gives you roughly the same result as no AI, except you are still paying for the licenses.So, lock down the data that genuinely needs it, then make it easy for people to get on with everything else, because overdo the governance and you kill creativity and adoption along with the risk.Make sure UX is in the roomIf you work in UX, you have an incredibly important role to fulfill here. I am not suggesting you should be the one leading AI adoption. There are HR issues, technology issues, and strategy questions that sit firmly with senior management, and none of those are ours to own. But, UX should very much be in the room and part of the conversation. After all, UX was born out of human-computer interaction, and AI is human-computer interaction in its purest form. We are now having actual conversations with machines, which is about as close to our core discipline as it gets. We also understand behavior, motivation, emotion, and resistance to change better than most people in an organization, and those are exactly the things that will decide whether AI adoption works. In the book I asked web teams to lead digital change. This time I am asking UX people to make sure they have a voice in it, because I am not convinced anyone else will speak up for how staff actually feel about all this.I am curious whether you are seeing the same patterns where you work. If enough of you are, this might turn into a series, and maybe one day another book, assuming I can stay focused long enough to finish one.I'm thinking about running a deeper workshop on this in January, for anyone who's been handed the job of getting their organization on board with AI. If that sounds useful, just reply and I'll let you know if it happens.It agrees with everything you say, it can't read the politics in your organization, and it won't warn you before you make a mess of that stakeholder conversation. I will.Six coaching packages, newsletter readers only. 4 hours of one-to-one coaching for £660, booked before the end of October. When they're gone, they're gone.Reply to this email to grab one.

As we all know, one of the key characteristics of somebody working in any user focused field is a fascination with people. How they think, what motivates them, how they make decisions. But that fascination should not just be focused on others, we should apply it to ourselves too.It is easy to go through life oblivious to what we are doing and why we are doing it. But as we become more self-aware, we also begin to understand more how others are likely to respond too.As an early adopter of any new technology, I have learned that what I go through when wrapping my head around a new tool is likely to be the experience of others slightly further down the road.This is why I have been particularly interested in my own use of AI, especially relating to using AI to inform my decision making.The contradiction in how I use AII have noticed a contradiction in my behavior when using AI and I suspect it is one that many of us share.When I ask AI about a subject I know little about, I have a tendency to accept its recommendations and responses without question. Meanwhile, if I talk to it about user experience design or conversion optimization, I am much more critical of its responses.I recognize its limitations such as its lack of context, its inability to pick up on subtle signals, and its fixation on one particular approach to the problem. Equally, I am much more aware of its proclivity to agree with me and to be overly confident in its responses.The conclusion is obvious. If I am not impressed by AI's responses on a subject I know deeply, I should not place too much trust in its responses on a subject I know little about. There is no reason to assume it knows more about a subject I am unfamiliar with than a subject I am an expert in.Where AI falls short in the real worldFurthermore, this shows that in truth, AI's real world knowledge is still fairly limited. Sure, it might excel at every benchmark under the sun, but when it comes to the complexities of real world human decision making, it is relatively poor.It doesn't know when to challenge and when to encourage, or when to ask for more information and when to just take action. It cannot make judgment calls or handle internal politics.It is great at presenting options, but it lacks judgment in its recommendations. It can write a set of compelling cases for a subject, but it has no idea which will sway the decision maker.But it has taken me, and I suspect all of us, time to identify the edges of what AI can and cannot do. This has been true of every new technology we have ever invented as a species. We are always exploring the edges of what is possible.Why many people are having a rough time right nowSo, why do I raise this? Well, it is to encourage you that things will get better, because at the moment many people are not having a good time.Take for example a member of the Agency Academy who was telling us about a meeting she had recently where the client was validating everything she said with Claude. Or others who have had their work picked apart by an AI.Then, of course, there is the naive belief of some executives that AI allows them to avoid recruiting or even to lay people off.Heck, I am even feeling the impact myself. The amount of coaching I have been doing has plummeted because of AI. Why hire a coach when you can just ask AI?Why I am not worriedBut I am not really worried about that. I am not worried, because I know it will pass, and it already is beginning to.Like us early adopters, who have begun to identify the edges of what AI can do, everybody will eventually come to the same understanding.In time, people will begin to trust the judgment of AI less than they trust the experts. They will realize that AI is most effective when it is used by those experts.The desktop publishing lessonApologies if you have heard me tell this story before, but when I was at university, desktop publishing became a thing. There was panic among those of us studying graphic design because suddenly anybody could create a flyer, brochure or poster. Why hire a graphic designer when you can just do it yourself?And indeed, for a while it was tough, but in time people realized that although they had an amazing new tool, it didn't replace an expert. After one too many posters with Comic Sans and clip art, people realized that they needed a graphic designer.Be patient, and watch your own hypocrisySo I would encourage you to be patient as people work out the limitations of AI, and to be aware of your own hypocrisy. You cannot get annoyed at people for using AI rather than trusting you, when you then use AI in the same way in other fields rather than asking an expert.Don't get me wrong, people won't stop using AI, and I am not expecting my coaching levels to ever return to what they were before. But I am confident that in time people will realize that AI doesn't replace human judgment, understand the complexity of a work environment, or tell you when you are the problem, which trust me, I will do.

Most of my clients come to me with a problem. These can be wide ranging from “we are seeing large churn in our app” to “we cannot get stakeholders to sign off on vital UX work”. They are sometimes expressed as a user need such as “we need to make it easier for users to do X” or as a business need such as “we need to increase the number of users who sign up for our demo”. Or sometimes just a scream of frustration! Whatever the case, the ability to diagnose the root causes of these problems and address them is a core part of my role and, I would argue, the role of anybody who is working in digital.Whether you are a product manager, UX designer, developer, marketer or business owner, the ability to troubleshoot these kinds of challenges is essential to being successful in your role.Fortunately, no matter the trouble that needs ‘shooting’, there is an approach you can use to resolve the challenge. Admittedly, it takes practice, experience and nuances that are far beyond what I can cover here. However, hopefully I can at least point you in the right direction.So, let’s take a real challenge that I often encounter and work through the process I use to troubleshoot and resolve it.Our example challengeThere are so many possible challenges I could use, but let’s pick one I hear all the time from marketing teams. They are running ad campaigns and yet they are seeing low conversion rates. They want me to help them understand why users are not acting and work out how to fix it.Well, whatever the challenge is, the first step is to diagnose the problem.Diagnosing the problemObviously that is easier said than done. But, normally I start by brainstorming a list of possible causes. For example, in this case, I might consider the following:The ads are targeting the wrong audience.The ad copy is not compelling enough.The landing page is not converting.Conversions are not being properly tracked.The post landing page experience is flawed in some way.The list could go on, but you get the idea.Narrow the fieldNext we need to identify which of the possible causes is the most likely to be the primary issue. Of course, it could be a combination of a few, so we need to bear that in mind. Problems are rarely black and white.We can do this with good old fashioned research. We might look at the analytics data, carry out user testing or run a survey. The idea is to find supporting evidence that the problem is real and that it is the right one.Once we are fairly confident that we have the right diagnosis, we need to zoom in on exactly the nature of the problem.Get specific about the problemLet’s say for example that the problem turns out to be the landing page experience. Ads are well targeted, but the conversion rate on the landing page is low.Well, what exactly is the problem with the landing page experience? Is it the design, the copy, the call to action or something else?Identifying this might be done through years of experience, research or user testing. However we do it, we need a specific diagnosis before we proceed.Now, at this point, most people will jump into fixing the problem, but that would be a mistake. Before doing that we need to ask, why that problem exists in the first place.Understanding why the problem existsI mean think about it. Is there a marketer on the planet who doesn’t know that a campaign will underperform if the landing page experience is poor?It’s easy to assume that the cause is incompetence, but that is rarely the case. Often there are underlying issues that have prevented the problem being addressed.For example, the solution might be to have customized landing pages for each campaign. But there are often barriers that prevent this. Barriers like:A lack of design and development capacity.No template that can be used.An overly restrictive template that cannot be customized for a specific campaign.A lack of time to produce multiple landing pages.Technological limitations.Legal or compliance issues.Again, I could go on.**Identifying these blockers is the most important part of troubleshooting. **Giving them a new beautiful landing page will not fix the problem if they cannot use it. Your solution has to be practical within the constraints of the real world or you need to at least be able to make a compelling case for why these barriers have to be addressed.Addressing the barriersThis is where you need to get creative. Ideally you want to circumvent the barriers, rather than try to overcome them. This will prove far more successful and faster to do.For example, it is not going to be easy to get more design and development capacity or replace the tech stack.Circumventing the barriersInstead, you need to look for workarounds that will get people 80% of the way there, even if it is not perfect. In the case of our landing pages, that might be to create a landing page playbook that teaches AI and marketers how to easily create high converting landing pages in minutes. A playbook that takes into account the constraints within which the organization operates.In fact, this is such a common scenario I have a packaged approach to do exactly this. This is so much more effective than some report telling people everything that is wrong or a prototype showing best practice, because they don’t address the underlying barriers.Of course, you cannot always circumvent the barriers. Sometimes they need to be overcome.Overcoming the barriersI came across this scenario recently. I recommended to a large charity that they needed customized landing pages for their fundraising campaigns. Unfortunately, their tech stack just didn’t allow for it without significant development investment and it just wasn’t a priority.My job therefore was to make it a priority. I had to build them a business case that showed this was a job that should be done and done soon.Step one was to gather evidence that the limitations of their tech stack were causing the organization real damage. We did that by running a test campaign with a custom landing page that did not use their tech stack.This was easy enough to spin up with the help of AI, despite still plugging into the existing tech stack for the actual donation.We tracked the number of people entering the donation flow and compared it to the numbers from previous campaigns. The uplift was significant.Despite poor tracking of average donation amounts, and lifetime value of donors, we were able to make some estimates about the financial impact of the improved landing page. Or put another way, we were able to estimate how much the barrier (existing tech stack) was costing the organization for each and every campaign they ran.These figures, alongside our proof of concept test, could be rolled into a business case alongside a small ask that the fundraising team be allowed to create landing pages separately from the existing tech stack, until resources were available to fix the issue.Notice I didn’t suggest the whole tech stack should be replaced. Neither did I demand development resources should be allocated immediately. Instead I suggested a small, temporary solution that would allow the organization to recover the money lost to the tech stack.Checking you actually fixed anythingSo, you have a solution that survives contact with the real world. But, that is not the end of the job.Yes, this is the point where everybody wants to move on, and I understand why. The fix has shipped, the pressure is off, and there is always another problem waiting. But, if nobody goes back to look at the numbers, you have no way of knowing whether you diagnosed the problem correctly or simply got lucky. You also throw away the evidence that would have made your next business case much easier to win. So, agree up front what you are going to measure and when you are going to look at it again.In our landing page example that might be the conversion rate per campaign, the point where people abandon the page, or the number of campaign pages the team manages to produce in a month. Pick 1 or 2 numbers, write down where they sit today, and put a date in the diary to revisit them. If the numbers have not moved, you have not solved the problem, you have only relocated it.The questions, in orderIf you take nothing else from this, take the order of the questions.What do we think the problem is?What evidence do we have that it is the real problem?What exactly about it is broken?Why has nobody fixed it already?Can we go around that barrier, or do we have to knock it down?How will we know whether it worked?Yes, most of us can answer question one in our sleep. But, the value sits in questions four and five, and those are the two it is easy to skip on the way to a nice slide deck of recommendations.A slower way of working, and worth itI am not going to pretend this is quicker than firing over a list of improvements. It isn’t. It involves awkward conversations about why the obvious fix has been sitting undone for 3 years, and those conversations are rarely fun.But, advice that nobody can act on is just an expensive opinion, and I have written more of those than I care to admit.It is also difficult when you work in-house. There are politics and hierarchies to navigate. That is where getting some outside help can make a difference. They sit outside of those structures and tend to be seen as more impartial.So if you are struggling with a barrier that needs to be circumvented or a problem that you just cannot solve, give me a shout.

I've sat through plenty of meetings where someone made a genuinely good case for UX work and got precisely nowhere. On more than one occasion in the past that someone was me. I have found myself standing in front of a slide covered in personas while the finance director quietly lost the will to live. The work was solid, my arguments were rubbish. But over the years I have learned. You see, most in-house teams lose this argument because they make the case for UX in the language of UX, to an audience that has never once been rewarded for caring about it. So senior managers nod politely, agree that it all sounds very interesting, and then fund the project that turned up with a number attached to it. So I want to walk through how you build a business case for UX work based on my years of mistakes. I am not necessarily talking about a formal document with a cover sheet and an approvals matrix, but any argument solid enough to get the work you need signed off. Nobody cares about UX as much as you do And why would they? You don't care about health and safety, and you'd glaze over inside 30 seconds if the accounts team started walking you through their reconciliation process, however lovely their diagram. Everybody has their own patch and defends their own patch, and UX happens to be yours, which means the translating is your job rather than theirs. That means selling UX rarely involves talking about users at all, which I admit feels like a small betrayal of everything we bang on about at conferences. Yes, talking about users is how we do the work. But, talking about business risk and opportunity is how you get permission to do the work in the first place. Risk for the comfortable, opportunity for the hungry A good business case leads with the risks and opportunities your proposal addresses, and the framing you pick depends enormously on the mood of the organization you happen to work for. If you're in a big, established, comfortable business, the risk of doing nothing is your strongest card, because these organizations have plenty to lose and a deep institutional fear of losing it. Talk about customers drifting to competitors with a better signup process, or support costs climbing because the website can't answer a simple question. If the business is newer and hungrier, flip it around and sell the upside, because nobody in a fast-growing company is lying awake worrying about protecting what they already have. There the conversation is about the sales you could win, the markets you could reach, and the growth currently leaking out of a checkout nobody has looked at properly. Work out who you actually need to convince Before you write a word, get clear on whose signature you need, what that specific person is measured on, and how your proposal makes their year easier. Business goals are useful, but personal goals are what get budget released, and the person approving your work has targets, a boss, and a nagging worry of their own. The emphasis shifts depending on where you work, and in my experience it breaks down roughly like this: Commercial businesses. Pick either customer acquisition or retention and build the case around one of them rather than gesturing at both. Government and public sector. Focus on reducing risk, avoiding the sort of failure that ends up in the press, and improving the profile of the service. Charities and non-profits. Talk about fundraising, supporter engagement, and building the profile of the cause. But, cost savings work almost everywhere, and they're badly underused by UX people who would rather talk about delight. Fewer support calls, less staff time spent on manual workarounds, and fewer expensive rebuilds are all things a CFO understands without any translation from you. Use numbers, even wobbly ones Wherever you can, tie your case to hard figures, and don't let the fact that they're estimates stop you. Be honest that they're estimates, explain the assumptions behind them, and offer to do a more detailed analysis if the decision hinges on it. A rough number invites a conversation, while no number invites a polite no. If the maths makes you nervous, I built an ROI calculator that does the heavy lifting for you, so you can walk in with something more persuasive than a strong feeling. Beyond the numbers, get people excited about what's possible, because approval is an emotional decision dressed up in a spreadsheet. Vibe code a rough prototype, mock up the improved journey, or build something shiny that stakeholders can see and immediately want. I've watched a scrappy 2 day prototype do more for a business case than 40 pages of analysis ever managed. What goes into the case Strip away the formatting and every decent business case answers the same handful of questions: The diagnosis. What's the problem or the opportunity, described in business terms rather than UX ones. The work. What you're proposing to actually do. The objective. What success looks like, and how you'll know you got there. The evidence. What research, data, or experience supports your case. The practicalities. What needs to happen, in what order. The resources. What you need in people, time, and money. The first step. One small, well defined thing you can start on now. Ask for less than you want Those last two points are where most business cases die, usually because they ask for too much in one go. Focus on reallocating resources you already have rather than requesting new money, especially at the start, because moving a designer onto a project for 3 weeks is a much smaller decision than approving a budget line. Don't ask anyone to sign off on the whole plan either. Build momentum with a small first step, whether that's a prototype, a limited pilot, or a focused piece of research, and make sure it's something you can deliver quickly so people see progress while they still remember agreeing to it. Then define, up front, what results would justify committing to the rest, so the next conversation becomes a matter of pointing at evidence everyone already agreed would be convincing. None of this is as satisfying as being handed budget because the work is obviously the right thing to do, and I spent years waiting for that to happen. It never did, so I learned to talk about money instead, and the UX work finally started getting approved. If you've got a case to make and no idea where to start with the figures, I can actually help with the process. You can learn more here.

I spent a good chunk of my career insisting that proper UX work should only be done by proper UX people, and I told myself that was about protecting quality, when honestly a fair amount of it was about protecting my own job description. I would sit in a meeting, watch a product owner sketch a screen on a whiteboard, and feel a small internal wince, as if they had wandered into my kitchen and started rearranging the crockery. It felt professional at the time. It was territorial, and it has not aged well. These days I find myself telling clients something that would have horrified younger me. If you want better digital products, the answer probably isn't sending more work through your UX team. It's changing what you employ them to do. Everybody is designing now, whether you sanctioned it or not You have almost certainly seen this happening inside your own organization. Somebody without design in their job title describes an idea to an AI tool and comes back a few hours later with a clickable prototype, realistic content, passable copy, and a flow that mostly hangs together. Developers are generating interface options before the ticket is even refined. Marketers are building and testing their own landing pages. Product owners are turning a rough thought into something demonstrable over a lunch break. Some of that work is genuinely good. Some of it is a small mountain of plausible looking rubbish that nobody has the expertise to spot. All of it is happening whether the design team blesses it or not, and it happens fast, which means it usually arrives before anyone thinks to involve them. Cutting the design team is the obvious response and the expensive one I understand the temptation. The team is expensive, the tooling has made production cheap, and somebody senior is asking what the return on all that research actually is. So the headcount that leaves doesn't get replaced, the budget line gets trimmed, and the design team's seat at the table quietly becomes an invitation to comment on decisions after they have been made. What you lose in that trade is judgment, and it shows up about two quarters later. Every team invents its own version of the same pattern, so the product starts to feel like it was assembled from three different companies. Accessibility problems accumulate because generated interfaces look fine and fail quietly. Decisions get made on assumption rather than evidence, so you build things nobody wanted and only find out after launch. Rework becomes the largest hidden line in your delivery costs, and nobody attributes it to the design cut that caused it. The organizations getting this right aren't the ones with the biggest design teams. They are the ones who moved their design people upstream, away from producing every screen and toward setting the conditions in which everybody else produces decent ones. What that structure actually looks like The version of this role that earns its keep looks less like a traditional designer and more like a conductor. Rather than routing all design work through a small team and watching a queue form, you fund that team to build the tools, standards, and guidance everyone else needs. Quality gets protected through what you hand people, rather than through gatekeeping that colleagues will route around anyway. In practice that means investing in a handful of assets. A design system with real usage guidance**, so a developer building a screen at 4pm on a Friday makes a reasonable decision without asking permission. Playbooks for the work people keep repeating**, like a landing page playbook that walks a marketer through structure, evidence, and calls to action without them inventing it from scratch each time. A research repository anybody can query**, tagged and maintained, so the research you already paid for keeps earning its money long after the readout deck has been forgotten. Functional personas that stakeholders can interrogate**, built around what customers are trying to get done rather than their age and job title, and useful enough to settle an argument in a meeting. Standards for briefing AI well, because the difference between useful output and confident nonsense sits almost entirely in the brief, and your design people are better placed than anyone to teach that. Alongside those assets, the team offers services rather than delivery. Open office hours for anyone about to build something, quick audits of work in progress, coaching for the team that keeps getting it wrong, training for the people who want to get it right. They still take on the genuinely hard, high risk design problems, but they stop being the only route to a wireframe. What has to change on your side None of this survives contact with the existing performance conversation, because most design teams are still measured on throughput. If you judge them on how many screens and tickets they got through, they will keep behaving like a production line and the queue will reappear within a month. Measure adoption of the design system instead, along with reuse of existing research, and the quality of what non-designers are shipping without help. The hiring mix shifts too. You need fewer people whose main strength is producing polished interfaces, and more who can think about systems, standards, research operations, and how to influence colleagues who don't report to them. Give them the authority to set standards that hold across teams, and get them into decisions early enough to shape what gets built rather than tidy it afterward. Somewhere sensible to start Ask whoever runs design for you what people keep coming to them for, week after week. Not what they think colleagues should want, the requests that genuinely keep landing. Then fund turning one of those into something the rest of the business can use without them. One playbook, one documented pattern, one persona people can question. See what it does to the queue, and do the next one. The uncomfortable part is that a team working this way looks less busy for a while, and busy has been our proxy for valuable for about two decades. That freed up time is the whole point, because it's where the strategic work finally happens. There is considerably more to it than I can fit in an email, which is why I have put together a free course on exactly this. Fourteen short lessons on shifting from doing the work to directing it, with the workshop slides thrown in. You can sign up here, and it's worth forwarding to whoever leads design for you. If you think I've got any of this wrong, hit reply and tell me, because I'm still working out how much of it I have.

Every website and app I’ve worked on has eventually developed the same problem. It accumulates content, features, navigation options, and stakeholder requests until everything is apparently important. Of course, when everything is important, nothing is. You end up with a homepage trying to please 14 departments, navigation labels negotiated by committee, and an interface that gives the refund policy the same prominence as whatever users came to do in the first place. Which is a slightly peculiar way to design something for humans. This is why I’ve relied on top task analysis for years. Find the few things that deserve attention Top task analysis identifies the tasks, questions, and features your audience values most. Rather than asking people whether they like a particular idea, it forces them to prioritize what matters. That distinction is useful because people can want many things in theory. But when they have to choose, a much smaller set usually rises to the top. Those top tasks give you an evidence-based foundation for decisions such as: What should appear prominently on a landing page Which features deserve attention in an app How a website’s information architecture should be organized What information belongs in a dashboard Which stakeholder requests can safely sit further down the list It won’t make the political conversations completely disappear, sadly. But “our users ranked this above that” is a considerably stronger position than “I feel this button should be bigger.” Why a normal survey isn’t enough A traditional survey can collect what people say they want, but the result is often another long list. You’ve discovered 47 things your audience cares about and somehow made the original problem worse. Well done, everyone. Top task analysis adds prioritization. Participants choose the 5 tasks that matter most to them and then rank those choices. That gives you a clearer picture of relative importance rather than a pile of individually reasonable requests. The approach can work for all sorts of digital products. On an ecommerce site, tasks might include checking delivery charges, tracking an order, or arranging a return. On a marketing site, they might be understanding pricing, comparing options, or finding evidence that a product works. In an application, they might be the handful of features people use every day. Once you know what sits at the top, you can design around those priorities and fit the smaller tasks around them. I’ve built a free app to make this easier Although top task analysis is valuable, running one has traditionally involved a slightly awkward collection of survey tools, spreadsheets, and manual cleanup. I’ve spent enough of my life staring at those spreadsheets, so I built a dedicated Top Task Analysis app instead. It is 100% free, and I intend to keep it that way. You can create a survey, add a few sample tasks, and share it with your audience. Participants select their 5 most important tasks, add missing options for others to choose, and then prioritize their selections. The admin area shows which tasks matter most, and you can compare the priorities of different audience groups. You can also rename, merge, or remove responses as you clean up the results, rather than performing spreadsheet surgery and hoping you haven’t accidentally deleted Western Europe. If you’d like to understand the process before creating a survey, I’ve also written a step-by-step guide to running a top task analysis. It covers gathering tasks, recruiting participants, analyzing the results, and using what you learn. The difficult bit remains reassuringly human The app will collect and organize the evidence, but it won’t decide what your interface should become. You still need to interpret the results, balance competing needs, and make sensible design choices. That is a good thing. We already have enough tools claiming to replace judgment while producing dashboards nobody reads. But top task analysis gives that judgment somewhere solid to start. It replaces a surprising amount of guesswork with direct evidence about what your audience came to do, and it makes prioritization conversations much easier to have.Try the free Top Task Analysis app A small Product Hunt-shaped favor I’m also launching the app on Product Hunt today, complete with a short video showing how it works. If you have a moment, please take a look at the launch and let me know what you think there. View the app on Product Hunt I’d genuinely value your first impressions, so if you have a moment, please leave a comment on Product Hunt. In particular, I’d love to know: Whether you can see a situation where you’d use it How you’d like to use it Whether there are any features you think are missing And once you’ve had a chance to try it properly, ongoing feedback is equally welcome. If you run a survey and discover something confusing, missing, or mildly irritating, please let me know. I built this to make a useful research approach easier to adopt, so real-world grumbling is far more useful than polite applause.

One of the most dangerous mistakes I see people make with their websites is fixating on what the competition is doing. Don't get me wrong. Competitive analysis is a valuable part of any digital strategy, but there's a fine line between being aware of the competition's strengths and weaknesses and letting them dictate your own direction. The slow slide into copying That's the danger here. Very quickly you can go from a healthy interest in your competition to essentially copying them every step. And if you fall into that trap, the inevitable result is that you're always going to be one step behind them. Not that anybody ever sets out to copy their competition, but it's insidious and it can happen without you even noticing. It starts out with a competitive review and then quickly moves to "Well, none of our competitors do that," or "Everybody has this kind of information architecture, so we should too," and before you know it, you've created a clone of your competitors. It's not only about being one step behind But this isn't just the worry of being one step behind your competition. There are two other considerations here as well. First, you quickly find that in some sectors all the companies end up looking the same, as they all copy one another, and so your site does nothing to stand out from the crowd, making it largely redundant. Secondly, and in my opinion more importantly, there's a false premise behind the desire to copy the competition. That's the belief that your competitors somehow know how to do things properly and that we should learn from them. There's an assumption that they've done their research, that they've made good decisions, which in my experience is simply not true. But they're bigger than us, surely they know what they're doing? Now I know what you might be thinking. "Our competition is much bigger than us. They've got more resources and more time, so surely they're making good decisions based on real data, and we can learn from that." However, that's rarely the case. I've worked with many large enterprise organizations, and to be frank they're just as disorganized, inefficient and over-stretched as their much smaller competitors. You are not your competitors And then, of course, there's the fact that you are not your competitors. Although you may be very similar, every organization is unique and needs to approach the market in a different way. If your competitors really are bigger than you, then you're not going to have the same success adopting their tactics. The real reason we copy However, in many ways, all of this is a distraction from the real reason that most people want to copy their competition. That's the fact that you don't get in trouble for doing what your competitors have done. They give you a point of reference that you can point at and say, "Well, they did this and it obviously worked for them." Of course, the chances are that's not actually true, and the very feature you're copying could well be underperforming for your competitors. Nevertheless, you have a justification for your actions. Do your own research instead But copying the competition is not the only justification you can use. Far better is to carry out your own research into user needs and behavior and base your decisions on that. Even if that research is just desk research, carried out online using the help of AI deep research tools like Perplexity. And if you really need to see a particular approach working in the real world, then I'd encourage you to look outside of your sector, where there are ample opportunities for you to find ideas that could be truly innovative in your own. So the next time you find yourself tempted to reject an idea because a competitor hasn't adopted that approach, or to implement a feature you've seen on a competitor's website, I'd encourage you to think twice. Because the best that approach can ever deliver is mediocrity.

I have had enough. I've spent a good chunk of my career nodding politely while a brand guideline told me to do something daft. Excessive use of all caps, color combinations that are unreadable and a complete lack of visual hierarchy in typography. I have seen all kinds of horrors and for a long time I went along with it, because questioning the brand felt a bit like questioning someone's child. Lately, though, I've run out of patience. I keep meeting people who use their brand as a reason not to change anything. The logo is sacred. The colors are locked. The fonts came down from a mountain on stone tablets. So the brand ends up quietly undermining the business completely untouched, because nobody wants to open that particular Pandora's box. A brand is not a mood board Don't get me wrong, I think branding matters enormously. Get your visual identity right, and it can shape whether an organization sinks or swims. I'm not one of those people who thinks design is decoration you sprinkle on at the end. But a good brand has to earn its keep. It has to work in the real world, on a real phone, for a real person squinting at the screen in bright sunlight. Looking pretty isn't the job. Looking pretty while also being legible, scannable, and accessible is what matters. This is where a lot of brands fall down. Somebody picked a color palette in a quiet studio on a lovely big monitor. It looked gorgeous. Then it hit the website, where it has to convince a distracted human to actually do something, and it fell apart. The web is an afterthought, and it shows Most branding is now seen online. That's where the majority of people meet your brand. Yet most branding agencies I come across still don't approach the work with a digital-first mindset. Oh sure, they'll tell you they know about digital. They might even include the odd mock-up for a website or a social media platform. But they're not specialists in usability or conversion, and the gaps in their knowledge shine through. And they do zero testing, despite having access to all the same testing tools the rest of us in UX use every day. They design for the brochure, the business card, and the launch presentation. The website is treated as one more place to paste the logo. So you get text baked into images, type that's beautiful at poster size and unreadable on mobile, and a palette that looks confident on a wall and washed out on a screen. It's a slightly depressing way to build something that lives mostly online. What this actually costs you I've had two clients recently where the visual branding was genuinely not fit for purpose. In one case it failed on accessibility. It flunked the legal tests, sure, but it also let people down in a simpler way. They just couldn't read it easily. In the other, the brand was all over the place. It may well have started life as a decent identity, but years of inconsistent use had distorted it beyond recognition. Different rules on every page, no hierarchy, and nothing to guide the eye. The symptoms are always familiar. There are walls of capital letters, which have been shown to cut readability by as much as 20%. There are color combinations that make body copy hard work. There's no typographic hierarchy, so headlines and sections blur together. And there are no visual containers, so the whole page becomes a soup of elements with nothing pulling your attention anywhere. None of these feels like a disaster on its own. Stack them up and you get a page that quietly repels the very people you spent a fortune attracting. The bit that tends to land Clients don't always take my word for this, which is fair enough. So recently I ran two versions of a homepage through an AI attention tool. The current brand-compliant design, and a tweaked version of mine. The numbers were uncomfortable for the brand identity and the existing website. Clarity and focus both climbed by around 20% in the new version. Predicted engagement with the main call to action jumped by more than 80%. Same content, same offer. The only real difference was loosening the grip of a brand that was fighting the reader instead of helping them. That's the conversation I would encourage you to have. Not "is the brand sacred," but "is the brand costing us more than it benefits us." At some point you have to decide which matters more. Honoring a set of brand assets that were never designed for the web, or actually converting the people who land on your site. What to do about it You don't need to burn the brand to the ground. That's rarely the answer, and it's rarely on the table anyway. Start small. Look at where the brand and basic readability are openly at war. Look for restrictive layouts, poor image choice, low-contrast text, and headlines you can't tell apart from the body copy. Fix those first, and you'll usually claw back most of the benefit without getting into a complete rebranding exercise. While you're at it, do the testing those branding agencies never bother with. You don't need a big research budget for it. A couple of cheap, practical checks will tell you most of what you need to know: A semantic differential survey, to see whether the brand actually communicates the values you think it does rather than the ones you hope it does. Accessibility and readability testing, to see whether it genuinely works on a screen rather than just in a presentation. Then push for one slightly braver conversation. Ask whether the brand was ever really designed for the screen, or just retrofitted onto it. If the honest answer is the second one, you've got a case for a proper digital-first refresh rather than another round of polishing something that doesn't work. And if you're the one clutching the brand guidelines like a holy relic, I'd gently suggest having a word with yourself. I've been that person. The brand is meant to serve the business, not the other way around. The moment it starts costing you customers, it's stopped doing its job, however nice it looks in a style guide.