Boagworld: UX, Design Leadership, Marketing & Conversion Optimization

This month we dig into whether Claude Design is any good, why so many people feel like AI is costing them time rather than saving it, and what it really means to stop being a doer and start being a director. Along the way we wander into the loss of craft, the ethics of AI, and a joke so niche it needs its own history lesson. App of the Month Claude Design is the tool that grabbed our attention this month. It builds out designs for you, and it is genuinely impressive. We used it to rebuild the website for a small UK charity that funds children's education in India, going from nothing to a finished static HTML site in around eight hours, with Claude Design handling the design and Claude Code doing the build. Beyond the standard twenty pounds a month subscription, it cost roughly fifty quid in extra credits, which for a small organization is a no-brainer. Claude design and code together allowed Paul to create a fully working website in less than 8 hours. It turns out it does more than websites. It builds presentations too, and exports them to PowerPoint or PDF for offline editing. We put together a fifty three slide deck for a client in about two hours, work that would normally have eaten the best part of four days. Here is what we liked. It works with design systems, you can import one from Figma, you can make manual edits without burning tokens, and you can select elements visually to tweak them. The things that hold it back are that you can't export back to Figma, there's no easy publish button, and the usage allowance vanishes in what feels like five minutes flat. When you hit the wall it cheerfully suggests you try again on Sunday, which is no use when you're mid project and have already forgotten what you were doing. One word of warning. If you don't guide it heavily, Claude Design has tells, like a recurring decorative bar under the hero section that serves no real purpose. Then again, every designer has a style you can spot, so we're not convinced that's the criticism people think it is. From Doer to Director A lot of people tell us AI isn't saving them time, it's costing them more of it. That confused us at first. How can a tool that turns four days of slide work into two hours possibly slow anyone down? The more we coached people through it, the clearer the answer became, and it has very little to do with the tools. It comes down to how organized you already are. If you're not fundamentally efficient in how you work, and especially if you've never had to delegate to other people, AI exposes that straight away. The people struggling most are the ones who still want to be doers. They want to be in the code, pushing pixels in Figma, or typing every word themselves. To get real value from AI you have to shift from that doer mindset to a director one. Be the conductor, not the violinist It reminded us of the moment in the Steve Jobs biopic where Wozniak asks Jobs what he actually does, given that Woz writes the code and builds the hardware. Jobs answers that he conducts the orchestra. Woz is the finest violinist in the room, but someone has to bring all the players together. That conductor role is exactly the shift most of us need to make. Running agents in parallel A real example from this month. Working on a client presentation, we had three things running at once. Notion AI was drafting the outline in one window. Claude Design was studying the client's website to build a matching design system in another. A third agent was drafting video transcripts for a separate project entirely. Three workstreams all moving at the same time, where you would once have plodded through them one after another. That is a genuinely hard skill to build. The people best placed for it are those with management experience, because they're used to handing work off and holding several threads in their head at once. If you've never worked that way, it can feel distressing, and there's even a name for where it leads, which our reader of the month gets into. The micromanaging trap There's a design leadership parallel too. Talented designers get promoted, then can't resist sneaking back into Figma to do the work themselves. The same thing happens with AI. The agent produces something perfectly good, but it isn't quite what was in your head, so you fiddle and fiddle and fiddle, burning the very time you were meant to save. The upside is that you can't hurt an AI's feelings, so just say "no, that's not it" and move on. Get organized first The fix is unglamorous. Get organized before the agents fully take over. Build the digital playbooks, SOPs and policies we keep banging on about, so the AI already knows how you work and gets it right first time. Keep your knowledge in one place it can reference, so you're not repeating yourself endlessly. Run a task system it can see, and learn markdown while you're at it. It takes ten minutes and AI loves it. Tool or output, where's the joy? We didn't agree on all of this. Marcus prefers using AI linearly and still enjoys the doing, the writing itself, rather than conducting an orchestra. That led us into deeper water about craft. Is the joy in the tool or in the output? Paul has found real satisfaction teaching AI to write in his voice while keeping the part he actually loves, communicating ideas with passion. Marcus worries that stripping away the craft, the genuine ability to play the instrument, costs us something real, and asks how the next generation of designers will learn without the junior grind. We tested it against Monet, photography and the industrial revolution. Someone recently posted a supposedly fake Monet online and asked people to explain why it fell short of the real thing. They wrote whole essays about flow and composition, until it turned out to be a genuine Monet. So how much of our resistance is legitimate and how much is simply discomfort with change? We don't pretend to know. There are real problems with AI, the blatant disregard for intellectual property and the environmental cost chief among them, and they deserve people shouting about them. But the genie is out of the bottle, and as a species we've never once managed to put one back. The one takeaway The single takeaway. Start building your management habits now. Get organized, practice delegating, and learn to hold several threads at once, before that choice gets made for you. Read of the Month Marcus brought the counterweight to all that optimism. The article is Life with AI causing human brain 'fry', which introduces a term coined by the Boston Consulting Group. "AI brain fry" is the mental exhaustion that comes from using or supervising AI tools past your cognitive limits, the sort caused by reviewing endless AI generated code, juggling multiple assistants, and rewriting lengthy prompts over and over. It hits software developers hardest, since agents now churn out code faster than humans can review it for security flaws and overall coherence. Fittingly, the piece reached us via one of the developers at Headscape, who waved it about as proof that AI is a problem. We agree the problem is real. The article's advice is for company leaders to set clear limits on AI use to prevent burnout, though quite how they're meant to spot the issue without us telling them is another matter. The catch is that a cynical manager will just point out that their whole day already feels like relentless context switching, so good luck getting much sympathy. For a related read, Marcus also flagged AI didn't delete your database, you did, a sharp piece arguing that you should take responsibility for what you ship to production rather than blaming the AI when it all goes wrong. Marcus' Joke We end, as ever, with Marcus’ joke. This one needs a UK history lesson, so our apologies to anyone under forty. I guessed orange, but it was chocolate. I guessed toffee, but it was peanut. I guessed strawberry, but it was coffee. I was wrong on so many Revels. Find The Latest Show Notes

This week, Paul and Marcus dig into why traditional user research repositories fail almost everyone in an organization, and how AI is quietly changing the game. There's also an App of the Month pick that's a little too on-the-nose, some pointed Google bashing, and a sheep-based punchline. AI-Powered User Research Repositories The pattern in most organizations is depressingly familiar: user research gets done, a PowerPoint gets presented to stakeholders, everyone nods along or ignores it entirely, and then the research disappears. It might prompt some short-term action, but the knowledge evaporates. Nobody references it again six months later. The traditional solution has been to build a research repository: a central place to store everything from interviews and surveys to usability tests and diary studies. The problem is that these repositories almost always become what Paul generously describes as "dumping grounds." Dense folder structures, difficult navigation, and search tools that require you to already know what you're looking for make them practically unusable for anyone outside the UX team. And who ends up using them? Other UX professionals, the people who already understand the research anyway. Everyone else ignores them. AI changes this in three meaningful ways. First, it makes the initial build far less painful. You can throw everything at it, PDFs, old PowerPoints, interview transcripts, survey exports, and AI will structure and organize that material into something coherent. What used to be a daunting, months-long project becomes manageable. Second, it makes the repository accessible to people who aren't UX specialists. Instead of requiring a precise search query, a conversational interface lets anyone ask vague, natural questions. A product manager can ask "what do our users think about the checkout process?" and get a synthesized answer drawn from five different studies they never knew existed. That's a genuinely different kind of value. Third, and this is the part Paul finds most compelling, it can identify gaps in your research. When someone asks the repository a question and there's no relevant research to draw on, a well-configured AI won't fabricate an answer. It flags the gap and notifies the UX team that this is an area worth investigating. Over time, the questions people ask become a demand-driven research roadmap, shaped by what people in the organization actually need to know rather than what the UX team assumes they need. Marcus pushed back on the reliability question, which is fair given AI's well-documented habit of confidently inventing things. Paul's response: proper setup matters enormously. You instruct the AI explicitly not to fabricate, you add a quality gate that checks answers before they're returned, and you can even have it verify claims against source material. Even with pessimistic assumptions, say one in ten answers being wrong, that's still more useful than having nothing at all. And the failure mode is reassuring: if the AI can't find relevant research, it defaults to generic best practice rather than making something specific up about your users. Paul then connected this to something he's discussed before: AI-powered virtual personas. The repository feeds the persona generation. AI analyzes the accumulated research and builds queryable personas from it. Unlike static persona documents that go stale almost immediately, these update as new research is added. And here's the detail Paul is clearly delighted by: put a QR code on your printed persona posters. Scan it, and you're now having a conversation with a virtual version of that persona. Marcus had recently written about the value of physical personas on walls as simple reminders of who you're designing for, and this neatly bridges the physical and digital. The upshot: organizations that invest in an AI-powered research repository end up with something that prevents duplicate research, makes user insights accessible to everyone, identifies gaps in what's known, and gives the whole organization a quick way to gut-check decisions against actual user data. The reason more organizations aren't doing this, Paul notes with characteristic subtlety, is that UX teams are too small and too busy. "Hire me to do it" being the conclusion he arrived at, live on air. App of the Month Notion Paul's pick this month is Notion, which he acknowledges he's almost certainly recommended before, given that he runs his entire business on it and describes its potential failure as roughly equivalent to his own. The recommendation here is specific though: Notion as the platform for building AI-powered user research repositories. Two things make it well-suited for this. First, structural flexibility: you can organize a repository however your organization needs, and bring in almost any format of research artifact. Second, Notion has a powerful built-in AI agent that can reference, search, and synthesize across everything stored in it. That said, Paul mentioned conversations with the RNLI, who use SharePoint and Copilot to achieve essentially the same thing. The principle works across platforms. Notion is Paul's preference, but he'd be the first to acknowledge the bias. Interesting Reads "Google is quietly rewriting headlines with AI in search results" Dan at Headscape surfaced this one. Google has been quietly rewriting the titles of content in its search results, not a new practice, but one that has apparently accelerated significantly with the arrival of Gemini. The example from the article: a piece originally titled "I used the cheat on everything AI tool, and it didn't help me cheat on anything" was shortened to "cheat on everything AI tool." The meaning flips completely. Paul's view: this isn't really an AI problem so much as a "no human in the loop" problem. Remove human judgment from the process and you get outcomes like this. "Testing suggests Google's AI overviews tell millions of lies per hour" This one prompted a longer and more genuinely interesting conversation. The article references New York Times analysis suggesting Google's AI overviews are incorrect around 10% of the time. The illustrative example: AI Overview cited three sources to answer a question about when Bob Marley's home became a museum. Two of the sources didn't address the date at all. The third, Wikipedia, listed two contradictory years, and AI confidently picked the wrong one. Paul and Marcus ended up in partial agreement. Paul's argument: we don't hold websites to a higher standard of accuracy than we hold AI, and the expectation of AI infallibility is inconsistent. The real issue is the word "confidently." AI states things with a certainty it hasn't earned, and the interface doesn't adequately signal uncertainty. Marcus's counter: AI summaries have effectively removed the click-through step, so an error now goes unchecked in a way a traditional search result didn't. They concluded it's largely a user interface problem, acknowledged that Google isn't going to remove the feature, and briefly proposed a BBC-funded public search engine before moving on. Marcus' Joke I'm entering the annual Give Helium to a Sheep contest again, and I'm a bit nervous. Last year the bar was very high. Find The Latest Show Notes

There's a scene in the Steve Jobs biopic where Steve Wozniak asks Jobs what he actually does. Wozniak understood his own role clearly: he was an engineer. He wrote code. He built things. But Jobs? Jobs described himself as the conductor of an orchestra. I've been thinking about that exchange a lot lately, because I think it captures exactly where we're all heading. AI isn't turning us into supercharged doers. It's turning us into conductors, and that requires a completely different mindset. The problem nobody talks about I've been coaching a number of people on integrating AI into their workflows recently, and I keep running into the same pattern. The people who aren't getting time savings from AI aren't failing because they don't understand what it can do. They're not failing because they lack access to the right tools. They're failing because they're fundamentally disorganized. AI is only as useful as the foundation it's built on. If your work processes are messy, your context is scattered, and your task management is a loose collection of mental notes and sticky tabs, AI can't do much for you. It needs structure to work from. I hear this complaint constantly: "AI has been mis-sold to me. I'm not saving any time." But it hasn't been mis-sold. It's just that AI can only deliver on its promise if there's an organized workflow underneath it. Build that first, and the time savings follow. That's why I've written before about building AI playbooks and developing proper AI skills. These aren't nice-to-haves. They're the infrastructure that lets AI actually work. The conductor problem But here's the deeper shift, the one that's genuinely harder to adapt to. When you're doing tactical work, you're usually focused on one or two tasks at a time. You go deep, you finish a thing, you move on. It's cognitively manageable. A conductor doesn't work like that. A conductor holds the entire orchestra in mind simultaneously: what the strings are doing, where the brass comes in, what the percussion is building toward. They're not playing any of the instruments. They're managing the relationships between all of them. In a world of AI agents, we're going to be managing multiple projects running in parallel, all moving faster than any human team would. We're task-switching constantly. We're accountable for outputs we didn't directly produce. And we have to resist the urge to dive in and do the work ourselves, because that's precisely where we get bogged down. The design leader parallel This isn't a new challenge, as it happens. Design leaders face exactly this transition when they move from senior practitioner to managing a team. I've watched a lot of talented designers struggle with that shift. They get promoted because they're brilliant at the work, and then they spend the next year quietly sneaking back into Figma because they can't let go of doing. They micromanage their reports. They redesign things that were already fine. They can't operate at the level of abstraction that leadership requires. Working with AI agents is going to feel very similar. The temptation to wrestle with the AI until it produces exactly the output you had in your head, rather than accepting a good result and moving on, is going to be real. Learning to let go of that control is a skill in itself. The good news is that unlike a team of designers, you can't upset an AI agent by micromanaging it. But you can waste enormous amounts of time doing it, and that defeats the whole point. AI burnout is already real There's one more aspect of this I want to flag, because I don't think it gets talked about enough. When you're managing a team of agents all moving at AI speed, the cognitive load is significant. You're context-switching constantly across multiple workstreams. Things are completing faster than you can review them. It's relentless in a way that managing a human team simply isn't. This is what's increasingly being called AI burnout. Learning to pace yourself, to batch your reviews, to build in breathing room: these are the organizational skills that will separate people who thrive in an AI-augmented world from those who burn out in it. Where to start If I had to distill this to one practical thing: start building the habits of a manager now, before the agents fully take over. Get organized. Build the infrastructure that AI needs to work from. Practice delegating, even to imperfect tools, rather than doing everything yourself. Work on your ability to hold multiple projects in your head without losing the thread on any of them. If you want help working through that transition, I offer coaching specifically for this. It's something I'm increasingly focused on, because I think it's one of the most valuable things I can help people with right now. I'm also running a workshop with Smashing Magazine in July. Modern UX Practitioner covers a lot of this ground in a more structured way, if that's more your style. The shift from doer to conductor is coming whether we prepare for it or not. The people who handle it best will be the ones who start thinking like managers now. Find The Latest Show Notes