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  • 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.

  • 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.

  • Hokum Review: Adam Scott’s Irish Holiday Is Like a (Grim) Fairy Tale

    Hokum Review: Adam Scott’s Irish Holiday Is Like a (Grim) Fairy Tale

    There might be something in the air in Ireland. It’s in the water and the soil too. Despite being surrounded by an endless, rugged sea of green, or perhaps because of that emerald desolation, it is a land marked in the popular imagination by centuries of hardship and sorrow. Some would even claim it’s haunted. […]

    The post Hokum Review: Adam Scott’s Irish Holiday Is Like a (Grim) Fairy Tale appeared first on Den of Geek.

    After two years and a title change, the third season of Interview with the Vampire, now rebranded as The Vampire Lestat in honor of the second novel in Anne Rice’s Vampire Chronicles series, will finally hit our screens. And AMC is leaning hard into the rock star agenda, dropping a new song, some extremely campy opening credits, and a date for when we can expect the tour, er….the new season to officially begin.

    The series will follow Lestat de Lioncourt as he takes center stage in his own narrative, an attempt to set the record straight after the release of Daniel Molly’s infamous book, Interview with the Vampire. That he does this by deciding to embark on a multi-city tour with his new rock band is perhaps the most Lestat-coded choice ever, but it’s also pretty much guaranteed to be a good time. Billing the titular character as the “world’s first immortal rockstar” in the press materials promoting the show’s return, the network is promising “a sexy pilgrimage across space, time, and trauma” as Lestat tours the nation and is haunted by various “muses” from his past.

    cnx.cmd.push(function() {
    cnx({
    playerId: “106e33c0-3911-473c-b599-b1426db57530”,

    }).render(“0270c398a82f44f49c23c16122516796”);
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    Anne Rice readers already know that this adventure won’t be for the faint of heart. While it recounts Lestat’s life as a mortal and his early years as a vampire, the novel also introduces key figures from his past, including Gabrielle, Magnus, Marius, Nicolas, and Those Who Must Be Kept, who all have a major role to play in the franchise’s future.

    In addition to confirming that The Vampire Lestat would officially premiere in June, AMC also dropped the series’ new opening titles, which feature another would-be banger from Lestat’s musical catalog. The slightly shortened track, called “All Fall Down,” is composed by Daniel Hart and performed by series star Sam Reid. Like Lestat’s previous single, “Long Face,” the track is now available on all major streaming platforms, with the promise of even more songs from everyone’s favorite immortal rocker to come.

    In the new credits, “All Fall Down” plays over a montage of various character images and possible Easter eggs from the forthcoming season. (No idea what’s up with the ice cream scoop, but those random road signs are definitely going to be song titles. Bet.) 

    Everything we’ve seen about this season thus far is dripping with glam rock, full-on brat prince vibes, right down to the supposed quotes from the man (vampire) himself slagging off his production partner (“Predictable”) as the show blurs the line between fictional character and real-life celebrity. How much crazier will this get in the lead-up to the premiere? Your guess is as good as ours, but it’s bound to be a wild ride.

    The Vampire Lestat will premiere June 7 on AMC and AMC+. 

    The post The Vampire Lestat’s Tour Will Hit AMC This Summer appeared first on Den of Geek.

  • Designing for the Unexpected

    Designing for the Unexpected

    I’m not sure when I first heard this quote, but it’s something that has stayed with me over the years. How do you create services for situations you can’t imagine? Or design products that work on devices yet to be invented?

    Flash, Photoshop, and responsive design

    When I first started designing websites, my go-to software was Photoshop. I created a 960px canvas and set about creating a layout that I would later drop content in. The development phase was about attaining pixel-perfect accuracy using fixed widths, fixed heights, and absolute positioning.

    Ethan Marcotte’s talk at An Event Apart and subsequent article “Responsive Web Design” in A List Apart in 2010 changed all this. I was sold on responsive design as soon as I heard about it, but I was also terrified. The pixel-perfect designs full of magic numbers that I had previously prided myself on producing were no longer good enough.

    The fear wasn’t helped by my first experience with responsive design. My first project was to take an existing fixed-width website and make it responsive. What I learned the hard way was that you can’t just add responsiveness at the end of a project. To create fluid layouts, you need to plan throughout the design phase.

    A new way to design

    Designing responsive or fluid sites has always been about removing limitations, producing content that can be viewed on any device. It relies on the use of percentage-based layouts, which I initially achieved with native CSS and utility classes:

    .column-span-6 {
      width: 49%;
      float: left;
      margin-right: 0.5%;
      margin-left: 0.5%;
    }
    
    
    .column-span-4 {
      width: 32%;
      float: left;
      margin-right: 0.5%;
      margin-left: 0.5%;
    }
    
    .column-span-3 {
      width: 24%;
      float: left;
      margin-right: 0.5%;
      margin-left: 0.5%;
    }

    Then with Sass so I could take advantage of @includes to re-use repeated blocks of code and move back to more semantic markup:

    .logo {
      @include colSpan(6);
    }
    
    .search {
      @include colSpan(3);
    }
    
    .social-share {
      @include colSpan(3);
    }

    Media queries

    The second ingredient for responsive design is media queries. Without them, content would shrink to fit the available space regardless of whether that content remained readable (The exact opposite problem occurred with the introduction of a mobile-first approach).

    Media queries prevented this by allowing us to add breakpoints where the design could adapt. Like most people, I started out with three breakpoints: one for desktop, one for tablets, and one for mobile. Over the years, I added more and more for phablets, wide screens, and so on. 

    For years, I happily worked this way and improved both my design and front-end skills in the process. The only problem I encountered was making changes to content, since with our Sass grid system in place, there was no way for the site owners to add content without amending the markup—something a small business owner might struggle with. This is because each row in the grid was defined using a div as a container. Adding content meant creating new row markup, which requires a level of HTML knowledge.

    Row markup was a staple of early responsive design, present in all the widely used frameworks like Bootstrap and Skeleton.

    1 of 7
    2 of 7
    3 of 7
    4 of 7
    5 of 7
    6 of 7
    7 of 7

    Another problem arose as I moved from a design agency building websites for small- to medium-sized businesses, to larger in-house teams where I worked across a suite of related sites. In those roles I started to work much more with reusable components. 

    Our reliance on media queries resulted in components that were tied to common viewport sizes. If the goal of component libraries is reuse, then this is a real problem because you can only use these components if the devices you’re designing for correspond to the viewport sizes used in the pattern library—in the process not really hitting that “devices that don’t yet exist”  goal.

    Then there’s the problem of space. Media queries allow components to adapt based on the viewport size, but what if I put a component into a sidebar, like in the figure below?

    Container queries: our savior or a false dawn?

    Container queries have long been touted as an improvement upon media queries, but at the time of writing are unsupported in most browsers. There are JavaScript workarounds, but they can create dependency and compatibility issues. The basic theory underlying container queries is that elements should change based on the size of their parent container and not the viewport width, as seen in the following illustrations.

    One of the biggest arguments in favor of container queries is that they help us create components or design patterns that are truly reusable because they can be picked up and placed anywhere in a layout. This is an important step in moving toward a form of component-based design that works at any size on any device.

    In other words, responsive components to replace responsive layouts.

    Container queries will help us move from designing pages that respond to the browser or device size to designing components that can be placed in a sidebar or in the main content, and respond accordingly.

    My concern is that we are still using layout to determine when a design needs to adapt. This approach will always be restrictive, as we will still need pre-defined breakpoints. For this reason, my main question with container queries is, How would we decide when to change the CSS used by a component? 

    A component library removed from context and real content is probably not the best place for that decision. 

    As the diagrams below illustrate, we can use container queries to create designs for specific container widths, but what if I want to change the design based on the image size or ratio?

    In this example, the dimensions of the container are not what should dictate the design; rather, the image is.

    It’s hard to say for sure whether container queries will be a success story until we have solid cross-browser support for them. Responsive component libraries would definitely evolve how we design and would improve the possibilities for reuse and design at scale. But maybe we will always need to adjust these components to suit our content.

    CSS is changing

    Whilst the container query debate rumbles on, there have been numerous advances in CSS that change the way we think about design. The days of fixed-width elements measured in pixels and floated div elements used to cobble layouts together are long gone, consigned to history along with table layouts. Flexbox and CSS Grid have revolutionized layouts for the web. We can now create elements that wrap onto new rows when they run out of space, not when the device changes.

    .wrapper {
      display: grid;
      grid-template-columns: repeat(auto-fit, 450px);
      gap: 10px;
    }

    The repeat() function paired with auto-fit or auto-fill allows us to specify how much space each column should use while leaving it up to the browser to decide when to spill the columns onto a new line. Similar things can be achieved with Flexbox, as elements can wrap over multiple rows and “flex” to fill available space. 

    .wrapper {
      display: flex;
      flex-wrap: wrap;
      justify-content: space-between;
    }
    
    .child {
      flex-basis: 32%;
      margin-bottom: 20px;
    }

    The biggest benefit of all this is you don’t need to wrap elements in container rows. Without rows, content isn’t tied to page markup in quite the same way, allowing for removals or additions of content without additional development.

    This is a big step forward when it comes to creating designs that allow for evolving content, but the real game changer for flexible designs is CSS Subgrid. 

    Remember the days of crafting perfectly aligned interfaces, only for the customer to add an unbelievably long header almost as soon as they’re given CMS access, like the illustration below?

    Subgrid allows elements to respond to adjustments in their own content and in the content of sibling elements, helping us create designs more resilient to change.

    .wrapper {
      display: grid;
      grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
         grid-template-rows: auto 1fr auto;
      gap: 10px;
    }
    
    .sub-grid {
      display: grid;
      grid-row: span 3;
      grid-template-rows: subgrid; /* sets rows to parent grid */
    }

    CSS Grid allows us to separate layout and content, thereby enabling flexible designs. Meanwhile, Subgrid allows us to create designs that can adapt in order to suit morphing content. Subgrid at the time of writing is only supported in Firefox but the above code can be implemented behind an @supports feature query. 

    Intrinsic layouts 

    I’d be remiss not to mention intrinsic layouts, the term created by Jen Simmons to describe a mixture of new and old CSS features used to create layouts that respond to available space. 

    Responsive layouts have flexible columns using percentages. Intrinsic layouts, on the other hand, use the fr unit to create flexible columns that won’t ever shrink so much that they render the content illegible.

    fr units is a way to say I want you to distribute the extra space in this way, but…don’t ever make it smaller than the content that’s inside of it.

    —Jen Simmons, “Designing Intrinsic Layouts”

    Intrinsic layouts can also utilize a mixture of fixed and flexible units, allowing the content to dictate the space it takes up.

    What makes intrinsic design stand out is that it not only creates designs that can withstand future devices but also helps scale design without losing flexibility. Components and patterns can be lifted and reused without the prerequisite of having the same breakpoints or the same amount of content as in the previous implementation. 

    We can now create designs that adapt to the space they have, the content within them, and the content around them. With an intrinsic approach, we can construct responsive components without depending on container queries.

    Another 2010 moment?

    This intrinsic approach should in my view be every bit as groundbreaking as responsive web design was ten years ago. For me, it’s another “everything changed” moment. 

    But it doesn’t seem to be moving quite as fast; I haven’t yet had that same career-changing moment I had with responsive design, despite the widely shared and brilliant talk that brought it to my attention. 

    One reason for that could be that I now work in a large organization, which is quite different from the design agency role I had in 2010. In my agency days, every new project was a clean slate, a chance to try something new. Nowadays, projects use existing tools and frameworks and are often improvements to existing websites with an existing codebase. 

    Another could be that I feel more prepared for change now. In 2010 I was new to design in general; the shift was frightening and required a lot of learning. Also, an intrinsic approach isn’t exactly all-new; it’s about using existing skills and existing CSS knowledge in a different way. 

    You can’t framework your way out of a content problem

    Another reason for the slightly slower adoption of intrinsic design could be the lack of quick-fix framework solutions available to kick-start the change. 

    Responsive grid systems were all over the place ten years ago. With a framework like Bootstrap or Skeleton, you had a responsive design template at your fingertips.

    Intrinsic design and frameworks do not go hand in hand quite so well because the benefit of having a selection of units is a hindrance when it comes to creating layout templates. The beauty of intrinsic design is combining different units and experimenting with techniques to get the best for your content.

    And then there are design tools. We probably all, at some point in our careers, used Photoshop templates for desktop, tablet, and mobile devices to drop designs in and show how the site would look at all three stages.

    How do you do that now, with each component responding to content and layouts flexing as and when they need to? This type of design must happen in the browser, which personally I’m a big fan of. 

    The debate about “whether designers should code” is another that has rumbled on for years. When designing a digital product, we should, at the very least, design for a best- and worst-case scenario when it comes to content. To do this in a graphics-based software package is far from ideal. In code, we can add longer sentences, more radio buttons, and extra tabs, and watch in real time as the design adapts. Does it still work? Is the design too reliant on the current content?

    Personally, I look forward to the day intrinsic design is the standard for design, when a design component can be truly flexible and adapt to both its space and content with no reliance on device or container dimensions.

    Content first 

    Content is not constant. After all, to design for the unknown or unexpected we need to account for content changes like our earlier Subgrid card example that allowed the cards to respond to adjustments to their own content and the content of sibling elements.

    Thankfully, there’s more to CSS than layout, and plenty of properties and values can help us put content first. Subgrid and pseudo-elements like ::first-line and ::first-letter help to separate design from markup so we can create designs that allow for changes.

    Instead of old markup hacks like this—

    First line of text with different styling...

    —we can target content based on where it appears.

    .element::first-line {
      font-size: 1.4em;
    }
    
    .element::first-letter {
      color: red;
    }

    Much bigger additions to CSS include logical properties, which change the way we construct designs using logical dimensions (start and end) instead of physical ones (left and right), something CSS Grid also does with functions like min(), max(), and clamp().

    This flexibility allows for directional changes according to content, a common requirement when we need to present content in multiple languages. In the past, this was often achieved with Sass mixins but was often limited to switching from left-to-right to right-to-left orientation.

    In the Sass version, directional variables need to be set.

    $direction: rtl;
    $opposite-direction: ltr;
    
    $start-direction: right;
    $end-direction: left;

    These variables can be used as values—

    body {
      direction: $direction;
      text-align: $start-direction;
    }

    —or as properties.

    margin-#{$end-direction}: 10px;
    padding-#{$start-direction}: 10px;

    However, now we have native logical properties, removing the reliance on both Sass (or a similar tool) and pre-planning that necessitated using variables throughout a codebase. These properties also start to break apart the tight coupling between a design and strict physical dimensions, creating more flexibility for changes in language and in direction.

    margin-block-end: 10px;
    padding-block-start: 10px;

    There are also native start and end values for properties like text-align, which means we can replace text-align: right with text-align: start.

    Like the earlier examples, these properties help to build out designs that aren’t constrained to one language; the design will reflect the content’s needs.

    Fixed and fluid 

    We briefly covered the power of combining fixed widths with fluid widths with intrinsic layouts. The min() and max() functions are a similar concept, allowing you to specify a fixed value with a flexible alternative. 

    For min() this means setting a fluid minimum value and a maximum fixed value.

    .element {
      width: min(50%, 300px);
    }

    The element in the figure above will be 50% of its container as long as the element’s width doesn’t exceed 300px.

    For max() we can set a flexible max value and a minimum fixed value.

    .element {
      width: max(50%, 300px);
    }

    Now the element will be 50% of its container as long as the element’s width is at least 300px. This means we can set limits but allow content to react to the available space. 

    The clamp() function builds on this by allowing us to set a preferred value with a third parameter. Now we can allow the element to shrink or grow if it needs to without getting to a point where it becomes unusable.

    .element {
      width: clamp(300px, 50%, 600px);
    }

    This time, the element’s width will be 50% (the preferred value) of its container but never less than 300px and never more than 600px.

    With these techniques, we have a content-first approach to responsive design. We can separate content from markup, meaning the changes users make will not affect the design. We can start to future-proof designs by planning for unexpected changes in language or direction. And we can increase flexibility by setting desired dimensions alongside flexible alternatives, allowing for more or less content to be displayed correctly.

    Situation first

    Thanks to what we’ve discussed so far, we can cover device flexibility by changing our approach, designing around content and space instead of catering to devices. But what about that last bit of Jeffrey Zeldman’s quote, “…situations you haven’t imagined”?

    It’s a very different thing to design for someone seated at a desktop computer as opposed to someone using a mobile phone and moving through a crowded street in glaring sunshine. Situations and environments are hard to plan for or predict because they change as people react to their own unique challenges and tasks.

    This is why choice is so important. One size never fits all, so we need to design for multiple scenarios to create equal experiences for all our users.

    Thankfully, there is a lot we can do to provide choice.

    Responsible design 

    “There are parts of the world where mobile data is prohibitively expensive, and where there is little or no broadband infrastructure.”

    I Used the Web for a Day on a 50 MB Budget

    Chris Ashton

    One of the biggest assumptions we make is that people interacting with our designs have a good wifi connection and a wide screen monitor. But in the real world, our users may be commuters traveling on trains or other forms of transport using smaller mobile devices that can experience drops in connectivity. There is nothing more frustrating than a web page that won’t load, but there are ways we can help users use less data or deal with sporadic connectivity.

    The srcset attribute allows the browser to decide which image to serve. This means we can create smaller ‘cropped’ images to display on mobile devices in turn using less bandwidth and less data.

    Image alt text

    The preload attribute can also help us to think about how and when media is downloaded. It can be used to tell a browser about any critical assets that need to be downloaded with high priority, improving perceived performance and the user experience. 

     
     

    There’s also native lazy loading, which indicates assets that should only be downloaded when they are needed.

    …

    With srcset, preload, and lazy loading, we can start to tailor a user’s experience based on the situation they find themselves in. What none of this does, however, is allow the user themselves to decide what they want downloaded, as the decision is usually the browser’s to make. 

    So how can we put users in control?

    The return of media queries 

    Media queries have always been about much more than device sizes. They allow content to adapt to different situations, with screen size being just one of them.

    We’ve long been able to check for media types like print and speech and features such as hover, resolution, and color. These checks allow us to provide options that suit more than one scenario; it’s less about one-size-fits-all and more about serving adaptable content. 

    As of this writing, the Media Queries Level 5 spec is still under development. It introduces some really exciting queries that in the future will help us design for multiple other unexpected situations.

    For example, there’s a light-level feature that allows you to modify styles if a user is in sunlight or darkness. Paired with custom properties, these features allow us to quickly create designs or themes for specific environments.

    @media (light-level: normal) {
      --background-color: #fff;
      --text-color: #0b0c0c;  
    }
    
    @media (light-level: dim) {
      --background-color: #efd226;
      --text-color: #0b0c0c;
    }

    Another key feature of the Level 5 spec is personalization. Instead of creating designs that are the same for everyone, users can choose what works for them. This is achieved by using features like prefers-reduced-data, prefers-color-scheme, and prefers-reduced-motion, the latter two of which already enjoy broad browser support. These features tap into preferences set via the operating system or browser so people don’t have to spend time making each site they visit more usable. 

    Media queries like this go beyond choices made by a browser to grant more control to the user.

    Expect the unexpected

    In the end, the one thing we should always expect is for things to change. Devices in particular change faster than we can keep up, with foldable screens already on the market.

    We can’t design the same way we have for this ever-changing landscape, but we can design for content. By putting content first and allowing that content to adapt to whatever space surrounds it, we can create more robust, flexible designs that increase the longevity of our products. 

    A lot of the CSS discussed here is about moving away from layouts and putting content at the heart of design. From responsive components to fixed and fluid units, there is so much more we can do to take a more intrinsic approach. Even better, we can test these techniques during the design phase by designing in-browser and watching how our designs adapt in real-time.

    When it comes to unexpected situations, we need to make sure our products are usable when people need them, whenever and wherever that might be. We can move closer to achieving this by involving users in our design decisions, by creating choice via browsers, and by giving control to our users with user-preference-based media queries. 

    Good design for the unexpected should allow for change, provide choice, and give control to those we serve: our users themselves.

  • Voice Content and Usability

    Voice Content and Usability

    We’ve been having conversations for thousands of years. Whether to convey information, conduct transactions, or simply to check in on one another, people have yammered away, chattering and gesticulating, through spoken conversation for countless generations. Only in the last few millennia have we begun to commit our conversations to writing, and only in the last few decades have we begun to outsource them to the computer, a machine that shows much more affinity for written correspondence than for the slangy vagaries of spoken language.

    Computers have trouble because between spoken and written language, speech is more primordial. To have successful conversations with us, machines must grapple with the messiness of human speech: the disfluencies and pauses, the gestures and body language, and the variations in word choice and spoken dialect that can stymie even the most carefully crafted human-computer interaction. In the human-to-human scenario, spoken language also has the privilege of face-to-face contact, where we can readily interpret nonverbal social cues.

    In contrast, written language immediately concretizes as we commit it to record and retains usages long after they become obsolete in spoken communication (the salutation “To whom it may concern,” for example), generating its own fossil record of outdated terms and phrases. Because it tends to be more consistent, polished, and formal, written text is fundamentally much easier for machines to parse and understand.

    Spoken language has no such luxury. Besides the nonverbal cues that decorate conversations with emphasis and emotional context, there are also verbal cues and vocal behaviors that modulate conversation in nuanced ways: how something is said, not what. Whether rapid-fire, low-pitched, or high-decibel, whether sarcastic, stilted, or sighing, our spoken language conveys much more than the written word could ever muster. So when it comes to voice interfaces—the machines we conduct spoken conversations with—we face exciting challenges as designers and content strategists.

    Voice Interactions

    We interact with voice interfaces for a variety of reasons, but according to Michael McTear, Zoraida Callejas, and David Griol in The Conversational Interface, those motivations by and large mirror the reasons we initiate conversations with other people, too (). Generally, we start up a conversation because:

    • we need something done (such as a transaction),
    • we want to know something (information of some sort), or
    • we are social beings and want someone to talk to (conversation for conversation’s sake).

    These three categories—which I call transactional, informational, and prosocial—also characterize essentially every voice interaction: a single conversation from beginning to end that realizes some outcome for the user, starting with the voice interface’s first greeting and ending with the user exiting the interface. Note here that a conversation in our human sense—a chat between people that leads to some result and lasts an arbitrary length of time—could encompass multiple transactional, informational, and prosocial voice interactions in succession. In other words, a voice interaction is a conversation, but a conversation is not necessarily a single voice interaction.

    Purely prosocial conversations are more gimmicky than captivating in most voice interfaces, because machines don’t yet have the capacity to really want to know how we’re doing and to do the sort of glad-handing humans crave. There’s also ongoing debate as to whether users actually prefer the sort of organic human conversation that begins with a prosocial voice interaction and shifts seamlessly into other types. In fact, in Voice User Interface Design, Michael Cohen, James Giangola, and Jennifer Balogh recommend sticking to users’ expectations by mimicking how they interact with other voice interfaces rather than trying too hard to be human—potentially alienating them in the process ().

    That leaves two genres of conversations we can have with one another that a voice interface can easily have with us, too: a transactional voice interaction realizing some outcome (“buy iced tea”) and an informational voice interaction teaching us something new (“discuss a musical”).

    Transactional voice interactions

    Unless you’re tapping buttons on a food delivery app, you’re generally having a conversation—and therefore a voice interaction—when you order a Hawaiian pizza with extra pineapple. Even when we walk up to the counter and place an order, the conversation quickly pivots from an initial smattering of neighborly small talk to the real mission at hand: ordering a pizza (generously topped with pineapple, as it should be).

    Alison: Hey, how’s it going?

    Burhan: Hi, welcome to Crust Deluxe! It’s cold out there. How can I help you?

    Alison: Can I get a Hawaiian pizza with extra pineapple?

    Burhan: Sure, what size?

    Alison: Large.

    Burhan: Anything else?

    Alison: No thanks, that’s it.

    Burhan: Something to drink?

    Alison: I’ll have a bottle of Coke.

    Burhan: You got it. That’ll be $13.55 and about fifteen minutes.

    Each progressive disclosure in this transactional conversation reveals more and more of the desired outcome of the transaction: a service rendered or a product delivered. Transactional conversations have certain key traits: they’re direct, to the point, and economical. They quickly dispense with pleasantries.

    Informational voice interactions

    Meanwhile, some conversations are primarily about obtaining information. Though Alison might visit Crust Deluxe with the sole purpose of placing an order, she might not actually want to walk out with a pizza at all. She might be just as interested in whether they serve halal or kosher dishes, gluten-free options, or something else. Here, though we again have a prosocial mini-conversation at the beginning to establish politeness, we’re after much more.

    Alison: Hey, how’s it going?

    Burhan: Hi, welcome to Crust Deluxe! It’s cold out there. How can I help you?

    Alison: Can I ask a few questions?

    Burhan: Of course! Go right ahead.

    Alison: Do you have any halal options on the menu?

    Burhan: Absolutely! We can make any pie halal by request. We also have lots of vegetarian, ovo-lacto, and vegan options. Are you thinking about any other dietary restrictions?

    Alison: What about gluten-free pizzas?

    Burhan: We can definitely do a gluten-free crust for you, no problem, for both our deep-dish and thin-crust pizzas. Anything else I can answer for you?

    Alison: That’s it for now. Good to know. Thanks!

    Burhan: Anytime, come back soon!

    This is a very different dialogue. Here, the goal is to get a certain set of facts. Informational conversations are investigative quests for the truth—research expeditions to gather data, news, or facts. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. Responses tend to be lengthier, more informative, and carefully communicated so the customer understands the key takeaways.

    Voice Interfaces

    At their core, voice interfaces employ speech to support users in reaching their goals. But simply because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. Because multimodal voice interfaces can lean on visual components like screens as crutches, we’re most concerned in this book with pure voice interfaces, which depend entirely on spoken conversation, lack any visual component whatsoever, and are therefore much more nuanced and challenging to tackle.

    Though voice interfaces have long been integral to the imagined future of humanity in science fiction, only recently have those lofty visions become fully realized in genuine voice interfaces.

    Interactive voice response (IVR) systems

    Though written conversational interfaces have been fixtures of computing for many decades, voice interfaces first emerged in the early 1990s with text-to-speech (TTS) dictation programs that recited written text aloud, as well as speech-enabled in-car systems that gave directions to a user-provided address. With the advent of interactive voice response (IVR) systems, intended as an alternative to overburdened customer service representatives, we became acquainted with the first true voice interfaces that engaged in authentic conversation.

    IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. Commonplace in the corporate world, these systems were primarily designed as metaphorical switchboards to guide customers to a real phone agent (“Say Reservations to book a flight or check an itinerary”); chances are you will enter a conversation with one when you call an airline or hotel conglomerate. Despite their functional issues and users’ frustration with their inability to speak to an actual human right away, IVR systems proliferated in the early 1990s across a variety of industries (, PDF).

    While IVR systems are great for highly repetitive, monotonous conversations that generally don’t veer from a single format, they have a reputation for less scintillating conversation than we’re used to in real life (or even in science fiction).

    Screen readers

    Parallel to the evolution of IVR systems was the invention of the screen reader, a tool that transcribes visual content into synthesized speech. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. Screen readers represent perhaps the closest equivalent we have today to an out-of-the-box implementation of content delivered through voice.

    Among the first screen readers known by that moniker was the Screen Reader for the BBC Micro and NEEC Portable developed by the Research Centre for the Education of the Visually Handicapped (RCEVH) at the University of Birmingham in 1986 (). That same year, Jim Thatcher created the first IBM Screen Reader for text-based computers, later recreated for computers with graphical user interfaces (GUIs) ().

    With the rapid growth of the web in the 1990s, the demand for accessible tools for websites exploded. Thanks to the introduction of semantic HTML and especially ARIA roles beginning in 2008, screen readers started facilitating speedy interactions with web pages that ostensibly allow disabled users to traverse the page as an aural and temporal space rather than a visual and physical one. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc.—into useful information,” writes Aaron Gustafson in A List Apart. “At least they do when documents are authored thoughtfully” ().

    Though deeply instructive for voice interface designers, there’s one significant problem with screen readers: they’re difficult to use and unremittingly verbose. The visual structures of websites and web navigation don’t translate well to screen readers, sometimes resulting in unwieldy pronouncements that name every manipulable HTML element and announce every formatting change. For many screen reader users, working with web-based interfaces exacts a cognitive toll.

    In Wired, accessibility advocate and voice engineer Chris Maury considers why the screen reader experience is ill-suited to users relying on voice:

    From the beginning, I hated the way that Screen Readers work. Why are they designed the way they are? It makes no sense to present information visually and then, and only then, translate that into audio. All of the time and energy that goes into creating the perfect user experience for an app is wasted, or even worse, adversely impacting the experience for blind users. ()

    In many cases, well-designed voice interfaces can speed users to their destination better than long-winded screen reader monologues. After all, visual interface users have the benefit of darting around the viewport freely to find information, ignoring areas irrelevant to them. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Disabled users who have long had no choice but to employ clunky screen readers may find that voice interfaces, particularly more modern voice assistants, offer a more streamlined experience.

    Voice assistants

    When we think of voice assistants (the subset of voice interfaces now commonplace in living rooms, smart homes, and offices), many of us immediately picture HAL from 2001: A Space Odyssey or hear Majel Barrett’s voice as the omniscient computer in Star Trek. Voice assistants are akin to personal concierges that can answer questions, schedule appointments, conduct searches, and perform other common day-to-day tasks. And they’re rapidly gaining more attention from accessibility advocates for their assistive potential.

    Before the earliest IVR systems found success in the enterprise, Apple published a demonstration video in 1987 depicting the Knowledge Navigator, a voice assistant that could transcribe spoken words and recognize human speech to a great degree of accuracy. Then, in 2001, Tim Berners-Lee and others formulated their vision for a Semantic Web “agent” that would perform typical errands like “checking calendars, making appointments, and finding locations” (, behind paywall). It wasn’t until 2011 that Apple’s Siri finally entered the picture, making voice assistants a tangible reality for consumers.

    Thanks to the plethora of voice assistants available today, there is considerable variation in how programmable and customizable certain voice assistants are over others (Fig 1.1). At one extreme, everything except vendor-provided features is locked down; for example, at the time of their release, the core functionality of Apple’s Siri and Microsoft’s Cortana couldn’t be extended beyond their existing capabilities. Even today, it isn’t possible to program Siri to perform arbitrary functions, because there’s no means by which developers can interact with Siri at a low level, apart from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and certain others.

    At the opposite end of the spectrum, voice assistants like Amazon Alexa and Google Home offer a core foundation on which developers can build custom voice interfaces. For this reason, programmable voice assistants that lend themselves to customization and extensibility are becoming increasingly popular for developers who feel stifled by the limitations of Siri and Cortana. Amazon offers the Alexa Skills Kit, a developer framework for building custom voice interfaces for Amazon Alexa, while Google Home offers the ability to program arbitrary Google Assistant skills. Today, users can choose from among thousands of custom-built skills within both the Amazon Alexa and Google Assistant ecosystems.

    As corporations like Amazon, Apple, Microsoft, and Google continue to stake their territory, they’re also selling and open-sourcing an unprecedented array of tools and frameworks for designers and developers that aim to make building voice interfaces as easy as possible, even without code.

    Often by necessity, voice assistants like Amazon Alexa tend to be monochannel—they’re tightly coupled to a device and can’t be accessed on a computer or smartphone instead. By contrast, many development platforms like Google’s Dialogflow have introduced omnichannel capabilities so users can build a single conversational interface that then manifests as a voice interface, textual chatbot, and IVR system upon deployment. I don’t prescribe any specific implementation approaches in this design-focused book, but in Chapter 4 we’ll get into some of the implications these variables might have on the way you build out your design artifacts.

    Voice Content

    Simply put, voice content is content delivered through voice. To preserve what makes human conversation so compelling in the first place, voice content needs to be free-flowing and organic, contextless and concise—everything written content isn’t.

    Our world is replete with voice content in various forms: screen readers reciting website content, voice assistants rattling off a weather forecast, and automated phone hotline responses governed by IVR systems. In this book, we’re most concerned with content delivered auditorily—not as an option, but as a necessity.

    For many of us, our first foray into informational voice interfaces will be to deliver content to users. There’s only one problem: any content we already have isn’t in any way ready for this new habitat. So how do we make the content trapped on our websites more conversational? And how do we write new copy that lends itself to voice interactions?

    Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many respects, colossal vaults of what I call macrocontent: lengthy prose that can extend for infinitely scrollable miles in a browser window, like microfilm viewers of newspaper archives. Back in 2002, well before the present-day ubiquity of voice assistants, technologist Anil Dash defined microcontent as permalinked pieces of content that stay legible regardless of environment, such as email or text messages:

    A day’s weather forcast [sic], the arrival and departure times for an airplane flight, an abstract from a long publication, or a single instant message can all be examples of microcontent. ()

    I’d update Dash’s definition of microcontent to include all examples of bite-sized content that go well beyond written communiqués. After all, today we encounter microcontent in interfaces where a small snippet of copy is displayed alone, unmoored from the browser, like a textbot confirmation of a restaurant reservation. Microcontent offers the best opportunity to gauge how your content can be stretched to the very edges of its capabilities, informing delivery channels both established and novel.

    As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can glance at a digital sign underground for an instant and know when the next train is arriving, but voice interfaces hold our attention captive for periods of time that we can’t easily escape or skip, something screen reader users are all too familiar with.

    Because microcontent is fundamentally made up of isolated blobs with no relation to the channels where they’ll eventually end up, we need to ensure that our microcontent truly performs well as voice content—and that means focusing on the two most important traits of robust voice content: voice content legibility and voice content discoverability.

    Fundamentally, the legibility and discoverability of our voice content both have to do with how voice content manifests in perceived time and space.

  • Sustainable Web Design, An Excerpt

    Sustainable Web Design, An Excerpt

    In the 1950s, many in the elite running community had begun to believe it wasn’t possible to run a mile in less than four minutes. Runners had been attempting it since the late 19th century and were beginning to draw the conclusion that the human body simply wasn’t built for the task. 

    But on May 6, 1956, Roger Bannister took everyone by surprise. It was a cold, wet day in Oxford, England—conditions no one expected to lend themselves to record-setting—and yet Bannister did just that, running a mile in 3:59.4 and becoming the first person in the record books to run a mile in under four minutes. 

    This shift in the benchmark had profound effects; the world now knew that the four-minute mile was possible. Bannister’s record lasted only forty-six days, when it was snatched away by Australian runner John Landy. Then a year later, three runners all beat the four-minute barrier together in the same race. Since then, over 1,400 runners have officially run a mile in under four minutes; the current record is 3:43.13, held by Moroccan athlete Hicham El Guerrouj.

    We achieve far more when we believe that something is possible, and we will believe it’s possible only when we see someone else has already done it—and as with human running speed, so it is with what we believe are the hard limits for how a website needs to perform.

    Establishing standards for a sustainable web

    In most major industries, the key metrics of environmental performance are fairly well established, such as miles per gallon for cars or energy per square meter for homes. The tools and methods for calculating those metrics are standardized as well, which keeps everyone on the same page when doing environmental assessments. In the world of websites and apps, however, we aren’t held to any particular environmental standards, and only recently have gained the tools and methods we need to even make an environmental assessment.

    The primary goal in sustainable web design is to reduce carbon emissions. However, it’s almost impossible to actually measure the amount of CO2 produced by a web product. We can’t measure the fumes coming out of the exhaust pipes on our laptops. The emissions of our websites are far away, out of sight and out of mind, coming out of power stations burning coal and gas. We have no way to trace the electrons from a website or app back to the power station where the electricity is being generated and actually know the exact amount of greenhouse gas produced. So what do we do? 

    If we can’t measure the actual carbon emissions, then we need to find what we can measure. The primary factors that could be used as indicators of carbon emissions are:

    1. Data transfer 
    2. Carbon intensity of electricity

    Let’s take a look at how we can use these metrics to quantify the energy consumption, and in turn the carbon footprint, of the websites and web apps we create.

    Data transfer

    Most researchers use kilowatt-hours per gigabyte (kWh/GB) as a metric of energy efficiency when measuring the amount of data transferred over the internet when a website or application is used. This provides a great reference point for energy consumption and carbon emissions. As a rule of thumb, the more data transferred, the more energy used in the data center, telecoms networks, and end user devices.

    For web pages, data transfer for a single visit can be most easily estimated by measuring the page weight, meaning the transfer size of the page in kilobytes the first time someone visits the page. It’s fairly easy to measure using the developer tools in any modern web browser. Often your web hosting account will include statistics for the total data transfer of any web application (Fig 2.1).

    The nice thing about page weight as a metric is that it allows us to compare the efficiency of web pages on a level playing field without confusing the issue with constantly changing traffic volumes. 

    Reducing page weight requires a large scope. By early 2020, the median page weight was 1.97 MB for setups the HTTP Archive classifies as “desktop” and 1.77 MB for “mobile,” with desktop increasing 36 percent since January 2016 and mobile page weights nearly doubling in the same period (Fig 2.2). Roughly half of this data transfer is image files, making images the single biggest source of carbon emissions on the average website. 

    History clearly shows us that our web pages can be smaller, if only we set our minds to it. While most technologies become ever more energy efficient, including the underlying technology of the web such as data centers and transmission networks, websites themselves are a technology that becomes less efficient as time goes on.

    You might be familiar with the concept of performance budgeting as a way of focusing a project team on creating faster user experiences. For example, we might specify that the website must load in a maximum of one second on a broadband connection and three seconds on a 3G connection. Much like speed limits while driving, performance budgets are upper limits rather than vague suggestions, so the goal should always be to come in under budget.

    Designing for fast performance does often lead to reduced data transfer and emissions, but it isn’t always the case. Web performance is often more about the subjective perception of load times than it is about the true efficiency of the underlying system, whereas page weight and transfer size are more objective measures and more reliable benchmarks for sustainable web design. 

    We can set a page weight budget in reference to a benchmark of industry averages, using data from sources like HTTP Archive. We can also benchmark page weight against competitors or the old version of the website we’re replacing. For example, we might set a maximum page weight budget as equal to our most efficient competitor, or we could set the benchmark lower to guarantee we are best in class. 

    If we want to take it to the next level, then we could also start looking at the transfer size of our web pages for repeat visitors. Although page weight for the first time someone visits is the easiest thing to measure, and easy to compare on a like-for-like basis, we can learn even more if we start looking at transfer size in other scenarios too. For example, visitors who load the same page multiple times will likely have a high percentage of the files cached in their browser, meaning they don’t need to transfer all of the files on subsequent visits. Likewise, a visitor who navigates to new pages on the same website will likely not need to load the full page each time, as some global assets from areas like the header and footer may already be cached in their browser. Measuring transfer size at this next level of detail can help us learn even more about how we can optimize efficiency for users who regularly visit our pages, and enable us to set page weight budgets for additional scenarios beyond the first visit.

    Page weight budgets are easy to track throughout a design and development process. Although they don’t actually tell us carbon emission and energy consumption analytics directly, they give us a clear indication of efficiency relative to other websites. And as transfer size is an effective analog for energy consumption, we can actually use it to estimate energy consumption too.

    In summary, reduced data transfer translates to energy efficiency, a key factor to reducing carbon emissions of web products. The more efficient our products, the less electricity they use, and the less fossil fuels need to be burned to produce the electricity to power them. But as we’ll see next, since all web products demand some power, it’s important to consider the source of that electricity, too.

    Carbon intensity of electricity

    Regardless of energy efficiency, the level of pollution caused by digital products depends on the carbon intensity of the energy being used to power them. Carbon intensity is a term used to define the grams of CO2 produced for every kilowatt-hour of electricity (gCO2/kWh). This varies widely, with renewable energy sources and nuclear having an extremely low carbon intensity of less than 10 gCO2/kWh (even when factoring in their construction); whereas fossil fuels have very high carbon intensity of approximately 200–400 gCO2/kWh. 

    Most electricity comes from national or state grids, where energy from a variety of different sources is mixed together with varying levels of carbon intensity. The distributed nature of the internet means that a single user of a website or app might be using energy from multiple different grids simultaneously; a website user in Paris uses electricity from the French national grid to power their home internet and devices, but the website’s data center could be in Dallas, USA, pulling electricity from the Texas grid, while the telecoms networks use energy from everywhere between Dallas and Paris.

    We don’t have control over the full energy supply of web services, but we do have some control over where we host our projects. With a data center using a significant proportion of the energy of any website, locating the data center in an area with low carbon energy will tangibly reduce its carbon emissions. Danish startup Tomorrow reports and maps this user-contributed data, and a glance at their map shows how, for example, choosing a data center in France will have significantly lower carbon emissions than a data center in the Netherlands (Fig 2.3).

    That said, we don’t want to locate our servers too far away from our users; it takes energy to transmit data through the telecom’s networks, and the further the data travels, the more energy is consumed. Just like food miles, we can think of the distance from the data center to the website’s core user base as “megabyte miles”—and we want it to be as small as possible.

    Using the distance itself as a benchmark, we can use website analytics to identify the country, state, or even city where our core user group is located and measure the distance from that location to the data center used by our hosting company. This will be a somewhat fuzzy metric as we don’t know the precise center of mass of our users or the exact location of a data center, but we can at least get a rough idea. 

    For example, if a website is hosted in London but the primary user base is on the West Coast of the USA, then we could look up the distance from London to San Francisco, which is 5,300 miles. That’s a long way! We can see that hosting it somewhere in North America, ideally on the West Coast, would significantly reduce the distance and thus the energy used to transmit the data. In addition, locating our servers closer to our visitors helps reduce latency and delivers better user experience, so it’s a win-win.

    Converting it back to carbon emissions

    If we combine carbon intensity with a calculation for energy consumption, we can calculate the carbon emissions of our websites and apps. A tool my team created does this by measuring the data transfer over the wire when loading a web page, calculating the amount of electricity associated, and then converting that into a figure for CO2 (Fig 2.4). It also factors in whether or not the web hosting is powered by renewable energy.

    If you want to take it to the next level and tailor the data more accurately to the unique aspects of your project, the Energy and Emissions Worksheet accompanying this book shows you how.

    With the ability to calculate carbon emissions for our projects, we could actually take a page weight budget one step further and set carbon budgets as well. CO2 is not a metric commonly used in web projects; we’re more familiar with kilobytes and megabytes, and can fairly easily look at design options and files to assess how big they are. Translating that into carbon adds a layer of abstraction that isn’t as intuitive—but carbon budgets do focus our minds on the primary thing we’re trying to reduce, and support the core objective of sustainable web design: reducing carbon emissions.

    Browser Energy

    Data transfer might be the simplest and most complete analog for energy consumption in our digital projects, but by giving us one number to represent the energy used in the data center, the telecoms networks, and the end user’s devices, it can’t offer us insights into the efficiency in any specific part of the system.

    One part of the system we can look at in more detail is the energy used by end users’ devices. As front-end web technologies become more advanced, the computational load is increasingly moving from the data center to users’ devices, whether they be phones, tablets, laptops, desktops, or even smart TVs. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Furthermore, JavaScript libraries such as Angular and React allow us to create applications where the “thinking” work is done partly or entirely in the browser. 

    All of these advances are exciting and open up new possibilities for what the web can do to serve society and create positive experiences. However, more computation in the user’s web browser means more energy used by their devices. This has implications not just environmentally, but also for user experience and inclusivity. Applications that put a heavy processing load on the user’s device can inadvertently exclude users with older, slower devices and cause batteries on phones and laptops to drain faster. Furthermore, if we build web applications that require the user to have up-to-date, powerful devices, people throw away old devices much more frequently. This isn’t just bad for the environment, but it puts a disproportionate financial burden on the poorest in society.

    In part because the tools are limited, and partly because there are so many different models of devices, it’s difficult to measure website energy consumption on end users’ devices. One tool we do currently have is the Energy Impact monitor inside the developer console of the Safari browser (Fig 2.5).

    You know when you load a website and your computer’s cooling fans start spinning so frantically you think it might actually take off? That’s essentially what this tool is measuring. 

    It shows us the percentage of CPU used and the duration of CPU usage when loading the web page, and uses these figures to generate an energy impact rating. It doesn’t give us precise data for the amount of electricity used in kilowatts, but the information it does provide can be used to benchmark how efficiently your websites use energy and set targets for improvement.

  • Design for Safety, An Excerpt

    Design for Safety, An Excerpt

    Antiracist economist Kim Crayton says that “intention without strategy is chaos.” We’ve discussed how our biases, assumptions, and inattention toward marginalized and vulnerable groups lead to dangerous and unethical tech—but what, specifically, do we need to do to fix it? The intention to make our tech safer is not enough; we need a strategy.

    This chapter will equip you with that plan of action. It covers how to integrate safety principles into your design work in order to create tech that’s safe, how to convince your stakeholders that this work is necessary, and how to respond to the critique that what we actually need is more diversity. (Spoiler: we do, but diversity alone is not the antidote to fixing unethical, unsafe tech.)

    The process for inclusive safety

    When you are designing for safety, your goals are to:

    • identify ways your product can be used for abuse,
    • design ways to prevent the abuse, and
    • provide support for vulnerable users to reclaim power and control.

    The Process for Inclusive Safety is a tool to help you reach those goals (Fig 5.1). It’s a methodology I created in 2018 to capture the various techniques I was using when designing products with safety in mind. Whether you are creating an entirely new product or adding to an existing feature, the Process can help you make your product safe and inclusive. The Process includes five general areas of action:

    • Conducting research
    • Creating archetypes
    • Brainstorming problems
    • Designing solutions
    • Testing for safety

    The Process is meant to be flexible—it won’t make sense for teams to implement every step in some situations. Use the parts that are relevant to your unique work and context; this is meant to be something you can insert into your existing design practice.

    And once you use it, if you have an idea for making it better or simply want to provide context of how it helped your team, please get in touch with me. It’s a living document that I hope will continue to be a useful and realistic tool that technologists can use in their day-to-day work.

    If you’re working on a product specifically for a vulnerable group or survivors of some form of trauma, such as an app for survivors of domestic violence, sexual assault, or drug addiction, be sure to read Chapter 7, which covers that situation explicitly and should be handled a bit differently. The guidelines here are for prioritizing safety when designing a more general product that will have a wide user base (which, we already know from statistics, will include certain groups that should be protected from harm). Chapter 7 is focused on products that are specifically for vulnerable groups and people who have experienced trauma.

    Step 1: Conduct research

    Design research should include a broad analysis of how your tech might be weaponized for abuse as well as specific insights into the experiences of survivors and perpetrators of that type of abuse. At this stage, you and your team will investigate issues of interpersonal harm and abuse, and explore any other safety, security, or inclusivity issues that might be a concern for your product or service, like data security, racist algorithms, and harassment.

    Broad research

    Your project should begin with broad, general research into similar products and issues around safety and ethical concerns that have already been reported. For example, a team building a smart home device would do well to understand the multitude of ways that existing smart home devices have been used as tools of abuse. If your product will involve AI, seek to understand the potentials for racism and other issues that have been reported in existing AI products. Nearly all types of technology have some kind of potential or actual harm that’s been reported on in the news or written about by academics. Google Scholar is a useful tool for finding these studies.

    Specific research: Survivors

    When possible and appropriate, include direct research (surveys and interviews) with people who are experts in the forms of harm you have uncovered. Ideally, you’ll want to interview advocates working in the space of your research first so that you have a more solid understanding of the topic and are better equipped to not retraumatize survivors. If you’ve uncovered possible domestic violence issues, for example, the experts you’ll want to speak with are survivors themselves, as well as workers at domestic violence hotlines, shelters, other related nonprofits, and lawyers.

    Especially when interviewing survivors of any kind of trauma, it is important to pay people for their knowledge and lived experiences. Don’t ask survivors to share their trauma for free, as this is exploitative. While some survivors may not want to be paid, you should always make the offer in the initial ask. An alternative to payment is to donate to an organization working against the type of violence that the interviewee experienced. We’ll talk more about how to appropriately interview survivors in Chapter 6.

    Specific research: Abusers

    It’s unlikely that teams aiming to design for safety will be able to interview self-proclaimed abusers or people who have broken laws around things like hacking. Don’t make this a goal; rather, try to get at this angle in your general research. Aim to understand how abusers or bad actors weaponize technology to use against others, how they cover their tracks, and how they explain or rationalize the abuse.

    Step 2: Create archetypes

    Once you’ve finished conducting your research, use your insights to create abuser and survivor archetypes. Archetypes are not personas, as they’re not based on real people that you interviewed and surveyed. Instead, they’re based on your research into likely safety issues, much like when we design for accessibility: we don’t need to have found a group of blind or low-vision users in our interview pool to create a design that’s inclusive of them. Instead, we base those designs on existing research into what this group needs. Personas typically represent real users and include many details, while archetypes are broader and can be more generalized.

    The abuser archetype is someone who will look at the product as a tool to perform harm (Fig 5.2). They may be trying to harm someone they don’t know through surveillance or anonymous harassment, or they may be trying to control, monitor, abuse, or torment someone they know personally.

    The survivor archetype is someone who is being abused with the product. There are various situations to consider in terms of the archetype’s understanding of the abuse and how to put an end to it: Do they need proof of abuse they already suspect is happening, or are they unaware they’ve been targeted in the first place and need to be alerted (Fig 5.3)?

    You may want to make multiple survivor archetypes to capture a range of different experiences. They may know that the abuse is happening but not be able to stop it, like when an abuser locks them out of IoT devices; or they know it’s happening but don’t know how, such as when a stalker keeps figuring out their location (Fig 5.4). Include as many of these scenarios as you need to in your survivor archetype. You’ll use these later on when you design solutions to help your survivor archetypes achieve their goals of preventing and ending abuse.

    It may be useful for you to create persona-like artifacts for your archetypes, such as the three examples shown. Instead of focusing on the demographic information we often see in personas, focus on their goals. The goals of the abuser will be to carry out the specific abuse you’ve identified, while the goals of the survivor will be to prevent abuse, understand that abuse is happening, make ongoing abuse stop, or regain control over the technology that’s being used for abuse. Later, you’ll brainstorm how to prevent the abuser’s goals and assist the survivor’s goals.

    And while the “abuser/survivor” model fits most cases, it doesn’t fit all, so modify it as you need to. For example, if you uncovered an issue with security, such as the ability for someone to hack into a home camera system and talk to children, the malicious hacker would get the abuser archetype and the child’s parents would get survivor archetype.

    Step 3: Brainstorm problems

    After creating archetypes, brainstorm novel abuse cases and safety issues. “Novel” means things not found in your research; you’re trying to identify completely new safety issues that are unique to your product or service. The goal with this step is to exhaust every effort of identifying harms your product could cause. You aren’t worrying about how to prevent the harm yet—that comes in the next step.

    How could your product be used for any kind of abuse, outside of what you’ve already identified in your research? I recommend setting aside at least a few hours with your team for this process.

    If you’re looking for somewhere to start, try doing a Black Mirror brainstorm. This exercise is based on the show Black Mirror, which features stories about the dark possibilities of technology. Try to figure out how your product would be used in an episode of the show—the most wild, awful, out-of-control ways it could be used for harm. When I’ve led Black Mirror brainstorms, participants usually end up having a good deal of fun (which I think is great—it’s okay to have fun when designing for safety!). I recommend time-boxing a Black Mirror brainstorm to half an hour, and then dialing it back and using the rest of the time thinking of more realistic forms of harm.

    After you’ve identified as many opportunities for abuse as possible, you may still not feel confident that you’ve uncovered every potential form of harm. A healthy amount of anxiety is normal when you’re doing this kind of work. It’s common for teams designing for safety to worry, “Have we really identified every possible harm? What if we’ve missed something?” If you’ve spent at least four hours coming up with ways your product could be used for harm and have run out of ideas, go to the next step.

    It’s impossible to guarantee you’ve thought of everything; instead of aiming for 100 percent assurance, recognize that you’ve taken this time and have done the best you can, and commit to continuing to prioritize safety in the future. Once your product is released, your users may identify new issues that you missed; aim to receive that feedback graciously and course-correct quickly.

    Step 4: Design solutions

    At this point, you should have a list of ways your product can be used for harm as well as survivor and abuser archetypes describing opposing user goals. The next step is to identify ways to design against the identified abuser’s goals and to support the survivor’s goals. This step is a good one to insert alongside existing parts of your design process where you’re proposing solutions for the various problems your research uncovered.

    Some questions to ask yourself to help prevent harm and support your archetypes include:

    • Can you design your product in such a way that the identified harm cannot happen in the first place? If not, what roadblocks can you put up to prevent the harm from happening?
    • How can you make the victim aware that abuse is happening through your product?
    • How can you help the victim understand what they need to do to make the problem stop?
    • Can you identify any types of user activity that would indicate some form of harm or abuse? Could your product help the user access support?

    In some products, it’s possible to proactively recognize that harm is happening. For example, a pregnancy app might be modified to allow the user to report that they were the victim of an assault, which could trigger an offer to receive resources for local and national organizations. This sort of proactiveness is not always possible, but it’s worth taking a half hour to discuss if any type of user activity would indicate some form of harm or abuse, and how your product could assist the user in receiving help in a safe manner.

    That said, use caution: you don’t want to do anything that could put a user in harm’s way if their devices are being monitored. If you do offer some kind of proactive help, always make it voluntary, and think through other safety issues, such as the need to keep the user in-app in case an abuser is checking their search history. We’ll walk through a good example of this in the next chapter.

    Step 5: Test for safety

    The final step is to test your prototypes from the point of view of your archetypes: the person who wants to weaponize the product for harm and the victim of the harm who needs to regain control over the technology. Just like any other kind of product testing, at this point you’ll aim to rigorously test out your safety solutions so that you can identify gaps and correct them, validate that your designs will help keep your users safe, and feel more confident releasing your product into the world.

    Ideally, safety testing happens along with usability testing. If you’re at a company that doesn’t do usability testing, you might be able to use safety testing to cleverly perform both; a user who goes through your design attempting to weaponize the product against someone else can also be encouraged to point out interactions or other elements of the design that don’t make sense to them.

    You’ll want to conduct safety testing on either your final prototype or the actual product if it’s already been released. There’s nothing wrong with testing an existing product that wasn’t designed with safety goals in mind from the onset—“retrofitting” it for safety is a good thing to do.

    Remember that testing for safety involves testing from the perspective of both an abuser and a survivor, though it may not make sense for you to do both. Alternatively, if you made multiple survivor archetypes to capture multiple scenarios, you’ll want to test from the perspective of each one.

    As with other sorts of usability testing, you as the designer are most likely too close to the product and its design by this point to be a valuable tester; you know the product too well. Instead of doing it yourself, set up testing as you would with other usability testing: find someone who is not familiar with the product and its design, set the scene, give them a task, encourage them to think out loud, and observe how they attempt to complete it.

    Abuser testing

    The goal of this testing is to understand how easy it is for someone to weaponize your product for harm. Unlike with usability testing, you want to make it impossible, or at least difficult, for them to achieve their goal. Reference the goals in the abuser archetype you created earlier, and use your product in an attempt to achieve them.

    For example, for a fitness app with GPS-enabled location features, we can imagine that the abuser archetype would have the goal of figuring out where his ex-girlfriend now lives. With this goal in mind, you’d try everything possible to figure out the location of another user who has their privacy settings enabled. You might try to see her running routes, view any available information on her profile, view anything available about her location (which she has set to private), and investigate the profiles of any other users somehow connected with her account, such as her followers.

    If by the end of this you’ve managed to uncover some of her location data, despite her having set her profile to private, you know now that your product enables stalking. Your next step is to go back to step 4 and figure out how to prevent this from happening. You may need to repeat the process of designing solutions and testing them more than once.

    Survivor testing

    Survivor testing involves identifying how to give information and power to the survivor. It might not always make sense based on the product or context. Thwarting the attempt of an abuser archetype to stalk someone also satisfies the goal of the survivor archetype to not be stalked, so separate testing wouldn’t be needed from the survivor’s perspective.

    However, there are cases where it makes sense. For example, for a smart thermostat, a survivor archetype’s goals would be to understand who or what is making the temperature change when they aren’t doing it themselves. You could test this by looking for the thermostat’s history log and checking for usernames, actions, and times; if you couldn’t find that information, you would have more work to do in step 4.

    Another goal might be regaining control of the thermostat once the survivor realizes the abuser is remotely changing its settings. Your test would involve attempting to figure out how to do this: are there instructions that explain how to remove another user and change the password, and are they easy to find? This might again reveal that more work is needed to make it clear to the user how they can regain control of the device or account.

    Stress testing

    To make your product more inclusive and compassionate, consider adding stress testing. This concept comes from Design for Real Life by Eric Meyer and Sara Wachter-Boettcher. The authors pointed out that personas typically center people who are having a good day—but real users are often anxious, stressed out, having a bad day, or even experiencing tragedy. These are called “stress cases,” and testing your products for users in stress-case situations can help you identify places where your design lacks compassion. Design for Real Life has more details about what it looks like to incorporate stress cases into your design as well as many other great tactics for compassionate design.

  • A Content Model Is Not a Design System

    A Content Model Is Not a Design System

    Do you remember when having a great website was enough? Now, people are getting answers from Siri, Google search snippets, and mobile apps, not just our websites. Forward-thinking organizations have adopted an omnichannel content strategy, whose mission is to reach audiences across multiple digital channels and platforms.

    But how do you set up a content management system (CMS) to reach your audience now and in the future? I learned the hard way that creating a content model—a definition of content types, attributes, and relationships that let people and systems understand content—with my more familiar design-system thinking would capsize my customer’s omnichannel content strategy. You can avoid that outcome by creating content models that are semantic and that also connect related content. 

    I recently had the opportunity to lead the CMS implementation for a Fortune 500 company. The client was excited by the benefits of an omnichannel content strategy, including content reuse, multichannel marketing, and robot delivery—designing content to be intelligible to bots, Google knowledge panels, snippets, and voice user interfaces. 

    A content model is a critical foundation for an omnichannel content strategy, and for our content to be understood by multiple systems, the model needed semantic types—types named according to their meaning instead of their presentation. Our goal was to let authors create content and reuse it wherever it was relevant. But as the project proceeded, I realized that supporting content reuse at the scale that my customer needed required the whole team to recognize a new pattern.

    Despite our best intentions, we kept drawing from what we were more familiar with: design systems. Unlike web-focused content strategies, an omnichannel content strategy can’t rely on WYSIWYG tools for design and layout. Our tendency to approach the content model with our familiar design-system thinking constantly led us to veer away from one of the primary purposes of a content model: delivering content to audiences on multiple marketing channels.

    Two essential principles for an effective content model

    We needed to help our designers, developers, and stakeholders understand that we were doing something very different from their prior web projects, where it was natural for everyone to think about content as visual building blocks fitting into layouts. The previous approach was not only more familiar but also more intuitive—at least at first—because it made the designs feel more tangible. We discovered two principles that helped the team understand how a content model differs from the design systems that we were used to:

    1. Content models must define semantics instead of layout.
    2. And content models should connect content that belongs together.

    Semantic content models

    A semantic content model uses type and attribute names that reflect the meaning of the content, not how it will be displayed. For example, in a nonsemantic model, teams might create types like teasers, media blocks, and cards. Although these types might make it easy to lay out content, they don’t help delivery channels understand the content’s meaning, which in turn would have opened the door to the content being presented in each marketing channel. In contrast, a semantic content model uses type names like product, service, and testimonial so that each delivery channel can understand the content and use it as it sees fit. 

    When you’re creating a semantic content model, a great place to start is to look over the types and properties defined by Schema.org, a community-driven resource for type definitions that are intelligible to platforms like Google search.

    A semantic content model has several benefits:

    • Even if your team doesn’t care about omnichannel content, a semantic content model decouples content from its presentation so that teams can evolve the website’s design without needing to refactor its content. In this way, content can withstand disruptive website redesigns. 
    • A semantic content model also provides a competitive edge. By adding structured data based on Schema.org’s types and properties, a website can provide hints to help Google understand the content, display it in search snippets or knowledge panels, and use it to answer voice-interface user questions. Potential visitors could discover your content without ever setting foot in your website.
    • Beyond those practical benefits, you’ll also need a semantic content model if you want to deliver omnichannel content. To use the same content in multiple marketing channels, delivery channels need to be able to understand it. For example, if your content model were to provide a list of questions and answers, it could easily be rendered on a frequently asked questions (FAQ) page, but it could also be used in a voice interface or by a bot that answers common questions.

    For example, using a semantic content model for articles, events, people, and locations lets A List Apart provide cleanly structured data for search engines so that users can read the content on the website, in Google knowledge panels, and even with hypothetical voice interfaces in the future.

    Content models that connect

    After struggling to describe what makes a good content model, I’ve come to realize that the best models are those that are semantic and that also connect related content components (such as a FAQ item’s question and answer pair), instead of slicing up related content across disparate content components. A good content model connects content that should remain together so that multiple delivery channels can use it without needing to first put those pieces back together.

    Think about writing an article or essay. An article’s meaning and usefulness depends upon its parts being kept together. Would one of the headings or paragraphs be meaningful on their own without the context of the full article? On our project, our familiar design-system thinking often led us to want to create content models that would slice content into disparate chunks to fit the web-centric layout. This had a similar impact to an article that were to have been separated from its headline. Because we were slicing content into standalone pieces based on layout, content that belonged together became difficult to manage and nearly impossible for multiple delivery channels to understand.

    To illustrate, let’s look at how connecting related content applies in a real-world scenario. The design team for our customer presented a complex layout for a software product page that included multiple tabs and sections. Our instincts were to follow suit with the content model. Shouldn’t we make it as easy and as flexible as possible to add any number of tabs in the future?

    Because our design-system instincts were so familiar, it felt like we had needed a content type called “tab section” so that multiple tab sections could be added to a page. Each tab section would display various types of content. One tab might provide the software’s overview or its specifications. Another tab might provide a list of resources. 

    Our inclination to break down the content model into “tab section” pieces would have led to an unnecessarily complex model and a cumbersome editing experience, and it would have also created content that couldn’t have been understood by additional delivery channels. For example, how would another system have been able to tell which “tab section” referred to a product’s specifications or its resource list—would that other system have to have resorted to counting tab sections and content blocks? This would have prevented the tabs from ever being reordered, and it would have required adding logic in every other delivery channel to interpret the design system’s layout. Furthermore, if the customer were to have no longer wanted to display this content in a tab layout, it would have been tedious to migrate to a new content model to reflect the new page redesign.

    We had a breakthrough when we discovered that our customer had a specific purpose in mind for each tab: it would reveal specific information such as the software product’s overview, specifications, related resources, and pricing. Once implementation began, our inclination to focus on what’s visual and familiar had obscured the intent of the designs. With a little digging, it didn’t take long to realize that the concept of tabs wasn’t relevant to the content model. The meaning of the content that they were planning to display in the tabs was what mattered.

    In fact, the customer could have decided to display this content in a different way—without tabs—somewhere else. This realization prompted us to define content types for the software product based on the meaningful attributes that the customer had wanted to render on the web. There were obvious semantic attributes like name and description as well as rich attributes like screenshots, software requirements, and feature lists. The software’s product information stayed together because it wasn’t sliced across separate components like “tab sections” that were derived from the content’s presentation. Any delivery channel—including future ones—could understand and present this content.

    Conclusion

    In this omnichannel marketing project, we discovered that the best way to keep our content model on track was to ensure that it was semantic (with type and attribute names that reflected the meaning of the content) and that it kept content together that belonged together (instead of fragmenting it). These two concepts curtailed our temptation to shape the content model based on the design. So if you’re working on a content model to support an omnichannel content strategy—or even if you just want to make sure that Google and other interfaces understand your content—remember:

    • A design system isn’t a content model. Team members may be tempted to conflate them and to make your content model mirror your design system, so you should protect the semantic value and contextual structure of the content strategy during the entire implementation process. This will let every delivery channel consume the content without needing a magic decoder ring.
    • If your team is struggling to make this transition, you can still reap some of the benefits by using Schema.org–based structured data in your website. Even if additional delivery channels aren’t on the immediate horizon, the benefit to search engine optimization is a compelling reason on its own.
    • Additionally, remind the team that decoupling the content model from the design will let them update the designs more easily because they won’t be held back by the cost of content migrations. They’ll be able to create new designs without the obstacle of compatibility between the design and the content, and ​they’ll be ready for the next big thing. 

    By rigorously advocating for these principles, you’ll help your team treat content the way that it deserves—as the most critical asset in your user experience and the best way to connect with your audience.

  • How to Sell UX Research with Two Simple Questions

    How to Sell UX Research with Two Simple Questions

    Do you find yourself designing screens with only a vague idea of how the things on the screen relate to the things elsewhere in the system? Do you leave stakeholder meetings with unclear directives that often seem to contradict previous conversations? You know a better understanding of user needs would help the team get clear on what you are actually trying to accomplish, but time and budget for research is tight. When it comes to asking for more direct contact with your users, you might feel like poor Oliver Twist, timidly asking, “Please, sir, I want some more.” 

    Here’s the trick. You need to get stakeholders themselves to identify high-risk assumptions and hidden complexity, so that they become just as motivated as you to get answers from users. Basically, you need to make them think it’s their idea. 

    In this article, I’ll show you how to collaboratively expose misalignment and gaps in the team’s shared understanding by bringing the team together around two simple questions:

    1. What are the objects?
    2. What are the relationships between those objects?

    A gauntlet between research and screen design

    These two questions align to the first two steps of the ORCA process, which might become your new best friend when it comes to reducing guesswork. Wait, what’s ORCA?! Glad you asked.

    ORCA stands for Objects, Relationships, CTAs, and Attributes, and it outlines a process for creating solid object-oriented user experiences. Object-oriented UX is my design philosophy. ORCA is an iterative methodology for synthesizing user research into an elegant structural foundation to support screen and interaction design. OOUX and ORCA have made my work as a UX designer more collaborative, effective, efficient, fun, strategic, and meaningful.

    The ORCA process has four iterative rounds and a whopping fifteen steps. In each round we get more clarity on our Os, Rs, Cs, and As.

    I sometimes say that ORCA is a “garbage in, garbage out” process. To ensure that the testable prototype produced in the final round actually tests well, the process needs to be fed by good research. But if you don’t have a ton of research, the beginning of the ORCA process serves another purpose: it helps you sell the need for research.

    In other words, the ORCA process serves as a gauntlet between research and design. With good research, you can gracefully ride the killer whale from research into design. But without good research, the process effectively spits you back into research and with a cache of specific open questions.

    Getting in the same curiosity-boat

    What gets us into trouble is not what we don’t know. It’s what we know for sure that just ain’t so.

    Mark Twain

    The first two steps of the ORCA process—Object Discovery and Relationship Discovery—shine a spotlight on the dark, dusty corners of your team’s misalignments and any inherent complexity that’s been swept under the rug. It begins to expose what this classic comic so beautifully illustrates:

    This is one reason why so many UX designers are frustrated in their job and why many projects fail. And this is also why we often can’t sell research: every decision-maker is confident in their own mental picture. 

    Once we expose hidden fuzzy patches in each picture and the differences between them all, the case for user research makes itself.

    But how we do this is important. However much we might want to, we can’t just tell everyone, “YOU ARE WRONG!” Instead, we need to facilitate and guide our team members to self-identify holes in their picture. When stakeholders take ownership of assumptions and gaps in understanding, BAM! Suddenly, UX research is not such a hard sell, and everyone is aboard the same curiosity-boat.

    Say your users are doctors. And you have no idea how doctors use the system you are tasked with redesigning.

    You might try to sell research by honestly saying: “We need to understand doctors better! What are their pain points? How do they use the current app?” But here’s the problem with that. Those questions are vague, and the answers to them don’t feel acutely actionable.

    Instead, you want your stakeholders themselves to ask super-specific questions. This is more like the kind of conversation you need to facilitate. Let’s listen in:

    “Wait a sec, how often do doctors share patients? Does a patient in this system have primary and secondary doctors?”

    “Can a patient even have more than one primary doctor?”

    “Is it a ‘primary doctor’ or just a ‘primary caregiver’… Can’t that role be a nurse practitioner?”

    “No, caregivers are something else… That’s the patient’s family contacts, right?”

    “So are caregivers in scope for this redesign?”

    “Yeah, because if a caregiver is present at an appointment, the doctor needs to note that. Like, tag the caregiver on the note… Or on the appointment?”

    Now we are getting somewhere. Do you see how powerful it can be getting stakeholders to debate these questions themselves? The diabolical goal here is to shake their confidence—gently and diplomatically.

    When these kinds of questions bubble up collaboratively and come directly from the mouths of your stakeholders and decision-makers, suddenly, designing screens without knowing the answers to these questions seems incredibly risky, even silly.

    If we create software without understanding the real-world information environment of our users, we will likely create software that does not align to the real-world information environment of our users. And this will, hands down, result in a more confusing, more complex, and less intuitive software product.

    The two questions

    But how do we get to these kinds of meaty questions diplomatically, efficiently, collaboratively, and reliably

    We can do this by starting with those two big questions that align to the first two steps of the ORCA process:

    1. What are the objects?
    2. What are the relationships between those objects?

    In practice, getting to these answers is easier said than done. I’m going to show you how these two simple questions can provide the outline for an Object Definition Workshop. During this workshop, these “seed” questions will blossom into dozens of specific questions and shine a spotlight on the need for more user research.

    Prep work: Noun foraging

    In the next section, I’ll show you how to run an Object Definition Workshop with your stakeholders (and entire cross-functional team, hopefully). But first, you need to do some prep work.

    Basically, look for nouns that are particular to the business or industry of your project, and do it across at least a few sources. I call this noun foraging.

    Here are just a few great noun foraging sources:

    • the product’s marketing site
    • the product’s competitors’ marketing sites (competitive analysis, anyone?)
    • the existing product (look at labels!)
    • user interview transcripts
    • notes from stakeholder interviews or vision docs from stakeholders

    Put your detective hat on, my dear Watson. Get resourceful and leverage what you have. If all you have is a marketing website, some screenshots of the existing legacy system, and access to customer service chat logs, then use those.

    As you peruse these sources, watch for the nouns that are used over and over again, and start listing them (preferably on blue sticky notes if you’ll be creating an object map later!).

    You’ll want to focus on nouns that might represent objects in your system. If you are having trouble determining if a noun might be object-worthy, remember the acronym SIP and test for:

    1. Structure
    2. Instances
    3. Purpose

    Think of a library app, for example. Is “book” an object?

    Structure: can you think of a few attributes for this potential object? Title, author, publish date… Yep, it has structure. Check!

    Instance: what are some examples of this potential “book” object? Can you name a few? The Alchemist, Ready Player One, Everybody Poops… OK, check!

    Purpose: why is this object important to the users and business? Well, “book” is what our library client is providing to people and books are why people come to the library… Check, check, check!

    As you are noun foraging, focus on capturing the nouns that have SIP. Avoid capturing components like dropdowns, checkboxes, and calendar pickers—your UX system is not your design system! Components are just the packaging for objects—they are a means to an end. No one is coming to your digital place to play with your dropdown! They are coming for the VALUABLE THINGS and what they can do with them. Those things, or objects, are what we are trying to identify.

    Let’s say we work for a startup disrupting the email experience. This is how I’d start my noun foraging.

    First I’d look at my own email client, which happens to be Gmail. I’d then look at Outlook and the new HEY email. I’d look at Yahoo, Hotmail…I’d even look at Slack and Basecamp and other so-called “email replacers.” I’d read some articles, reviews, and forum threads where people are complaining about email. While doing all this, I would look for and write down the nouns.

    (Before moving on, feel free to go noun foraging for this hypothetical product, too, and then scroll down to see how much our lists match up. Just don’t get lost in your own emails! Come back to me!)

    Drumroll, please…

    Here are a few nouns I came up with during my noun foraging:

    • email message
    • thread
    • contact
    • client
    • rule/automation
    • email address that is not a contact?
    • contact groups
    • attachment
    • Google doc file / other integrated file
    • newsletter? (HEY treats this differently)
    • saved responses and templates

    Scan your list of nouns and pick out words that you are completely clueless about. In our email example, it might be client or automation. Do as much homework as you can before your session with stakeholders: google what’s googleable. But other terms might be so specific to the product or domain that you need to have a conversation about them.

    Aside: here are some real nouns foraged during my own past project work that I needed my stakeholders to help me understand:

    • Record Locator
    • Incentive Home
    • Augmented Line Item
    • Curriculum-Based Measurement Probe

    This is really all you need to prepare for the workshop session: a list of nouns that represent potential objects and a short list of nouns that need to be defined further.

    Facilitate an Object Definition Workshop

    You could actually start your workshop with noun foraging—this activity can be done collaboratively. If you have five people in the room, pick five sources, assign one to every person, and give everyone ten minutes to find the objects within their source. When the time’s up, come together and find the overlap. Affinity mapping is your friend here!

    If your team is short on time and might be reluctant to do this kind of grunt work (which is usually the case) do your own noun foraging beforehand, but be prepared to show your work. I love presenting screenshots of documents and screens with all the nouns already highlighted. Bring the artifacts of your process, and start the workshop with a five-minute overview of your noun foraging journey.

    HOT TIP: before jumping into the workshop, frame the conversation as a requirements-gathering session to help you better understand the scope and details of the system. You don’t need to let them know that you’re looking for gaps in the team’s understanding so that you can prove the need for more user research—that will be our little secret. Instead, go into the session optimistically, as if your knowledgeable stakeholders and PMs and biz folks already have all the answers. 

    Then, let the question whack-a-mole commence.

    1. What is this thing?

    Want to have some real fun? At the beginning of your session, ask stakeholders to privately write definitions for the handful of obscure nouns you might be uncertain about. Then, have everyone show their cards at the same time and see if you get different definitions (you will). This is gold for exposing misalignment and starting great conversations.

    As your discussion unfolds, capture any agreed-upon definitions. And when uncertainty emerges, quietly (but visibly) start an “open questions” parking lot. 😉

    After definitions solidify, here’s a great follow-up:

    2. Do our users know what these things are? What do users call this thing?

    Stakeholder 1: They probably call email clients “apps.” But I’m not sure.

    Stakeholder 2: Automations are often called “workflows,” I think. Or, maybe users think workflows are something different.

    If a more user-friendly term emerges, ask the group if they can agree to use only that term moving forward. This way, the team can better align to the users’ language and mindset.

    OK, moving on. 

    If you have two or more objects that seem to overlap in purpose, ask one of these questions:

    3. Are these the same thing? Or are these different? If they are not the same, how are they different?

    You: Is a saved response the same as a template?

    Stakeholder 1: Yes! Definitely.

    Stakeholder 2: I don’t think so… A saved response is text with links and variables, but a template is more about the look and feel, like default fonts, colors, and placeholder images. 

    Continue to build out your growing glossary of objects. And continue to capture areas of uncertainty in your “open questions” parking lot.

    If you successfully determine that two similar things are, in fact, different, here’s your next follow-up question:

    4. What’s the relationship between these objects?

    You: Are saved responses and templates related in any way?

    Stakeholder 3:  Yeah, a template can be applied to a saved response.

    You, always with the follow-ups: When is the template applied to a saved response? Does that happen when the user is constructing the saved response? Or when they apply the saved response to an email? How does that actually work?

    Listen. Capture uncertainty. Once the list of “open questions” grows to a critical mass, pause to start assigning questions to groups or individuals. Some questions might be for the dev team (hopefully at least one developer is in the room with you). One question might be specifically for someone who couldn’t make it to the workshop. And many questions will need to be labeled “user.” 

    Do you see how we are building up to our UXR sales pitch?

    5. Is this object in scope?

    Your next question narrows the team’s focus toward what’s most important to your users. You can simply ask, “Are saved responses in scope for our first release?,” but I’ve got a better, more devious strategy.

    By now, you should have a list of clearly defined objects. Ask participants to sort these objects from most to least important, either in small breakout groups or individually. Then, like you did with the definitions, have everyone reveal their sort order at once. Surprisingly—or not so surprisingly—it’s not unusual for the VP to rank something like “saved responses” as #2 while everyone else puts it at the bottom of the list. Try not to look too smug as you inevitably expose more misalignment.

    I did this for a startup a few years ago. We posted the three groups’ wildly different sort orders on the whiteboard.

    The CEO stood back, looked at it, and said, “This is why we haven’t been able to move forward in two years.”

    Admittedly, it’s tragic to hear that, but as a professional, it feels pretty awesome to be the one who facilitated a watershed realization.

    Once you have a good idea of in-scope, clearly defined things, this is when you move on to doing more relationship mapping.

    6. Create a visual representation of the objects’ relationships

    We’ve already done a bit of this while trying to determine if two things are different, but this time, ask the team about every potential relationship. For each object, ask how it relates to all the other objects. In what ways are the objects connected? To visualize all the connections, pull out your trusty boxes-and-arrows technique. Here, we are connecting our objects with verbs. I like to keep my verbs to simple “has a” and “has many” statements.

    This system modeling activity brings up all sorts of new questions:

    • Can a saved response have attachments?
    • Can a saved response use a template? If so, if an email uses a saved response with a template, can the user override that template?
    • Do users want to see all the emails they sent that included a particular attachment? For example, “show me all the emails I sent with ProfessionalImage.jpg attached. I’ve changed my professional photo and I want to alert everyone to update it.” 

    Solid answers might emerge directly from the workshop participants. Great! Capture that new shared understanding. But when uncertainty surfaces, continue to add questions to your growing parking lot.

    Light the fuse

    You’ve positioned the explosives all along the floodgates. Now you simply have to light the fuse and BOOM. Watch the buy-in for user research flooooow.

    Before your workshop wraps up, have the group reflect on the list of open questions. Make plans for getting answers internally, then focus on the questions that need to be brought before users.

    Here’s your final step. Take those questions you’ve compiled for user research and discuss the level of risk associated with NOT answering them. Ask, “if we design without an answer to this question, if we make up our own answer and we are wrong, how bad might that turn out?” 

    With this methodology, we are cornering our decision-makers into advocating for user research as they themselves label questions as high-risk. Sorry, not sorry. 

    Now is your moment of truth. With everyone in the room, ask for a reasonable budget of time and money to conduct 6–8 user interviews focused specifically on these questions. 

    HOT TIP: if you are new to UX research, please note that you’ll likely need to rephrase the questions that came up during the workshop before you present them to users. Make sure your questions are open-ended and don’t lead the user into any default answers.

    Final words: Hold the screen design!

    Seriously, if at all possible, do not ever design screens again without first answering these fundamental questions: what are the objects and how do they relate?

    I promise you this: if you can secure a shared understanding between the business, design, and development teams before you start designing screens, you will have less heartache and save more time and money, and (it almost feels like a bonus at this point!) users will be more receptive to what you put out into the world. 

    I sincerely hope this helps you win time and budget to go talk to your users and gain clarity on what you are designing before you start building screens. If you find success using noun foraging and the Object Definition Workshop, there’s more where that came from in the rest of the ORCA process, which will help prevent even more late-in-the-game scope tugs-of-war and strategy pivots. 

    All the best of luck! Now go sell research!

  • Breaking Out of the Box

    Breaking Out of the Box

    CSS is about styling boxes. In fact, the whole web is made of boxes, from the browser viewport to elements on a page. But every once in a while a new feature comes along that makes us rethink our design approach.

    Round displays, for example, make it fun to play with circular clip areas. Mobile screen notches and virtual keyboards offer challenges to best organize content that stays clear of them. And dual screen or foldable devices make us rethink how to best use available space in a number of different device postures.

    These recent evolutions of the web platform made it both more challenging and more interesting to design products. They’re great opportunities for us to break out of our rectangular boxes.

    I’d like to talk about a new feature similar to the above: the Window Controls Overlay for Progressive Web Apps (PWAs).

    Progressive Web Apps are blurring the lines between apps and websites. They combine the best of both worlds. On one hand, they’re stable, linkable, searchable, and responsive just like websites. On the other hand, they provide additional powerful capabilities, work offline, and read files just like native apps.

    As a design surface, PWAs are really interesting because they challenge us to think about what mixing web and device-native user interfaces can be. On desktop devices in particular, we have more than 40 years of history telling us what applications should look like, and it can be hard to break out of this mental model.

    At the end of the day though, PWAs on desktop are constrained to the window they appear in: a rectangle with a title bar at the top.

    Here’s what a typical desktop PWA app looks like:

    Sure, as the author of a PWA, you get to choose the color of the title bar (using the Web Application Manifest theme_color property), but that’s about it.

    What if we could think outside this box, and reclaim the real estate of the app’s entire window? Doing so would give us a chance to make our apps more beautiful and feel more integrated in the operating system.

    This is exactly what the Window Controls Overlay offers. This new PWA functionality makes it possible to take advantage of the full surface area of the app, including where the title bar normally appears.

    About the title bar and window controls

    Let’s start with an explanation of what the title bar and window controls are.

    The title bar is the area displayed at the top of an app window, which usually contains the app’s name. Window controls are the affordances, or buttons, that make it possible to minimize, maximize, or close the app’s window, and are also displayed at the top.

    Window Controls Overlay removes the physical constraint of the title bar and window controls areas. It frees up the full height of the app window, enabling the title bar and window control buttons to be overlaid on top of the application’s web content. 

    If you are reading this article on a desktop computer, take a quick look at other apps. Chances are they’re already doing something similar to this. In fact, the very web browser you are using to read this uses the top area to display tabs.

    Spotify displays album artwork all the way to the top edge of the application window.

    Microsoft Word uses the available title bar space to display the auto-save and search functionalities, and more.

    The whole point of this feature is to allow you to make use of this space with your own content while providing a way to account for the window control buttons. And it enables you to offer this modified experience on a range of platforms while not adversely affecting the experience on browsers or devices that don’t support Window Controls Overlay. After all, PWAs are all about progressive enhancement, so this feature is a chance to enhance your app to use this extra space when it’s available.

    Let’s use the feature

    For the rest of this article, we’ll be working on a demo app to learn more about using the feature.

    The demo app is called 1DIV. It’s a simple CSS playground where users can create designs using CSS and a single HTML element.

    The app has two pages. The first lists the existing CSS designs you’ve created:

    The second page enables you to create and edit CSS designs:

    Since I’ve added a simple web manifest and service worker, we can install the app as a PWA on desktop. Here is what it looks like on macOS:

    And on Windows:

    Our app is looking good, but the white title bar in the first page is wasted space. In the second page, it would be really nice if the design area went all the way to the top of the app window.

    Let’s use the Window Controls Overlay feature to improve this.

    Enabling Window Controls Overlay

    The feature is still experimental at the moment. To try it, you need to enable it in one of the supported browsers.

    As of now, it has been implemented in Chromium, as a collaboration between Microsoft and Google. We can therefore use it in Chrome or Edge by going to the internal about://flags page, and enabling the Desktop PWA Window Controls Overlay flag.

    Using Window Controls Overlay

    To use the feature, we need to add the following display_override member to our web app’s manifest file:

    {
      "name": "1DIV",
      "description": "1DIV is a mini CSS playground",
      "lang": "en-US",
      "start_url": "/",
      "theme_color": "#ffffff",
      "background_color": "#ffffff",
      "display_override": [
        "window-controls-overlay"
      ],
      "icons": [
        ...
      ]
    }
    

    On the surface, the feature is really simple to use. This manifest change is the only thing we need to make the title bar disappear and turn the window controls into an overlay.

    However, to provide a great experience for all users regardless of what device or browser they use, and to make the most of the title bar area in our design, we’ll need a bit of CSS and JavaScript code.

    Here is what the app looks like now:

    The title bar is gone, which is what we wanted, but our logo, search field, and NEW button are partially covered by the window controls because now our layout starts at the top of the window.

    It’s similar on Windows, with the difference that the close, maximize, and minimize buttons appear on the right side, grouped together with the PWA control buttons:

    Screenshot of the 1DIV app thumbnail display using Window Controls Overlay on the Windows operating system. The separate top bar area is gone, but the window controls are now blocking some of the app’s content.

    Using CSS to keep clear of the window controls

    Along with the feature, new CSS environment variables have been introduced:

    • titlebar-area-x
    • titlebar-area-y
    • titlebar-area-width
    • titlebar-area-height

    You use these variables with the CSS env() function to position your content where the title bar would have been while ensuring it won’t overlap with the window controls. In our case, we’ll use two of the variables to position our header, which contains the logo, search bar, and NEW button. 

    header {
      position: absolute;
      left: env(titlebar-area-x, 0);
      width: env(titlebar-area-width, 100%);
      height: var(--toolbar-height);
    }
    

    The titlebar-area-x variable gives us the distance from the left of the viewport to where the title bar would appear, and titlebar-area-width is its width. (Remember, this is not equivalent to the width of the entire viewport, just the title bar portion, which as noted earlier, doesn’t include the window controls.)

    By doing this, we make sure our content remains fully visible. We’re also defining fallback values (the second parameter in the env() function) for when the variables are not defined (such as on non-supporting browsers, or when the Windows Control Overlay feature is disabled).

    Now our header adapts to its surroundings, and it doesn’t feel like the window control buttons have been added as an afterthought. The app looks a lot more like a native app.

    Changing the window controls background color so it blends in

    Now let’s take a closer look at our second page: the CSS playground editor.

    Not great. Our CSS demo area does go all the way to the top, which is what we wanted, but the way the window controls appear as white rectangles on top of it is quite jarring.

    We can fix this by changing the app’s theme color. There are a couple of ways to define it:

    • PWAs can define a theme color in the web app manifest file using the theme_color manifest member. This color is then used by the OS in different ways. On desktop platforms, it is used to provide a background color to the title bar and window controls.
    • Websites can use the theme-color meta tag as well. It’s used by browsers to customize the color of the UI around the web page. For PWAs, this color can override the manifest theme_color.

    In our case, we can set the manifest theme_color to white to provide the right default color for our app. The OS will read this color value when the app is installed and use it to make the window controls background color white. This color works great for our main page with the list of demos.

    The theme-color meta tag can be changed at runtime, using JavaScript. So we can do that to override the white with the right demo background color when one is opened.

    Here is the function we’ll use:

    function themeWindow(bgColor) {
      document.querySelector("meta[name=theme-color]").setAttribute('content', bgColor);
    }

    With this in place, we can imagine how using color and CSS transitions can produce a smooth change from the list page to the demo page, and enable the window control buttons to blend in with the rest of the app’s interface.

    Dragging the window

    Now, getting rid of the title bar entirely does have an important accessibility consequence: it’s much more difficult to move the application window around.

    The title bar provides a sizable area for users to click and drag, but by using the Window Controls Overlay feature, this area becomes limited to where the control buttons are, and users have to very precisely aim between these buttons to move the window.

    Fortunately, this can be fixed using CSS with the app-region property. This property is, for now, only supported in Chromium-based browsers and needs the -webkit- vendor prefix. 

    To make any element of the app become a dragging target for the window, we can use the following: 

    -webkit-app-region: drag;

    It is also possible to explicitly make an element non-draggable: 

    -webkit-app-region: no-drag; 

    These options can be useful for us. We can make the entire header a dragging target, but make the search field and NEW button within it non-draggable so they can still be used as normal.

    However, because the editor page doesn’t display the header, users wouldn’t be able to drag the window while editing code. So let’s use a different approach. We’ll create another element before our header, also absolutely positioned, and dedicated to dragging the window.

    ...
    .drag {
      position: absolute;
      top: 0;
      width: 100%;
      height: env(titlebar-area-height, 0);
      -webkit-app-region: drag;
    }

    With the above code, we’re making the draggable area span the entire viewport width, and using the titlebar-area-height variable to make it as tall as what the title bar would have been. This way, our draggable area is aligned with the window control buttons as shown below.

    And, now, to make sure our search field and button remain usable:

    header .search,
    header .new {
      -webkit-app-region: no-drag;
    }

    With the above code, users can click and drag where the title bar used to be. It is an area that users expect to be able to use to move windows on desktop, and we’re not breaking this expectation, which is good.

    Adapting to window resize

    It may be useful for an app to know both whether the window controls overlay is visible and when its size changes. In our case, if the user made the window very narrow, there wouldn’t be enough space for the search field, logo, and button to fit, so we’d want to push them down a bit.

    The Window Controls Overlay feature comes with a JavaScript API we can use to do this: navigator.windowControlsOverlay.

    The API provides three interesting things:

    • navigator.windowControlsOverlay.visible lets us know whether the overlay is visible.
    • navigator.windowControlsOverlay.getBoundingClientRect() lets us know the position and size of the title bar area.
    • navigator.windowControlsOverlay.ongeometrychange lets us know when the size or visibility changes.

    Let’s use this to be aware of the size of the title bar area and move the header down if it’s too narrow.

    if (navigator.windowControlsOverlay) {
      navigator.windowControlsOverlay.addEventListener('geometrychange', () => {
        const { width } = navigator.windowControlsOverlay.getBoundingClientRect();
        document.body.classList.toggle('narrow', width < 250);
      });
    }

    In the example above, we set the narrow class on the body of the app if the title bar area is narrower than 250px. We could do something similar with a media query, but using the windowControlsOverlay API has two advantages for our use case:

    • It’s only fired when the feature is supported and used; we don’t want to adapt the design otherwise.
    • We get the size of the title bar area across operating systems, which is great because the size of the window controls is different on Mac and Windows. Using a media query wouldn’t make it possible for us to know exactly how much space remains.
    .narrow header {
      top: env(titlebar-area-height, 0);
      left: 0;
      width: 100%;
    }

    Using the above CSS code, we can move our header down to stay clear of the window control buttons when the window is too narrow, and move the thumbnails down accordingly.

    Thirty pixels of exciting design opportunities


    Using the Window Controls Overlay feature, we were able to take our simple demo app and turn it into something that feels so much more integrated on desktop devices. Something that reaches out of the usual window constraints and provides a custom experience for its users.

    In reality, this feature only gives us about 30 pixels of extra room and comes with challenges on how to deal with the window controls. And yet, this extra room and those challenges can be turned into exciting design opportunities.

    More devices of all shapes and forms get invented all the time, and the web keeps on evolving to adapt to them. New features get added to the web platform to allow us, web authors, to integrate more and more deeply with those devices. From watches or foldable devices to desktop computers, we need to evolve our design approach for the web. Building for the web now lets us think outside the rectangular box.

    So let’s embrace this. Let’s use the standard technologies already at our disposal, and experiment with new ideas to provide tailored experiences for all devices, all from a single codebase!


    If you get a chance to try the Window Controls Overlay feature and have feedback about it, you can open issues on the spec’s repository. It’s still early in the development of this feature, and you can help make it even better. Or, you can take a look at the feature’s existing documentation, or this demo app and its source code