Category: Blog

The personalization space is real, between the dream of getting it right and the fear of it going wrong ( like when we encounter “persofails” in the spirit of a company that regularly asks regular people to buy more toilet seats ). It’s an particularly confusing place to be a modern professional without a map, a map, or a strategy.

Because successful personalization is so dependent on each group’s skill, technology, and market position, there are no Lonely Planet and some tour guides for those of you who want to personalize.

But you can ensure that your group has packed its carriers rationally.

There’s a DIY method to increase your chances for achievement. You’ll at least at least disarm your boss ‘ irrational exuberance. Before the group you’ll need to properly plan.

We refer to it as prepersonalization.

Behind the audio

Take into account the DJ have on Spotify, which was introduced last month.

We’re used to seeing the polished final outcome of a personalization have. A personal have had to be developed, budgeted, and given priority before the year-end prize, the making-of-backstory, or the behind-the-scenes success chest. Before any customisation have goes live in your product or service, it lives amid a delay of valuable ideas for expressing consumer experiences more automatically.

How do you decide where to position customisation wagers? How do you design regular interactions that didn’t journey up users or—worse—breed mistrust? We’ve found that for many well-known budgeted programs to support their continued investments, they initially required one or more workshops to join vital technologies users and stakeholders. Make yours count.

We’ve witnessed the same evolution up close with our clients, from big tech to fledgling startups. In our experiences with working on small and large personalization efforts, a program’s ultimate track record—and its ability to weather tough questions, work steadily toward shared answers, and organize its design and technology efforts—turns on how effectively these prepersonalization activities play out.

Effective workshops consistently separate successful future endeavors from unsuccessful ones, saving countless hours of time, resources, and overall well-being.

A personalization practice involves a multiyear effort of testing and feature development. It’s not a tech stack switch-flip. It’s best managed as a backlog that often evolves through three steps:

1. customer experience optimization ( CXO, also known as A/B testing or experimentation )
2. always-on automations ( whether rules-based or machine-generated )
3. mature features or standalone product development ( such as Spotify’s DJ experience )

This is why we created our progressive personalization framework and why we’re field-testing an accompanying deck of cards: we believe that there’s a base grammar, a set of “nouns and verbs” that your organization can use to design experiences that are customized, personalized, or automated. You won’t require these cards. But we strongly recommend that you create something similar, whether that might be digital or physical.

Set the timer for the kitchen.

How long does it take to cook up a prepersonalization workshop? The evaluation activities that we suggest include can last for a number of weeks ( and frequently do ). For the core workshop, we recommend aiming for two to three days. Here are a summary of our broad approach and information on the most crucial first-day activities.

The full arc of the wider workshop is threefold:

Kickstart: This specifies the terms of engagement as you concentrate on the potential, the readiness and drive of your team, and your leadership.
1. Plan your work: This is the heart of the card-based workshop activities where you specify a plan of attack and the scope of work.
2. Work your plan: This stage essentially entails creating a competitive environment in which team members can individually present their own pilots that each contain a proof-of-concept project, its business case, and its operating model.

Give yourself at least a day, split into two large time blocks, to power through a concentrated version of those first two phases.

Kickstart: Apt your appetite

We call the first lesson the “landscape of connected experience“. It looks at the possibilities for personalization at your company. A connected experience, in our parlance, is any UX requiring the orchestration of multiple systems of record on the backend. This might be a marketing-automation platform combined with a content-management system. It could be a digital-asset manager combined with a customer-data platform.

Give examples of connected experience interactions that you admire, find familiar, or even dislike, as examples of consumer and business-to-business examples. This should cover a representative range of personalization patterns, including automated app-based interactions ( such as onboarding sequences or wizards ), notifications, and recommenders. These cards contain a catalog, which we have. Here’s a list of 142 different interactions to jog your thinking.

It’s all about setting the tone. What are the possible paths for the practice in your organization? Here’s a long-form primer and a strategic framework for a broad perspective.

Assess each example that you discuss for its complexity and the level of effort that you estimate that it would take for your team to deliver that feature ( or something similar ). We break down connected experiences into five categories in our cards: functions, features, experiences, complete products, and portfolios. Size your own build here. This will help to draw attention to the benefits of ongoing investment as well as the difference between what you deliver right now and what you want to deliver in the future.

Next, have your team plot each idea on the following 2×2 grid, which lays out the four enduring arguments for a personalized experience. This is crucial because it emphasizes how personalization can affect your own methods of working as well as your external customers. It’s also a reminder ( which is why we used the word argument earlier ) of the broader effort beyond these tactical interventions.

Each team member should decide where their focus should be placed for your product or service. Naturally, you can’t prioritize all of them. Here, the goal is to demonstrate how various departments may view their own advantages over the effort, which can be different from one department to the next. Documenting your desired outcomes lets you know how the team internally aligns across representatives from different departments or functional areas.

The third and final kickstart activity is about filling in the personalization gap. Is your customer journey well documented? Will ensuring data and privacy is a major challenge too much? Do you have content metadata needs that you have to address? ( We’re pretty sure you do; it’s just a matter of acknowledging the magnitude of that need and finding a solution. ) In our cards, we’ve noted a number of program risks, including common team dispositions. For instance, our Detractor card lists six protracted behavior that is harmful to the development of our country.

Effectively collaborating and managing expectations is critical to your success. Consider the potential obstacles to your progress in the future. Press the participants to name specific steps to overcome or mitigate those barriers in your organization. According to research, personalization initiatives face a number of common obstacles.

At this point, you’ve hopefully discussed sample interactions, emphasized a key area of benefit, and flagged key gaps? You’re all set to go on, good.

Hit that test kitchen

Next, let’s take a look at what you’ll need to create personalization recipes. Personalization engines, which are robust software suites for automating and expressing dynamic content, can intimidate new customers. They give you a variety of options for how your organization can conduct its activities because of their broad and potent capabilities. This presents the question: Where do you begin when you’re configuring a connected experience?

The key here is to avoid treating the installed software ( as one of our client executives humorously put it ) like some sort of dream kitchen. These software engines are more like test kitchens where your team can begin devising, tasting, and refining the snacks and meals that will become a part of your personalization program’s regularly evolving menu.

Over the course of the workshop, the ultimate menu of the prioritized backlog will come together. And creating “dishes” is the way that you’ll have individual team stakeholders construct personalized interactions that serve their needs or the needs of others.

The dishes will be made using recipes that have predetermined ingredients.

Verify your ingredients

Like a good product manager, you’ll make sure you have everything you need to make your desired interaction ( or that you can figure out what needs to be added to your pantry ) and that you validate with the right stakeholders present. These ingredients include the audience that you’re targeting, content and design elements, the context for the interaction, and your measure for how it’ll come together.

This doesn’t just involve identifying requirements. Documenting your personalizations as a series of if-then statements lets the team:

1. compare findings to a common strategy for developing features, similar to how artists paint with the same color palette,
2. specify a consistent set of interactions that users find uniform or familiar,
3. and establish parity among performance indicators and key performance indicators as well.

This helps you streamline your designs and your technical efforts while you deliver a shared palette of core motifs of your personalized or automated experience.

Create a recipe.

What ingredients are important to you? Consider the construct of a who-what-when-why

• Who are your key audience segments or groups?
• What content, what design elements, and under what circumstances will you give them?
• And for which business and user benefits?

Five years ago, we created these cards and card categories. We regularly play-test their fit with conference audiences and clients. And there are still fresh possibilities. But they all follow an underlying who-what-when-why logic.

In the cards in the accompanying photo below, you can typically follow along with right to left in three examples of subscription-based reading apps.

1. Nurture personalization: When a guest or an unknown visitor interacts with a product title, a banner or alert bar appears that makes it easier for them to encounter a related title they may want to read, saving them time.
2. Welcome automation: An email is sent when a new user registers to highlight the breadth of the content catalog and convert them to happy subscribers.
3. Winback automation: Before their subscription lapses or after a recent failed renewal, a user is sent an email that gives them a promotional offer to suggest that they reconsider renewing or to remind them to renew.

A good preworkshop activity might be to consider a first draft of what these cards might be for your organization, though we’ve also found that cocreating the recipes themselves can sometimes help this process. Start with a set of blank cards, and begin labeling and grouping them through the design process, eventually distilling them to a refined subset of highly useful candidate cards.

The later stages of the workshop could be characterized as moving from focusing on a cookbook to a more nuanced customer-journey mapping. Individual” cooks” will pitch their recipes to the team, using a common jobs-to-be-done format so that measurability and results are baked in, and from there, the resulting collection will be prioritized for finished design and delivery to production.

Better architecture is required for better kitchens.

Simplifying a customer experience is a complicated effort for those who are inside delivering it. Beware of anyone who contradicts your advice. With that being said,” Complicated problems can be hard to solve, but they are addressable with rules and recipes“.

A team overfitting: they aren’t designing with their best data, is what causes personalization to become a laugh line. Like a sparse pantry, every organization has metadata debt to go along with its technical debt, and this creates a drag on personalization effectiveness. For instance, your AI’s output quality is in fact impacted by your IA. Spotify’s poster-child prowess today was unfathomable before they acquired a seemingly modest metadata startup that now powers its underlying information architecture.

You can withstand the heat without a doubt.

Personalization technology opens a doorway into a confounding ocean of possible designs. Only a deliberate and cooperative approach will produce the desired outcome. So banish the dream kitchen. Instead, head to the test kitchen to save time, preserve job security, and avoid imagining the creative concepts that come from the doers in your organization. There are meals to serve and mouths to feed.

You have a better chance of lasting success and sound beginnings with this workshop framework. Wiring up your information layer isn’t an overnight affair. However, you’ll have solid ground for success if you use the same cookbook and the same recipes. We designed these activities to make your organization’s needs concrete and clear, long before the hazards pile up.

Your time well spent is being able to assess your unique situation and digital skills, despite the associated costs associated with investing in this kind of technology and product design. Don’t squander it. The pudding is the proof, as they say.

The same holds true for those of us who are currently employed in design and development. Having worked on the web for about three years at this point, I’ve seen the typical wax and wane of concepts, strategies, and systems. Every day we as developers and designers re-enter a routine pattern, a brand-new concept or technology emerges to shake things up and completely alter our world.

How we got below

I built my first website in the mid-’90s. Design and development on the web back then was a free-for-all, with few established norms. For any layout aside from a single column, we used table elements, often with empty cells containing a single pixel spacer GIF to add empty space. We styled text with numerous font tags, nesting the tags every time we wanted to vary the font style. And we had only three or four typefaces to choose from: Arial, Courier, or Times New Roman. When Verdana and Georgia came out in 1996, we rejoiced because our options had nearly doubled. The only safe colors to choose from were the 216 “web safe” colors known to work across platforms. The few interactive elements (like contact forms, guest books, and counters) were mostly powered by CGI scripts (predominantly written in Perl at the time). Achieving any kind of unique look involved a pile of hacks all the way down. Interaction was often limited to specific pages in a site.

the development of online standards

At the turn of the century, a new cycle started. Crufty code littered with table layouts and font tags waned, and a push for web standards waxed. Newer technologies like CSS got more widespread adoption by browsers makers, developers, and designers. This shift toward standards didn’t happen accidentally or overnight. It took active engagement between the W3C and browser vendors and heavy evangelism from folks like the Web Standards Project to build standards. A List Apart and books like Designing with Web Standards by Jeffrey Zeldman played key roles in teaching developers and designers why standards are important, how to implement them, and how to sell them to their organizations. And approaches like progressive enhancement introduced the idea that content should be available for all browsers—with additional enhancements available for more advanced browsers. Meanwhile, sites like the CSS Zen Garden showcased just how powerful and versatile CSS can be when combined with a solid semantic HTML structure.

Server-side language like PHP, Java, and.NET took Perl as the primary back-end computers, and the cgi-bin was tossed in the garbage bin. With these improved server-side software, the first period of internet programs started with content-management methods (especially those used in blogs like Blogger, Grey Matter, Movable Type, and WordPress ) In the mid-2000s, AJAX opened gates for sequential interaction between the front end and back close. Pages was now revise their content without having to reload it. A grain of Script frameworks like Prototype, YUI, and ruby arose to aid developers develop more credible client-side conversation across browsers that had wildly varying levels of standards support. Techniques like picture alternative enable the use of fonts by skilled developers and developers. And technology like Flash made it possible to include movies, sports, and even more engagement.

These new methods, requirements, and solutions greatly reenergized the sector. Web style flourished as manufacturers and designers explored more different styles and designs. However, we also relied heavily on numerous tricks. Early CSS was a huge improvement over table-based layouts when it came to basic layout and text styling, but its limitations at the time meant that designers and developers still relied heavily on images for complex shapes ( such as rounded or angled corners ) and tiled backgrounds for the appearance of full-length columns (among other hacks ). All kinds of nested floats or absolute positioning ( or both ) were necessary for complicated layouts. Display and photo substitute for specialty styles was a great start toward varying the designs from the big five, but both tricks introduced convenience and efficiency issues. And JavaScript libraries made it simple for anyone to add a dash of interaction to pages, even at the expense of double, even quadrupling, the download size of basic websites.

The web as software platform

The front-end and back-end symbiosis continued to improve, leading to the development of the modern web application. Between expanded server-side programming languages ( which kept growing to include Ruby, Python, Go, and others ) and newer front-end tools like React, Vue, and Angular, we could build fully capable software on the web. Along with these tools, there were additional options, such as collaborative build automation, collaborative version control, and shared package libraries. What was once primarily an environment for linked documents became a realm of infinite possibilities.

Mobile devices increased in their capabilities as well, and they gave us access to the internet in our pockets at the same time. Mobile apps and responsive design opened up opportunities for new interactions anywhere and any time.

This fusion of potent mobile devices and potent development tools contributed to the growth of social media and other centralized tools for user interaction and consumption. As it became easier and more common to connect with others directly on Twitter, Facebook, and even Slack, the desire for hosted personal sites waned. Social media made connections on a global scale, with both positive and negative outcomes.

Want a much more extensive history of how we got here, with some other takes on ways that we can improve? ” Of Time and the Web” was written by Jeremy Keith. Or check out the” Web Design History Timeline” at the Web Design Museum. A fun tour through” Internet Artifacts” is also provided by Neal Agarwal.

Where we are now

It seems like we’ve reached yet another significant turning point in the last couple of years. As social-media platforms fracture and wane, there’s been a growing interest in owning our own content again. There are many different ways to create a website, from the tried-and-true classic of hosting plain HTML files to static site generators to content management systems of all varieties. The fracturing of social media also comes with a cost: we lose crucial infrastructure for discovery and connection. The IndieWeb‘s Webmentions, RSS, ActivityPub, and other tools can assist with this, but they’re still largely underdeveloped and difficult to use for the less geeky. We can build amazing personal websites and add to them regularly, but without discovery and connection, it can sometimes feel like we may as well be shouting into the void.

Browser support for CSS, JavaScript, and other web components has increased, particularly with initiatives like Interop. New technologies gain support across the board in a fraction of the time that they used to. When I first learn about a new feature, I frequently discover that its coverage is already over 80 % when I check the browser support. Nowadays, the barrier to using newer techniques often isn’t browser support but simply the limits of how quickly designers and developers can learn what’s available and how to adopt it.

With a few commands and a few lines of code, we can currently prototype almost any concept. All the tools that we now have available make it easier than ever to start something new. However, as we upgrade and maintain these frameworks, we eventually pay the upfront costs that these frameworks may initially save in terms of our technical debt.

If we rely on third-party frameworks, adopting new standards can sometimes take longer since we may have to wait for those frameworks to adopt those standards. These frameworks, which previously made it easier to adopt new techniques sooner, have since evolved into obstacles. These same frameworks often come with performance costs too, forcing users to wait for scripts to load before they can read or interact with pages. And when scripts fail ( whether due to poor code, network issues, or other environmental factors ), users frequently have no choice but to use blank or broken pages.

Where do we go from here?

Hacks of today help to shape standards for tomorrow. And there’s nothing inherently wrong with embracing hacks —for now—to move the present forward. Problems only arise when we refuse to acknowledge that they are hacks or when we choose not to replace them. So what can we do to create the future we want for the web?

Build for the long haul. Optimize for performance, for accessibility, and for the user. weigh the costs associated with those user-friendly tools. They may make your job a little easier today, but how do they affect everything else? What is the price to the users? To future developers? To adoption of standards? Sometimes the convenience may be worth it. It’s occasionally just a hack that you’ve gotten used to. And sometimes it’s holding you back from even better options.

Start with standards. Standards continue to evolve over time, but browsers have done a remarkably good job of continuing to support older standards. The same holds true for third-party frameworks, though. Sites built with even the hackiest of HTML from the’ 90s still work just fine today. The same can’t be said about websites created with frameworks even after a few years.

Design with care. Consider the effects of each choice, whether your craft is code, pixels, or processes. The convenience of many a modern tool comes at the cost of not always understanding the underlying decisions that have led to its design and not always considering the impact that those decisions can have. Use the time saved by modern tools to consider more carefully and design with consideration rather than rush to “move fast and break things”

Always be learning. If you constantly learn, you also develop. Sometimes it may be hard to pinpoint what’s worth learning and what’s just today’s hack. Even if you were to concentrate solely on learning standards, you might end up focusing on something that won’t matter next year. ( Remember XHTML? ) However, ongoing learning opens up new neural connections, and the techniques you learn in one day may be useful for guiding future experiments.

Play, experiment, and be weird! The ultimate experiment is this web that we’ve created. It’s the single largest human endeavor in history, and yet each of us can create our own pocket within it. Be brave and try something new. Build a playground for ideas. In your own bizarre science lab, perform bizarre experiments. Start your own small business. There has never been a place where we have more room to be creative, take risks, and discover our potential.

Share and amplify. Share what you think has worked for you as you experiment, play, and learn. Write on your own website, post on whichever social media site you prefer, or shout it from a TikTok. Write something for A List Apart! But take the time to amplify others too: find new voices, learn from them, and share what they’ve taught you.

Go ahead and create a masterpiece.

As designers and developers for the web ( and beyond ), we’re responsible for building the future every day, whether that may take the shape of personal websites, social media tools used by billions, or anything in between. Let’s incorporate our values into the products we produce, and let’s improve the world for everyone. Create that thing that only you are uniquely qualified to make. Then distribute it, improve it, re-use it, or create something new with it. Learn. Make. Share. grow. Rinse and repeat. Everything will change whenever you believe you have mastered the web.

I’d like you to consider this a “yes … and” piece to complement Joe’s post. I’m not trying to reject any of what he’s saying, but rather to give some context to initiatives and options where AI may produce real, positive impacts on people with disabilities. To be clear, I want to take some time to speak about what’s possible in hope that we’ll get there one evening. There are, and we’ve needed to address them, like, yesterday.

Other words

Joe’s article spends a lot of time examining how computer vision versions can create other words. He raises a number of true points about the state of affairs right now. And while computer-vision concepts continue to improve in the quality and complexity of information in their information, their benefits aren’t wonderful. He argues to be accurate that the state of image research is currently very poor, especially for some image types, in large part due to the lack of context-based analysis that exists in the AI systems ( which is a result of having separate “foundation” models for text analysis and image analysis ). Today’s models aren’t trained to distinguish between images that are contextually relevant ( which should probably have descriptions ) and those that are purely decorative ( which might not even need a description ) either. However, I still think there’s possible in this area.

As Joe points out, alt text publishing via human-in-the-loop should be a given. And if AI can intervene to provide a starting place for alt text, even if the swift might say What is this BS? That’s not correct at all … Let me try to offer a starting point— I think that’s a gain.

If we can specifically station a design to examine image usage in context, this may help us more quickly determine which images are likely to be elegant and which ones are likely to be descriptive. That will clarify which situations require image descriptions, and it will increase authors ‘ effectiveness in making their sites more visible.

While complex images—like graphs and charts—are challenging to describe in any sort of succinct way ( even for humans ), the image example shared in the GPT4 announcement points to an interesting opportunity as well. Let’s say you came across a map that was simply the description of the chart’s name and the type of representation it was: Pie graph comparing smartphone usage to have phone usage in US households earning under$ 30, 000 annually. ( That would be a pretty bad alt text for a chart because it would frequently leave many unanswered questions about the data, but let’s just assume that that was the description in place. ) If your website knew that that picture was a pie graph ( because an ship model concluded this ), imagine a world where people could ask questions like these about the creative:

• Are there more smartphone users than have phones?
• How many more?
• Is there a group of people that don’t fall into either of these pots?
• That number, how some?

For a moment, the chance to learn more about graphics and data in this way could be innovative for people who are blind and low vision as well as for those with various types of color blindness, cognitive impairments, and other issues. Putting aside the challenges of large language model ( LLM) hallucinations, where a model only makes up plausible-sounding “facts,” It could also be useful in educational contexts to help people who can see these charts, as is, to understand the data in the charts.

What if you could ask your browser to make a complicated chart simpler? What if you demanded that the line graph be isolated into just one line? What if you could ask your browser to transpose the colors of the different lines to work better for form of color blindness you have? What if you could ask it to switch colors for patterns? That seems like a possibility given the chat-based interfaces and our current ability to manipulate images in modern AI tools.

Now imagine a purpose-built model that could extract the information from that chart and convert it to another format. Perhaps it could convert that pie chart (or, better yet, a series of pie charts ) into more usable ( and useful ) formats, like spreadsheets, for instance. That would be incredible!

Matching algorithms

When Safiya Umoja Noble chose to put her book Algorithms of Oppression, she hit the nail on the head. Although her book focused on how search engines can foster racism, I believe it’s equally true that all computer models have the potential to foster conflict, prejudice, and intolerance. Whether it’s Twitter always showing you the latest tweet from a bored billionaire, YouTube sending us into a Q-hole, or Instagram warping our ideas of what natural bodies look like, we know that poorly authored and maintained algorithms are incredibly harmful. Many of these are the result of a lack of diversity in the people who create and build them. However, when these platforms are built with inclusive features in mind, there is real potential for algorithm development to help people with disabilities.

Take Mentra, for example. They serve as a network of employment for people who are neurodivers. They match job seekers with potential employers using an algorithm based on more than 75 data points. On the job-seeker side of things, it considers each candidate’s strengths, their necessary and preferred workplace accommodations, environmental sensitivities, and so on. On the employer side, it takes into account each work environment, communication strategies for each job, and other factors. Mentra made the decision to change the script when it came to typical employment websites because it was run by neurodivergent people. They use their algorithm to propose available candidates to companies, who can then connect with job seekers that they are interested in, reducing the emotional and physical labor on the job-seeker side of things.

When more people with disabilities are involved in developing algorithms, this can lower the likelihood that these algorithms will harm their communities. That’s why diverse teams are so crucial.

Imagine that a social media company’s recommendation engine was tuned to analyze who you’re following and if it was tuned to prioritize follow recommendations for people who talked about similar things but who were different in some key ways from your existing sphere of influence. For instance, if you follow a group of white men who are not white or aren’t white and who also discuss AI, it might be wise to follow those who are also disabled or who are not white. If you followed its advice, you might gain a more in-depth and nuanced understanding of what’s happening in the AI field. These same systems should also use their understanding of biases about particular communities—including, for instance, the disability community—to make sure that they aren’t recommending any of their users follow accounts that perpetuate biases against (or, worse, spewing hate toward ) those groups.

Other ways that AI can assist people with disabilities

I’m sure I could go on and on about using AI to assist people with disabilities, but I’m going to make this last section into a bit of a lightning round. In no particular order:

Voice preservation You may be aware of the voice-prescribing options from Microsoft, Acapela, or others, or you may have seen the announcement for VALL-E or Apple’s Global Accessibility Awareness Day. It’s possible to train an AI model to replicate your voice, which can be a tremendous boon for people who have ALS ( Lou Gehrig’s disease ) or motor-neuron disease or other medical conditions that can lead to an inability to talk. We need to approach this tech responsibly because it has the potential to have a truly transformative impact, which is why it can also be used to create audio deepfakes.
• voice recognition Researchers like those in the Speech Accessibility Project are paying people with disabilities for their help in collecting recordings of people with atypical speech. As I type, they are actively seeking out people who have Parkinson’s and related conditions, and they intend to expand this list as the project develops. More people with disabilities will be able to use voice assistants, dictation software, and voice-response services, as well as to use only their voices to control computers and other devices, according to this research.
• Text transformation. The most recent generation of LLMs is capable of altering already-existing text without giving off hallucinations. This is incredibly empowering for those who have cognitive disabilities and who may benefit from text summaries or simplified versions, or even text that has been prepared for bionic reading.

The importance of diverse teams and data

We must acknowledge that our differences matter. The intersections of the identities we live in have an impact on our lived experiences. These lived experiences—with all their complexities ( and joys and pain ) —are valuable inputs to the software, services, and societies that we shape. Our differences must be reflected in the data we use to develop new models, and those who provide that valuable information must be compensated for doing so. More robust models are produced by inclusive data sets, which promote more justifiable outcomes.

Want a model that doesn’t demean or patronize or objectify people with disabilities? Make sure that you include information about disabilities that is written by people who have a range of disabilities and that is well represented in the training data.

Want a model that doesn’t speak in ableist language? You may be able to use existing data sets to build a filter that can intercept and remediate ableist language before it reaches readers. Despite this, AI models won’t be replacing human copy editors anytime soon when it comes to sensitivity reading.

Want a copilot for coding that provides recomprehensible recommendations after the jump? Train it on code that you know to be accessible.

I have no doubt that AI has the potential to harm people today, tomorrow, and long into the future. However, I also think that we can acknowledge this and make thoughtful, thoughtful, and intentional changes in our approaches to AI that will reduce harm over time as well. Today, tomorrow, and well into the future.

Many thanks to Kartik Sawhney for supporting the development of this article, Ashley Bischoff for providing me with invaluable editorial support, and, of course, Joe Dolson for the prompt.

Voices are present on the web. Our pattern processes may also.

Designing methods as living language

Design techniques are living languages, not element libraries. The elements are called terms, the patterns are called phrases, and the sentences are called layouts. The conversations we have with people are what shape the stories that our goods represent.

The more tones a language can help without losing its meaning, the more smoothly it is spoken. English in Scotland and English in Sydney are clearly different, but both are clearly English. The terminology adapts to the situation while maintaining its fundamental message. As a Brazilian Portuguese speech who learned English with an American highlight and resides in Sydney, this couldn’t be more visible to me.

Our pattern processes must operate in the same manner. Systems that flex under pressure from the environment are weak due to rigorous adhesion to visual rules. Fluidic devices can bend without rupturing.

Consistent behavior turns into a captivity

Regular components would speed up development and bring together experiences, which was a promise of design systems. But as methods evolved and products developed more sophisticated, that claim has grown to the point of being a prison. Team submit “exception” demands innumerate. Alternatively of system parts, items build with solutions. Designers devote more time defending persistence than resolving customer issues.

Accents must be learned in our style systems.

A design pronunciation is a comprehensive adaptation of a design system that maintains its foundational principles while creating novel patterns for particular situations. Dials maintain the state’s necessary language while expanding its vocabulary to fit various people, conditions, or constraints, unlike one-off customizations or product themes.

When Perfect Consistency Is A Problem

I at Booking.com learned this lesson the hard way. Everything we A/B tested was color, version, key, and logo colors. I found this stunning as a specialist with a background in graphic design and practice creating brand style manuals. Booking expanded into a giant without ever taking into account physical consistency, despite everyone’s adoration for Airbnb’s flawless design system.

The conflict taught me things important: solved issues are, not consistency.

At Shopify Our most cherished piece of technology was Polyris ( ), a mature design language that worked well for laptop manufacturers. We were expected to follow Polaris as-is as a product group. Then my accomplishment group slammed an” Oh, Ship”! momentous as we had to create an app for inventory pickers using our program on shared, battered Android scanners in dark aisles, wearing heavy gloves, scanning dozens of items per second, some with only minimal English comprehension.

Polaris common: 0 % work completion.

Every element that worked flawlessly for retailers entirely failed to satisfy pickers. Bright backgrounds produced light. Click targets for 44px were hidden behind covered fingers. Sentence-case brands took too long to interpret. Multi-step flows confused non-native listeners.

We had to choose whether to completely reject Polaris or learn to speak warehouse.

The Birth of a Pronunciation

We favored creation over trend. We developed what we now refer to as a pattern dialect by adhering to Polaris’s key principles of clarity, efficiency, consistency.

Results: Task completion increased from 0 % to 100 %. From three days to one change, recruitment time was cut.

This was a dialect, not one of flexibility or theming; it was a rigorous version that preserved Polaris ‘ core grammar while creating new words for a particular context. Polis hadn’t failed; it had picked up the language inventory.

The Flexibility Framework

Working on the Jira platform, which is a component of the larger Atlassian structure, I advocated formalizing this understanding at Atlassian. We needed organized flexibility because dozens of products shared a design language across various codebases, but we built our processes from scratch. The previous model, which included special approvals and exception calls, was failing on a level.

To help manufacturers determine how flexible their elements should remain, we created the Flexibility Framework:

Every aspect was tied together during a transportation remodel. International search and logo remain constant. The actions of situational context and breadcrumbs became flexible. Product teams could quickly identify areas where creativity was welcomed and where consistency was important.

The Decision Ladder

Freedom requires restrictions. When principles should be broken, we created a straightforward rope.

Good: Send with already-existing system parts. Strong, reliable, and proven.

Better: somewhat stretch a part. Document the shift. Bring developments up to the program so that everyone can use it.

Best to first prototype the best experience. Update the system to support it if consumer assessment validates the profit.

Which option allows users to achieve the quickest?

Laws are tools, not replicas.

Unity defeats consistency

Email, Drive, and Maps all have a distinctive Google voice, but each one speaks with its own. They achieve cohesion through shared rules, no copied parts. About$ 30K in engineer time is spent on one more year of key color debate.

Competency is a user outcome, while unification is a brand outcome. Part with the customer when the two fight.

Leadership Without Gates

How can symmetry be maintained while enabling languages? Treat your diction like a life dictionary:

Document every change, such as dialects or warehouses. director with explanations for before and after pictures.

Promote shared designs: when three teams freely adopt a dialect and assess its core inclusion.

Retire old idioms using flags and migration notes; this is never a big-bang cleanse. Degrade with context.

A living vocabulary performs better than a freezing handbook.

Your First Dialect: Start Small

Do you have time to introduce accents? Begin with a bad practice:

Get one user flow this week where best consistency prevents tasks from being completed. Could be that mobile users have trouble with desktop-sized components or mobility issues that your regular patterns don’t target.

What causes common patterns to fail in this environment of documentation? climate restrictions person capabilities intensity of the process?

Focus on actions rather than aesthetics, style one systematic change. If gloves are the issue, bigger targets aren’t “broken the program”; they’re serving the consumer. Create the adjustments and incorporate them into your life.

Test and determine: Does the shift make tasks more effective? Time for performance User pleasure

Present the benefits: Fluency has paid for itself if that pronunciation frees perhaps half a jump.

Beyond the Component Library

We’re cultivating design languages, no managing design systems anymore. language that develop along with their speakers. tones without losing their significance in language. language that prioritize the needs of people over visual ideals.

Our buttons breaking the style guide didn’t matter to the warehouse workers who went from 0 % to 100 % on their jobs. They emphasized the success of the keys.

Your customers share your opinion. Offer your program permission to speak their speech.

Imagine this: Two people are conversing in what appears to be the same style issue in a conference room at your software company. One is talking about whether the staff has the proper skills to handle it. The other is examining whether the answer really addresses the user’s issue. Similar room, the same issue, and entirely different perspectives.

This is the lovely, sometimes messy fact of having both a Design Manager and a Guide Designer on the same group. And you’re asking the right question if you’re wondering how to make this job without creating confusion, coincide, or the feared” to some cooks” situation.

The conventional solution has been to create clear traces on an organizational chart. The Design Manager handles persons, the Lead Designer handles art. Problem is fixed, isn’t it? Except that fresh nonprofit charts are fantasy. In fact, both roles care greatly about crew health, style quality, and shipping great work.

When you begin to think of your style organization as a pattern organism, the magic happens when you accept collide rather than fight it.

A Healthy Design Team’s Biology

Here’s what I’ve learned from years of being on both sides of this formula: think of your design team as a living cell. The Design Manager concentrates on the internal security, career advancement, team dynamics, and other factors. The Lead Designer concentrates on the body ( the handiwork, the design standards, the hands-on projects that are delivered to users ).

But just like mind and body aren’t totally separate systems, but, also, do these tasks overlap in significant ways. Without working in harmony with one person, you can’t have a good person. The technique is to know where those aligns are and how to manage them gently.

When we look at how good team really function, three critical devices emerge. Each requires the collaboration of both jobs, but one must assume the lead role in maintaining that system sturdy.

Folks & Psychology: The Nervous System

Major caretaker: Design Manager
Supporting position: Direct Artist

The anxious system is all about mental health, comments, and signals. When this technique is good, information flows easily, people feel safe to take risks, and the staff may react quickly to new problems.

The main caretaker here is the Design Manager. They are keeping track of the team’s emotional state, making sure feedback loops are healthier, and creating the environment for growth. They’re hosting job meetings, managing task, and making sure no single burns out.

However, the Lead Designer has a significant supporting position. They’re offering visual feedback on build development needs, identifying stagnant design skills in someone, and pointing out potential growth opportunities that the Design Manager might overlook.

Design Manager tends to:

• development planning and job conversations
• mental stability and dynamics of the group
• Job management and resource planning
• Performance evaluations and opinions management methods
• Providing learning options

Direct Custom supports by:

• Providing craft-specific evaluation of team member creation
• identifying opportunities for growth and style ability gaps
• Giving design mentoring and assistance
• indicating when a group is prepared for more challenging tasks.

The Muscular System: Design & Execution

Major custodian: Lead Designer
Design Manager supporting position

The skeletal structure focuses on developing strength, coordination, and talent development. When this technique is healthy, the team can do complicated design work with precision, maintain regular quality, and adjust their craft to fresh challenges.

The Lead Designer is the main caregiver at this place. They oversee the creation of quality standards, provide craft instruction, and set design standards. They’re the ones who can tell you if a design decision is sound or if we’re solving the right problem.

However, a significant supporting role is played by the Design Manager. They are making sure the team has the resources and support they need to perform their best work, such as ensuring that an athlete receives proper nutrition and recovery time.

Lead Designer tends to:

• Definition of system usage and design standards
• Feedback on design output that meets the required standards
• Experience direction for the product
• Design choices and product-wide alignment are important.
• advancement of craft and innovation

Design Manager supports by:

• ensuring that design standards are understood and accepted by all members of the team
• Confirming that the right direction is being used is being done
• Supporting practices and systems that scale without bottlenecking
• facilitating design alignment among all teams
• Providing resources and removing obstacles to outstanding craft work

The Circulatory System: Strategy &amp, Flow

Shared caretakers: Lead Designer and Design Manager, respectively.

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

This is the true partnership that occurs. Although both roles are responsible for maintaining the circulation, they both have unique perspectives to offer.

Lead Designer contributes:

• User requirements are satisfied with the finished product
• overall experience and product quality
• Strategic design initiatives
• User needs for each initiative are based on research.

Contributes the design manager:

• Communication to team and stakeholders
• Stakeholder management and alignment
• Team accountability across all levels
• Strategic business initiatives

Both parties work together on:

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

Keeping the Organism Healthy

Understanding that all three systems must work together is the key to making this partnership sing. A team will eventually lose their way despite excellent craftmanship and poor psychological safety. A team with great culture but weak craft execution will ship mediocre work. A team that has both but poor strategic planning will concentrate on the wrong things.

Be Specific About the System You’re Defending.

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

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

Create Positive Feedback Loops

Which partnerships have created clear feedback loops between the systems in the most effective ways?

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

The nervous system receives the message” The team’s craft skills are progressing more quickly than their project complexity.”

We’re seeing patterns in team health and craft development that suggest we need to adjust our strategic priorities, both systems say to the circulatory system.

Handle Handoffs Gracefully

When something switches from one system to another, this partnership’s most crucial moments occur. This might occur when a team’s ( nervous system ) needs to be exposed to a design standard ( muscular system ), or when a strategic initiative ( circulatory system ) needs specific craft execution ( muscular system ).

Make these transitions explicit. I’ve defined the new component requirements. Can you give me some ideas on how to get the team up to speed?” or” We’ve agreed on this strategic direction. From here, I’ll concentrate on the particular user experience approach.

Stay curious and avoid being territorial.

The Design Manager who never thinks about craft, or the Lead Designer who never considers team dynamics, is like a doctor who only looks at one body system. Great design leadership requires both parties to be concerned with the entire organism, even when they are not the primary caregiver.

This entails posing questions rather than making assumptions. ” What do you think about the team’s craft development in this area”? or” How do you think this is affecting team morale and workload?” keeps both viewpoints at the forefront of every choice.

When the Organism Gets Sick

This partnership can go wrong even with clear roles. Here are the most typical failure modes I’ve seen:

System Isolation

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

The signs: Team members receive conflicting messages, poor morale, and poor communication.

Reconnect with other people and discuss shared outcomes. What are you both trying to achieve? It’s typically excellent design work that arrives on time from a capable team. Discover how both systems accomplish that goal.

Poor Circulation

There is no clear strategic direction, shifting priorities, or accepting responsibility for the flow of information.

The signs: Team members are unsure of their priorities, work is duplicated or dropped, and deadlines are missed.

The treatment: Explicitly assign responsibility for circulation. Who is communicating with whom? When? What’s the feedback loop?

Autoimmune Response

The other person’s expertise makes them feel threatened. The Design Manager thinks the Lead Designer is undermining their authority. The Design Manager is allegedly misunderstanding the craft, according to the Lead Designer.

The symptoms: defensive behavior, territorial disputes, middle-class teammates, etc.

The treatment: Remember that you’re both caretakers of the same organism. The entire team suffers when one system fails. The team thrives when both systems are strong.

The Payoff

Yes, this model calls for more interaction. Yes, it requires that both parties be able to assume full responsibility for team health. But the payoff is worth it: better decisions, stronger teams, and design work that’s both excellent and sustainable.

The best of both worlds can be found in the combination of strong people leadership and deep craft expertise. When one person is overly sick, on vacation, or overworked, the other can help keep the team’s health. When a decision requires both the people perspective and the craft perspective, you’ve got both right there in the room.

The framework scales, which is most important. You can apply the same system thinking to fresh challenges as your team expands. Need to launch a design system? Both the muscular system ( standards and implementation ), the nervous system (team adoption and change management ), and both have a tendency to circulate ( communication and stakeholder alignment ).

The End result

The relationship between a Design Manager and Lead Designer isn’t about dividing territories. Multipliering impact is what is concerned with. Magic occurs when both roles are aware that they are promoting various aspects of a healthy organism.

The mind and body work together. The team receives both the craft excellence and strategic thinking they need. And most importantly, the work that is distributed to users benefits both sides.

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

I’ve lost count of the times when promising ideas go from being useless in a few days to being useless after working as a solution designer for too long to explain.

Financial goods, which is my area of expertise, are no exception. It’s tempting to put as many features at the ceiling as possible and hope someone sticks because people’s true, hard-earned money is on the line, user expectations are high, and a crammed market. However, this strategy will lead to disaster. Why? How’s why:

The drawbacks of feature-first creation

It’s simple to get swept up in the enthusiasm of developing innovative features when you start developing a financial product from scratch or are migrating existing user journeys from papers or telephony channels to online bank or mobile apps. They may think,” If I may only add one more thing that solves this particular person problem, they’ll enjoy me”! But what happens if you eventually encounter a roadblock as a result of your security team’s negligence? don’t like it? When a difficult-fought film fails to win over viewers or fails due to unanticipated difficulty?

The concept of Minimum Viable Product ( MVP ) comes into play in this context. Even if Jason Fried doesn’t usually refer to this concept, his book Getting Real and his audio Redo frequently discuss it. An MVP is a product that offers only enough value to your users to keep them interested, but not so much that it becomes difficult to keep up. Although the idea seems simple, it requires a razor-sharp eye, a brutal edge, and the courage to stand up for your position because” the Columbo Effect” makes it easy to fall for something when one always says” just one more thing …” to add.

The issue with most fund apps is that they frequently turn out to be reflections of the company’s internal politics rather than an experience created exclusively for the customer. This implies that the priority is to provide as some features and functionalities as possible to satisfy the requirements and desires of competing internal departments as opposed to a distinct value statement that is focused on what people in the real world actually want. These products may therefore quickly become a muddled mess of confusing, related, and finally unlovable client experiences—a feature salad, you might say.

The significance of the foundation

What is a better strategy, then? How may we create products that are user-friendly, firm, and, most importantly, stick?

The concept of “bedrock” comes into play in this context. The main component of your item that really matters to people is Bedrock. The foundation of worth and relevance over time is built upon it.

The core must be in and around the standard servicing journeys in the retail banking industry, which is where I work. People only look at their existing accounts once every blue sky, but they do so every day. They purchase a credit card every year or every other year, but they at least once a month assess their stability and pay their bills.

The key is in identifying the main tasks that individuals want to complete and therefore persistently striving to make them simple, reliable, and trustworthy.

But how do you reach the foundation? By focusing on the” MVP” strategy, giving ease precedence, and working incrementally toward a clear value proposition. This means avoiding pointless extras and putting your customers first, making the most of them.

It also requires some nerve, as your coworkers might not always agree on your eyesight at first. And dubiously, occasionally it can even suggest making it clear to customers that you won’t be coming to their house and making their breakfast. Sometimes you need to use the sporadic “opinionated user interface design” ( i .e. clunky workaround for edge cases ) to test a concept or to give yourself some more time to work on something more crucial.

Functional methods for creating stick-like financial goods

What are the main learnings I’ve made from my own research and practice, then?

1. What trouble are you trying to solve first, and make a distinct “why”? For whom? Before beginning any project, make sure your goal is completely clear. Make certain it also complies with the goals of your business.
2. Avoid the temptation to put too many features at once and focus on getting that right first. Choose one that actually adds benefit, and work from that.
3. When it comes to financial items, clarity is often over richness. Eliminate unwanted details and concentrate solely on what matters most.
4. Accept ongoing iteration: Bedrock is not a fixed destination; it is a fluid process. Continuously collect customer comments, make product improvements, and advance in that direction.
5. Stop, glance, and talk: You must test your product frequently in the field rather than just as part of the shipping process. Use it for yourself. Work A/B testing. User opinions on Gatter. Speak to those who use it, and change things up correctly.

The “bedrock dilemma”

This is an intriguing conundrum: sacrificing some of the potential for short-term progress in favor of long-term stability is at play. But the reward is worthwhile: products built with a focus on rock will outlive and surpass their rivals over time and provide users with long-term value.

How do you begin your quest for rock, then? Take it slowly. Start by identifying the underlying factors that your customers actually care about. Concentrate on developing and improving a second, potent function that delivers real value. And most importantly, make an obsessive effort because, in the words of Abraham Lincoln, Alan Kay, or Peter Drucker ( whew! The best way to foretell the future is to make it, he said.

Justin Long and Kate Bosworth are not outsiders to wolves, just like so many people who live in the greater Southern California. The music power couple, who first met on 2022’s House of Darkness, frequently encounter the shaggy little men in their Los Angeles neighborhood. They also see bobcats, mountain cats, and a amazingly wide range of […]…

The first article Foxes ‘ Justin Long and Kate Bosworth Channel Real-Life Terror into Horror-Comedy appeared first on Den of Geek.

Justin Long and Kate Bosworth are not strangers to foxes, just like so many people who live in the greater Southern California. The music power couple, who first met on 2022’s House of Darkness, frequently encounter the shaggy little men in their Los Angeles neighborhood, as well as wildcats, mountain lions, and a amazingly wide range of wildlife.

With a sardonic laugh, Bosworth admits,” We have animals that go through our garbage all the time. We frequently run into a bear in our town that I’ve nicknamed Sugar.

However, it is still the wolves that capture the imagination of the multimedia and dog owners. In the first show of his Youtube talk show, John Mulaney talked about them being a popular concern, and the occasional dog attack can be national news.

” We have known some neighbors who have lost their dogs that way,” says Colin Minihan, a director who was piqued by the Wolves story by Tad Daggerhart and Nick Simon. Although it was a semi-common issue, it only sounded absurdly funny sufficiently to make people laugh as well as scare people.

Kate “read the text first,” Long informs us. ” And the text was quite entertaining. There is a B-movie component to it; we also watched” Spielberg Presents” films in the 1980s and 1990s, along with films like Gremlins and Arachnophobia, so there’s a little bit of that.

There was also a chance to confront their own apprehensions as dog owners.

Because our dog is very large, Bosworth explains,” We think about it particularly with our cat.” He is an 85-pound large son called Happy. He actually plays with foxes. He enjoys playing with them. On my relatives ‘ city in Los Angeles, there are wolves that live there, and he calls them out when he goes to their lair. He is so large, and like Marmaduke, they won’t let him down. However, our cats are tiny subjects.

Bosworth and Long, who enjoy treating the fabric with a smile, were drawn to the Arachnophobia levels of station, though. After all, Long has frequently fought for the elimination of foxes ‘ fur trade with PETA and has made a point to mention in this film that “people have a lot of myths about wolves.” We didn’t need to be a part of demonizing them. We simply want people to be aware that these are foxes and that something has happened to them. They’re never your usual coyote.

These are scary movie wolves, right down to how they were eventually created by Minihan and firm, to put it bluntly. The animals film in the completed movie more closely resemble wolves, perhaps of the lycanthrope variety, than actual coyotes.

” One of the problems of shooting in Bogotá, Colombia is that we don’t really sail wolves inside,” Minihan explains. Second was discussing how a fox can travel on a movie set with coaches. They are scared, but they don’t. You may set three of them up, and you might be able to get one to perform an A-B behavior, which is trek from this point forward. However, there is no way to go and stalk real coyotes from LA because I can’t take pictures of them because we built puppets and had several of them so the actors may interact with them, but we created a ferocious being that we could create.

The end result was a movie that reflected the mood Bosworth and Long wanted in their first engagement as manufacturers, stars, and spouses. It is somewhat disrespectful and lighthearted in its portrayal of a family under siege, but still gnarly enough to be premiered at Fantastic Fest. Although the film is full of around jokes about residing in the Hollywood Hills, Minihan claims that Long and Bosworth would always be portrayed as the usual all-American home surrounded by Tinseltown weirdos. Ironic because, as the chairman notes, Long and Bosworth are” the similar people” on as out.

Bosworth remarks,” We have a lot of fun together. We may forget that the heroes, our fictitious engaged few, were tense with one another because we are so fun as people. When Colin would interrupt us and say,” Men, this pair is supposed to be on the rocks,” we would come,” Oh yeah, we forgot” as we would get lost in a field that was just playing.

There is a distance between them, but I guess I wasn’t a good sufficient professional to keep track of that, the long, smiley faces.

In the end, Coyotes is a family-friendly film. In addition to Long and Bosworth playing the lead roles in the movie, Minihan’s real-life companion, Brittany Allen, plays one of those Hollywood oddballs, named Julie, and writes the film’s score, all while Minihan edited the picture.

When he’s in his chairman mode and I’m in my actor mode, our collaboration is quite different from the late nights when we’re staring at a piece up and obsessing over details of “oh, this jump scare go here”? ‘ &#8221, says Allen. It uses various parts of our brains and various methods of communication.

They even experienced an eerie astute fear while editing the image. The strange reason the creatures are attacking relatives in the evening is not fully explained until the third action, which is also when a dramatic, artificial fire starts blazing in the hills. But, the original text stated that the coyotes went on a frenzy because a large fire was spread throughout Hollywood; however, this was a clever decision that was made, though Minihan claims that it was for “budgetary” reasons. In publish, it turned out to be beautiful.

” We reside in Pasadena,” says Minihan. And I watched Eaton Canyon crumble as I waited until three or four in the morning to hear the policeman tell us to leave our home. I am aware that the same thing occurred with Kate and Justin. Our lives are just so closely resembling artwork, which is strange.

Additionally, it was a time that persisted throughout the completed movie.

According to Minihan,” I wanted to find a way in the change to recognize that time… so I walked around Altadena, utterly destroyed, with an ancient 16mm film camera and shot imagery that I was heartbroken by, and I made that part of the movie’s opening credit sequence.” In consequence, it seems that fires are still at least partially to blame for the carnage that occurs in the narrative. It’s impossible to ignore the real crises occurring in the natural world, even when embracing B-creature feature fantasy.

Coyotes debuts on October 3.

The first article Foxes ‘ Justin Long and Kate Bosworth Channel Real-Life Terror into Horror-Comedy appeared first on Den of Geek.

Although I’m not sure when I first heard this statement, it has stuck with me over the centuries. How do you generate solutions for scenarios you can’t think? Or create items that function on products that have not yet been created?

Flash, Photoshop, and flexible pattern

When I first started designing sites, my go-to technology was Photoshop. I set about making a layout that I would eventually fall content into a 960px cloth. The growth phase was about attaining pixel-perfect reliability using set widths, fixed levels, and absolute placement.

All of this was altered by Ethan Marcotte’s 2010 post in A List Off entitled” Responsive Web Design.” I was sold on responsive pattern as soon as I heard about it, but I was even terrified. The pixel-perfect models full of special figures that I had formerly prided myself on producing were no longer good enough.

My first encounter with flexible style didn’t help my fear. My second project was to get an active fixed-width website and make it reactive. I quickly realized that you didn’t just put responsiveness at the end of a job. To make smooth design, you need to prepare throughout the style stage.

A new way to style

Removing restrictions and creating content that can be viewed on any device has always been the goal of designing responsive or liquid websites. It relies on the use of percentage-based design, which I immediately achieved with local CSS and power groups:

.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%;}

Therefore using Sass to re-use repeated slabs of code and transition to more semantic html:

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

Media answers

The next ingredient for reactive design is press queries. Without them, regardless of whether the content remained readable, would shrink to fit the available space. ( The exact opposite issue developed with the introduction of a mobile-first approach. )

Media answers 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.

String premium was a mainstay of early flexible design, present in all the frequently used systems 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 difficulty arose as I moved from a design firm building websites for smaller- to medium-sized companies, to larger in-house teams where I worked across a collection of related sites. In those positions, I began to work more frequently with recyclable parts.

Our rely on multimedia queries resulted in parts that were tied to frequent screen sizes. If the goal of part libraries is modify, then this is a real problem because you can just use these components if the devices you’re designing for correspond to the viewport sizes used in the pattern library—in the process never really hitting that “devices that don’t already occur” goal.

Then there’s the problem of space. Media answers 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. Workarounds for JavaScript exist, but they can lead to dependencies 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 elements are meant 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 issue is that layout is still used 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?

The best place to make that choice is probably not a component library that is disconnected from context and real content.

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.

Without having strong cross-browser support for them, it’s difficult to say for certain whether container queries will be a success story. Responsive component libraries would definitely evolve how we design and would improve the possibilities for reuse and design at scale. However, we might always need to modify these elements to fit 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 of this is that you don’t have 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 is only supported in Firefox at the time of writing, but the above code can be implemented behind an @supports feature query.

Intrinsic layouts

I’d be remiss not to mention intrinsic layouts, a term used by Jen Simmons to describe a mix of contemporary and traditional 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.

frunits is a statement that says,” I want you to distribute the extra space in this way, but never make it smaller than the content that is inside.”

—Jen Simmons,” Designing Intrinsic Layouts”

Intrinsic layouts can also make use of a mix of fixed and flexible units, letting the content choose how much space it occupies.

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. Without having the same breakpoints or the same amount of content as in the previous implementation, components and patterns can be lifted and reused.

We can now create designs that adapt to the space they have, the content within them, and the content around them. We can create responsive components using an intrinsic approach without relying 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. It’s another “everything changed” moment for me.

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 possible explanation for that is that I now work for a sizable company, which is quite different from the design agency position I held 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 possibility is that I’m now more prepared for change. In 2010 I was new to design in general, the shift was frightening and required a lot of learning. Additionally, an intrinsic approach isn’t exactly new; it’s about applying existing skills and CSS knowledge in a unique 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.

Ten years ago, responsive grid systems were everywhere. With a framework like Bootstrap or Skeleton, you had a responsive design template at your fingertips.

Because the benefit of having a selection of units is a hindrance when it comes to creating layout templates, intrinsic design and frameworks do not go hand in hand quite as well. 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 used Photoshop templates for desktop, tablet, and mobile devices to drop designs into and show how the site would appear throughout our careers at some point.

How do you do that now, with each component responding to content and layouts flexing as and when they need to? This kind of design must take place in the browser, which is something I’m very fond 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. It’s not ideal to do this in a graphics-based software package. In code, we can add longer sentences, more radio buttons, and extra tabs, and watch in real time as the design adapts. Does it continue to function? 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.

First, the content

Content is not constant. After all, to design for the unanticipated or unexpected, we must take into account changes in content, like in our earlier Subgrid card illustration, which allowed the cards to modify both their own content and that of their sibling components.

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 the dated markup tricks below,

 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.

Directional variables must be set in the Sass version.

$direction: rtl;$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 real estate.

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.

Fluid and fixed

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 % of its container’s preferred value, with no exceptions for 300px and 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. By anticipating unforeseen language or direction changes, we can begin creating future-proofing designs. And we can increase flexibility by setting desired dimensions alongside flexible alternatives, allowing for more or less content to be displayed correctly.

First, the circumstances

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 completely different design process for someone using a mobile phone and moving through a crowded street in glaring sunshine from a person using a desktop computer. Situations and environments are hard to plan for or predict because they change as people react to their own unique challenges and tasks.

Choice is so crucial because of this. 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. However, in the real world, our users may be commuters using smaller mobile devices that may experience drops in connectivity while traveling on trains or other modes of transportation. 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.

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 inquiries

Media answers 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.

The Media Queries Level 5 spec is still being developed as of this writing. It introduces some really exciting queries that in the future will help us design for multiple other unexpected situations.

For instance, there is a light-level feature that enables you to alter a user’s style when they are in the sun or the 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 answers 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 anticipate is that things will change. Devices in particular change faster than we can keep up, with foldable screens already on the market.

We can design for content, but we can’t do it the same way we have for this constantly changing landscape. 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. There is a lot more we can do to adopt a more intrinsic approach, from responsive components to fixed and fluid units. 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 circumstances, we need to make sure our goods are usable when people need them, whenever and wherever that may 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.

” Any opinion”? is perhaps one of the worst ways to ask for opinions. It’s obscure and unfocused, and it doesn’t give us a sense of what we’re looking for. Getting good opinions starts sooner than we might hope: it starts with the demand.

When we realize that receiving input can be seen as a form of pattern analysis, it might seem counterintuitive to begin the process with a question. In the same way that we wouldn’t perform any studies without the correct questions to get the insight that we need, the best way to ask for feedback is also to build strong issues.

Design analysis is not a one-time procedure. Sure, any great comments process continues until the project is finished, but this is especially true for layout because architecture work continues iteration after iteration, from a high level to the finest details. Each stage requires its unique set of questions.

And suddenly, as with any great research, we need to examine what we got up, get to the base of its perspectives, and take action. Iteration, evaluation, and issue. This look at each of those.

The query

Being available to input is important, but we need to be specific about what we’re looking for. Any comments,” What do you think,” or” I’d love to hear your mind” at the end of a presentation are likely to garner a lot of different ideas, or worse, to make people follow the lead of the first speaker. And next… we get frustrated because vague issues like those you turn a high-level moves review into folks rather commenting on the borders of buttons. Which theme may be important, so it might be difficult to get the team to pay attention to it.

But how do we get into this scenario? It’s a combination of various components. One is that we don’t often consider asking as a part of the input approach. Another is how healthy it is to keep the issue open and assume that everyone else will agree. Another is that in nonprofessional debate, there’s usually no need to be that exact. In summary, we tend to undervalue the value of the concerns, so we don’t work to make them better.

The work of asking good questions guidelines and focuses the criticism. It also serves as a form of acceptance, outlining your willingness to make comments and the types of responses you want to receive. It puts people in the right emotional position, especially in situations when they weren’t expecting to provide feedback.

There isn’t a second best method to request comments. It simply needs to be certain, and sensitivity can take several shapes. The stage than depth model for design critique has been a particularly helpful tool for my coaching.

” Stage” refers to each of the actions of the process—in our event, the design process. The type of input changes as the customer research moves forward to the final design. But within a single stage, one might also examine whether some assumptions are correct and whether there’s been a suitable language of the amassed input into updated designs as the task has evolved. The layers of user experience could serve as a starting point for potential questions. What do you want to know: Project objectives? user requirements? Functionality? Content? Interaction design? a system of information architecture UI design? navigation planning Visual design? Branding?

Here’re a few example questions that are precise and to the point that refer to different layers:

• Functionality: Is it desirable to automate account creation?
• Interaction design: Take a look through the updated flow and let me know whether you see any steps or error states that I might’ve missed.
• Information architecture: This page contains two competing pieces of information. Is the structure effective in communicating them both?
• User interface design: What do you think about the top-most error counter, which ensures that you can see the next error even when the error is outside the viewport?
• Navigation design: From research, we identified these second-level navigation items, but once you’re on the page, the list feels too long and hard to navigate. Do you have any suggestions for how to handle this?
• Visual design: Are the sticky notifications in the bottom-right corner visible enough?

How much of a presentation’s depth would be on the other axis of specificity. For example, we might have introduced a new end-to-end flow, but there was a specific view that you found particularly challenging and you’d like a detailed review of that. This can be especially helpful from one iteration to the next when it’s crucial to highlight the areas that have changed.

There are other things that we can consider when we want to achieve more specific—and more effective—questions.

A quick fix is to get rid of the generic qualifiers from questions like “good”, “well,” “nice,” “bad,” “okay,” and” cool.” For example, asking,” When the block opens and the buttons appear, is this interaction good”? is it possible to look specific, but you can spot the “good” qualifier and make the question” When the block opens and the buttons appear, is it clear what the next action is” look like?

Sometimes we actually do want broad feedback. That’s uncommon, but it can occur. In that sense, you might still make it explicit that you’re looking for a wide range of opinions, whether at a high level or with details. Or perhaps you should just say,” At first glance, what do you think”? so that it’s clear that what you’re asking is open ended but focused on someone’s impression after their first five seconds of looking at it.

Sometimes the project is particularly broad, and some areas may have already been thoroughly explored. In these situations, it might be useful to explicitly say that some parts are already locked in and aren’t open to feedback. Although it’s not something I’d recommend in general, I’ve found it helpful in avoiding falling into rabbit holes like those that could lead to further refinement but aren’t what’s important right now.

Asking specific questions can completely change the quality of the feedback that you receive. People who have less refined critique abilities will now be able to provide more useful feedback, and even experienced designers will appreciate the clarity and effectiveness gained from concentrating solely on what is required. It can save a lot of time and frustration.

The iteration

Design iterations are probably the most visible part of the design work, and they provide a natural checkpoint for feedback. Many design tools have inline commenting, but many of those methods typically display changes as a single fluid stream in the same file. These methods cause conversations to vanish once they’re resolved, update shared UI components automatically, and require designs to always display the most recent version unless these would-be useful features were manually turned off. The implied goal that these design tools seem to have is to arrive at just one final copy with all discussions closed, probably because they inherited patterns from how written documents are collaboratively edited. That approach to design critiques is probably not the best approach, but some teams might benefit from it even if I don’t want to be too prescriptive.

The asynchronous design-critique approach that I find most effective is to create explicit checkpoints for discussion. I’m going to use the term iteration post for this. It refers to a write-up or presentation of the design iteration followed by a discussion thread of some kind. This can be used on any platform that can accommodate this structure. By the way, when I refer to a “write-up or presentation“, I’m including video recordings or other media too: as long as it’s asynchronous, it works.

Using iteration posts has a number of benefits:

• It creates a rhythm in the design work so that the designer can review feedback from each iteration and prepare for the next.
• Decisions are always available, and conversations are also made accessible for future review.
• It creates a record of how the design changed over time.
• Depending on the tool, it might also make it simpler to collect and act on feedback.

These posts of course don’t mean that no other feedback approach should be used, just that iteration posts could be the primary rhythm for a remote design team to use. And from there, other feedback techniques ( such as live critique, pair designing, or inline comments ) can emerge.

I don’t think there’s a standard format for iteration posts. However, there are a few high-level components that make sense as a baseline:

1. The goal
2. The layout
3. The list of changes
4. The querys

Each project is likely to have a goal, and hopefully it’s something that’s already been summarized in a single sentence somewhere else, such as the client brief, the product manager’s outline, or the project owner’s request. In every iteration post, I would copy and paste this, so I could do it again. The idea is to provide context and to repeat what’s essential to make each iteration post complete so that there’s no need to find information spread across multiple posts. The most recent iteration post will have everything I need if I want to know about the most recent design.

This copy-and-paste part introduces another relevant concept: alignment comes from repetition. Therefore, repeating information in posts is actually very effective at ensuring that everyone is on the same page.

The design is then the actual series of information-architecture outlines, diagrams, flows, maps, wireframes, screens, visuals, and any other kind of design work that’s been done. It’s any design object, to put it briefly. For the final stages of work, I prefer the term blueprint to emphasize that I’ll be showing full flows instead of individual screens to make it easier to understand the bigger picture.

It might also be helpful to have clear names on the artifacts so that it is easier to refer to them. Write the post in a way that helps people understand the work. It’s not very different from creating a strong live presentation.

For an efficient discussion, you should also include a bullet list of the changes from the previous iteration to let people focus on what’s new, which can be especially useful for larger pieces of work where keeping track, iteration after iteration, could become a challenge.

Finally, as mentioned earlier, it’s crucial that you include a list of the questions to help you guide the design critique in the desired direction. Doing this as a numbered list can also help make it easier to refer to each question by its number.

Not every iteration is the same. Earlier iterations don’t need to be as tightly focused—they can be more exploratory and experimental, maybe even breaking some of the design-language guidelines to see what’s possible. Then, later, the iterations begin coming to a decision and improving it until the design process is complete and the feature is ready.

I want to highlight that even if these iteration posts are written and conceived as checkpoints, by no means do they need to be exhaustive. A post might be a draft, just a concept to start a discussion, or it might be a cumulative list of all the features that have been added over the course of each iteration until the full picture is achieved.

Over time, I also started using specific labels for incremental iterations: i1, i2, i3, and so on. Although this may seem like a minor labeling tip, it can be useful in many ways:

• Unique—It’s a clear unique marker. One can quickly say,” This was discussed in i4″ with each project, and everyone knows where to go to review things.
• Unassuming—It works like versions ( such as v1, v2, and v3 ) but in contrast, versions create the impression of something that’s big, exhaustive, and complete. Attempts must be exploratory, incomplete, or partial.
• Future proof—It resolves the “final” naming problem that you can run into with versions. No more files with the title “final final complete no-really-its-done” Within each project, the largest number always represents the latest iteration.

The wording release candidate (RC ) could be used to describe a design as complete enough to be worked on, even if there might be some bits that still need more attention and in turn, more iterations would be required, such as” with i8 we reached RC” or “i12 is an RC” to indicate when it is finished.

The review

What typically occurs during a design critique is an open discussion that can be very productive between two people. This approach is particularly effective during live, synchronous feedback. However, using a different approach when we work asynchronously is more effective: adopting a user-research mindset. Written feedback from teammates, stakeholders, or others can be treated as if it were the result of user interviews and surveys, and we can analyze it accordingly.

Asynchronous feedback is particularly effective around these friction points because of this shift’s significant benefits:

1. It removes the pressure to reply to everyone.
2. It lessens the annoyance of snoop-by comments.
3. It lessens our personal stake.

The first friction point is having to feel pressured to respond to each and every comment. Sometimes we write the iteration post, and we get replies from our team. It’s simple, straightforward, and doesn’t cause any issues. But other times, some solutions might require more in-depth discussions, and the amount of replies can quickly increase, which can create a tension between trying to be a good team player by replying to everyone and doing the next design iteration. This might be especially true if the respondent is a stakeholder or a person who is directly involved in the project and whom we feel we need to speak with. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. Responding to all comments at times can be effective, but when we consider a design critique more like user research, we realize that we don’t need to respond to every comment, and there are alternatives in asynchronous spaces:

One is to let the next iteration speak for itself. The response is received when the design changes and a follow-up iteration is made. You might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement.
• Another option is to respond politely to acknowledge each comment, such as” Understood. Thank you”,” Good points— I’ll review”, or” Thanks. These will be included in the upcoming iteration. In some cases, this could also be just a single top-level comment along the lines of” Thanks for all the feedback everyone—the next iteration is coming soon”!
• One more thing is to quickly summarize the comments before proceeding. Depending on your workflow, this can be particularly useful as it can provide a simplified checklist that you can then use for the next iteration.

The swoop-by comment, which is the kind of feedback that comes from a member of a team or non-project who might not be aware of the context, restrictions, decisions, or requirements, or of the discussions from earlier iterations, is the second friction point. On their side, there’s something that one can hope that they might learn: they could start to acknowledge that they’re doing this and they could be more conscious in outlining where they’re coming from. Swoop-by comments frequently prompt the simple thought,” We’ve already discussed this,” and it can be frustrating to have to keep saying the same thing over and over.

Let’s begin by acknowledging again that there’s no need to reply to every comment. However, if responding to a previously litigated point might be helpful, a brief response with a link to the previous discussion for additional information is typically sufficient. Remember, alignment comes from repetition, so it’s okay to repeat things sometimes!

Swoop-by commenting can still be useful for two reasons: first, they might point out something that isn’t clear, and second, they might have the power to fit in with a user’s perspective when they are seeing the design for the first time. Sure, you’ll still be frustrated, but that might at least help in dealing with it.

The personal stake we might have in relation to the design could be the third friction point, which might cause us to feel defensive if the review turned out to be more of a discussion. Treating feedback as user research helps us create a healthy distance between the people giving us feedback and our ego ( because yes, even if we don’t want to admit it, it’s there ). In the end, presenting everything in aggregated form helps us to prioritize our work more.

Always remember that while you need to listen to stakeholders, project owners, and specific advice, you don’t have to accept every piece of feedback. You must examine it and come up with a conclusion that you can support, but sometimes “no” is the best choice.

As the designer leading the project, you’re in charge of that decision. In the end, everyone has their area of expertise, and as a designer, you are the one with the most background and knowledge to make the right choice. And by listening to the feedback that you’ve received, you’re making sure that it’s also the best and most balanced decision.

Thanks to Mike Shelton and Brie Anne Demkiw for their initial review of this article.

We’ve been conversing for a long time. Whether to present information, perform transactions, or just to check in on one another, people have yammered aside, chattering and gesticulating, through spoken discussion for many generations. Only recently have we begun to write our conversations, and only recently have we outsourced them to the system, a system that exhibits a far greater affection for written communications than for the vernacular rigors of spoken speech.

Laptops have trouble because between spoken and written speech, talk is more primitive. Machines must wrestle with the complexity of human statement, including the disfluencies and pauses, the gestures and body speech, and the variations in expression choice and spoken dialect, which may impede even the most skillfully crafted human-computer interaction. In the human-to-human situation, spoken language also has the opportunity of face-to-face call, where we can easily interpret visual interpersonal cues.

In contrast, written language develops its own fossil record of dated terms and phrases as we report it and keep utilization long after they are no longer needed in spoken communication ( for example, the welcome” To whom it may concern” ). Because it tends to be more consistent, smooth, and proper, written word is necessarily far easier for machines to interpret and know.

This luxury is not available in spoken language. 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. Our spoken language conveys much more than the written word can ever contain, whether it’s rapid-fire, low-pitched, high-decibel, sarcastic, stilted, or sighing. So when it comes to voice interfaces—the machines we conduct spoken conversations with—we face exciting challenges as designers and content strategists.

Voice Compositions

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 ( ). We typically strike up a discussion in the following ways:

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

These three categories, which I refer to as transactional, informational, and prosocial, also apply to virtually every voice interaction: a single conversation that begins with the voice interface’s first greeting and ends with the user leaving 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 it is not always just one 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. Additionally, there is ongoing debate about whether users actually prefer the type of organic human conversation that starts with a prosocial voice and progresses seamlessly into new ones. 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 ( ).

A voice interface can also have two types of conversations we can have with one another that are both transactional and informational, each learning something new ( “discuss a musical” ).

Transactional voice interactions

When you order a Hawaiian pizza with extra pineapple, you’re typically having a conversation and a voice interaction when you’re tapping buttons on a food delivery app. 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 ).

How are things going, Alison?

Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?

Alison: Can I get a pizza from Hawaii with extra pineapple.

Burhan: Sure, what size?

Alison: Big.

Burhan: Anything else?

Alison: No thanks, that’s it.

Burhan: Something to drink?

I’ll have a bottle of Coke, Alison.

Burhan: You got it. It will cost about$ 15 and take fifteen minutes to complete.

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. Conversations that are transactional have certain characteristics: they are direct, precise, and cost-effective. They quickly dispense with pleasantries.

Informational voice interactions

Meanwhile, some conversations are primarily about obtaining information. Alison might visit Crust Deluxe with the sole intention of placing an order, but she might not want to leave 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. We’re after much more than just a prosocial mini-conversation at the beginning, even though we do it once more to establish politeness.

How are things going, Alison?

Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?

Alison: Can I ask a few questions?

Burhan: Of course! Go right ahead.

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

Burhan: Absolutely! On request, we can make any pie halal. We also have lots of vegetarian, ovo-lacto, and vegan options. Do you have any other dietary restrictions in mind?

Alison: What about gluten-free pizzas?

Burhan: For both our deep-dish and thin-crust pizzas, we can definitely make a gluten-free crust for you, without a problem. Anything else I can answer for you?

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

Burhan: Anytime, come back soon!

This dialogue is radically different. Here, the goal is to get a certain set of facts. Informational conversations are research expeditions to gather data, news, or facts, or they are investigative quests for the truth. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. Responses are typically longer, more in-depth, and carefully communicated to ensure that the customer understands the main ideas.

Voice Interfaces

Voice interfaces, in essence, use speech to assist users in accomplishing their objectives. But simply because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. We’re most concerned in this book with pure voice interfaces because multimodal voice interfaces can lean on visual components like screens as crutches, which are completely dependent on spoken conversation and lack any visual component, making them much more nuanced and challenging to deal with.

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.

IVR ( interactive voice response ) 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. We became familiar with the first real voice interfaces that could actually be spoken to without having to deal with overburdened customer service representatives as a result of the development of interactive voice response ( IVR ) systems.

IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. These systems, which are commonplace in the corporate world, were primarily intended as metaphorical switchboards to direct customers to real phone agents (” Say Reservations to book a flight or check an itinerary” ), and it is likely that when you call an airline or hotel conglomerate, you will have the opportunity to have a conversation with one. 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).

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

Screen readers

The invention of the screen reader, a tool that converts visual content into synthesized speech, was a development of IVR systems in parallel. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. Perhaps the closest thing we have today to an out-of-the-box implementation of content delivered through voice is represented by screen readers.

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 ( ). The first IBM Screen Reader for text-based computers was created by Jim Thatcher in the same year, which was later recreated for a computer with graphical user interfaces ( GUIs ) ( ).

With the rapid growth of the web in the 1990s, the demand for accessible tools for websites exploded. Screen readers started facilitating quick 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 with the introduction of semantic HTML and especially ARIA roles in 2008, enabling speedy interactions with the pages. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc. —into useful information,” according to Aaron Gustafson in A List Apart. ” At least they do when documents are authored thoughtfully” ( ).

There’s a big deal with screen readers: they’re difficult to use and relentlessly verbose, despite being incredibly instructive for voice interface designers. 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. Working with web-based interfaces is a cognitive burden for many screen reader users.

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

I hated the way Screen Readers operated from the beginning. Why are they designed the way they are? It makes no sense to present information visually and then only to have that information translated 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, users of the visual interface have the advantage of freely scurrying around the viewport to find information, ignoring areas that are unimportant to them. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Users with disabilities who have long had no choice but to use clumsy screen readers might find that voice interfaces, especially more contemporary voice assistants, provide a more streamlined experience.

Voice assistants

Many of us immediately associate voice assistants with the popular subset of voice interfaces found in living rooms, smart homes, and offices with the film Star Trek or with Majel Barrett’s voice as the omniscient computer. Voice assistants are akin to personal concierges that can answer questions, schedule appointments, conduct searches, and perform other common day-to-day tasks. And because of their assistive potential, they are quickly receiving more attention from accessibility advocates.

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 created their vision for a” semantic web agent” that would carry out routine tasks like” checking calendars, making appointments, and finding locations” ( hinter paywall ). It wasn’t until 2011 that Apple’s Siri finally entered the picture, making voice assistants a tangible reality for consumers.

There are a lot of variations in the programmability and customization of some voice assistants compared to others ( Fig. 1 ). As a result of the breadth of voice assistants available today ( Fig. 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. There are no other means by which developers can interact with Siri at a low level, aside from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and other things, which are still unavoidable today.

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, developers who feel constrained by the limitations of Siri and Cortana are increasingly using programmable voice assistants that are extensibable and customizable. 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. Users today have the option to choose from among the thousands of custom-built skills available in the Google Assistant and Amazon Alexa ecosystems.

As businesses like Amazon, Apple, Microsoft, and Google continue to occupy their positions, they are also selling and open-sourcing an unheard array of tools and frameworks for designers and developers, aiming to make creating voice interfaces as simple 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. In contrast, many development platforms, like Google’s Dialogflow, now support omnichannel features, allowing users to create a single conversational interface that then becomes 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. Voice content must be free-flowing and organic, contextless and concise in order to preserve what makes human conversation so compelling in the first place. Everything written content is not.

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. We’re most concerned with the content in this book being delivered auditorically, 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. One issue is that any content we already have isn’t in any way suitable for this new environment. So how do we make the content trapped on our websites more conversational? And how do we create fresh copy that works with voice-activated text?

Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many ways, massive vaults of what I call macrocontent: lengthy prose that can last for miles in a browser window while being viewed in microfilm format in 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:

An example of microcontent can be a day’s weather forecast [sic], an airplane flight’s arrival and departure times, an abstract from a lengthy publication, or a single instant message. __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

I would update Dash’s definition of microcontent to include all instances of bite-sized content that transcends 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. The best way to learn how your content can be stretched to the limits of its potential is through microcontent, which will inform both established and new delivery channels.

As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can instantly see when the next train is coming from a digital sign underground, but voice interfaces keep our attention captive for so long that we can’t quickly evade or skip, a feature that 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.

Our voice content’s legibility and discoverability in general both depend on how it manifests in terms of perceived space and time.