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  • User Research Is Storytelling

    User Research Is Storytelling

    Ever since I was a boy, I’ve been fascinated with movies. I loved the characters and the excitement—but most of all the stories. I wanted to be an actor. And I believed that I’d get to do the things that Indiana Jones did and go on exciting adventures. I even dreamed up ideas for movies that my friends and I could make and star in. But they never went any further. I did, however, end up working in user experience (UX). Now, I realize that there’s an element of theater to UX—I hadn’t really considered it before, but user research is storytelling. And to get the most out of user research, you need to tell a good story where you bring stakeholders—the product team and decision makers—along and get them interested in learning more.

    Think of your favorite movie. More than likely it follows a three-act structure that’s commonly seen in storytelling: the setup, the conflict, and the resolution. The first act shows what exists today, and it helps you get to know the characters and the challenges and problems that they face. Act two introduces the conflict, where the action is. Here, problems grow or get worse. And the third and final act is the resolution. This is where the issues are resolved and the characters learn and change. I believe that this structure is also a great way to think about user research, and I think that it can be especially helpful in explaining user research to others.

    Use storytelling as a structure to do research

    It’s sad to say, but many have come to see research as being expendable. If budgets or timelines are tight, research tends to be one of the first things to go. Instead of investing in research, some product managers rely on designers or—worse—their own opinion to make the “right” choices for users based on their experience or accepted best practices. That may get teams some of the way, but that approach can so easily miss out on solving users’ real problems. To remain user-centered, this is something we should avoid. User research elevates design. It keeps it on track, pointing to problems and opportunities. Being aware of the issues with your product and reacting to them can help you stay ahead of your competitors.

    In the three-act structure, each act corresponds to a part of the process, and each part is critical to telling the whole story. Let’s look at the different acts and how they align with user research.

    Act one: setup

    The setup is all about understanding the background, and that’s where foundational research comes in. Foundational research (also called generative, discovery, or initial research) helps you understand users and identify their problems. You’re learning about what exists today, the challenges users have, and how the challenges affect them—just like in the movies. To do foundational research, you can conduct contextual inquiries or diary studies (or both!), which can help you start to identify problems as well as opportunities. It doesn’t need to be a huge investment in time or money.

    Erika Hall writes about minimum viable ethnography, which can be as simple as spending 15 minutes with a user and asking them one thing: “‘Walk me through your day yesterday.’ That’s it. Present that one request. Shut up and listen to them for 15 minutes. Do your damndest to keep yourself and your interests out of it. Bam, you’re doing ethnography.” According to Hall, [This] will probably prove quite illuminating. In the highly unlikely case that you didn’t learn anything new or useful, carry on with enhanced confidence in your direction.”  

    This makes total sense to me. And I love that this makes user research so accessible. You don’t need to prepare a lot of documentation; you can just recruit participants and do it! This can yield a wealth of information about your users, and it’ll help you better understand them and what’s going on in their lives. That’s really what act one is all about: understanding where users are coming from. 

    Jared Spool talks about the importance of foundational research and how it should form the bulk of your research. If you can draw from any additional user data that you can get your hands on, such as surveys or analytics, that can supplement what you’ve heard in the foundational studies or even point to areas that need further investigation. Together, all this data paints a clearer picture of the state of things and all its shortcomings. And that’s the beginning of a compelling story. It’s the point in the plot where you realize that the main characters—or the users in this case—are facing challenges that they need to overcome. Like in the movies, this is where you start to build empathy for the characters and root for them to succeed. And hopefully stakeholders are now doing the same. Their sympathy may be with their business, which could be losing money because users can’t complete certain tasks. Or maybe they do empathize with users’ struggles. Either way, act one is your initial hook to get the stakeholders interested and invested.

    Once stakeholders begin to understand the value of foundational research, that can open doors to more opportunities that involve users in the decision-making process. And that can guide product teams toward being more user-centered. This benefits everyone—users, the product, and stakeholders. It’s like winning an Oscar in movie terms—it often leads to your product being well received and successful. And this can be an incentive for stakeholders to repeat this process with other products. Storytelling is the key to this process, and knowing how to tell a good story is the only way to get stakeholders to really care about doing more research. 

    This brings us to act two, where you iteratively evaluate a design or concept to see whether it addresses the issues.

    Act two: conflict

    Act two is all about digging deeper into the problems that you identified in act one. This usually involves directional research, such as usability tests, where you assess a potential solution (such as a design) to see whether it addresses the issues that you found. The issues could include unmet needs or problems with a flow or process that’s tripping users up. Like act two in a movie, more issues will crop up along the way. It’s here that you learn more about the characters as they grow and develop through this act. 

    Usability tests should typically include around five participants according to Jakob Nielsen, who found that that number of users can usually identify most of the problems: “As you add more and more users, you learn less and less because you will keep seeing the same things again and again… After the fifth user, you are wasting your time by observing the same findings repeatedly but not learning much new.” 

    There are parallels with storytelling here too; if you try to tell a story with too many characters, the plot may get lost. Having fewer participants means that each user’s struggles will be more memorable and easier to relay to other stakeholders when talking about the research. This can help convey the issues that need to be addressed while also highlighting the value of doing the research in the first place.

    Researchers have run usability tests in person for decades, but you can also conduct usability tests remotely using tools like Microsoft Teams, Zoom, or other teleconferencing software. This approach has become increasingly popular since the beginning of the pandemic, and it works well. You can think of in-person usability tests like going to a play and remote sessions as more like watching a movie. There are advantages and disadvantages to each. In-person usability research is a much richer experience. Stakeholders can experience the sessions with other stakeholders. You also get real-time reactions—including surprise, agreement, disagreement, and discussions about what they’re seeing. Much like going to a play, where audiences get to take in the stage, the costumes, the lighting, and the actors’ interactions, in-person research lets you see users up close, including their body language, how they interact with the moderator, and how the scene is set up.

    If in-person usability testing is like watching a play—staged and controlled—then conducting usability testing in the field is like immersive theater where any two sessions might be very different from one another. You can take usability testing into the field by creating a replica of the space where users interact with the product and then conduct your research there. Or you can go out to meet users at their location to do your research. With either option, you get to see how things work in context, things come up that wouldn’t have in a lab environment—and conversion can shift in entirely different directions. As researchers, you have less control over how these sessions go, but this can sometimes help you understand users even better. Meeting users where they are can provide clues to the external forces that could be affecting how they use your product. In-person usability tests provide another level of detail that’s often missing from remote usability tests. 

    That’s not to say that the “movies”—remote sessions—aren’t a good option. Remote sessions can reach a wider audience. They allow a lot more stakeholders to be involved in the research and to see what’s going on. And they open the doors to a much wider geographical pool of users. But with any remote session there is the potential of time wasted if participants can’t log in or get their microphone working. 

    The benefit of usability testing, whether remote or in person, is that you get to see real users interact with the designs in real time, and you can ask them questions to understand their thought processes and grasp of the solution. This can help you not only identify problems but also glean why they’re problems in the first place. Furthermore, you can test hypotheses and gauge whether your thinking is correct. By the end of the sessions, you’ll have a much clearer picture of how usable the designs are and whether they work for their intended purposes. Act two is the heart of the story—where the excitement is—but there can be surprises too. This is equally true of usability tests. Often, participants will say unexpected things, which change the way that you look at things—and these twists in the story can move things in new directions. 

    Unfortunately, user research is sometimes seen as expendable. And too often usability testing is the only research process that some stakeholders think that they ever need. In fact, if the designs that you’re evaluating in the usability test aren’t grounded in a solid understanding of your users (foundational research), there’s not much to be gained by doing usability testing in the first place. That’s because you’re narrowing the focus of what you’re getting feedback on, without understanding the users’ needs. As a result, there’s no way of knowing whether the designs might solve a problem that users have. It’s only feedback on a particular design in the context of a usability test.  

    On the other hand, if you only do foundational research, while you might have set out to solve the right problem, you won’t know whether the thing that you’re building will actually solve that. This illustrates the importance of doing both foundational and directional research. 

    In act two, stakeholders will—hopefully—get to watch the story unfold in the user sessions, which creates the conflict and tension in the current design by surfacing their highs and lows. And in turn, this can help motivate stakeholders to address the issues that come up.

    Act three: resolution

    While the first two acts are about understanding the background and the tensions that can propel stakeholders into action, the third part is about resolving the problems from the first two acts. While it’s important to have an audience for the first two acts, it’s crucial that they stick around for the final act. That means the whole product team, including developers, UX practitioners, business analysts, delivery managers, product managers, and any other stakeholders that have a say in the next steps. It allows the whole team to hear users’ feedback together, ask questions, and discuss what’s possible within the project’s constraints. And it lets the UX research and design teams clarify, suggest alternatives, or give more context behind their decisions. So you can get everyone on the same page and get agreement on the way forward.

    This act is mostly told in voiceover with some audience participation. The researcher is the narrator, who paints a picture of the issues and what the future of the product could look like given the things that the team has learned. They give the stakeholders their recommendations and their guidance on creating this vision.

    Nancy Duarte in the Harvard Business Review offers an approach to structuring presentations that follow a persuasive story. “The most effective presenters use the same techniques as great storytellers: By reminding people of the status quo and then revealing the path to a better way, they set up a conflict that needs to be resolved,” writes Duarte. “That tension helps them persuade the audience to adopt a new mindset or behave differently.”

    This type of structure aligns well with research results, and particularly results from usability tests. It provides evidence for “what is”—the problems that you’ve identified. And “what could be”—your recommendations on how to address them. And so on and so forth.

    You can reinforce your recommendations with examples of things that competitors are doing that could address these issues or with examples where competitors are gaining an edge. Or they can be visual, like quick mockups of how a new design could look that solves a problem. These can help generate conversation and momentum. And this continues until the end of the session when you’ve wrapped everything up in the conclusion by summarizing the main issues and suggesting a way forward. This is the part where you reiterate the main themes or problems and what they mean for the product—the denouement of the story. This stage gives stakeholders the next steps and hopefully the momentum to take those steps!

    While we are nearly at the end of this story, let’s reflect on the idea that user research is storytelling. All the elements of a good story are there in the three-act structure of user research: 

    • Act one: You meet the protagonists (the users) and the antagonists (the problems affecting users). This is the beginning of the plot. In act one, researchers might use methods including contextual inquiry, ethnography, diary studies, surveys, and analytics. The output of these methods can include personas, empathy maps, user journeys, and analytics dashboards.
    • Act two: Next, there’s character development. There’s conflict and tension as the protagonists encounter problems and challenges, which they must overcome. In act two, researchers might use methods including usability testing, competitive benchmarking, and heuristics evaluation. The output of these can include usability findings reports, UX strategy documents, usability guidelines, and best practices.
    • Act three: The protagonists triumph and you see what a better future looks like. In act three, researchers may use methods including presentation decks, storytelling, and digital media. The output of these can be: presentation decks, video clips, audio clips, and pictures. 

    The researcher has multiple roles: they’re the storyteller, the director, and the producer. The participants have a small role, but they are significant characters (in the research). And the stakeholders are the audience. But the most important thing is to get the story right and to use storytelling to tell users’ stories through research. By the end, the stakeholders should walk away with a purpose and an eagerness to resolve the product’s ills. 

    So the next time that you’re planning research with clients or you’re speaking to stakeholders about research that you’ve done, think about how you can weave in some storytelling. Ultimately, user research is a win-win for everyone, and you just need to get stakeholders interested in how the story ends.

  • The Marketing Agency Business Model Is Outdated. Here’s What Replaces It.

    The Marketing Agency Business Model Is Outdated. Here’s What Replaces It.

    The Marketing Agency Business Model Is Outdated. Here’s What Replaces It. written by John Jantsch read more at Duct Tape Marketing

    I’ve spent 30+ years working with small businesses and the people who advise them. I wrote Duct Tape Marketing in 2006 because I watched too many owners buy random tactics from agencies that never asked what the strategy was. And for most of those 30 years, the agency business model itself held up fine. You […]

    How Inbound Marketing Is Changing in the Age of AI written by John Jantsch read more at Duct Tape Marketing

    Catch the Full Episode:

     

    Overview

    Duct Tape Marketing Podcast cover art featuring host John Jantsch and guest Kipp Bodnar for "How Inbound Marketing Is Changing in the Age of AI"HubSpot spent over a decade teaching small businesses how to build inbound marketing funnels. Then AI-driven search cost the company 140 million visits in under a year, an 80% drop in traffic. Revenue kept climbing anyway.

    John Jantsch talks with Kipp Bodnar about what replaced that lost traffic. They cover building a “taste profile” so AI tools produce work that sounds like you, the upside and risk of simulating customer reactions before spending a dollar, and why answer engine optimization means writing for machines that now read like humans.

    This episode is for marketers, agency owners, and solopreneurs who’ve watched their own traffic slide and want a concrete next step versus another AI framework to file away.

    Guest Bio

    Kipp Bodnar is CMO at HubSpot, where he’s worked for over 15 years, joining when the company had under $10 million in revenue. He co-hosts the podcast Marketing Against the Grain and sits on the boards of Gusto and Similarweb. His new book, co-written with Kieran Flanagan, is Loop: Outlearn. Outmarket. Outgrow., releasing September 22, 2026.

    Key Takeaways

    • Build a taste profile (a few hours clarifying what you believe about your customers and your brand) before using AI for content. If writing it out is hard, have someone interview you and feed the recording to AI instead.
    • AI buyer simulations get more predictable, but the trade-off is average results. Save your riskiest ideas for real-world tests instead of running everything through a simulation first.
    • The 3 most-cited sources on tools like ChatGPT and Claude are currently YouTube, LinkedIn, and Reddit. If you’re not active there, you’re less likely to get mentioned.
    • If you don’t publish your pricing, AI answer engines will guess it, and often get it wrong. Being transparent earlier in the buyer journey works in your favor.
    • What separates strong content from AI sameness is what’s unique to you: your own data, your customers’ stories, your specific history.

    Great Moments

    • [01:36] – Bodnar explains HubSpot’s 140-million-visit traffic drop and the decision to diversify beyond the blog.
    • [03:45] – The 4 steps of the Loop framework: express, personalize, amplify, evolve.
    • [08:56] – The risk of over-relying on AI buyer simulations for predictable results.
    • [12:37] – Answer engine optimization and the shift to writing for machines that now read like humans.
    • [18:05] – The big question: is inbound marketing dead.

    Memorable Quotes

    • “My taste profile version is always way better. I’m normally a C with generic AI, and an A with a taste profile.” — Kipp Bodnar
    • “When you’re trying to simulate customer reactions so your results are really predictable, the risk is you end up doing what everybody else is doing. You get a highly predictable result, but the magnitude is low or average.” — Kipp Bodnar
    • “We spent the last 20 years writing for machines that were trying to parse information like humans. Now we have machines that act exactly like humans, so you need to write exactly like you’re writing to a human.” — Kipp Bodnar
    • “Inbound marketing as we know it is dead because it was predicated on a world where information was scarce. Now knowledge is abundant, and actions and attention are the scarce things.” — Kipp Bodnar
    • “When we saw our traffic drop that fast, it was like, there has to be a better way. If this is happening to us, I’m sure it’s happening to others, and we need to get ahead of it.” — Kipp Bodnar

    Resources

     

    John Jantsch (00:01.24)

    So, what if the same people that taught millions of businesses to build marketing funnels to generate inbound leads admitted maybe some of that’s dead because they’re the ones that killed it? Their own traffic dropped 80% almost overnight, but revenue kept climbing anyway. Hello, and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch. My guest today is Kipp Bodnar. He’s the CMO at HubSpot.

    Where he spent over 15 years since company had a little less than 10 million in revenue at that time. He also co-hosts the podcast Marketing Against the Green and serves on the board of Gusto and Similar Web. We’re gonna talk about his new book, co-written with Kieran Flanagan, as called Loop. Outlearn, outmarket, and outgrow. So Kip, welcome to the show.

    Kipp Bodnar (00:50.602)

    John, thanks so much for having me. Pleasure to be here.

    John Jantsch (00:52.332)

    So so so when I read your co-author’s name, I just immediately go into this Irish accent, which is terrible. But I’m I’m sh well, I’m afraid that people get very tired of that, but it’s just it’s such an Irish name. So I I mentioned the idea of HubSpot’s traffic numbers going down. was there a like a time period? I mean, HubSpot’s not loaned.

    Kipp Bodnar (00:58.334)

    I love it. Please. He he has a great Irish accent accent. Do the whole show in it if you want.

    Kipp Bodnar (01:06.932)

    completely.

    John Jantsch (01:21.932)

    A lot you guys had just done such a good Yeah, I was gonna say, you guys had just done such a good job of building a lot of organic traffic. was there like a day when somebody said, This is a problem. I mean we we actually we need to do something about this?

    Kipp Bodnar (01:22.88)

    Tons tons of people have.

    Kipp Bodnar (01:36.821)

    There’s a couple things. One before this all happened, we knew it was going to be a risk for the future. So we bought a company called The Hustle. We we diversified well well beyond the blog, but we lost 140 million visits over the course of a year. And so what happened was between the rise of AI and Google doing a bunch of algorithm updates, you saw a pretty dramatic. Like at the start of that, it wasn’t like you lose a little bit of visits and then it got

    John Jantsch (02:04.216)

    Yeah.

    Kipp Bodnar (02:06.88)

    gradually worse. It’s like it dropped off pretty good, pretty quickly. And it’s like, gosh, there has to be a better way. And if this is happening to us, I’m sure it’s happening to others and will like or will likely happen to others. And we need to get ahead of all of this.

    John Jantsch (02:19.234)

    Yeah, yeah.

    John Jantsch (02:23.138)

    Just from my own experience, our traffic is probably down 50% from its, you know, from its high. But we pr pretty quickly realized it was a lot of garbage traffic. you know, it yeah. Yeah. I mean, and you guys did, you know, you had the listicles. I mean, you had all the stuff that that drove eyeballs that probably wasn’t very high value traffic. So, you know, in some ways are we better off, you know, well, you know, not having to try to chase that.

    Kipp Bodnar (02:32.116)

    Lot of it was garbage traffic. It’s a key insight for everyone.

    Kipp Bodnar (02:39.37)

    Yeah, of course. Yeah.

    Kipp Bodnar (02:54.354)

    look, I think we’re better and worse off at the same time. I think I think the ability to bring people to a site that you owned and you controlled and you could really shape their interactions versus being more reliant on podcasts and YouTube and TikTok and reels and everything else that’s out there, you know, which you’re limited to those platforms and their guardrails and their rules, that’s probably the tough trade off.

    John Jantsch (02:56.962)

    Yeah, okay.

    John Jantsch (03:03.79)

    Right, right, right.

    John Jantsch (03:12.374)

    LinkedIn, even yeah.

    Kipp Bodnar (03:21.834)

    Are we better off for maybe not wasting as much time and effort on people who are never gonna buy our products? Also, probably a good thing. So I think like everything in life, there’s good and bad.

    John Jantsch (03:28.472)

    Yeah.

    Yeah, yeah, yeah. So one of the things you talk about in the book is the idea of the marketing funnel being dead. what’s something that loop does that the funnel maybe structurally didn’t or couldn’t?

    Kipp Bodnar (03:45.109)

    Yeah, so if if I think about Loop, Loop is our framework for how you actually do marketing in this post AI world. And the reason for that, it you have to optimize for learning. AI, what it actually does is it enables you to scale your brains, your taste, all the things that make you and your company really good. And allows you to do a lot more, but you can also do a bunch of crap. And you can also fail to learn and compel in those lessons. So what Loop does is it gives you a playbook to

    John Jantsch (04:01.762)

    Yeah, yeah.

    Kipp Bodnar (04:14.208)

    Kind of do any marketing tactic or campaign that you want. And there’s kind of four simple steps to it. First is you work with AI to express your ideas and your and get them into content that’s really remarkable and personal to your audience because AI can bring all that context together, your customer interviews, what people are saying you about online, conversation your sales teams are having, and make that and turn all of that into really great content with you based on your insights and your perspective. Then

    The other thing we found that AI is really good at is helping you tailor the second part of the framework to make that content deeply personal on an individual basis. Then AI has opened up new distribution channels, and that’s the third step amplification. Those are things like answer engine optimization, working with influencers. AI has transformed advertising. It’s made advertising far more scalable than I think it was in the pre-AI world. And the fourth step is evolve. The one thing that AI

    John Jantsch (05:00.95)

    Mm-hmm.

    Kipp Bodnar (05:13.492)

    has really does well that nobody’s really taken on yet is it helps you codify your learnings and put them into systems that keep getting smarter every time you use them. And so that’s what we set out to do. We wanted to answer the question, like every market I talk to is getting yelled at by their CEO. Well, why is our traffic down and how do we do AI in this AI world? Like what the heck do we do? And we wanted to, I wanted to write something that I could hand to anybody who asks me that question and give them a real concrete answer.

    John Jantsch (05:43.117)

    Yeah, in fact I I just started playing with it today. It may come out earlier in the week, but Claude just introduced a anthropic just introduced a skill builder that it basically just follows you around. It’s like, you know, if you’re gonna do a process, you’re gonna go on Slack for this, you’re gonna go here, you’re gonna go here, and it and then it’s like, okay, I’ll build a skill that does that. so that that idea of codifying is just getting easier and easier and easier, isn’t it?

    Kipp Bodnar (05:53.92)

    Mm-hmm.

    Kipp Bodnar (06:09.539)

    I i the thing it’s a perfect example.

    John Jantsch (06:11.414)

    Yeah. So you talk about something called a taste profile. I wonder if you could walk me through the solo entrepreneur, you know, who doesn’t have an entire marketing team, how do they build a taste profile?

    Kipp Bodnar (06:15.243)

    Yeah.

    Kipp Bodnar (06:20.012)

    Yeah.

    Well, see, this is the fun part, is that the taste profile I think is most beneficial to like the small, small team or the solopreneur, right? Because all a taste profile is, is spending a few hours to make the decisions that you know, but haven’t like had the exercise to clarify all of them, so that you can actually then give those decisions to AI and AI knows what you want to achieve and has all the context around what you want to achieve. And so it’s essentially two parts. The first is

    John Jantsch (06:31.362)

    Yeah, yeah.

    Kipp Bodnar (06:52.011)

    Customer taste and might be a s we give you a list of questions to go have AI do research for you. Even so if you’re a solopreneur, you use those questions, you go do the research, and you kind of understand what the market and the customer thinks your category and how your product might fit into there. The second part of this is like brand taste. So like what do you think about? Like, why does your company exist? What does your product solve in the world? You know.

    What do you what do you believe about the world that’s unique and differentiated? Like how do you think about your thought leadership? And we give you very specific questions to kind of go through and get to clarity on those. And then once you have all that together, you put that in any AI tool. I do it all the time. I’ll do a blank version and then I’ll do a taste profile version. And my taste profile version is always way better. I actually built like an independent grader to C. And I’m normally like a C with generic AI and like I’m an A with a taste profile. And it’s one simple thing that

    It takes you a couple hours to do once and then you probably need to update it, you know, a couple of times a year, depending on how your your business changes.

    John Jantsch (07:53.154)

    Yeah, I mean we run across that all the time. You know, that that we because we’re the same way. We’re like, look, you gotta put all this stuff together. It’s a little work in the beginning, but it will save you so much time and and so much better output, right? In the end. and and people want to skip that. It’s like, I don’t want to sit down here and answer all these questions, but I’m yeah.

    Kipp Bodnar (08:12.287)

    It’s hard. You have to make the hard choices. You know, like that’s the like this is real marketing though. Marketing is the I I had David Epstein on the marketing Instagram podcast recently. And he’s like, Look, the people who are succeeding in this new world are brain first, tool second versus tool first, brain second, right? And that’s that’s what this is all about.

    John Jantsch (08:27.35)

    Yeah, yeah. Yeah. Yeah. It’s it’s another vote for a good liberal arts degree, isn’t it? So you talk about something in the book called the AI buyer sim. and you go as far as saying I think that it can predict customer reactions with ninety percent accuracy. first off, that’s amazing. we ought to all be using that right, but

    Kipp Bodnar (08:34.277)

    Yeah, g exactly right.

    Kipp Bodnar (08:52.575)

    Yeah. Yeah, absolutely.

    John Jantsch (08:56.77)

    What is the I’m I’m gonna go go the opposite side of you of of that idea. What is the risk of kind of relying on that type of data and being wrong?

    Kipp Bodnar (09:08.289)

    I like this question. here’s the risk. marketing, I I think of marketing as this interesting relationship. And it and I see everything in like frameworks and graphs and charts and two by twos. And the two by two here is like how predictable the results you’ll get from it, and then how high or what’s the magnitude of those results, right? And so when you’re trying to simulate your results and predict your results so that they’re really predictable, the risk of that.

    John Jantsch (09:19.383)

    Yep.

    Kipp Bodnar (09:36.8)

    Is that you’re gonna do what everybody else is doing. And when you do what everybody else is doing, you’re gonna get an average result. So you’re gonna get something that’s highly predictable, but the magnitude is gonna be kind of low or average. And so what you’re leaving on the table is like the crazy thing that might fail a bunch of times, but when it hits, hits really big. And that’s the biggest risk in taking taking that. And so you should use the taste profile for things that you know, or excuse me, you should use the BIOSIM for things you know, like kind of.

    John Jantsch (09:46.926)

    Mm-hmm.

    Kipp Bodnar (10:03.861)

    I know how this is gonna work. I I have this tried and true, but for new things I wanna go outside of that and really do some wild tests.

    John Jantsch (10:12.685)

    So one of the things that I think a lot of people are suffering from i is this, you know, even though organic traffic is way down, people are still producing, you know, stuff that AI sameness, I think you call it. A lot of people have called it that. so so what’s the sort of what’s the marker that says, no, this is actually above all of that? This is better quality, this is you know, this is done I mean, is it just the amount of time you spend, the amount of research, the amount of

    Kipp Bodnar (10:25.58)

    Yes.

    Kipp Bodnar (10:35.671)

    Yeah.

    John Jantsch (10:41.429)

    Citations, you know, I mean what is it that makes it get out of that sameness?

    Kipp Bodnar (10:46.231)

    So I think this is what’s interesting. Pre AI, you could just be prolific. Right? You could just, hey, I’m gonna outgrind, I’m going to write some stuff. The stuff doesn’t have to be great.

    John Jantsch (10:50.859)

    Yes. Right.

    John Jantsch (10:55.795)

    I remember I remember people I remember people asking me all the time when I’d talk about blogging, how many words does it have to be? You know, like like that was the yeah that was the marker.

    Kipp Bodnar (11:04.233)

    yeah, that was a that was a topic for years. Yeah. And and so, and now now it’s not good enough to be prolific. Like I call this kind of like the Taylor Swift problem. Like you have to be prolific like she is, but you also have to be great. Like the things you have to do have to be great. And you’re asking me the questions like what makes great content in a world where somebody can type something into a chat GPT, a Claude, and get any information they want. And what I what I found is that.

    John Jantsch (11:17.761)

    Yeah.

    Kipp Bodnar (11:34.004)

    It is the things that make your that are unique to you or your business. And so that is, do you have unique data? You I know you have unique customers, and those customers have unique stories. You yourself, if you’re a solopreneur, have a unique history and framing and life story that you have to bring to the table. There is there is a level of like research and rigor and putting things together in clever ways that people wouldn’t expect.

    John Jantsch (11:39.521)

    Yeah. Yeah it’s

    Kipp Bodnar (12:02.975)

    I think those are some of the key highlights that make if you just go around and pay attention to what you think is good and interesting, you’ll find that those are kind of the backbone of most of most of the things.

    John Jantsch (12:14.377)

    Yeah, I tell people all the time. It’s like, what’s the only thing what’s the thing that only you could write about? Nobody else in the world could. You know, and they they they start thinking about that and they’re like, okay, I could add that. Like you said, customer stories, you know, is is an easy one because everybody should everybody should have those. Yeah. So talk a little bit about you mentioned already, I think, answer engine optimization. how does that go beyond just writing FAQs?

    Kipp Bodnar (12:18.761)

    Yes. I love that.

    Kipp Bodnar (12:28.927)

    One hundred percent. Everybody has that.

    Kipp Bodnar (12:37.718)

    Yeah.

    Kipp Bodnar (12:41.877)

    Yeah, so answer engine optimization is a very interesting topic. It’s something that everybody’s obsessed with. Like, what does ChatGPT, G Google Gemini, Claude, Perplexity, what do all these things say about me and how do they talk about me? And the first thing you need to do is understand like how visible you are on those answer engines. So what’s your visibility? And that comes in two terms: mentions and citations. Mentions are just like, do they talk about you and do they talk about you positively or negatively?

    John Jantsch (12:47.553)

    Right.

    John Jantsch (12:50.869)

    Yeah.

    Kipp Bodnar (13:11.105)

    Then citations are like, do they link back back to you? And something you you you have to say. And you’re right that FAQ pages are one way to do that. The three most cited resources on Chat GPT and Claude, for example, though, and Gemini, for example, though, are YouTube, LinkedIn, and Reddit. So if you’re not involved in YouTube, LinkedIn, or Reddit, you’re probably less likely to get mentioned on the topics that are relevant to your business.

    John Jantsch (13:13.877)

    Mm-hmm.

    John Jantsch (13:32.577)

    Yeah, yeah.

    Kipp Bodnar (13:39.489)

    The other thing you have to do for content you do own, like your website, it’s not just FAQs. The way I like to explain it is we spent the last 20 years writing for machines who were trying to parse information like humans. Right? It’s like you had all this deep meta description, keyword density, all these things. Now we have machines who act like exactly like humans. And so you need to write exactly like you’re writing to a human, but simple, plain spoken.

    John Jantsch (13:58.348)

    Right. Schema, yeah.

    Kipp Bodnar (14:08.694)

    non you know, non-jargon framed in easy chunked segments so that this machine who re who acts exactly like a human can pick those couple sentences up. Like if you go to our CRM page, right, there’s a what is the CRM box and it’s three sentences and it’s very in plain English explaining to you what a CRM is.

    John Jantsch (14:30.197)

    I think in your particular case, like all SaaS offerings, you know, there’s typically pricing, you know, has been on your pages forever. but but but for a lot of businesses, that’s a new idea, or just even the fact that, you know, their whole goal was to get somebody on a phone call so that they could then explain how everything worked. How how do we have to now start thinking about the fact that that the buyer journey is going to go a lot farther?

    Kipp Bodnar (14:36.47)

    Yeah. for for sure.

    John Jantsch (14:57.356)

    you know, bef maybe before we get that phone call and that we need to reveal a lot of information that maybe we wanted to hide because we didn’t want our competitors to have it.

    Kipp Bodnar (15:08.088)

    So the reality is the interesting things, good and bad, about LLMs is they will give you an answer. Right? It will always give you an answer. So if somebody asks what your price is, one, if it had if there’s just no information on the internet about it, it will make something up. If there is information your customers are talking about it on Reddit or G2.com or some of these places, it’ll aggregate that. And what I have found is it’s often wrong.

    John Jantsch (15:13.931)

    You’re right. Yeah. Yeah.

    John Jantsch (15:25.337)

    Yeah.

    John Jantsch (15:29.877)

    Right, right,

    John Jantsch (15:35.533)

    Yeah. Yes, yes, yeah.

    Kipp Bodnar (15:36.225)

    And it’s often misanchors me. It’s like, I think this thing’s gonna be $50. And it turns out it’s $500. And like, wow, I was that I I don’t want that thing. I was expecting it was gonna cost a very different amount. So I look at this as like, you have to provide that information because if you don’t, you’re gonna have buyers who are gonna get an answer anyway, and it’s not an answer you want them to get. And so you’re gonna have to operate more transparently than I think that you want. And by the way.

    I think that’s a good thing. I think you’re probably likely going to attract more people by doing that than by hiding it.

    John Jantsch (16:06.636)

    Yeah.

    John Jantsch (16:12.373)

    So one of the steps you mentioned was evolve. what does that look like day to day for a marketer?

    Kipp Bodnar (16:15.286)

    Yeah.

    Kipp Bodnar (16:21.152)

    Yeah, so the way I think about the evolution of marketing and what it means to evolve is like it used to be, let’s say I had a I have a Google AdWords campaign on. I maybe I’ve run a Google AdWords campaign, I run a weekly email campaign. It used to be, well, all right, like once a month, maybe once every couple weeks, I’ll look and see how that’s going. Right? And I’ll look and I’ll make make a few little tweaks. Now it’s like I can, you know, at HubSpot, we have our Breeze assistant, like our version of Claude inside HubSpot’s like,

    You can ask any of it any of these insights anytime you want and get instant learnings and change much faster, right? And be like, not only do I can I get this information, I can get recommendations from this thing that’s really smart and knows my business, right? And then I can actually change way more rapidly. The other part of what Evolve means is you have some system. You run your business off systems. And in this AI world, there are

    John Jantsch (16:59.393)

    Yeah, yeah.

    Kipp Bodnar (17:19.756)

    You know, agents, there’s skills, there’s workflows. You can actually have AI update your systems based on what you learn. And that’s the big unlock. Before AI, you couldn’t do that. You would have to remember, I need to go make this change to my system based on this thing I learned. Exactly. It’s in eight places. my cousin Tim actually set this up for me, so I gotta wait till he’s back from vacation so that he can update it for me. Now you can just.

    John Jantsch (17:28.095)

    Mm. Yeah, yeah, yeah.

    John Jantsch (17:35.341)

    And it and by the way, it’s in eight places.

    Kipp Bodnar (17:47.523)

    have it do it in the background and like run a recurring task. And that is transformative because we all know the power of compounding, right? Like you you do that, you add have an update a smart learning every week, you know, half a year in, you’re like getting massively better results.

    John Jantsch (18:01.46)

    Yeah, yeah, yeah. Yeah, yeah. With with real data. All right, here’s the here’s the big question, you ready? Is is inbound marketing dead?

    Kipp Bodnar (18:05.75)

    With real data.

    Kipp Bodnar (18:10.7)

    I’m ready, please.

    Kipp Bodnar (18:15.372)

    I think inbound marketing as we know it is dead because it was predicated on a world where information was scarce. And and and and knowledge was scarce. Now knowledge is abundant and actions and attention are more scarce. And so I think the loop loop framework as well as all the work that everybody’s doing in the marketing world today is trying to go beyond that old world and help companies thrive in in this new one.

    John Jantsch (18:25.025)

    Yeah, yeah.

    John Jantsch (18:43.936)

    Did did you have to actually be the one to tell Brian and Dormash that that that finding?

    Kipp Bodnar (18:47.032)

    We had a we had a nice debate. You know, so the the loop book that that everybody’s gonna read on September twenty second started as like a ten page memo that I wrote. And the name of that memo was In Bell Marking is Dead. And it it wasn’t even called Loop at the time, but it was all the these observations that you and I are talking about. But this was, you know, eighteen months ago, you know, a long time ago.

    John Jantsch (18:58.18)

    okay.

    John Jantsch (19:02.56)

    Mm-hmm.

    John Jantsch (19:12.128)

    Yeah, awesome. All right. So if a small business owner, this is always the hard question, actually. Small business owner reads reads the book. What’s the one page they should act on this week? You don’t have to cite a page number. As a as an author also, I I know when people ask me that, I’m like, I don’t know. I wrote that 18 months ago. But what’s the one concept? How’s that that they should act on this week?

    Kipp Bodnar (19:16.002)

    Yeah. Yeah, let’s do it.

    Kipp Bodnar (19:26.206)

    Mm-hmm. Yeah.

    Kipp Bodnar (19:36.672)

    Yeah, we talked about it earlier in the show. I think you should do fill out your taste profile. It’s it’s it’s it’s on it’s i early on in the book, because that way your your AI tools have all the context of you, your business, and your taste, and they will just make far better decisions. Even if you don’t know it, it will happen.

    John Jantsch (19:58.112)

    Do you one thing that we’ve we’ve found s like if I tell somebody you need to fill out your taste profile, they sit there and they go, I can’t answer all these. But if I actually ask them the questions, interview them, th all of a sudden they’ll talk for hours. so th that’s that’s a tip you might give people. Yeah. Yeah.

    Kipp Bodnar (20:08.759)

    Yes.

    One hundred percent.

    well first of all I love that and second of all if you’re listening to this show and you’re feeling that way, have a friend, have your spouse, have somebody just, you know, open the book, write down the questions separately and just record you. And then by the way, you can just upload that video to AI and you won’t have to ever type or write anything and it will take care of it all for you.

    John Jantsch (20:25.004)

    Yes, exactly.

    John Jantsch (20:33.024)

    Plus it sort of automatically gets your voice and tone and how you speak and all that kind of stuff. I love. Yeah. Yeah. Awesome. Well, Kip, I appreciate you taking a moment to stop by the Duct Tape Marketing Podcast. Is there some place you’d invite people to connect with you, find out more about Loop and everything else you’re up to?

    Kipp Bodnar (20:35.724)

    Yeah, exactly. That’s a that’s a great point.

    Kipp Bodnar (20:49.0)

    Yes. So you can obviously learn more about Hubswata Hubs dot com. You can find the book at loopmarketing dot com. And then for me, you can find me on Marketing Against the Grain, on YouTube and wherever you get your podcast.

    John Jantsch (21:01.908)

    Awesome. Well again, appreciate you stopping by. Hopefully we’ll run into you one of these days out there on the road.

    Kipp Bodnar (21:06.462)

    Awesome. Thanks, John. Appreciate you having me.

    powered by

  • Designed for a Dead Language

    Designed for a Dead Language

    Every language app in your pocket inherited a teaching method built for Latin. Understanding why that happened is a more useful design lesson than anything the apps themselves will teach you.

    In 1788, Prussia introduced the Abitur, a standardized national examination required for entry into universities and the civil service. To pass it, students needed to demonstrate measurable, gradable knowledge. The system needed to teach language to large classrooms, produce consistent outcomes, and do it with one teacher and thirty students. The educators responsible for designing this system reached for the only teaching template they had, one that had been used in European schools for two centuries: the method developed to teach Latin.

    Latin, by 1788, was a dead language. Nobody needed to speak it. The scholars who studied it were reading Cicero and Virgil, not conducting conversations. The method built around it, memorizing grammar rules, constructing translations, analyzing written texts, reflected that reality exactly. Oral skills were irrelevant. Comprehension of written form was everything. The method was not designed to produce speakers. It was designed to produce readers of texts in a language nobody spoke.

    When Prussia applied this template to French and German, living languages spoken by living people, the premise did not change. Johann Valentin Meidinger’s textbook Praktische Französische Grammatik, published in 1804, ran to 37 editions across Europe by 1857. Karl Plotz formalized the approach into what became the dominant model for teaching modern languages across Europe and eventually the United States, where it became known simply as the Prussian Method [1]. Each institution that adopted it trained teachers in it, who trained students who became teachers. The constraint that created the method, how do you grade language at scale with limited resources, became invisible inside the method itself. What remained was the assumption: language is a body of rules to be learned consciously and measured. It was a design decision dressed up, over time, as a pedagogical truth.

    The observation that should have ended it

    There are people in the world who cannot read or write a language and speak it fluently. There are children who hold full conversations years before they can read a single word. There are immigrants who arrive in a country knowing nothing of its language and come out, years later, speaking it naturally, not because they studied it, but because they lived inside it. Literacy and fluency are separate things produced by entirely separate mechanisms. The Grammar-Translation method, as it became known, assumed they were the same thing. That assumption was inherited from a method designed for a language nobody needed to speak, and it was wrong the moment it was applied to a language people actually used.

    The evidence against it accumulated slowly. In the mid to late nineteenth century, reformers including François Gouin in France and Maximilian Berlitz in the United States argued independently that language should be taught the way it is actually acquired, through immersive exposure to real communication in the target language, not through analysis of its rules. Berlitz built an entire school network around this principle. The reformers were correct. They were also largely ignored by mainstream education systems, because the Grammar-Translation method had one decisive advantage that direct immersion did not: it could be graded.

    In 1982, the linguist Stephen Krashen gave the argument its most formal articulation in what he called the Monitor Model of second language acquisition. His distinction was precise: language acquisition, the unconscious process through which children absorb their native language and through which adults succeed in immersive environments, is categorically different from language learning, the conscious study of grammar rules and vocabulary that classrooms deliver [2]. Acquisition produces fluency. Learning, at best, produces the ability to pass a test. The evidence supporting this distinction, and the observation that immersive exposure to real native-speaker communication is the mechanism that produces genuine fluency, has only grown since.

    I went to Brazil without a word of Portuguese and came out speaking it. I studied French in a classroom for years and cannot hold a conversation in French today. This is not an unusual experience. It is the expected outcome, and it has been the expected outcome for as long as we have had formal language education.

    The same decision, made again in a different medium

    Prussian educators faced the question: How do you deliver language learning at scale, measure progress, and retain users over time? The answer it arrived at was structurally identical to the one arrived at in 1788. Duolingo gamified the grammar drill into a streak. Anki formalized the translation exercise into a spaced-repetition flashcard. Babbel organized grammar lessons into structured modules. The interfaces were new. The underlying assumption, that language is a thing you study rather than an environment you inhabit, was not.

    This was not a failure of design skill. The products that emerged from these decisions are, in many respects, genuinely well-crafted. Duolingo’s retention mechanics are sophisticated. Anki’s spaced repetition is grounded in real cognitive science. They are excellent at what they actually do. The problem is what they actually do: produce measurable engagement with a proxy for language rather than the conditions that produce language itself. A streak is measurable. A vocabulary score is measurable. The moment a user walks out of an app and holds a real conversation in another language, that happens in the world, outside the product, and cannot be instrumented.

    When the outcome a user needs is difficult to measure directly, the design process tends to reach for something that can be measured. The proxy becomes the goal. The interface optimizes for it. The gap between what the product delivers and what the user actually needed grows. This is not a pattern unique to language learning. It is a pattern that repeats across product categories whenever a design constraint—the need to measure, the need to scale, the need to produce a grade—gets built into a system so deeply that it stops being visible as a constraint and starts being mistaken for a truth about the problem itself.

    What happens when the constraint changes

    The constraint that made the Grammar-Translation method necessary in 1788 was real and rational. One teacher. Thirty students. A standardized exam. You cannot grade a conversation at scale. You can grade a translation exercise. The method was not chosen because it produced fluency. It was chosen because it produced a score.

    That constraint no longer exists in the same form. Technology has made it possible to deliver immersive, real-time conversation practice to anyone with a smartphone, at a cost that continues to fall. The design problem is no longer how to make language learning gradable at scale. It is how to make the conditions of genuine language acquisition accessible to people who cannot move to another country or afford a native-speaker tutor.

    The products that are now closest to solving the actual problem are not the ones that invented a new pedagogy. They are the ones that removed the access barrier to an old one. Praktika builds AI conversation partners with distinct personalities, regional dialects, and cultural context, replicating the specificity of a real native speaker rather than a generic language-learning voice. Langua clones native speaker voices so that the interaction feels like a real conversation rather than a lesson. Rosetta Stone’s foundational methodology, image association in the target language with no translation, was built on the same insight Berlitz arrived at in the nineteenth century: language is acquired through immersive exposure, not through analysis of its rules [3]. A 2025 meta-analysis of 31 studies found that AI conversation tools produced a statistically significant improvement in language learning outcomes, a result that no amount of flashcard optimization has consistently matched [4].

    None of these products invented a new theory of language acquisition. They translated an existing one into something more people could reach.

    The design question this leaves

    The Grammar-Translation method persisted not because educators were wrong about design, but because a design decision made under a specific constraint became, over two centuries, indistinguishable from the thing itself. The constraint, how do you grade language at scale, was forgotten. The method it produced was inherited as if it were a description of how language works, passed from Prussia to Europe to America to the App Store, from the grammar drill to the streak.

    Every time a design team optimizes for a metric because the actual outcome is hard to measure, they are making a version of the same decision. It is often the right decision given real constraints. The question worth asking is whether the constraint that made it necessary still exists, or whether it has simply become invisible inside the system it originally produced.

    Before reaching for what can be measured, it is worth asking what the user actually needs to do, and what stopped them from doing it before. Sometimes the answer is a new solution. More often it is an old one that was always out of reach.

  • Good designers, bad websites: a proposal

    Good designers, bad websites: a proposal

    I want to discuss accessibility because it is the most important thing for making websites. Other A List Apart articles give you innovation and insight. This article will give you homework. These are just my personal views, but they’re pretty good.

    I want to start off with a couple of statements, and you will agree:

    1. Designers are good people. I have never heard a designer say, “I don’t care if somebody can’t read this text”, “Not my fault if somebody can’t use this device”, or “Who cares if this is confusing?”
    2. Some designs exclude people. You have seen people unable to read the text on a website or app that somebody designed. You’ve seen people unable to use a physical device that somebody has designed. You’ve seen people utterly bamboozled while trying to use a service that somebody designed.

    So what?

    The first question is, “Is this life-or-death stuff?” The answer is, “Yes.” In my favorite essay, This Is All There Is, Aral Balkan makes the point that pretty much everything that we design can affect life events and death events. Aral gives the example of how even a straightforward bus timetable app can affect life and death events, if we design it badly:

    • somebody might miss a life event, such as their daughter’s fifth birthday party; or
    • somebody might miss a death event, such as the chance to say goodbye to a dying grandmother.

    The next—and frustrating—question is, “Why do some designs still exclude people?” After all, we know that:

    • not everybody can see perfectly;
    • not everybody can hear perfectly;
    • not everybody thinks the same way; and
    • not everybody moves the same way.

    I think the answer is that there’s too much to recall. Consider, if you will, the wide variety of topics that A List Apart articles cover. Designers are expected to remember all of that guidance, plus all of the accessibility guidance, plus so much more. It is too much.

    Recognizing accessibility issues while designing

    I’d like to point toward one possible solution, starting from Jakob Nielsen’s 10 Usability Heuristics for User Interface Design. These are from the mid-1990s, and—although there’s a good chance that you, gentle reader, are a lot younger than that—please bear with me. 

    Seeing as the problem is that there’s too much to recall, I want to look at heuristic № 6, “Recognition rather than Recall.” Jakob Nielsen said that for users, information required to use the design should be visible or easily retrievable when needed. I suggest we tweak that to make life easier for designers. Let’s say that the information required to produce the design should be visible or easily retrievable when needed. In other words, let’s make it easier to recognise accessibility issues while we’re designing.

    How are we going to do that? I really like the book A Web for Everyone—Designing Accessible User Experiences by Sarah Horton and Whitney Quesenbery. I really like this book not only because it includes a quote from me—actually two quotes, but I don’t like to boast—but because it includes personas that are perfect for helping us to recognise accessibility issues. That’s the good news. The even better news is that these personas are available now for free on the companion website to the book What Every Engineer Should Know About Digital Accessibility, again by Sarah Horton, with David Sloan this time.

    Meet your users

    I’m going to introduce you to these personas now:

    I want to throw one more persona at you now, because, well, A List Apart readers are overachievers. One of my favorite authors, Cennydd Bowles—who literally wrote the book on Future Ethics—says to create Personas Non Grata. In other words, every time we design something, we have to think about what a bad guy could do with that thing, and whom that might affect.

    To actually use these personas while designing, I like what Eric Meyer and Sara Wachter-Boettcher in Design for Real Life call the Designated Dissenter: for each project that you work on, one of your teams should be responsible for asking, “Will this work for Vishnu?”, “How’s Trevor going to get on with this?”, and so on. 

    Then, once you’ve used the personas to recognise the accessibility issues, you can look up the guidelines for whichever platforms you’re designing for: 

    Your mission, should you choose to accept it

    I told you in the introduction of this article that I would give you homework. You thought I was joking. So, here’s your homework: I want you to grab the personas from the Know About Accessibility website, and use them throughout every design project to help you recognise accessibility issues while you work—and reclaim design for everyone.


    NOTE: This article is based on “Recognise,” my five-minute presentation from Interaction Design Association (IxDA) Dublin’s Defuse (Design for Use) event in 2025.

  • Design for Amiability: Lessons from Vienna

    Design for Amiability: Lessons from Vienna

    Today’s web is not always an amiable place. Sites greet you with a popover that demands assent to their cookie policy, and leave you with Taboola ads promising “One Weird Trick!” to cure your ailments. Social media sites are tuned for engagement, and few things are more engaging than a fight. Today it seems that people want to quarrel; I have seen flame wars among birders.  

    These tensions are often at odds with a site’s goals. If we are providing support and advice to customers, we don’t want those customers to wrangle with each other. If we offer news about the latest research, we want readers to feel at ease; if we promote upcoming marches, we want our core supporters to feel comfortable and we want curious newcomers to feel welcome. 

    In a study for a conference on the History of the Web, I looked to the origins of Computer Science in Vienna (1928-1934)  for a case study of the importance of amiability in a research community and the disastrous consequences of its loss. That story has interesting implications for web environments that promote amiable interaction among disparate, difficult (and sometimes disagreeable) people.

    The Vienna Circle

    Though people had been thinking about calculating engines and thinking machines from antiquity, Computing really got going in Depression-era Vienna.  The people who worked out the theory had no interest in building machines; they wanted to puzzle out the limits of reason in the absence of divine authority. If we could not rely on God or Aristotle to tell us how to think, could we instead build arguments that were self-contained and demonstrably correct? Can we be sure that mathematics is consistent? Are there things that are true but that cannot be expressed in language? 

    The core ideas were worked out in the weekly meetings (Thursdays at 6) of a group remembered as the Vienna Circle. They got together in the office of Professor Moritz Schlick at the University of Vienna to discuss problems in philosophy, math, and language. The intersection of physics and philosophy had long been a specialty of this Vienna department, and this work had placed them among the world leaders.  Schlick’s colleague Hans Hahn was a central participant, and by 1928 Hahn brought along his graduate students Karl Menger and Kurt Gödel. Other frequent participants included philosopher Rudolf Carnap, psychologist Karl Popper, economist Ludwig von Mises (brought by his brother Frederick, a physicist),  graphic designer Otto Neurath (inventor of infographics), and architect Josef Frank (brought by his physicist brother, Phillip).  Out-of-town visitors often joined, including the young Johnny von Neumann, Alfred Tarski, and the irascible Ludwig Wittgenstein. 

    When Schlick’s office grew too dim, participants adjourned to a nearby café for additional discussion with an even larger circle of participants.  This convivial circle was far from unique.  An intersecting circle–Neurath, von Mises, Oskar Morgenstern–established the Austrian School of free-market economics. There were theatrical circles (Peter Lorre, Hedy Lamarr, Max Reinhardt), and literary circles. The café was where things happened.

    The interdisciplinarity of the group posed real challenges of temperament and understanding. Personalities were often a challenge. Gödel was convinced people were trying to poison him. Architect Josef Frank depended on contracts for public housing, which Mises opposed as wasteful. Wittgenstein’s temper had lost him his job as a secondary school teacher, and for some of these years he maintained a detailed list of whom he was willing to meet. Neurath was eager to detect muddled thinking and would interrupt a speaker with a shouted “Metaphysics!” The continuing amity of these meetings was facilitated by the personality of their leader, Moritz Schlick, who would be remembered as notably adept in keeping disagreements from becoming quarrels.

    In the Café

    The Viennese café of this era was long remembered as a particularly good place to argue with your friends, to read, and to write. Built to serve an imperial capital, the cafés found themselves with too much space and too few customers now that the Empire was gone. There was no need to turn tables: a café could only survive by coaxing customers to linger. Perhaps they would order another coffee, or one of their friends might drop by. One could play chess, or billiards, or read newspapers from abroad. Coffee was invariably served with a glass of purified spring water, still a novelty in an era in which most water was still unsafe to drink. That water glass would be refilled indefinitely. 

    In the basement of one café, the poet Jura Soyfer staged “The End Of The World,” a musical comedy in which Professor Peep has discovered a comet heading for earth.

    Prof. Peep: The comet is going to destroy everybody!

    Hitler:  Destroying everybody is my business.

    Of course, coffee can be prepared in many ways, and the Viennese café developed a broad vocabulary to represent precisely how one preferred to drink it: melange, Einspänner, Brauner, Schwarzer, Kapuziner. This extensive customization, with correspondingly esoteric conventions of service, established the café as a comfortable and personal third space, a neutral ground in which anyone who could afford a coffee would be welcome. Viennese of this era were fastidious in their use of personal titles, of which an abundance were in common use. Café waiters greeted regular customers with titles too, but were careful to address their patrons with titles a notch or two greater than they deserved. A graduate student would be Doktor, an unpaid postdoc Professor.  This assurance mattered all the more because so many members of the Circle (and so many other Viennese) came from elsewhere: Carnap from Wuppertal, Gödel from Brno, von Neumann from Budapest. No one was going to make fun of your clothes, mannerisms, or accent. Your friends wouldn’t be bothered by the pram in the hall. Everyone shared a Germanic Austrian literary and philosophical culture, not least those whose ancestors had been Eastern European Jews who knew that culture well, having read all about it in books.

    The amiability of the café circle was enhanced by its openness. Because the circle sometimes extended to architects and actors, people could feel less constrained to admit shortfalls in their understanding. It was soon discovered that marble tabletops made a useful surface for pencil sketches, serving all as an improvised and accessible blackboard.

    Comedies like “The End Of The World” and fictional newspaper sketches or feuilletons of writers like Joseph Roth and Stefan Zweig served as a second defense against disagreeable or churlish behavior. The knowledge that, if one got carried away, a parody of one’s remarks might shortly appear in Neue Freie Presse surely helped Professor Schlick keep matters in hand.

    The End Of Red Vienna

    Though Austria’s government drifted to the right after the War, Vienna’s city council had been Socialist, dedicated to public housing based on user-centered design, and embracing  ambitious programs of public outreach and adult education. In 1934 the Socialists lost a local election, and this era soon came to its end as the new administration focused on the imagined threat of the International Jewish Conspiracy. Most members of the Circle fled within months: von Neumann to Princeton, Neurath to Holland and Oxford, Popper to New Zealand, Carnap to Chicago. Prof. Schlick was murdered on the steps of the University by a student outraged by his former association with Jews.  Jura Soyfer, who wrote “The End Of The World,” died in Buchenwald.

    In 1939, von Neumann finally convinced Gödel to accept a job in Princeton. Gödel was required to pay large fines to emigrate. The officer in charge of these fees would look back on this as the best posting of his career; his name was Eichmann.

    Design for Amiability

    An impressive literature recounts those discussions and the environment that facilitated the development of computing. How can we design for amiability?  This is not just a matter of choosing rounded typefaces and a cheerful pastel palette. I believe we may identify eight distinct issues that exert design forces in usefully amiable directions.

    Seriousness: The Vienna Circle was wrestling with a notoriously difficult book—Wittgenstein’s Tractus Logico-Philosophicus—and a catalog of outstanding open questions in mathematics. They were concerned with consequential problems, not merely scoring points for debating. Constant reminders that the questions you are considering matter—not only that they are consequential or that those opposing you are scoundrels—help promote amity.

    Empiricism: The characteristic approach of the Vienna Circle demanded that knowledge be grounded either in direct observation or in rigorous reasoning. Disagreement, when it arose, could be settled by observation or by proof. If neither seemed ready to hand, the matter could not be settled. On these terms, one can seldom if ever demolish an opposing argument, and trolling is pointless.

    Abstraction: Disputes grow worse when losing the argument entails lost face or lost jobs. The Vienna Circle’s focus on theory—the limits of mathematics, the capability of language—promoted amity. Without seriousness, abstraction could have been merely academic, but the limits of reason and the consistency of mathematics were clearly serious.

    Formality: The punctilious demeanor of waiters and the elaborated rituals of coffee service helped to establish orderly attitudes amongst the argumentative participants. This stands in contrast to the contemptuous sneer that now dominates social media.  

    Schlamperei: Members of the Vienna Circle maintained a global correspondence, and they knew their work was at the frontier of research. Still, this was Vienna, at the margins of Europe: old-fashioned, frumpy, and dingy. Many participants came from even more obscure backwaters. Most or all harbored the suspicion that they were really schleppers, and a tinge of the ridiculous helped to moderate tempers. The director of “The End Of The World” had to pass the hat for money to purchase a moon for the set, and thought it was funny enough to write up for publication.

    Openness: All sorts of people were involved in discussion, anyone might join in. Each week would bring different participants. Fluid borders reduce tension, and provide opportunities to broaden the range of discussion and the terms of engagement. Low entrance friction was characteristic of the café: anyone could come, and if you came twice you were virtually a regular. Permeable boundaries and café culture made it easier for moderating influences to draw in raconteurs and storytellers to defuse awkward moments, and Vienna’s cafés had no shortage of humorists. Openness counteracts the suspicion that promoters of amiability are exerting censorship.

    Parody: The environs of the Circle—the university office and the café—were unmistakably public. There were writers about, some of them renowned humorists. The prospect that one’s bad taste or bad behavior might be ridiculed in print kept discussion within bounds. The sanction of public humiliation, however, was itself made mild by the veneer of fiction; even if you got a little carried away and a character based on you made a splash in some newspaper fiction, it wasn’t the end of the world.

    Engagement: The subject matter was important to the participants, but it was esoteric: it did not matter very much to their mothers or their siblings. A small stumble or a minor humiliation could be shrugged off in ways that major media confrontations cannot.

    I believe it is notable that this environment was designed to promote amiability through several different voices.  The café waiter flattered each newcomer and served everyone, and also kept out local pickpockets and drunks who would be mere disruptions. Schlick and other regulars kept discussion moving and on track. The fiction writers and raconteurs—perhaps the most peripheral of the participants—kept people in a good mood and reminded them that bad behavior could make anyone ridiculous.  Crucially, each of these voices were human: you could reason with them. Algorithmic or AI moderators, however clever, are seldom perceived as reasonable. The café circles had no central authority or Moderator against whom everyone’s resentments might be focused. Even after the disaster of 1934, what people remembered were those cheerful arguments.

  • Design Dialects: Breaking the Rules, Not the System

    Design Dialects: Breaking the Rules, Not the System

    “Language is not merely a set of unrelated sounds, clauses, rules, and meanings; it is a totally coherent system bound to context and behavior.” — Kenneth L. Pike

    The web has accents. So should our design systems.

    Design Systems as Living Languages

    Design systems aren’t component libraries—they’re living languages. Tokens are phonemes, components are words, patterns are phrases, layouts are sentences. The conversations we build with users become the stories our products tell.

    But here’s what we’ve forgotten: the more fluently a language is spoken, the more accents it can support without losing meaning. English in Scotland differs from English in Sydney, yet both are unmistakably English. The language adapts to context while preserving core meaning. This couldn’t be more obvious to me, a Brazilian Portuguese speaker, who learned English with an American accent, and lives in Sydney.

    Our design systems must work the same way. Rigid adherence to visual rules creates brittle systems that break under contextual pressure. Fluent systems bend without breaking.

    Consistency becomes a prison

    The promise of design systems was simple: consistent components would accelerate development and unify experiences. But as systems matured and products grew more complex, that promise has become a prison. Teams file “exception” requests by the hundreds. Products launch with workarounds instead of system components. Designers spend more time defending consistency than solving user problems.

    Our design systems must learn to speak dialects.

    A design dialect is a systematic adaptation of a design system that maintains core principles while developing new patterns for specific contexts. Unlike one-off customizations or brand themes, dialects preserve the system’s essential grammar while expanding its vocabulary to serve different users, environments, or constraints.

    When Perfect Consistency Fails

    At Booking.com, I learned this lesson the hard way. We A/B-tested everything—color, copy, button shapes, even logo colors. As a professional with a graphic design education and experience building brand style guides, I found this shocking. While everyone fell in love with Airbnb’s pristine design system, Booking grew into a giant without ever considering visual consistency.  

    The chaos taught me something profound: consistency isn’t ROI; solved problems are.

    At Shopify. Polaris () was our crown jewel—a mature design language perfect for merchants on laptops. As a product team, we were expected to adopt Polaris as-is. Then my fulfillment team hit an “Oh, Ship!” moment, as we faced the challenge of building an app for warehouse pickers using our interface on shared, battered Android scanners in dim aisles, wearing thick gloves, scanning dozens of items per minute, many with limited levels of English understanding.

    Task completion with standard Polaris: 0%.

    Every component that worked beautifully for merchants failed completely for pickers. White backgrounds created glare. 44px tap targets were invisible to gloved fingers. Sentence-case labels took too long to parse. Multi-step flows confused non-native speakers.

    We faced a choice: abandon Polaris entirely, or teach it to speak warehouse.

    The Birth of a Dialect

    We chose evolution over revolution. Working within Polaris’s core principles—clarity, efficiency, consistency—we developed what we now call a design dialect:

    ConstraintFluent MoveRationale
    Glare & low lightDark surfaces + light textReduce glare on low-DPI screens
    Gloves & haste90px tap targets (~2cm)Accommodate thick gloves
    MultilingualSingle-task screens, plain languageReduce cognitive load

    Result: Task completion jumped from 0% to 100%. Onboarding time dropped from three weeks to one shift.

    This wasn’t customization or theming—this was a dialect: a systematic adaptation that maintained Polaris’s core grammar while developing new vocabulary for a specific context. Polaris hadn’t failed; it had learned to speak warehouse.

    The Flexibility Framework

    At Atlassian, working on the Jira platform—itself a system within the larger Atlassian system—I pushed for formalizing this insight. With dozens of products sharing a design language across different codebases, we needed systematic flexibility so we built directly into our ways of working. The old model—exception requests and special approvals—was failing at scale.

    We developed the Flexibility Framework to help designers define how flexible they wanted their components to be:

    TierActionOwnership
    ConsistentAdopt unchangedPlatform locks design + code
    OpinionatedAdapt within boundsPlatform provides smart defaults, products customize
    FlexibleExtend freelyPlatform defines behavior, products own presentation

    During a navigation redesign, we tiered every element. Logo and global search stayed Consistent. Breadcrumbs and contextual actions became Flexible. Product teams could immediately see where innovation was welcome and where consistency mattered.

    The Decision Ladder

    Flexibility needs boundaries. We created a simple ladder for evaluating when rules should bend:

    Good: Ship with existing system components. Fast, consistent, proven.

    Better: Stretch a component slightly. Document the change. Contribute improvements back to the system for all to use.

    Best: Prototype the ideal experience first. If user testing validates the benefit, update the system to support it.

    The key question: “Which option lets users succeed fastest?”

    Rules are tools, not relics.

    Unity Beats Uniformity

    Gmail, Drive, and Maps are unmistakably Google—yet each speaks with its own accent. They achieve unity through shared principles, not cloned components. One extra week of debate over button color costs roughly $30K in engineer time.

    Unity is a brand outcome; fluency is a user outcome. When the two clash, side with the user.

    Governance Without Gates

    How do you maintain coherence while enabling dialects? Treat your system like a living vocabulary:

    Document every deviation – e.g., dialects/warehouse.md with before/after screenshots and rationale.

    Promote shared patterns – when three teams adopt a dialect independently, review it for core inclusion.

    Deprecate with context – retire old idioms via flags and migration notes, never a big-bang purge.

    A living dictionary scales better than a frozen rulebook.

    Start Small: Your First Dialect

    Ready to introduce dialects? Start with one broken experience:

    This week: Find one user flow where perfect consistency blocks task completion. Could be mobile users struggling with desktop-sized components, or accessibility needs your standard patterns don’t address.

    Document the context: What makes standard patterns fail here? Environmental constraints? User capabilities? Task urgency?

    Design one systematic change: Focus on behavior over aesthetics. If gloves are the problem, bigger targets aren’t “”breaking the system””—they’re serving the user. Earn the variations and make them intentional.

    Test and measure: Does the change improve task completion? Time to productivity? User satisfaction?

    Show the savings: If that dialect frees even half a sprint, fluency has paid for itself.

    Beyond the Component Library

    We’re not managing design systems anymore—we’re cultivating design languages. Languages that grow with their speakers. Languages that develop accents without losing meaning. Languages that serve human needs over aesthetic ideals.

    The warehouse workers who went from 0% to 100% task completion didn’t care that our buttons broke the style guide. They cared that the buttons finally worked.

    Your users feel the same way. Give your system permission to speak their language.

  • An Holistic Framework for Shared Design Leadership

    An Holistic Framework for Shared Design Leadership

    Picture this: You’re in a meeting room at your tech company, and two people are having what looks like the same conversation about the same design problem. One is talking about whether the team has the right skills to tackle it. The other is diving deep into whether the solution actually solves the user’s problem. Same room, same problem, completely different lenses.

    This is the beautiful, sometimes messy reality of having both a Design Manager and a Lead Designer on the same team. And if you’re wondering how to make this work without creating confusion, overlap, or the dreaded “too many cooks” scenario, you’re asking the right question.

    The traditional answer has been to draw clean lines on an org chart. The Design Manager handles people, the Lead Designer handles craft. Problem solved, right? Except clean org charts are fantasy. In reality, both roles care deeply about team health, design quality, and shipping great work. 

    The magic happens when you embrace the overlap instead of fighting it—when you start thinking of your design org as a design organism.

    The Anatomy of a Healthy Design Team

    Here’s what I’ve learned from years of being on both sides of this equation: think of your design team as a living organism. The Design Manager tends to the mind (the psychological safety, the career growth, the team dynamics). The Lead Designer tends to the body (the craft skills, the design standards, the hands-on work that ships to users).

    But just like mind and body aren’t completely separate systems, so, too, do these roles overlap in important ways. You can’t have a healthy person without both working in harmony. The trick is knowing where those overlaps are and how to navigate them gracefully.

    When we look at how healthy teams actually function, three critical systems emerge. Each requires both roles to work together, but with one taking primary responsibility for keeping that system strong.

    The Nervous System: People & Psychology

    Primary caretaker: Design Manager
    Supporting role: Lead Designer

    The nervous system is all about signals, feedback, and psychological safety. When this system is healthy, information flows freely, people feel safe to take risks, and the team can adapt quickly to new challenges.

    The Design Manager is the primary caretaker here. They’re monitoring the team’s psychological pulse, ensuring feedback loops are healthy, and creating the conditions for people to grow. They’re hosting career conversations, managing workload, and making sure no one burns out.

    But the Lead Designer plays a crucial supporting role. They’re providing sensory input about craft development needs, spotting when someone’s design skills are stagnating, and helping identify growth opportunities that the Design Manager might miss.

    Design Manager tends to:

    • Career conversations and growth planning
    • Team psychological safety and dynamics
    • Workload management and resource allocation
    • Performance reviews and feedback systems
    • Creating learning opportunities

    Lead Designer supports by:

    • Providing craft-specific feedback on team member development
    • Identifying design skill gaps and growth opportunities
    • Offering design mentorship and guidance
    • Signaling when team members are ready for more complex challenges

    The Muscular System: Craft & Execution

    Primary caretaker: Lead Designer
    Supporting role: Design Manager

    The muscular system is about strength, coordination, and skill development. When this system is healthy, the team can execute complex design work with precision, maintain consistent quality, and adapt their craft to new challenges.

    The Lead Designer is the primary caretaker here. They’re setting design standards, providing craft coaching, and ensuring that shipping work meets the quality bar. They’re the ones who can tell you if a design decision is sound or if we’re solving the right problem.

    But the Design Manager plays a crucial supporting role. They’re ensuring the team has the resources and support to do their best craft work, like proper nutrition and recovery time for an athlete.

    Lead Designer tends to:

    • Definition of design standards and system usage
    • Feedback on what design work meets the standard
    • Experience direction for the product
    • Design decisions and product-wide alignment
    • Innovation and craft advancement

    Design Manager supports by:

    • Ensuring design standards are understood and adopted across the team
    • Confirming experience direction is being followed
    • Supporting practices and systems that scale without bottlenecking
    • Facilitating design alignment across teams
    • Providing resources and removing obstacles to great craft work

    The Circulatory System: Strategy & Flow

    Shared caretakers: Both Design Manager and Lead Designer

    The circulatory system is about how information, decisions, and energy flow through the team. When this system is healthy, strategic direction is clear, priorities are aligned, and the team can respond quickly to new opportunities or challenges.

    This is where true partnership happens. Both roles are responsible for keeping the circulation strong, but they’re bringing different perspectives to the table.

    Lead Designer contributes:

    • User needs are met by the product
    • Overall product quality and experience
    • Strategic design initiatives
    • Research-based user needs for each initiative

    Design Manager contributes:

    • Communication to team and stakeholders
    • Stakeholder management and alignment
    • Cross-functional team accountability
    • Strategic business initiatives

    Both collaborate on:

    • Co-creation of strategy with leadership
    • Team goals and prioritization approach
    • Organizational structure decisions
    • Success measures and frameworks

    Keeping the Organism Healthy

    The key to making this partnership sing is understanding that all three systems need to work together. A team with great craft skills but poor psychological safety will burn out. A team with great culture but weak craft execution will ship mediocre work. A team with both but poor strategic circulation will work hard on the wrong things.

    Be Explicit About Which System You’re Tending

    When you’re in a meeting about a design problem, it helps to acknowledge which system you’re primarily focused on. “I’m thinking about this from a team capacity perspective” (nervous system) or “I’m looking at this through the lens of user needs” (muscular system) gives everyone context for your input.

    This isn’t about staying in your lane. It’s about being transparent as to which lens you’re using, so the other person knows how to best add their perspective.

    Create Healthy Feedback Loops

    The most successful partnerships I’ve seen establish clear feedback loops between the systems:

    Nervous system signals to muscular system: “The team is struggling with confidence in their design skills” → Lead Designer provides more craft coaching and clearer standards.

    Muscular system signals to nervous system: “The team’s craft skills are advancing faster than their project complexity” → Design Manager finds more challenging growth opportunities.

    Both systems signal to circulatory system: “We’re seeing patterns in team health and craft development that suggest we need to adjust our strategic priorities.”

    Handle Handoffs Gracefully

    The most critical moments in this partnership are when something moves from one system to another. This might be when a design standard (muscular system) needs to be rolled out across the team (nervous system), or when a strategic initiative (circulatory system) needs specific craft execution (muscular system).

    Make these transitions explicit. “I’ve defined the new component standards. Can you help me think through how to get the team up to speed?” or “We’ve agreed on this strategic direction. I’m going to focus on the specific user experience approach from here.”

    Stay Curious, Not Territorial

    The Design Manager who never thinks about craft, or the Lead Designer who never considers team dynamics, is like a doctor who only looks at one body system. Great design leadership requires both people to care about the whole organism, even when they’re not the primary caretaker.

    This means asking questions rather than making assumptions. “What do you think about the team’s craft development in this area?” or “How do you see this impacting team morale and workload?” keeps both perspectives active in every decision.

    When the Organism Gets Sick

    Even with clear roles, this partnership can go sideways. Here are the most common failure modes I’ve seen:

    System Isolation

    The Design Manager focuses only on the nervous system and ignores craft development. The Lead Designer focuses only on the muscular system and ignores team dynamics. Both people retreat to their comfort zones and stop collaborating.

    The symptoms: Team members get mixed messages, work quality suffers, morale drops.

    The treatment: Reconnect around shared outcomes. What are you both trying to achieve? Usually it’s great design work that ships on time from a healthy team. Figure out how both systems serve that goal.

    Poor Circulation

    Strategic direction is unclear, priorities keep shifting, and neither role is taking responsibility for keeping information flowing.

    The symptoms: Team members are confused about priorities, work gets duplicated or dropped, deadlines are missed.

    The treatment: Explicitly assign responsibility for circulation. Who’s communicating what to whom? How often? What’s the feedback loop?

    Autoimmune Response

    One person feels threatened by the other’s expertise. The Design Manager thinks the Lead Designer is undermining their authority. The Lead Designer thinks the Design Manager doesn’t understand craft.

    The symptoms: Defensive behavior, territorial disputes, team members caught in the middle.

    The treatment: Remember that you’re both caretakers of the same organism. When one system fails, the whole team suffers. When both systems are healthy, the team thrives.

    The Payoff

    Yes, this model requires more communication. Yes, it requires both people to be secure enough to share responsibility for team health. But the payoff is worth it: better decisions, stronger teams, and design work that’s both excellent and sustainable.

    When both roles are healthy and working well together, you get the best of both worlds: deep craft expertise and strong people leadership. When one person is out sick, on vacation, or overwhelmed, the other can help maintain the team’s health. When a decision requires both the people perspective and the craft perspective, you’ve got both right there in the room.

    Most importantly, the framework scales. As your team grows, you can apply the same system thinking to new challenges. Need to launch a design system? Lead Designer tends to the muscular system (standards and implementation), Design Manager tends to the nervous system (team adoption and change management), and both tend to circulation (communication and stakeholder alignment).

    The Bottom Line

    The relationship between a Design Manager and Lead Designer isn’t about dividing territories. It’s about multiplying impact. When both roles understand they’re tending to different aspects of the same healthy organism, magic happens.

    The mind and body work together. The team gets both the strategic thinking and the craft excellence they need. And most importantly, the work that ships to users benefits from both perspectives.

    So the next time you’re in that meeting room, wondering why two people are talking about the same problem from different angles, remember: you’re watching shared leadership in action. And if it’s working well, both the mind and body of your design team are getting stronger.

  • From Beta to Bedrock: Build Products that Stick.

    From Beta to Bedrock: Build Products that Stick.

    As a product builder over too many years to mention, I’ve lost count of the number of times I’ve seen promising ideas go from zero to hero in a few weeks, only to fizzle out within months.

    Financial products, which is the field I work in, are no exception. With people’s real hard-earned money on the line, user expectations running high, and a crowded market, it’s tempting to throw as many features at the wall as possible and hope something sticks. But this approach is a recipe for disaster. Here’s why:

    The pitfalls of feature-first development

    When you start building a financial product from the ground up, or are migrating existing customer journeys from paper or telephony channels onto online banking or mobile apps, it’s easy to get caught up in the excitement of creating new features. You might think, “If I can just add one more thing that solves this particular user problem, they’ll love me!” But what happens when you inevitably hit a roadblock because the narcs (your security team!) don’t like it? When a hard-fought feature isn’t as popular as you thought, or it breaks due to unforeseen complexity?

    This is where the concept of Minimum Viable Product (MVP) comes in. Jason Fried’s book Getting Real and his podcast Rework often touch on this idea, even if he doesn’t always call it that. An MVP is a product that provides just enough value to your users to keep them engaged, but not so much that it becomes overwhelming or difficult to maintain. It sounds like an easy concept but it requires a razor sharp eye, a ruthless edge and having the courage to stick by your opinion because it is easy to be seduced by “the Columbo Effect”… when there’s always “just one more thing…” that someone wants to add.

    The problem with most finance apps, however, is that they often become a reflection of the internal politics of the business rather than an experience solely designed around the customer. This means that the focus is on delivering as many features and functionalities as possible to satisfy the needs and desires of competing internal departments, rather than providing a clear value proposition that is focused on what the people out there in the real world want. As a result, these products can very easily bloat to become a mixed bag of confusing, unrelated and ultimately unlovable customer experiences—a feature salad, you might say.

    The importance of bedrock

    So what’s a better approach? How can we build products that are stable, user-friendly, and—most importantly—stick?

    That’s where the concept of “bedrock” comes in. Bedrock is the core element of your product that truly matters to users. It’s the fundamental building block that provides value and stays relevant over time.

    In the world of retail banking, which is where I work, the bedrock has got to be in and around the regular servicing journeys. People open their current account once in a blue moon but they look at it every day. They sign up for a credit card every year or two, but they check their balance and pay their bill at least once a month.

    Identifying the core tasks that people want to do and then relentlessly striving to make them easy to do, dependable, and trustworthy is where the gravy’s at.

    But how do you get to bedrock? By focusing on the “MVP” approach, prioritizing simplicity, and iterating towards a clear value proposition. This means cutting out unnecessary features and focusing on delivering real value to your users.

    It also means having some guts, because your colleagues might not always instantly share your vision to start with. And controversially, sometimes it can even mean making it clear to customers that you’re not going to come to their house and make their dinner. The occasional “opinionated user interface design” (i.e. clunky workaround for edge cases) might sometimes be what you need to use to test a concept or buy you space to work on something more important.

    Practical strategies for building financial products that stick

    So what are the key strategies I’ve learned from my own experience and research?

    1. Start with a clear “why”: What problem are you trying to solve? For whom? Make sure your mission is crystal clear before building anything. Make sure it aligns with your company’s objectives, too.
    2. Focus on a single, core feature and obsess on getting that right before moving on to something else: Resist the temptation to add too many features at once. Instead, choose one that delivers real value and iterate from there.
    3. Prioritize simplicity over complexity: Less is often more when it comes to financial products. Cut out unnecessary bells and whistles and keep the focus on what matters most.
    4. Embrace continuous iteration: Bedrock isn’t a fixed destination—it’s a dynamic process. Continuously gather user feedback, refine your product, and iterate towards that bedrock state.
    5. Stop, look and listen: Don’t just test your product as part of your delivery process—test it repeatedly in the field. Use it yourself. Run A/B tests. Gather user feedback. Talk to people who use it, and refine accordingly.

    The bedrock paradox

    There’s an interesting paradox at play here: building towards bedrock means sacrificing some short-term growth potential in favour of long-term stability. But the payoff is worth it—products built with a focus on bedrock will outlast and outperform their competitors, and deliver sustained value to users over time.

    So, how do you start your journey towards bedrock? Take it one step at a time. Start by identifying those core elements that truly matter to your users. Focus on building and refining a single, powerful feature that delivers real value. And above all, test obsessively—for, in the words of Abraham Lincoln, Alan Kay, or Peter Drucker (whomever you believe!!), “The best way to predict the future is to create it.”

  • 15 Famous Places We Almost Lost Forever

    15 Famous Places We Almost Lost Forever

    Some landmarks feel so permanent that imagining the world without them is nearly impossible. Yet plenty of places we now treat as untouchable came surprisingly close to disappearing. Developers wanted to replace beloved buildings, engineers proposed flooding extraordinary landscapes, and wars, fires, neglect, and unstable foundations nearly finished the job elsewhere. In several cases, preservationists had to fight for years before anyone agreed that saving the old thing was better than replacing it with something new. Others survived because of enormous engineering projects or remarkably fortunate last-minute interventions. Today, millions of people visit these places without realizing how differently things could have turned out. Here are 15 famous places we almost lost forever.

    The post 15 Famous Places We Almost Lost Forever appeared first on Den of Geek.

    For more than 50 years, the X-Men have been the subject of some of the best superhero stories ever made. This part and parcel for a world defined by the always compelling mutant metaphor, in which social outcasts fight to save a world that fears and hates them, their ever-cool costumes, and their ever-more-complicated romantic entanglements.

    And yet, the X-Men are still superheroes in an ongoing soap opera. That means they’ve had many, many embarrassing moments. Sometimes these embarrassments stem from compelling character choices (e.g., teenage Jean Grey using her powers to out Iceman), and sometimes they’re just products of their time (e.g., Dazzler). But some embarrassments are just embarrassing—useful reminders that even the coolest kids do things that are dumb from time to time.

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    Marvel Comics

    1. Logan Is Named By a Leprechaun

    Wolverine is the best at what he does, and what he does is sell a whole lot of comic books. It’s easy to see why Logan became the definitive X-Men character, what with his claws and his attitude and his improbable hair-do. Logan hits that sweet spot between tragic hero forever unable to atone for the bad things he’s done and unrepentant romantic; a man who longs for a love he can never have.

    Still… doesn’t change the fact he he got his name from a leprechaun. Yeah…

    In 1977’s Uncanny X-Men #103 by Chris Claremont and Dave Cockrum, the X-Men visit Cassidy’s Keep, the ancestral home of Irish teammate Banshee and his cousin/general enemy Black Tom. When Juggernaut starts making trouble, a leprechaun called Padraic offers to help Wolverine get into the battle, addressing the Canucklehead as “Mr. Logan.” Wolverine responds in shock (in part because, as he tells the leprechaun standing in front of him, he doesn’t believe in leprechauns). Fortunately, he doesn’t have to deal with the reveal at that moment, because it will take several more issues before even Wolverine’s teammates learn about Logan’s name, and it will take decades for readers to find out where the name came from.

    kitty pryde is racist in X-Men God Loves Man Kills
    Marvel Comics

    2. Kitty Pryde Says Slurs. A Lot.

    Wolverine may be the definitive X-Men character, but Kitty Pryde is the ideal X-Men character. When she debuted in 1979’s Uncanny X-Men #129 by Claremont and John Byrne, Kitty was an awkward 13-year-old trying to make sense of her powers. She came of age with the X-Men, and while she’s one of the team’s most complex and compelling characters, she had a lot of growing pains along the way. We could include on this list her habit of changing codename and costume every couple of issues, or her romance with the legally adult Colossus (that’s obviously more on Claremont than on the character).

    But easily the most embarrassing part of Kitty Pryde’s past involves her habit of using racial slurs, including the N-word. It occurs most notably in three issues written by Chris Claremont: 1982’s God Loves, Man Kills (illustrated by Brent Anderson), 1985’s Uncanny X-Men #196 (illustrated by John Romita Jr.), and 1986’s New Mutants #45 (illustrated by Jackson Guice). In each instance, Kitty’s trying to make a point about the bigotry faced by mutants, arguing that humanity too often treats people as subhuman. While we believe that a privileged kid could be so reckless with her language (and, to be fair, Kitty is Jewish, and often included slurs against her people in her litanies). But that doesn’t make these instances any less embarrassing to read today.

    New Mutants Graduation Costumes
    Marvel Comics

    3. The New Mutants Graduation Costumes

    Even though she vociferously refused to be counted among their roster, Kitty Pryde set the model for the teenagers who would become the New Mutants. Launched in an original graphic novel in 1982, the New Mutants represented the second generation of students at Xavier’s school. Although Professor X initially insisted that they never become superheroes like their predecessors, the New Mutants absolutely do find themselves constantly forced to use their powers against bad guys, walking in the footsteps of the original X-Men.

    And Xavier always knew that would happen. So when their elders disappear in Uncanny X-Men Annual #10, written by Claremont and penciled by Arthur Adams, the New Mutants decide it’s time to join the big leagues. Declaring themselves the new X-Men, the team dons “graduation uniforms,” perhaps the ugliest set of costumes ever seen in a mainstream comic. It’s not just the obvious stereotypes chosen for Mirage and Karma. It’s also the extraneous pouches on Cypher’s tech jacket, the bland nothing that is Wolfsbane’s get-up, and, worst of all, the helmet that Cannonball wears—as if no one realized he’s nigh-invincible when he’s blasting! Fortunately, the graduation uniforms only make a few appearances, and the team settles into less ugly suits. At least until Cable shows up and changes them into X-Force

    Angel and Husk in X-Men Comics
    Marvel Comics

    4. Angel and Husk and Husk’s Mom

    This entire list could consist of nothing but moments from writer Chuck Austen’s run on Uncanny X-Men, which lasted from 2002’s issue #410 to issue #443 in 2004. On one hand, Austen had been dealt a tough hand, forced to write the companion book to Grant Morrison‘s dazzling New X-Men. On the other hand, Austen responded with his own set of big swings, which often felt less like mind-benders and more like head-scratchers. Austen gave us “The Draco,” which retcons Nightcrawler from being a pure-hearted guy who happens to look like the devil, thus proving that no one should be judged for their appearances, into the actual scion of Satan, thus proving that “no, you were right to judge him.” Austen also gave us the time the X-Men almost built Iceman a new body out of their collected urine, a plan proposed by one Alex Summers (more about him shortly).

    But the most embarrassing part of Austen’s run involved the romance between founding X-Man Angel and Husk, younger sister of New Mutants founder Cannonball. Thanks its sliding timeline, it’s sometimes hard to track the ages of various characters. But the relative math going from original member Angel (who even had a superhero career before joining the team) to the little sister of a New Mutant is enough to solidify a substantial age gap between the two. Worse, Angel and Husk consummates their romance at the end of the “She Lies With Angels” storyline (Uncanny X-Men #437–441, penciled by Salvador Larroca) when he lifts her up in the air above the Guthrie family home. We don’t see what happens, but we do see the various articles of clothing that drop to the ground, raining not just on their teammates but also on Husk’s mother.

    Havok in Ultimate Avengers
    Marvel Comics

    5. Havok. Just… Havok.

    It can’t be easy to live in the shadow of Cyclops, the leader of the X-Men and one of the most respected heroes in the Marvel Universe. But even if we cut him a little slack, Alex Summers, aka Havok, finds incredible new ways of making himself look stupid. Introduced in X-Men #54 by Arnold Drake and Don Heck, Havok joined after the initial team and before the 1970s relaunch. Moreover, he was a fun, if indistinct character in those days, more interesting for his relationship to Cyclops and his on-again, off-again girlfriend Polaris.

    But since then, Alex’s life has been a cavalcade of mistakes. There was that time he became the Goblin King, the right-hand man to the evil Goblin Queen Madelyne Pryor. He gets himself brainwashed into serving the anti-mutant government of Genosha, and later takes a job leading the U.S. government-sponsored team X-Factor. He fumbles his relationship with Polaris time and again, tries and fails to be a good step-dad while dating a nurse named Annie, and eventually gets sent to an alternate universe filled with evil doppelgängers of his friends and allies. More recently, Alex gave a big speech about how “mutant” is a slur and shouldn’t be used and then signed up for a new incarnation of X-Factor, this one run by obviously amoral tech bros. Havok, we love you, but you’re an idiot.

    The post The Most Embarrassing Moments in X-Men History appeared first on Den of Geek.

  • Coyote vs. Acme Reception Confirms the Looney Tunes Have Long Deserved Better

    Coyote vs. Acme Reception Confirms the Looney Tunes Have Long Deserved Better

    There are several ways to look at the Coyote vs. Acme opening this past weekend. The first is that the movie performed well past expectations and deserves a carrot in addition to a well-timed “what’s up doc?” for its effort. This picture was, after all, generally projected to earn between $11 and $14 million by […]

    The post Coyote vs. Acme Reception Confirms the Looney Tunes Have Long Deserved Better appeared first on Den of Geek.

    For more than 50 years, the X-Men have been the subject of some of the best superhero stories ever made. This part and parcel for a world defined by the always compelling mutant metaphor, in which social outcasts fight to save a world that fears and hates them, their ever-cool costumes, and their ever-more-complicated romantic entanglements.

    And yet, the X-Men are still superheroes in an ongoing soap opera. That means they’ve had many, many embarrassing moments. Sometimes these embarrassments stem from compelling character choices (e.g., teenage Jean Grey using her powers to out Iceman), and sometimes they’re just products of their time (e.g., Dazzler). But some embarrassments are just embarrassing—useful reminders that even the coolest kids do things that are dumb from time to time.

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    Marvel Comics

    1. Logan Is Named By a Leprechaun

    Wolverine is the best at what he does, and what he does is sell a whole lot of comic books. It’s easy to see why Logan became the definitive X-Men character, what with his claws and his attitude and his improbable hair-do. Logan hits that sweet spot between tragic hero forever unable to atone for the bad things he’s done and unrepentant romantic; a man who longs for a love he can never have.

    Still… doesn’t change the fact he he got his name from a leprechaun. Yeah…

    In 1977’s Uncanny X-Men #103 by Chris Claremont and Dave Cockrum, the X-Men visit Cassidy’s Keep, the ancestral home of Irish teammate Banshee and his cousin/general enemy Black Tom. When Juggernaut starts making trouble, a leprechaun called Padraic offers to help Wolverine get into the battle, addressing the Canucklehead as “Mr. Logan.” Wolverine responds in shock (in part because, as he tells the leprechaun standing in front of him, he doesn’t believe in leprechauns). Fortunately, he doesn’t have to deal with the reveal at that moment, because it will take several more issues before even Wolverine’s teammates learn about Logan’s name, and it will take decades for readers to find out where the name came from.

    kitty pryde is racist in X-Men God Loves Man Kills
    Marvel Comics

    2. Kitty Pryde Says Slurs. A Lot.

    Wolverine may be the definitive X-Men character, but Kitty Pryde is the ideal X-Men character. When she debuted in 1979’s Uncanny X-Men #129 by Claremont and John Byrne, Kitty was an awkward 13-year-old trying to make sense of her powers. She came of age with the X-Men, and while she’s one of the team’s most complex and compelling characters, she had a lot of growing pains along the way. We could include on this list her habit of changing codename and costume every couple of issues, or her romance with the legally adult Colossus (that’s obviously more on Claremont than on the character).

    But easily the most embarrassing part of Kitty Pryde’s past involves her habit of using racial slurs, including the N-word. It occurs most notably in three issues written by Chris Claremont: 1982’s God Loves, Man Kills (illustrated by Brent Anderson), 1985’s Uncanny X-Men #196 (illustrated by John Romita Jr.), and 1986’s New Mutants #45 (illustrated by Jackson Guice). In each instance, Kitty’s trying to make a point about the bigotry faced by mutants, arguing that humanity too often treats people as subhuman. While we believe that a privileged kid could be so reckless with her language (and, to be fair, Kitty is Jewish, and often included slurs against her people in her litanies). But that doesn’t make these instances any less embarrassing to read today.

    New Mutants Graduation Costumes
    Marvel Comics

    3. The New Mutants Graduation Costumes

    Even though she vociferously refused to be counted among their roster, Kitty Pryde set the model for the teenagers who would become the New Mutants. Launched in an original graphic novel in 1982, the New Mutants represented the second generation of students at Xavier’s school. Although Professor X initially insisted that they never become superheroes like their predecessors, the New Mutants absolutely do find themselves constantly forced to use their powers against bad guys, walking in the footsteps of the original X-Men.

    And Xavier always knew that would happen. So when their elders disappear in Uncanny X-Men Annual #10, written by Claremont and penciled by Arthur Adams, the New Mutants decide it’s time to join the big leagues. Declaring themselves the new X-Men, the team dons “graduation uniforms,” perhaps the ugliest set of costumes ever seen in a mainstream comic. It’s not just the obvious stereotypes chosen for Mirage and Karma. It’s also the extraneous pouches on Cypher’s tech jacket, the bland nothing that is Wolfsbane’s get-up, and, worst of all, the helmet that Cannonball wears—as if no one realized he’s nigh-invincible when he’s blasting! Fortunately, the graduation uniforms only make a few appearances, and the team settles into less ugly suits. At least until Cable shows up and changes them into X-Force

    Angel and Husk in X-Men Comics
    Marvel Comics

    4. Angel and Husk and Husk’s Mom

    This entire list could consist of nothing but moments from writer Chuck Austen’s run on Uncanny X-Men, which lasted from 2002’s issue #410 to issue #443 in 2004. On one hand, Austen had been dealt a tough hand, forced to write the companion book to Grant Morrison‘s dazzling New X-Men. On the other hand, Austen responded with his own set of big swings, which often felt less like mind-benders and more like head-scratchers. Austen gave us “The Draco,” which retcons Nightcrawler from being a pure-hearted guy who happens to look like the devil, thus proving that no one should be judged for their appearances, into the actual scion of Satan, thus proving that “no, you were right to judge him.” Austen also gave us the time the X-Men almost built Iceman a new body out of their collected urine, a plan proposed by one Alex Summers (more about him shortly).

    But the most embarrassing part of Austen’s run involved the romance between founding X-Man Angel and Husk, younger sister of New Mutants founder Cannonball. Thanks its sliding timeline, it’s sometimes hard to track the ages of various characters. But the relative math going from original member Angel (who even had a superhero career before joining the team) to the little sister of a New Mutant is enough to solidify a substantial age gap between the two. Worse, Angel and Husk consummates their romance at the end of the “She Lies With Angels” storyline (Uncanny X-Men #437–441, penciled by Salvador Larroca) when he lifts her up in the air above the Guthrie family home. We don’t see what happens, but we do see the various articles of clothing that drop to the ground, raining not just on their teammates but also on Husk’s mother.

    Havok in Ultimate Avengers
    Marvel Comics

    5. Havok. Just… Havok.

    It can’t be easy to live in the shadow of Cyclops, the leader of the X-Men and one of the most respected heroes in the Marvel Universe. But even if we cut him a little slack, Alex Summers, aka Havok, finds incredible new ways of making himself look stupid. Introduced in X-Men #54 by Arnold Drake and Don Heck, Havok joined after the initial team and before the 1970s relaunch. Moreover, he was a fun, if indistinct character in those days, more interesting for his relationship to Cyclops and his on-again, off-again girlfriend Polaris.

    But since then, Alex’s life has been a cavalcade of mistakes. There was that time he became the Goblin King, the right-hand man to the evil Goblin Queen Madelyne Pryor. He gets himself brainwashed into serving the anti-mutant government of Genosha, and later takes a job leading the U.S. government-sponsored team X-Factor. He fumbles his relationship with Polaris time and again, tries and fails to be a good step-dad while dating a nurse named Annie, and eventually gets sent to an alternate universe filled with evil doppelgängers of his friends and allies. More recently, Alex gave a big speech about how “mutant” is a slur and shouldn’t be used and then signed up for a new incarnation of X-Factor, this one run by obviously amoral tech bros. Havok, we love you, but you’re an idiot.

    The post The Most Embarrassing Moments in X-Men History appeared first on Den of Geek.