Category: Blog

This Person Does Not Exist is a website that generates human faces with a machine learning algorithm. It takes real portraits and recombines them into fake human faces. We recently scrolled past a LinkedIn post stating that this website could be useful “if you are developing a persona and looking for a photo.” 

We agree: the computer-generated faces could be a great match for personas—but not for the reason you might think. Ironically, the website highlights the core issue of this very common design method: the person(a) does not exist. Like the pictures, personas are artificially made. Information is taken out of natural context and recombined into an isolated snapshot that’s detached from reality. 

But strangely enough, designers use personas to inspire their design for the real world. 

Personas: A step back

Most designers have created, used, or come across personas at least once in their career. In their article “Personas – A Simple Introduction,” the Interaction Design Foundation defines personas as “fictional characters, which you create based upon your research in order to represent the different user types that might use your service, product, site, or brand.” In their most complete expression, personas typically consist of a name, profile picture, quotes, demographics, goals, needs, behavior in relation to a certain service/product, emotions, and motivations (for example, see Creative Companion’s Persona Core Poster). The purpose of personas, as stated by design agency Designit, is “to make the research relatable, [and] easy to communicate, digest, reference, and apply to product and service development.”

The decontextualization of personas

Personas are popular because they make “dry” research data more relatable, more human. However, this method constrains the researcher’s data analysis in such a way that the investigated users are removed from their unique contexts. As a result, personas don’t portray key factors that make you understand their decision-making process or allow you to relate to users’ thoughts and behavior; they lack stories. You understand what the persona did, but you don’t have the background to understand why. You end up with representations of users that are actually less human.

This “decontextualization” we see in personas happens in four ways, which we’ll explain below. 

Personas assume people are static 

Although many companies still try to box in their employees and customers with outdated personality tests (referring to you, Myers-Briggs), here’s a painfully obvious truth: people are not a fixed set of features. You act, think, and feel differently according to the situations you experience. You appear different to different people; you might act friendly to some, rough to others. And you change your mind all the time about decisions you’ve taken. 

Modern psychologists agree that while people generally behave according to certain patterns, it’s actually a combination of background and environment that determines how people act and take decisions. The context—the environment, the influence of other people, your mood, the entire history that led up to a situation—determines the kind of person you are in each specific moment. 

In their attempt to simplify reality, personas do not take this variability into account; they present a user as a fixed set of features. Like personality tests, personas snatch people away from real life. Even worse, people are reduced to a label and categorized as “that kind of person” with no means to exercise their innate flexibility. This practice reinforces stereotypes, lowers diversity, and doesn’t reflect reality. 

Personas focus on individuals, not the environment

In the real world, you’re designing for a context, not for an individual. Each person lives in a family, a community, an ecosystem, where there are environmental, political, and social factors you need to consider. A design is never meant for a single user. Rather, you design for one or more particular contexts in which many people might use that product. Personas, however, show the user alone rather than describe how the user relates to the environment. 

Would you always make the same decision over and over again? Maybe you’re a committed vegan but still decide to buy some meat when your relatives are coming over. As they depend on different situations and variables, your decisions—and behavior, opinions, and statements—are not absolute but highly contextual. The persona that “represents” you wouldn’t take into account this dependency, because it doesn’t specify the premises of your decisions. It doesn’t provide a justification of why you act the way you do. Personas enact the well-known bias called fundamental attribution error: explaining others’ behavior too much by their personality and too little by the situation.

As mentioned by the Interaction Design Foundation, personas are usually placed in a scenario that’s a “specific context with a problem they want to or have to solve”—does that mean context actually is considered? Unfortunately, what often happens is that you take a fictional character and based on that fiction determine how this character might deal with a certain situation. This is made worse by the fact that you haven’t even fully investigated and understood the current context of the people your persona seeks to represent; so how could you possibly understand how they would act in new situations? 

Personas are meaningless averages

As mentioned in Shlomo Goltz’s introductory article on Smashing Magazine, “a persona is depicted as a specific person but is not a real individual; rather, it is synthesized from observations of many people.” A well-known critique to this aspect of personas is that the average person does not exist, as per the famous example of the USA Air Force designing planes based on the average of 140 of their pilots’ physical dimensions and not a single pilot actually fitting within that average seat. 

The same limitation applies to mental aspects of people. Have you ever heard a famous person say, “They took what I said out of context! They used my words, but I didn’t mean it like that.” The celebrity’s statement was reported literally, but the reporter failed to explain the context around the statement and didn’t describe the non-verbal expressions. As a result, the intended meaning was lost. You do the same when you create personas: you collect somebody’s statement (or goal, or need, or emotion), of which the meaning can only be understood if you provide its own specific context, yet report it as an isolated finding. 

But personas go a step further, extracting a decontextualized finding and joining it with another decontextualized finding from somebody else. The resulting set of findings often does not make sense: it’s unclear, or even contrasting, because it lacks the underlying reasons on why and how that finding has arisen. It lacks meaning. And the persona doesn’t give you the full background of the person(s) to uncover this meaning: you would need to dive into the raw data for each single persona item to find it. What, then, is the usefulness of the persona?

The relatability of personas is deceiving

To a certain extent, designers realize that a persona is a lifeless average. To overcome this, designers invent and add “relatable” details to personas to make them resemble real individuals. Nothing captures the absurdity of this better than a sentence by the Interaction Design Foundation: “Add a few fictional personal details to make the persona a realistic character.” In other words, you add non-realism in an attempt to create more realism. You deliberately obscure the fact that “John Doe” is an abstract representation of research findings; but wouldn’t it be much more responsible to emphasize that John is only an abstraction? If something is artificial, let’s present it as such.

It’s the finishing touch of a persona’s decontextualization: after having assumed that people’s personalities are fixed, dismissed the importance of their environment, and hidden meaning by joining isolated, non-generalizable findings, designers invent new context to create (their own) meaning. In doing so, as with everything they create, they introduce a host of biases. As phrased by Designit, as designers we can “contextualize [the persona] based on our reality and experience. We create connections that are familiar to us.” This practice reinforces stereotypes, doesn’t reflect real-world diversity, and gets further away from people’s actual reality with every detail added. 

To do good design research, we should report the reality “as-is” and make it relatable for our audience, so everyone can use their own empathy and develop their own interpretation and emotional response.

Dynamic Selves: The alternative to personas

If we shouldn’t use personas, what should we do instead? 

Designit has proposed using Mindsets instead of personas. Each Mindset is a “spectrum of attitudes and emotional responses that different people have within the same context or life experience.” It challenges designers to not get fixated on a single user’s way of being. Unfortunately, while being a step in the right direction, this proposal doesn’t take into account that people are part of an environment that determines their personality, their behavior, and, yes, their mindset. Therefore, Mindsets are also not absolute but change in regard to the situation. The question remains, what determines a certain Mindset?

Another alternative comes from Margaret P., author of the article “Kill Your Personas,” who has argued for replacing personas with persona spectrums that consist of a range of user abilities. For example, a visual impairment could be permanent (blindness), temporary (recovery from eye surgery), or situational (screen glare). Persona spectrums are highly useful for more inclusive and context-based design, as they’re based on the understanding that the context is the pattern, not the personality. Their limitation, however, is that they have a very functional take on users that misses the relatability of a real person taken from within a spectrum. 

In developing an alternative to personas, we aim to transform the standard design process to be context-based. Contexts are generalizable and have patterns that we can identify, just like we tried to do previously with people. So how do we identify these patterns? How do we ensure truly context-based design? 

Understand real individuals in multiple contexts

Nothing is more relatable and inspiring than reality. Therefore, we have to understand real individuals in their multi-faceted contexts, and use this understanding to fuel our design. We refer to this approach as Dynamic Selves.

Let’s take a look at what the approach looks like, based on an example of how one of us applied it in a recent project that researched habits of Italians around energy consumption. We drafted a design research plan aimed at investigating people’s attitudes toward energy consumption and sustainable behavior, with a focus on smart thermostats. 

1. Choose the right sample

When we argue against personas, we’re often challenged with quotes such as “Where are you going to find a single person that encapsulates all the information from one of these advanced personas[?]” The answer is simple: you don’t have to. You don’t need to have information about many people for your insights to be deep and meaningful. 

In qualitative research, validity does not derive from quantity but from accurate sampling. You select the people that best represent the “population” you’re designing for. If this sample is chosen well, and you have understood the sampled people in sufficient depth, you’re able to infer how the rest of the population thinks and behaves. There’s no need to study seven Susans and five Yuriys; one of each will do. 

Similarly, you don’t need to understand Susan in fifteen different contexts. Once you’ve seen her in a couple of diverse situations, you’ve understood the scheme of Susan’s response to different contexts. Not Susan as an atomic being but Susan in relation to the surrounding environment: how she might act, feel, and think in different situations. 

Given that each person is representative of a part of the total population you’re researching, it becomes clear why each should be represented as an individual, as each already is an abstraction of a larger group of individuals in similar contexts. You don’t want abstractions of abstractions! These selected people need to be understood and shown in their full expression, remaining in their microcosmos—and if you want to identify patterns you can focus on identifying patterns in contexts.

Yet the question remains: how do you select a representative sample? First of all, you have to consider what’s the target audience of the product or service you are designing: it might be useful to look at the company’s goals and strategy, the current customer base, and/or a possible future target audience. 

In our example project, we were designing an application for those who own a smart thermostat. In the future, everyone could have a smart thermostat in their house. Right now, though, only early adopters own one. To build a significant sample, we needed to understand the reason why these early adopters became such. We therefore recruited by asking people why they had a smart thermostat and how they got it. There were those who had chosen to buy it, those who had been influenced by others to buy it, and those who had found it in their house. So we selected representatives of these three situations, from different age groups and geographical locations, with an equal balance of tech savvy and non-tech savvy participants. 

2. Conduct your research

After having chosen and recruited your sample, conduct your research using ethnographic methodologies. This will make your qualitative data rich with anecdotes and examples. In our example project, given COVID-19 restrictions, we converted an in-house ethnographic research effort into remote family interviews, conducted from home and accompanied by diary studies.

To gain an in-depth understanding of attitudes and decision-making trade-offs, the research focus was not limited to the interviewee alone but deliberately included the whole family. Each interviewee would tell a story that would then become much more lively and precise with the corrections or additional details coming from wives, husbands, children, or sometimes even pets. We also focused on the relationships with other meaningful people (such as colleagues or distant family) and all the behaviors that resulted from those relationships. This wide research focus allowed us to shape a vivid mental image of dynamic situations with multiple actors. 

It’s essential that the scope of the research remains broad enough to be able to include all possible actors. Therefore, it normally works best to define broad research areas with macro questions. Interviews are best set up in a semi-structured way, where follow-up questions will dive into topics mentioned spontaneously by the interviewee. This open-minded “plan to be surprised” will yield the most insightful findings. When we asked one of our participants how his family regulated the house temperature, he replied, “My wife has not installed the thermostat’s app—she uses WhatsApp instead. If she wants to turn on the heater and she is not home, she will text me. I am her thermostat.”

3. Analysis: Create the Dynamic Selves

During the research analysis, you start representing each individual with multiple Dynamic Selves, each “Self” representing one of the contexts you have investigated. The core of each Dynamic Self is a quote, which comes supported by a photo and a few relevant demographics that illustrate the wider context. The research findings themselves will show which demographics are relevant to show. In our case, as our research focused on families and their lifestyle to understand their needs for thermal regulation, the important demographics were family type, number and nature of houses owned, economic status, and technological maturity. (We also included the individual’s name and age, but they’re optional—we included them to ease the stakeholders’ transition from personas and be able to connect multiple actions and contexts to the same person).

To capture exact quotes, interviews need to be video-recorded and notes need to be taken verbatim as much as possible. This is essential to the truthfulness of the several Selves of each participant. In the case of real-life ethnographic research, photos of the context and anonymized actors are essential to build realistic Selves. Ideally, these photos should come directly from field research, but an evocative and representative image will work, too, as long as it’s realistic and depicts meaningful actions that you associate with your participants. For example, one of our interviewees told us about his mountain home where he used to spend every weekend with his family. Therefore, we portrayed him hiking with his little daughter. 

At the end of the research analysis, we displayed all of the Selves’ “cards” on a single canvas, categorized by activities. Each card displayed a situation, represented by a quote and a unique photo. All participants had multiple cards about themselves.

4. Identify design opportunities

Once you have collected all main quotes from the interview transcripts and diaries, and laid them all down as Self cards, you will see patterns emerge. These patterns will highlight the opportunity areas for new product creation, new functionalities, and new services—for new design. 

In our example project, there was a particularly interesting insight around the concept of humidity. We realized that people don’t know what humidity is and why it is important to monitor it for health: an environment that’s too dry or too wet can cause respiratory problems or worsen existing ones. This highlighted a big opportunity for our client to educate users on this concept and become a health advisor.

Benefits of Dynamic Selves

When you use the Dynamic Selves approach in your research, you start to notice unique social relations, peculiar situations real people face and the actions that follow, and that people are surrounded by changing environments. In our thermostat project, we have come to know one of the participants, Davide, as a boyfriend, dog-lover, and tech enthusiast. 

Davide is an individual we might have once reduced to a persona called “tech enthusiast.” But we can have tech enthusiasts who have families or are single, who are rich or poor. Their motivations and priorities when deciding to purchase a new thermostat can be opposite according to these different frames. 

Once you have understood Davide in multiple situations, and for each situation have understood in sufficient depth the underlying reasons for his behavior, you’re able to generalize how he would act in another situation. You can use your understanding of him to infer what he would think and do in the contexts (or scenarios) that you design for.

The Dynamic Selves approach aims to dismiss the conflicted dual purpose of personas—to summarize and empathize at the same time—by separating your research summary from the people you’re seeking to empathize with. This is important because our empathy for people is affected by scale: the bigger the group, the harder it is to feel empathy for others. We feel the strongest empathy for individuals we can personally relate to.  

If you take a real person as inspiration for your design, you no longer need to create an artificial character. No more inventing details to make the character more “realistic,” no more unnecessary additional bias. It’s simply how this person is in real life. In fact, in our experience, personas quickly become nothing more than a name in our priority guides and prototype screens, as we all know that these characters don’t really exist. 

Another powerful benefit of the Dynamic Selves approach is that it raises the stakes of your work: if you mess up your design, someone real, a person you and the team know and have met, is going to feel the consequences. It might stop you from taking shortcuts and will remind you to conduct daily checks on your designs.

And finally, real people in their specific contexts are a better basis for anecdotal storytelling and therefore are more effective in persuasion. Documentation of real research is essential in achieving this result. It adds weight and urgency behind your design arguments: “When I met Alessandra, the conditions of her workplace struck me. Noise, bad ergonomics, lack of light, you name it. If we go for this functionality, I’m afraid we’re going to add complexity to her life.”

Conclusion

Designit mentioned in their article on Mindsets that “design thinking tools offer a shortcut to deal with reality’s complexities, but this process of simplification can sometimes flatten out people’s lives into a few general characteristics.” Unfortunately, personas have been culprits in a crime of oversimplification. They are unsuited to represent the complex nature of our users’ decision-making processes and don’t account for the fact that humans are immersed in contexts. 

Design needs simplification but not generalization. You have to look at the research elements that stand out: the sentences that captured your attention, the images that struck you, the sounds that linger. Portray those, use them to describe the person in their multiple contexts. Both insights and people come with a context; they cannot be cut from that context because it would remove meaning. 

It’s high time for design to move away from fiction, and embrace reality—in its messy, surprising, and unquantifiable beauty—as our guide and inspiration.

” Any opinion” you might have? is perhaps one of the worst ways to ask for suggestions. It’s obscure and unfocused, and it doesn’t give us a sense of what we’re looking for. Great comments begins sooner than we might anticipate: it begins with the demand.

It might seem contradictory to start the process of receiving feedback with a problem, but that makes sense if we realize that getting feedback can be thought of as a form of design study. The best way to ask for feedback is to write down some insightful questions, just like we wouldn’t do any research without the correct questions to obtain the insight we need.

Design criticism is never 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.

Lastly, we need to review what we received, get to the heart of its conclusions, and take action, like with any great exploration. Problem, generation, and evaluation. Let’s take a closer 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 finally, we become irritated because ambiguous queries like those can result in people leaving reviews that don’t even consider buttons. Which might be a savory matter, so it might be hard at that point to divert the crew to the topics that you had wanted to focus on.

But how do we enter this circumstance? 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 there are frequently no need to be that specific in nonprofessional conversations. In short, we tend to underestimate the importance of the concerns, so we don’t work on improving them.

The practice of asking good issues guidelines and concentrates 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 suggestions. Sensitivity can take countless forms, and it just needs to be that. A design for design critique that I’ve found especially helpful in my training is the one of stage over depth.

The term” level” refers to each stage of the process, specifically the design phase. The type of input changes as the customer research moves on 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 job has evolved. The levels of consumer experience could serve as a starting point for possible questions. What are your job goals, exactly? User requirements? Funnality? the glad Contact design? a system of information structures Interface pattern Navigation style? Visual layout packaging?

Here’re a some example questions that are specific and to the place that refer to different levels:

• Features: Is it desired to automate accounts creation?
• Contact design: Please review the updated flow for any errors or steps I might have missed.
• Information infrastructure: We have two competing bits of information on this site. Does the construction work to effectively communicate both of them?
• User interface design: What do you think about the top-most error counter, which ensures that you can see the future error even when the error is outside the viewport?
• Navigation style: From study, we identified these second-level routing items, but when you’re on the webpage, the list feels overly long and hard to understand. Exist any recommendations for resolving this?
• Are the thick alerts in the bottom-right corner of the page obvious enough?

The other plane of sensitivity is about how heavy you’d like to go on what’s being presented. For instance, we may have introduced a new end-to-end movement, but you might want to know more about a particular viewpoint you found challenging. This can be particularly helpful from one generation to the next when it’s crucial to identify the areas that have changed.

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

A quick fix is to get rid of the common qualifiers from issues like “good”, “well,” “nice,” “bad,” “okay,” and” cool.” For instance, what is the question” When the wall opens and the switches appear, is this connection good”? may seem precise, but you can place the “good” tournament, and transfer it to an even better query:” When the wall opens and the buttons appear, is it clear what the next action is”?

Often, we do need a lot of comments. Although that is uncommon, it is possible. In that feel, you may also make it obvious that you’re looking for a wide range of ideas, whether at a high level or with information. Or perhaps just say,” At first glance, what do you think”? so that it is obvious that what you’re asking is open ended but focused on a person’s impression after their first five seconds of inquiry.

Sometimes the project is particularly expansive, and some areas may have already been explored in detail. In these circumstances, it might be helpful to state explicitly that some parts are already locked in and aren’t accessible for 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. Even experienced designers will appreciate the clarity and efficiency gained from concentrating solely on what is required, and those with less refined critique skills will now be able to offer more actionable feedback. It can save a lot of time and frustration.

The iteration

Design iterations are probably the most recognizable component of the design process, and they act as a natural checkpoint for feedback. Many design tools have inline commenting, but many of them only display changes as a single fluid stream in the same file. These types of design tools cause conversations to end after they are resolved, update shared UI components automatically, and require designers to always display the most recent version unless these would-be useful features were manually disabled. 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’s probably not the most effective way to go about designing critiques, but even if I don’t want to be too prescriptive, it might work for some teams.

Create explicit checkpoints for discussion is the asynchronous design-critique strategy that I believe works the best. I’m going to use the term iteration post for this. It refers to a write-up or presentation of the design iteration that is 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.

There are many benefits to using iteration posts:

It establishes a rhythm in the design process, allowing the designer to review the feedback from each iteration and get ready for the following.
• It makes decisions visible for future review, and conversations are likewise always available.
• It keeps a record of how the design evolved 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. From there, there can be additional feedback techniques ( such as live critique, pair designing, or inline comments ).

There isn’t, in my opinion, a common format for iteration posts. But there are a few high-level elements that make sense to include as a baseline:

1. The objective is.
2. The layout
3. The list of changes
4. The querys

Each project is likely to have a goal, and it should most likely be one that has already been summarized in one sentence elsewhere, such as the client brief, the product manager’s outline, or the request of the project owner. So this is something that I’d repeat in every iteration post—literally copy and pasting it. The goal is to provide context and repeat what is necessary to complete each iteration post so that there is no need to search for information in different 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 actual series of information-architecture outlines, diagrams, flows, maps, wireframes, screens, visuals, and any other kind of design work that has been done is then the design. In short, it’s any design artifact. In the final stages of the project, I prefer to use the term “blank” to indicate that I’ll be displaying complete flows rather than individual screens to make it simpler to comprehend the larger 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 much different from creating a strong live presentation.

For a successful discussion, you should also include a bullet list of the changes made in the previous iteration to help people concentrate on what’s changed. This can be especially useful for larger pieces of work where keeping track, iteration after iteration, may prove difficult.

And finally, as noted earlier, it’s essential that you include a list of the questions to drive the design critique in the direction you want. Making a numbered list of questions available in the form of a number can also make it simpler to refer to each one by its name.

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 feature development is complete.

Even if these iteration posts are written and intended as checkpoints, I want to point out that they are not by any means required to be exhaustive. A post might be a draft—just a concept to get a conversation going—or it could be a cumulative list of each feature that was added over the course of each iteration until the full picture is done.

I also started using particular labels for incremental iterations over time, such as 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 functions like versions ( such as v1, v2, and v3 ), but versions give the impression of something that is large, exhaustive, and complete. Iterations must be able to be exploratory, incomplete, partial.
• Future proof—It resolves the “final” naming issue that versions can encounter. 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 indicate when a design is finished enough to be worked on, even if there are some areas that still need improvement and, in turn, require more iterations, such as” with i8 we reached RC” or “i12 is an RC” to indicate when it is finished.

The evaluation

What usually happens during a design critique is an open discussion, with a back and forth between people that can be very productive. This strategy is particularly successful when synchronous feedback is being received live. 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 because of this shift, especially around these friction points:

It makes it easier to respond to everyone.
1. It reduces the frustration from swoop-by comments.
2. It lessens our own worth.

The first friction point is having to press yourself 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. Sometimes, however, some solutions may require more in-depth discussions, and responding to everyone quickly can add up to the pressure of trying to be a good team player by doing the same design iteration. This might be especially true if the person who’s replying is a stakeholder or someone directly involved in the project who we feel that we need to listen to. We must come to terms with the fact that this pressure is perfectly normal and that it is human nature to try to accommodate those we care about. When we treat 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, responding to all comments can be effective.

One is to let the next iteration speak for itself. That is the response when the design changes and we publish a follow-up iteration. You could tag everyone in the previous discussion, but that’s just a choice, not a requirement.
• Another is to briefly reply to acknowledge each comment, such as” Understood. Thank you,”” Good points— I’ll review,” or” Thanks. In the upcoming iteration, I’ll include these. 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”!
• Another option is to provide a quick summary of the comments before moving on. This may be particularly helpful if your workflow allows you to create a simplified checklist that you can use for the following iteration.

The second friction point is the swoop-by comment, which is the kind of feedback that comes from someone outside the project or team who might not be aware of the context, restrictions, decisions, or requirements —or of the previous iterations ‘ discussions. One can hope that they will learn something from them, starting with acknowledging that they are doing this and making their location more explicit. Swoop-by comments frequently prompt the simple thought,” We’ve already discussed this,” and it can be frustrating to have to keep coming back and forth.

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

Swoop-by commenting can still be useful for two reasons: they might point out something that still isn’t clear, and they also have the potential to stand in for the point of view of a user who’s seeing the design for the first time. Yes, you’ll still be frustrated, but that might at least make things better for you.

The personal stake we might have in the design could be the third friction point, which might cause us to feel defensive if the review turned into 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, putting everything in aggregate form helps us to prioritize our work more.

You don’t have to accept every piece of feedback, but you do need to listen to stakeholders, project owners, and specific advice. You have to analyze it and make a decision that you can justify, but sometimes “no” is the right answer.

You are in charge of making that choice as the project designer. In the end, everyone has their area of specialization, and the designer is 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.

Feedback, in whichever form it takes, and whatever it may be called, is one of the most effective soft skills that we have at our disposal to collaboratively get our designs to a better place while growing our own skills and perspectives.

Feedback is also one of the most underestimated tools, and often by assuming that we’re already good at it, we settle, forgetting that it’s a skill that can be trained, grown, and improved. Poor feedback can create confusion in projects, bring down morale, and affect trust and team collaboration over the long term. Quality feedback can be a transformative force. 

Practicing our skills is surely a good way to improve, but the learning gets even faster when it’s paired with a good foundation that channels and focuses the practice. What are some foundational aspects of giving good feedback? And how can feedback be adjusted for remote and distributed work environments? 

On the web, we can identify a long tradition of asynchronous feedback: from the early days of open source, code was shared and discussed on mailing lists. Today, developers engage on pull requests, designers comment in their favorite design tools, project managers and scrum masters exchange ideas on tickets, and so on.

Design critique is often the name used for a type of feedback that’s provided to make our work better, collaboratively. So it shares a lot of the principles with feedback in general, but it also has some differences.

The content

The foundation of every good critique is the feedback’s content, so that’s where we need to start. There are many models that you can use to shape your content. The one that I personally like best—because it’s clear and actionable—is this one from Lara Hogan.

While this equation is generally used to give feedback to people, it also fits really well in a design critique because it ultimately answers some of the core questions that we work on: What? Where? Why? How? Imagine that you’re giving some feedback about some design work that spans multiple screens, like an onboarding flow: there are some pages shown, a flow blueprint, and an outline of the decisions made. You spot something that could be improved. If you keep the three elements of the equation in mind, you’ll have a mental model that can help you be more precise and effective.

Here is a comment that could be given as a part of some feedback, and it might look reasonable at a first glance: it seems to superficially fulfill the elements in the equation. But does it?

Not sure about the buttons’ styles and hierarchy—it feels off. Can you change them?

Observation for design feedback doesn’t just mean pointing out which part of the interface your feedback refers to, but it also refers to offering a perspective that’s as specific as possible. Are you providing the user’s perspective? Your expert perspective? A business perspective? The project manager’s perspective? A first-time user’s perspective?

When I see these two buttons, I expect one to go forward and one to go back.

Impact is about the why. Just pointing out a UI element might sometimes be enough if the issue may be obvious, but more often than not, you should add an explanation of what you’re pointing out.

When I see these two buttons, I expect one to go forward and one to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow.

The question approach is meant to provide open guidance by eliciting the critical thinking in the designer receiving the feedback. Notably, in Lara’s equation she provides a second approach: request, which instead provides guidance toward a specific solution. While that’s a viable option for feedback in general, for design critiques, in my experience, defaulting to the question approach usually reaches the best solutions because designers are generally more comfortable in being given an open space to explore.

The difference between the two can be exemplified with, for the question approach:

When I see these two buttons, I expect one to go forward and one to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Would it make sense to unify them?

Or, for the request approach:

When I see these two buttons, I expect one to go forward and one to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same pair of forward and back buttons.

At this point in some situations, it might be useful to integrate with an extra why: why you consider the given suggestion to be better.

When I see these two buttons, I expect one to go forward and one to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.

Choosing the question approach or the request approach can also at times be a matter of personal preference. A while ago, I was putting a lot of effort into improving my feedback: I did rounds of anonymous feedback, and I reviewed feedback with other people. After a few rounds of this work and a year later, I got a positive response: my feedback came across as effective and grounded. Until I changed teams. To my shock, my next round of feedback from one specific person wasn’t that great. The reason is that I had previously tried not to be prescriptive in my advice—because the people who I was previously working with preferred the open-ended question format over the request style of suggestions. But now in this other team, there was one person who instead preferred specific guidance. So I adapted my feedback for them to include requests.

One comment that I heard come up a few times is that this kind of feedback is quite long, and it doesn’t seem very efficient. No… but also yes. Let’s explore both sides.

No, this style of feedback is actually efficient because the length here is a byproduct of clarity, and spending time giving this kind of feedback can provide exactly enough information for a good fix. Also if we zoom out, it can reduce future back-and-forth conversations and misunderstandings, improving the overall efficiency and effectiveness of collaboration beyond the single comment. Imagine that in the example above the feedback were instead just, “Let’s make sure that all screens have the same two forward and back buttons.” The designer receiving this feedback wouldn’t have much to go by, so they might just apply the change. In later iterations, the interface might change or they might introduce new features—and maybe that change might not make sense anymore. Without the why, the designer might imagine that the change is about consistency… but what if it wasn’t? So there could now be an underlying concern that changing the buttons would be perceived as a regression.

Yes, this style of feedback is not always efficient because the points in some comments don’t always need to be exhaustive, sometimes because certain changes may be obvious (“The font used doesn’t follow our guidelines”) and sometimes because the team may have a lot of internal knowledge such that some of the whys may be implied.

So the equation above isn’t meant to suggest a strict template for feedback but a mnemonic to reflect and improve the practice. Even after years of active work on my critiques, I still from time to time go back to this formula and reflect on whether what I just wrote is effective.

The tone

Well-grounded content is the foundation of feedback, but that’s not really enough. The soft skills of the person who’s providing the critique can multiply the likelihood that the feedback will be well received and understood. Tone alone can make the difference between content that’s rejected or welcomed, and it’s been demonstrated that only positive feedback creates sustained change in people.

Since our goal is to be understood and to have a positive working environment, tone is essential to work on. Over the years, I’ve tried to summarize the required soft skills in a formula that mirrors the one for content: the receptivity equation.

Respectful feedback comes across as grounded, solid, and constructive. It’s the kind of feedback that, whether it’s positive or negative, is perceived as useful and fair.

Timing refers to when the feedback happens. To-the-point feedback doesn’t have much hope of being well received if it’s given at the wrong time. Questioning the entire high-level information architecture of a new feature when it’s about to ship might still be relevant if that questioning highlights a major blocker that nobody saw, but it’s way more likely that those concerns will have to wait for a later rework. So in general, attune your feedback to the stage of the project. Early iteration? Late iteration? Polishing work in progress? These all have different needs. The right timing will make it more likely that your feedback will be well received.

Attitude is the equivalent of intent, and in the context of person-to-person feedback, it can be referred to as radical candor. That means checking before we write to see whether what we have in mind will truly help the person and make the project better overall. This might be a hard reflection at times because maybe we don’t want to admit that we don’t really appreciate that person. Hopefully that’s not the case, but that can happen, and that’s okay. Acknowledging and owning that can help you make up for that: how would I write if I really cared about them? How can I avoid being passive aggressive? How can I be more constructive?

Form is relevant especially in a diverse and cross-cultural work environments because having great content, perfect timing, and the right attitude might not come across if the way that we write creates misunderstandings. There might be many reasons for this: sometimes certain words might trigger specific reactions; sometimes nonnative speakers might not understand all the nuances of some sentences; sometimes our brains might just be different and we might perceive the world differently—neurodiversity must be taken into consideration. Whatever the reason, it’s important to review not just what we write but how.

A few years back, I was asking for some feedback on how I give feedback. I received some good advice but also a comment that surprised me. They pointed out that when I wrote “Oh, […],” I made them feel stupid. That wasn’t my intent! I felt really bad, and I just realized that I provided feedback to them for months, and every time I might have made them feel stupid. I was horrified… but also thankful. I made a quick fix: I added “oh” in my list of replaced words (your choice between: macOS’s text replacement, aText, TextExpander, or others) so that when I typed “oh,” it was instantly deleted. 

Something to highlight because it’s quite frequent—especially in teams that have a strong group spirit—is that people tend to beat around the bush. It’s important to remember here that a positive attitude doesn’t mean going light on the feedback—it just means that even when you provide hard, difficult, or challenging feedback, you do so in a way that’s respectful and constructive. The nicest thing that you can do for someone is to help them grow.

We have a great advantage in giving feedback in written form: it can be reviewed by another person who isn’t directly involved, which can help to reduce or remove any bias that might be there. I found that the best, most insightful moments for me have happened when I’ve shared a comment and I’ve asked someone who I highly trusted, “How does this sound?,” “How can I do it better,” and even “How would you have written it?”—and I’ve learned a lot by seeing the two versions side by side.

The format

Asynchronous feedback also has a major inherent advantage: we can take more time to refine what we’ve written to make sure that it fulfills two main goals: the clarity of communication and the actionability of the suggestions.

Let’s imagine that someone shared a design iteration for a project. You are reviewing it and leaving a comment. There are many ways to do this, and of course context matters, but let’s try to think about some elements that may be useful to consider.

In terms of clarity, start by grounding the critique that you’re about to give by providing context. Specifically, this means describing where you’re coming from: do you have a deep knowledge of the project, or is this the first time that you’re seeing it? Are you coming from a high-level perspective, or are you figuring out the details? Are there regressions? Which user’s perspective are you taking when providing your feedback? Is the design iteration at a point where it would be okay to ship this, or are there major things that need to be addressed first?

Providing context is helpful even if you’re sharing feedback within a team that already has some information on the project. And context is absolutely essential when giving cross-team feedback. If I were to review a design that might be indirectly related to my work, and if I had no knowledge about how the project arrived at that point, I would say so, highlighting my take as external.

We often focus on the negatives, trying to outline all the things that could be done better. That’s of course important, but it’s just as important—if not more—to focus on the positives, especially if you saw progress from the previous iteration. This might seem superfluous, but it’s important to keep in mind that design is a discipline where there are hundreds of possible solutions for every problem. So pointing out that the design solution that was chosen is good and explaining why it’s good has two major benefits: it confirms that the approach taken was solid, and it helps to ground your negative feedback. In the longer term, sharing positive feedback can help prevent regressions on things that are going well because those things will have been highlighted as important. As a bonus, positive feedback can also help reduce impostor syndrome.

There’s one powerful approach that combines both context and a focus on the positives: frame how the design is better than the status quo (compared to a previous iteration, competitors, or benchmarks) and why, and then on that foundation, you can add what could be improved. This is powerful because there’s a big difference between a critique that’s for a design that’s already in good shape and a critique that’s for a design that isn’t quite there yet.

Another way that you can improve your feedback is to depersonalize the feedback: the comments should always be about the work, never about the person who made it. It’s “This button isn’t well aligned” versus “You haven’t aligned this button well.” This is very easy to change in your writing by reviewing it just before sending.

In terms of actionability, one of the best approaches to help the designer who’s reading through your feedback is to split it into bullet points or paragraphs, which are easier to review and analyze one by one. For longer pieces of feedback, you might also consider splitting it into sections or even across multiple comments. Of course, adding screenshots or signifying markers of the specific part of the interface you’re referring to can also be especially useful.

One approach that I’ve personally used effectively in some contexts is to enhance the bullet points with four markers using emojis. So a red square 🟥 means that it’s something that I consider blocking; a yellow diamond 🔶 is something that I can be convinced otherwise, but it seems to me that it should be changed; and a green circle 🟢 is a detailed, positive confirmation. I also use a blue spiral 🌀 for either something that I’m not sure about, an exploration, an open alternative, or just a note. But I’d use this approach only on teams where I’ve already established a good level of trust because if it happens that I have to deliver a lot of red squares, the impact could be quite demoralizing, and I’d reframe how I’d communicate that a bit.

Let’s see how this would work by reusing the example that we used earlier as the first bullet point in this list:

• 🔶 Navigation—When I see these two buttons, I expect one to go forward and one to go back. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.
• 🟢 Overall—I think the page is solid, and this is good enough to be our release candidate for a version 1.0.
• 🟢 Metrics—Good improvement in the buttons on the metrics area; the improved contrast and new focus style make them more accessible.
•  🟥  Button Style—Using the green accent in this context creates the impression that it’s a positive action because green is usually perceived as a confirmation color. Do we need to explore a different color?
• 🔶Tiles—Given the number of items on the page, and the overall page hierarchy, it seems to me that the tiles shouldn’t be using the Subtitle 1 style but the Subtitle 2 style. This will keep the visual hierarchy more consistent.
• 🌀 Background—Using a light texture works well, but I wonder whether it adds too much noise in this kind of page. What is the thinking in using that?

What about giving feedback directly in Figma or another design tool that allows in-place feedback? In general, I find these difficult to use because they hide discussions and they’re harder to track, but in the right context, they can be very effective. Just make sure that each of the comments is separate so that it’s easier to match each discussion to a single task, similar to the idea of splitting mentioned above.

One final note: say the obvious. Sometimes we might feel that something is obviously good or obviously wrong, and so we don’t say it. Or sometimes we might have a doubt that we don’t express because the question might sound stupid. Say it—that’s okay. You might have to reword it a little bit to make the reader feel more comfortable, but don’t hold it back. Good feedback is transparent, even when it may be obvious.

There’s another advantage of asynchronous feedback: written feedback automatically tracks decisions. Especially in large projects, “Why did we do this?” could be a question that pops up from time to time, and there’s nothing better than open, transparent discussions that can be reviewed at any time. For this reason, I recommend using software that saves these discussions, without hiding them once they are resolved. 

Content, tone, and format. Each one of these subjects provides a useful model, but working to improve eight areas—observation, impact, question, timing, attitude, form, clarity, and actionability—is a lot of work to put in all at once. One effective approach is to take them one by one: first identify the area that you lack the most (either from your perspective or from feedback from others) and start there. Then the second, then the third, and so on. At first you’ll have to put in extra time for every piece of feedback that you give, but after a while, it’ll become second nature, and your impact on the work will multiply.

Thanks to Brie Anne Demkiw and Mike Shelton for reviewing the first draft of this article.

Are you like me, reading about people fading away as they burn out, and feeling unable to relate? Do you feel like your feelings are invisible to the world because you’re experiencing burnout differently? When burnout starts to push down on us, our core comes through more. Beautiful, peaceful souls get quieter and fade into that distant and distracted burnout we’ve all read about. But some of us, those with fires always burning on the edges of our core, get hotter. In my heart I am fire. When I face burnout I double down, triple down, burning hotter and hotter to try to best the challenge. I don’t fade—I am engulfed in a zealous burnout. 

So what on earth is a zealous burnout?

Imagine a woman determined to do it all. She has two amazing children whom she, along with her husband who is also working remotely, is homeschooling during a pandemic. She has a demanding client load at work—all of whom she loves. She gets up early to get some movement in (or often catch up on work), does dinner prep as the kids are eating breakfast, and gets to work while positioning herself near “fourth grade” to listen in as she juggles clients, tasks, and budgets. Sound like a lot? Even with a supportive team both at home and at work, it is. 

Sounds like this woman has too much on her plate and needs self-care. But no, she doesn’t have time for that. In fact, she starts to feel like she’s dropping balls. Not accomplishing enough. There’s not enough of her to be here and there; she is trying to divide her mind in two all the time, all day, every day. She starts to doubt herself. And as those feelings creep in more and more, her internal narrative becomes more and more critical.

Suddenly she KNOWS what she needs to do! She should DO MORE. 

This is a hard and dangerous cycle. Know why? Because once she doesn’t finish that new goal, that narrative will get worse. Suddenly she’s failing. She isn’t doing enough. SHE is not enough. She might fail, she might fail her family…so she’ll find more she should do. She doesn’t sleep as much, move as much, all in the efforts to do more. Caught in this cycle of trying to prove herself to herself, never reaching any goal. Never feeling “enough.” 

So, yeah, that’s what zealous burnout looks like for me. It doesn’t happen overnight in some grand gesture but instead slowly builds over weeks and months. My burning out process looks like speeding up, not a person losing focus. I speed up and up and up…and then I just stop.

I am the one who could

It’s funny the things that shape us. Through the lens of childhood, I viewed the fears, struggles, and sacrifices of someone who had to make it all work without having enough. I was lucky that my mother was so resourceful and my father supportive; I never went without and even got an extra here or there. 

Growing up, I did not feel shame when my mother paid with food stamps; in fact, I’d have likely taken on any debate on the topic, verbally eviscerating anyone who dared to criticize the disabled woman trying to make sure all our needs were met with so little. As a child, I watched the way the fear of not making those ends meet impacted people I love. As the non-disabled person in my home, I would take on many of the physical tasks because I was “the one who could” make our lives a little easier. I learned early to associate fears or uncertainty with putting more of myself into it—I am the one who can. I learned early that when something frightens me, I can double down and work harder to make it better. I can own the challenge. When people have seen this in me as an adult, I’ve been told I seem fearless, but make no mistake, I’m not. If I seem fearless, it’s because this behavior was forged from other people’s fears. 

And here I am, more than 30 years later still feeling the urge to mindlessly push myself forward when faced with overwhelming tasks ahead of me, assuming that I am the one who can and therefore should. I find myself driven to prove that I can make things happen if I work longer hours, take on more responsibility, and do more. 

I do not see people who struggle financially as failures, because I have seen how strong that tide can be—it pulls you along the way. I truly get that I have been privileged to be able to avoid many of the challenges that were present in my youth. That said, I am still “the one who can” who feels she should, so if I were faced with not having enough to make ends meet for my own family, I would see myself as having failed. Though I am supported and educated, most of this is due to good fortune. I will, however, allow myself the arrogance of saying I have been careful with my choices to have encouraged that luck. My identity stems from the idea that I am “the one who can” so therefore feel obligated to do the most. I can choose to stop, and with some quite literal cold water splashed in my face, I’ve made the choice to before. But that choosing to stop is not my go-to; I move forward, driven by a fear that is so a part of me that I barely notice it’s there until I’m feeling utterly worn away.

So why all the history? You see, burnout is a fickle thing. I have heard and read a lot about burnout over the years. Burnout is real. Especially now, with COVID, many of us are balancing more than we ever have before—all at once! It’s hard, and the procrastinating, the avoidance, the shutting down impacts so many amazing professionals. There are important articles that relate to what I imagine must be the majority of people out there, but not me. That’s not what my burnout looks like.

The dangerous invisibility of zealous burnout

A lot of work environments see the extra hours, extra effort, and overall focused commitment as an asset (and sometimes that’s all it is). They see someone trying to rise to challenges, not someone stuck in their fear. Many well-meaning organizations have safeguards in place to protect their teams from burnout. But in cases like this, those alarms are not always tripped, and then when the inevitable stop comes, some members of the organization feel surprised and disappointed. And sometimes maybe even betrayed. 

Parents—more so mothers, statistically speaking—are praised as being so on top of it all when they can work, be involved in the after-school activities, practice self-care in the form of diet and exercise, and still meet friends for coffee or wine. During COVID many of us have binged countless streaming episodes showing how it’s so hard for the female protagonist, but she is strong and funny and can do it. It’s a “very special episode” when she breaks down, cries in the bathroom, woefully admits she needs help, and just stops for a bit. Truth is, countless people are hiding their tears or are doom-scrolling to escape. We know that the media is a lie to amuse us, but often the perception that it’s what we should strive for has penetrated much of society.

Women and burnout

I love men. And though I don’t love every man (heads up, I don’t love every woman or nonbinary person either), I think there is a beautiful spectrum of individuals who represent that particular binary gender. 

That said, women are still more often at risk of burnout than their male counterparts, especially in these COVID stressed times. Mothers in the workplace feel the pressure to do all the “mom” things while giving 110%. Mothers not in the workplace feel they need to do more to “justify” their lack of traditional employment. Women who are not mothers often feel the need to do even more because they don’t have that extra pressure at home. It’s vicious and systemic and so a part of our culture that we’re often not even aware of the enormity of the pressures we put on ourselves and each other. 

And there are prices beyond happiness too. Harvard Health Publishing released a study a decade ago that “uncovered strong links between women’s job stress and cardiovascular disease.” The CDC noted, “Heart disease is the leading cause of death for women in the United States, killing 299,578 women in 2017—or about 1 in every 5 female deaths.” 

This relationship between work stress and health, from what I have read, is more dangerous for women than it is for their non-female counterparts.

But what if your burnout isn’t like that either?

That might not be you either. After all, each of us is so different and how we respond to stressors is too. It’s part of what makes us human. Don’t stress what burnout looks like, just learn to recognize it in yourself. Here are a few questions I sometimes ask friends if I am concerned about them.

Are you happy? This simple question should be the first thing you ask yourself. Chances are, even if you’re burning out doing all the things you love, as you approach burnout you’ll just stop taking as much joy from it all.

Do you feel empowered to say no? I have observed in myself and others that when someone is burning out, they no longer feel they can say no to things. Even those who don’t “speed up” feel pressure to say yes to not disappoint the people around them.

What are three things you’ve done for yourself? Another observance is that we all tend to stop doing things for ourselves. Anything from skipping showers and eating poorly to avoiding talking to friends. These can be red flags. 

Are you making excuses? Many of us try to disregard feelings of burnout. Over and over I have heard, “It’s just crunch time,” “As soon as I do this one thing, it will all be better,” and “Well I should be able to handle this, so I’ll figure it out.” And it might really be crunch time, a single goal, and/or a skill set you need to learn. That happens—life happens. BUT if this doesn’t stop, be honest with yourself. If you’ve worked more 50-hour weeks since January than not, maybe it’s not crunch time—maybe it’s a bad situation that you’re burning out from.

Do you have a plan to stop feeling this way? If something is truly temporary and you do need to just push through, then it has an exit route with a
defined end.

Take the time to listen to yourself as you would a friend. Be honest, allow yourself to be uncomfortable, and break the thought cycles that prevent you from healing. 

So now what?

What I just described is a different path to burnout, but it’s still burnout. There are well-established approaches to working through burnout:

• Get enough sleep.
• Eat healthy.
• Work out.
• Get outside.
• Take a break.
• Overall, practice self-care.

Those are hard for me because they feel like more tasks. If I’m in the burnout cycle, doing any of the above for me feels like a waste. The narrative is that if I’m already failing, why would I take care of myself when I’m dropping all those other balls? People need me, right? 

If you’re deep in the cycle, your inner voice might be pretty awful by now. If you need to, tell yourself you need to take care of the person your people depend on. If your roles are pushing you toward burnout, use them to help make healing easier by justifying the time spent working on you. 

To help remind myself of the airline attendant message about putting the mask on yourself first, I have come up with a few things that I do when I start feeling myself going into a zealous burnout.

Cook an elaborate meal for someone! 

OK, I am a “food-focused” individual so cooking for someone is always my go-to. There are countless tales in my home of someone walking into the kitchen and turning right around and walking out when they noticed I was “chopping angrily.” But it’s more than that, and you should give it a try. Seriously. It’s the perfect go-to if you don’t feel worthy of taking time for yourself—do it for someone else. Most of us work in a digital world, so cooking can fill all of your senses and force you to be in the moment with all the ways you perceive the world. It can break you out of your head and help you gain a better perspective. In my house, I’ve been known to pick a place on the map and cook food that comes from wherever that is (thank you, Pinterest). I love cooking Indian food, as the smells are warm, the bread needs just enough kneading to keep my hands busy, and the process takes real attention for me because it’s not what I was brought up making. And in the end, we all win!

Vent like a foul-mouthed fool

Be careful with this one! 

I have been making an effort to practice more gratitude over the past few years, and I recognize the true benefits of that. That said, sometimes you just gotta let it all out—even the ugly. Hell, I’m a big fan of not sugarcoating our lives, and that sometimes means that to get past the big pile of poop, you’re gonna wanna complain about it a bit. 

When that is what’s needed, turn to a trusted friend and allow yourself some pure verbal diarrhea, saying all the things that are bothering you. You need to trust this friend not to judge, to see your pain, and, most importantly, to tell you to remove your cranium from your own rectal cavity. Seriously, it’s about getting a reality check here! One of the things I admire the most about my husband (though often after the fact) is his ability to break things down to their simplest. “We’re spending our lives together, of course you’re going to disappoint me from time to time, so get over it” has been his way of speaking his dedication, love, and acceptance of me—and I could not be more grateful. It also, of course, has meant that I needed to remove my head from that rectal cavity. So, again, usually those moments are appreciated in hindsight.

Pick up a book! 

There are many books out there that aren’t so much self-help as they are people just like you sharing their stories and how they’ve come to find greater balance. Maybe you’ll find something that speaks to you. Titles that have stood out to me include:

• Thrive by Arianna Huffington
• Tools of Titans by Tim Ferriss
• Girl, Stop Apologizing by Rachel Hollis
• Dare to Lead by Brené Brown

Or, another tactic I love to employ is to read or listen to a book that has NOTHING to do with my work-life balance. I’ve read the following books and found they helped balance me out because my mind was pondering their interesting topics instead of running in circles:

• The Drunken Botanist by Amy Stewart
• Superlife by Darin Olien
• A Brief History of Everyone Who Ever Lived by Adam Rutherford
• Gaia’s Garden by Toby Hemenway 

If you’re not into reading, pick up a topic on YouTube or choose a podcast to subscribe to. I’ve watched countless permaculture and gardening topics in addition to how to raise chickens and ducks. For the record, I do not have a particularly large food garden, nor do I own livestock of any kind…yet. I just find the topic interesting, and it has nothing to do with any aspect of my life that needs anything from me.

Forgive yourself 

You are never going to be perfect—hell, it would be boring if you were. It’s OK to be broken and flawed. It’s human to be tired and sad and worried. It’s OK to not do it all. It’s scary to be imperfect, but you cannot be brave if nothing were scary.

This last one is the most important: allow yourself permission to NOT do it all. You never promised to be everything to everyone at all times. We are more powerful than the fears that drive us. 

This is hard. It is hard for me. It’s what’s driven me to write this—that it’s OK to stop. It’s OK that your unhealthy habit that might even benefit those around you needs to end. You can still be successful in life.

I recently read that we are all writing our eulogy in how we live. Knowing that your professional accomplishments won’t be mentioned in that speech, what will yours say? What do you want it to say? 

Look, I get that none of these ideas will “fix it,” and that’s not their purpose. None of us are in control of our surroundings, only how we respond to them. These suggestions are to help stop the spiral effect so that you are empowered to address the underlying issues and choose your response. They are things that work for me most of the time. Maybe they’ll work for you.

Does this sound familiar? 

If this sounds familiar, it’s not just you. Don’t let your negative self-talk tell you that you “even burn out wrong.” It’s not wrong. Even if rooted in fear like my own drivers, I believe that this need to do more comes from a place of love, determination, motivation, and other wonderful attributes that make you the amazing person you are. We’re going to be OK, ya know. The lives that unfold before us might never look like that story in our head—that idea of “perfect” or “done” we’re looking for, but that’s OK. Really, when we stop and look around, usually the only eyes that judge us are in the mirror. 

Do you remember that Winnie the Pooh sketch that had Pooh eat so much at Rabbit’s house that his buttocks couldn’t fit through the door? Well, I already associate a lot with Rabbit, so it came as no surprise when he abruptly declared that this was unacceptable. But do you recall what happened next? He put a shelf across poor Pooh’s ankles and decorations on his back, and made the best of the big butt in his kitchen. 

At the end of the day we are resourceful and know that we are able to push ourselves if we need to—even when we are tired to our core or have a big butt of fluff ‘n’ stuff in our room. None of us has to be afraid, as we can manage any obstacle put in front of us. And maybe that means we will need to redefine success to allow space for being uncomfortably human, but that doesn’t really sound so bad either. 

So, wherever you are right now, please breathe. Do what you need to do to get out of your head. Forgive and take care.

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

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

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

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

Voice Interactions

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

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

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

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

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

Transactional voice interactions

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

Alison: Hey, how’s it going?

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

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

Burhan: Sure, what size?

Alison: Large.

Burhan: Anything else?

Alison: No thanks, that’s it.

Burhan: Something to drink?

Alison: I’ll have a bottle of Coke.

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

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

Informational voice interactions

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

Alison: Hey, how’s it going?

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

Alison: Can I ask a few questions?

Burhan: Of course! Go right ahead.

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

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

Alison: What about gluten-free pizzas?

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

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

Burhan: Anytime, come back soon!

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

Voice Interfaces

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

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

Interactive voice response (IVR) systems

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

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

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

Screen readers

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

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

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

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

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

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

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

Voice assistants

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

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

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

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

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

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

Voice Content

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

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

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

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

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

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

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

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

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

Although I’m not certain 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 are functional on products that have not yet been created?

Flash, Photoshop, and flexible pattern

My go-to program when I first started designing websites was Photoshop. I created a 960px paint and set about creating a design that I would eventually lose information in. Set widths, fixed heights, and total placement were the keys to pixel-perfect accuracy during the development phase.

Ethan Marcotte’s speak at An Event Off and later content” Responsive Web Design” in A List Off in 2010 changed all this. As soon as I learned about responsive style, I was convinced, 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 design didn’t help my fear. My second project was to get an active fixed-width website and make it reactive. You can’t really put responsiveness at the end of a job, which I learned the hard way. To make smooth design, you need to prepare throughout the style stage.

a novel style process

Developing flexible or smooth sites has always been about removing limitations, producing material that can be viewed on any system. I originally used local CSS and utility classes, but it now relies on percentage-based layouts:

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

Then with Sass so I could take advantage of @includes to re-use repeated slabs of script and walk up to more semantic html:

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

internet inquiries

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

internet inquiries 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 capacities, I began to work more with washable parts.

Our rely on multimedia queries resulted in parts that were tied to frequent window sizes. If modify is the goal of part libraries, then this is a real issue because you can just use these components if the devices you’re designing for match the window sizes in the design library, which prevents you from actually achieving the “devices that don’t yet occur” goal.

Then there’s the problem of space. internet inquiries 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: a false dawn or our savior?

Container queries have long been touted as an improvement upon media queries, but at the time of writing are unsupported in most browsers. Although there are JavaScript workarounds, they can lead to dependability 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 a significant step in the direction of a component-based design that can be used on any device of any size.

In other words, responsive components to replace responsive layouts.

Container queries will enable us to design components that can be placed in a sidebar or in the main content and respond accordingly rather than designing pages that respond to the browser or device size.

My concern is that we are still using layout to determine when a design needs to adapt. This strategy will always be restrictive because we will still require 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 instance, the container’s dimensions are not what should be used to dictate the design; rather, the image is.

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

CSS is evolving.

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

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

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

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

The biggest benefit of all this is you don’t need to wrap elements in container rows. Without rows, content is not directly linked to page markup, allowing for content removals or additions without further development.

This is a significant improvement when it comes to developing designs that allow for dynamic content, but CSS Subgrid is the real game changer for flexible designs.

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. Subgrid also enables us to create designs that can change to fit changing content. Subgrid at the time of writing is only supported in Firefox but the above code can be implemented behind an @supports feature query.

Intrinsic layouts

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

Columns with percentages are flexible in responsive layouts. 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 manner, but never that it should be smaller than the content 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 distinguishes intrinsic design is that it not only creates designs that can withstand future devices but also helps scale designs without losing flexibility. Components and patterns can be lifted and reused without the prerequisite of having the same breakpoints or the same amount of content as in the previous implementation.

They now have the ability to adapt to the content both inside and outside of them. With an intrinsic approach, we can construct responsive components without depending on container queries.

Another 2010 moment?

This intrinsic approach should in my view be every bit as groundbreaking as responsive web design was ten years ago. 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 might be that I now work for a sizable company, which is significantly different from the role I held as a design agency in 2010: In my agency days, every new project was a clean slate, a chance to try something new. Modern projects frequently improve existing websites with an existing codebase and use existing tools and frameworks.

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

You can’t framework your way out of a content issue.

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 having a selection of units is a hindrance when creating layout templates, intrinsic design and frameworks do not work together quite as well. The beauty of intrinsic design is combining different units and experimenting with techniques to get the best for your content.

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

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

Another topic that has persisted for years is the debate over “whether designers should code.” 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?

I’m personally anticipating the day when a design component can truly be flexible and adapt to both its space and content without relying on the device or container dimensions. This is the day.

Content first

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

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

Instead of 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. This was frequently accomplished with Sass mixins in the past, but it was frequently limited to a switch from a left-to-right to a right-to-left orientation.

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

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

These variables can be used as values.

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

—or as properties.

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

However, with native logical properties, there is no longer a need to rely on Sass ( or another similar tool ) or pre-planning, which made using variables throughout a codebase necessary. 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);}

As long as the element’s width is not greater than 300px, the element in the figure above will cover 50 % of its container.

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

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

As long as the element’s width is at least 300px, it will now cover 50 % of its container. 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’t change markup because content can’t be changed, so user modifications won’t have an impact on the design. We can start to future-proof designs by planning for unexpected changes in language or direction. Additionally, we can increase flexibility by specifying desired dimensions alongside adaptable alternatives, which will allow for the display of more or less content correctly.

Situation first

We can address device flexibility by changing our approach, which focuses on content and space rather than devices, as we’ve discussed so far. 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.

This is why making a decision is so crucial. 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 give people choices.

Responsible design

” Mobile data is prohibitively expensive in some places around the world, and broadband infrastructure is sparse or absent.”

” 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, 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. 

Additionally, there is native lazy loading, which indicates that only required files should be downloaded for use.

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

internet inquiries 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. Because of these checks, we can offer options that work for more than one situation. It’s less about one-size-fits-all and more about providing adaptable content.

As of this writing, the Media Queries Level 5 spec is still under development. It introduces some really intriguing queries that will enable us to design for a number of other unanticipated situations in the future.

For example, there’s a light-level feature that allows you to modify styles if a user is in sunlight or darkness. These features, which have custom properties, make it simple to create designs or themes for particular 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. 

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

Expect the unanticipated

In the end, the one thing we should always expect is for things to change. With foldable screens already available on the market, devices especially change more quickly than we can keep up.

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

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 must make sure our goods are accessible whenever and wherever needed. 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.

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

This book will provide you with that plan of action. It covers how to incorporate safety concepts into your design work to create healthy technology, how to persuade stakeholders that this work is required, and how to respond to criticism that there isn’t really enough diversity. ( Spoiler: we do, but diversity alone is not the antidote to fixing unethical, unsafe tech. )

The procedure for ensuring equitable safety

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

• determine the best ways to abuse your item.
• style ways to prevent the maltreatment, and
• offer assistance for harmed people to regain control and power.

The Process for Inclusive Safety is a tool to help you reach those goals ( Fig 5.1 ). I developed this strategy in 2018 to better understand the various methods I used to create products that were designed with safety in mind. Whether you are creating an entirely new product or adding to an existing element, the Process can help you produce your product secure and diverse. Five main public areas of action are included in the Process:

• Conducting study
• creating themes
• Pondering problems
• creating answers
• Testing for security

It is intended to be flexible, so teams might not want to apply every action in all circumstances. Use the parts that are related to your special function and environment, this is meant to be something you can put into your existing style process.

And if you’ve used it, if you’ve got ideas for improving it, or just want to give an example of how it helped your staff, please get in touch with me. It’s a dwelling report that I hope will continue to be a helpful and practical tool that technicians can use in their day-to-day job.

If you’re developing a product especially for a defenseless group or victims of some kind of stress, like an application for victims of domestic violence, sexual abuse, or drug habit, make sure to read Chapter 7, which specifically addresses the issue and should be handled a little different. The guidelines below are for evaluating safety when designing a more basic product that will have a large customer base ( which, we now know from data, will include specific groups that should be protected from harm ). Chapter 7 concentrates on goods made especially for those who are most vulnerable and those who have gone through stress.

Step 1: Do study

A thorough examination of how your technology might be used to abuse people as well as a detailed analysis of the experiences of those who have survived and perpetrated that kind of abuse should be included in the design research. At this stage, you and your group does investigate issues of emotional damage and abuse, and examine any other safety, security, or inclusivity issues that might be a concern for your product or service, like data security, prejudiced algorithms, and harassment.

broad-based research

Your project should begin with broad, general research into similar products and issues around safety and ethical concerns that have already been reported. A team building a smart home device would be wise to comprehend the many ways that already-existing smart home devices have been misused as abuse tools. If your product will involve AI, seek to understand the potentials for racism and other issues that have been reported in existing AI products. Nearly all different types of technology have some sort of potential or actual harm that has been covered in the media or written about by academics. Google Scholar is a useful tool for finding these studies.

Specific research: Survivors

When possible and appropriate, include direct research ( surveys and interviews ) with people who are experts in the forms of harm you have uncovered. In order to gain a better understanding of the subject and be better positioned to avoid traumatizing survivors, you should first interview those who work in the area of your research. If you’ve uncovered possible domestic violence issues, for example, the experts you’ll want to speak with are survivors themselves, as well as workers at domestic violence hotlines, shelters, other related nonprofits, and lawyers.

It is important to pay people for their knowledge and lived experiences, especially when interviewing survivors of any kind of trauma. Don’t ask survivors to share their trauma for free, as this is exploitative. You should always make the offer in the first interview, even though some survivors might not want to be paid. An alternative to payment is to donate to an organization working against the type of violence that the interviewee experienced. In Chapter 6, we’ll discuss more about how to appropriately interview survivors.

Specific research: Abusers

Teams aiming to design for safety are unlikely to be able to interview self-declared abductors or those who have broken laws in areas like hacking. Don’t make this a goal, rather, try to get at this angle in your general research. Attempt to understand how abusers or bad actors use technology to harm others, how they use it against others, and how they justify or explain the abuse.

Step 2: Create archetypes

Use your research after you’ve finished conducting it to create abuser and survivor archetypes. Archetypes are not personas, as they’re not based on real people that you interviewed and surveyed. Instead, they are based on your investigation into potential safety problems, much like when we design for accessibility: we don’t need to have identified any blind or deaf people in our interview pool to come up with a design that is representative of them. Instead, we base those designs on existing research into what this group needs. While archetypes are broad and can be more generalized, real users typically represent real users and contain many details.

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

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

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

It may be useful for you to create persona-like artifacts for your archetypes, such as the three examples shown. Focus on their objectives rather than the demographic details we frequently see in personas. The goals of the abuser will be to carry out the specific abuse you’ve identified, while the goals of the survivor will be to prevent abuse, understand that abuse is happening, make ongoing abuse stop, or regain control over the technology that’s being used for abuse. Later, you’ll think about how to help the survivor’s goals and the abuser’s goals.

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

Step 3: Brainstorm problems

Brainstorm novel abuse cases and safety concerns after creating archetypes. ” Novel” means things not found in your research, you’re trying to identify completely new safety issues that are unique to your product or service. This step is intended to exhaust every effort put forth to identify potential harms your product might cause. You aren’t worrying about how to prevent the harm yet—that comes in the next step.

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

Try conducting a Black Mirror brainstorming session if you want to start somewhere. This exercise is based on the show Black Mirror, which features stories about the dark possibilities of technology. Find out the most outrageous, horrible, and out-of-control ways your product could be used for harm in an episode of the show. When I’ve led Black Mirror brainstorms, participants usually end up having a good deal of fun ( which I think is great—it’s okay to have fun when designing for safety! ). I suggest time-boxing a Black Mirror brainstorm for the first half an hour, then dialing back, and using the remaining time to consider more plausible forms of harm.

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

It’s impossible to say 100 % assurance that you’ve done everything, but instead of aiming for 100 %, acknowledge that you’ve done it and will continue to prioritize safety in the future. Once your product is released, your users may identify new issues that you missed, aim to receive that feedback graciously and course-correct quickly.

4: Create solutions

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

Questions to ask yourself include: What are some ways to protect your archetypes and to support your self-identity?

• Can you design your product in such a way that the identified harm cannot happen in the first place? If not, what barriers can you place to stop the harm from occurring?
• How can you make the victim aware that abuse is happening through your product?
• How can you explain to the victim what they must do to stop the problem?
• Can you identify any types of user activity that would indicate some form of harm or abuse? Could your product provide support for the user?

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

Nonetheless, be careful when doing anything that could harm a user if their devices are being monitored. If you do offer some kind of proactive help, always make it voluntary, and think through other safety issues, such as the need to keep the user in-app in case an abuser is checking their search history. In the next chapter, we’ll walk through a good illustration of this.

Step 5: Test for safety

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

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

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

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

You as the designer are most likely too closely connected to the product and its design at this point, just like other types of usability testing, and you know the product too well. Instead of doing it yourself, set up testing as you would with other usability testing: find someone who is not familiar with the product and its design, set the scene, give them a task, encourage them to think out loud, and observe how they attempt to complete it.

Abuse testing

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

For instance, we can imagine that the abuser archetype would have the goal of discovering where his ex-girlfriend currently lives in a fitness app with GPS-enabled location features. With this goal in mind, you’d try everything possible to figure out the location of another user who has their privacy settings enabled. You might try to follow her running routes, view any information she has on her profile, view any information she has made private, and check out other users ‘ profiles, such as those of her followers.

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

Survivor testing

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

There are times, however, when it makes sense. For example, for a smart thermostat, a survivor archetype’s goals would be to understand who or what is making the temperature change when they aren’t doing it themselves. If you couldn’t find the information in step 4, you would need to perform more work in step 4. You could test this by looking for the thermostat’s history log and looking for usernames, actions, and times.

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

stress testing

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

Some members of the elite running group were beginning to think it was impossible to run a hour in less than four hours in the 1950s. Riders had been attempting it since the later 19th century and were beginning to draw the conclusion that the human body just wasn’t built for the job.

However, on May 6, 1956, Roger Bannister caught anyone by surprise. It was a cold, damp morning in Oxford, England—conditions no one expected to give themselves to record-setting—and but Bannister did really that, running a mile in 3: 59.4 and becoming the first people in the history books to run a mile in under four hours.

The world today knew that the four-minute hour could be accomplished thanks to this change in the standard. Bannister’s history lasted just forty-six days, when it was snatched aside by American sprinter John Landy. Finally, in the same race, three athletes all managed to cross the four-minute challenge. Since therefore, over 1, 400 walkers have actually run a mile in under four days, the current document is 3: 43.13, held by Moroccan performer Hicham El Guerrouj.

We do a lot more when we think something is possible, and we only think it can be done when we see someone else doing it once more. As for individual running speed, we also think there are strict guidelines for how a website should do.

Establishing requirements for a green website

The key indicators of climate performance in most big companies are very well established, such as power per square metre for homes and miles per gallon for cars. The tools and methods for calculating those measures are standardized as well, which keeps everyone on the same site when doing economic evaluations. But, we are not required to follow any specific environmental standards in the world of websites and apps, and we have only recently developed the tools and methods to do so.

The main objective in green web layout is to reduce carbon emissions. However, it’s nearly impossible to accurately assess the amount of CO₂ that a website merchandise produces. We didn’t measure the pollutants coming out of the exhaust valves on our laptops. Our websites produce far-away, invisible, and unremarkable emissions when they leave fuel and gas-burning power plants. We have no way to track the particles from a website or app up to the power station where the light is being generated and really know the exact amount of house oil produced. What then do we do?

If we can‘t measure the actual carbon emissions, then we need to get what we can estimate. The following are the main elements that could be used as measures of coal emissions:

1. Transfer of data
2. Electricity’s coal power

Let’s take a look at how we can use these indicators to calculate the energy use, and in turn the carbon footprint, of the sites and web applications we create.

Transfer of data

Most researchers use kilowatt-hours per gigabyte (k Wh/GB ) as a metric of energy efficiency when measuring the amount of data transferred over the internet when a website or application is used. This serves as a wonderful example of how much energy is consumed and how much coal is released. As a rule of thumb, the more files transferred, the more electricity used in the data center, telecoms systems, and end users products.

The easiest way to calculate data exchange for a second visit for web pages is to measure the site weight, which is the page’s transfer size in kilobytes when someone first visits the page. It’s very easy to measure using the engineer equipment in any modern internet browser. Statistics for the total data transfer of any web application are frequently included in your web hosting account ( Fig. 2.1 ).

The great thing about website weight as a parameter is that it allows us to compare the effectiveness of web pages on a level playing field without confusing the issue with frequently changing traffic volumes.

A large scope is necessary to reduce page weight. By early 2020, the median page weight was 1.97 MB for setups the HTTP Archive classifies as “desktop” and 1.77 MB for “mobile”, with desktop increasing 36 percent since January 2016 and mobile page weights nearly doubling in the same period ( Fig 2.2 ). Image files account for the majority of this data transfer, making them the single biggest contributor to carbon emissions on a typical website.

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

You may be aware of the idea of performance budgeting as a method for directing a project team to deliver faster user experiences. For example, we might specify that the website must load in a maximum of one second on a broadband connection and three seconds on a 3G connection. Performance budgets are upper limits rather than hazy ideas, much like speed limits while driving. As a result, the goal should always be to stay within budget.

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

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

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

Page weight budgets are easy to track throughout a design and development process. Although they don’t directly disclose their data on energy consumption and carbon emissions, they do provide a clear indicator of efficiency in comparison to other websites. And as transfer size is an effective analog for energy consumption, we can actually use it to estimate energy consumption too.

In summary, less data transfer leads to more energy efficiency, which is a crucial component of reducing web product carbon emissions. The more efficient our products, the less electricity they use, and the less fossil fuels need to be burned to produce the electricity to power them. However, as we’ll see next, it’s important to take into account the source of that electricity because all web products require some power.

Electricity’s coal power

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

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

Although we don’t have complete control over the energy supply of web services, we do have some control over where our projects are hosted. With a data center using a significant proportion of the energy of any website, locating the data center in an area with low carbon energy will tangibly reduce its carbon emissions. This user-provided data is reported and mapped by Danish startup Tomorrow, and a look at their map demonstrates how, for instance, choosing a data center in France will result in significantly lower carbon emissions than choosing a data center in the Netherlands ( Fig. 2.3 ).

However, we don’t want to move our servers too far away from our users because it requires energy to transmit data through the telecom’s networks, and the more energy is used. Just like food miles, we can think of the distance from the data center to the website’s core user base as “megabyte miles” —and we want it to be as small as possible.

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

For instance, if a website is hosted in London but the main audience is on the United States ‘ West Coast, we could calculate the distance between San Francisco and London, which is 5,300 miles. That’s a long way! We can see how hosting it somewhere in North America, ideally on the West Coast, would significantly shorten the distance and the amount of energy needed to transmit the data. In addition, locating our servers closer to our visitors helps reduce latency and delivers better user experience, so it’s a win-win.

Reverting it to carbon emissions

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

The Energy and Emissions Worksheet that comes with this book teaches you how to take it to the next level and tailor the data more accurately to the individual aspects of your project.

With the ability to calculate carbon emissions for our projects, we could actually expand our page weight budget and establish carbon budgets as well. CO₂ is not a metric commonly used in web projects, we’re more familiar with kilobytes and megabytes, and can fairly easily look at design options and files to assess how big they are. Although translating that into carbon adds a layer of abstraction that isn’t as intuitive, carbon budgets do focus our minds on the main thing we’re trying to reduce, and this is in line with the main goal of sustainable web design: reducing carbon emissions.

Browser Energy

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

One part of the system we can look at in more detail is the energy used by end users ‘ devices. The computational burden is increasingly shifting from the data center to the users ‘ devices, whether they are phones, tablets, laptops, desktops, or even smart TVs, as front-end web technologies advance. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Additionally, JavaScript libraries like Angular and React make it possible to create applications where the” thinking” process is performed partially or completely in the browser.

All of these advances are exciting and open up new possibilities for what the web can do to serve society and create positive experiences. However, more computation in a web browser requires more energy to be used by the user’s devices. This has implications not just environmentally, but also for user experience and inclusivity. Applications that put a lot of processing power on a user’s device unintentionally exclude those who have older, slower devices and make the batteries on phones and laptops drain more quickly. Furthermore, if we build web applications that require the user to have up-to-date, powerful devices, people throw away old devices much more frequently. This not only harms the environment, but it places a disproportionate financial burden on the poorest members of society.

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

You are aware of the moment your computer’s cooling fans start spinning so frantically that you mistakenly believe it might take off when you load a website? That’s essentially what this tool is measuring.

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

But how can a content management system ( CMS ) be set up to reach your current and future audience? I learned the hard way that creating a content model—a concept of information types, attributes, and relationships that let people and systems understand content—with my more comfortable design-system wondering would collapse my patient’s holistic information strategy. By developing willing versions that are conceptual and that also connect related information, you can avoid that result.

I just had the opportunity to direct the CMS application for a Fortune 500 company. The customer was excited by the benefits of an holistic information plan, including material modify, multichannel marketing, and robot delivery—designing content to be comprehensible to bots, Google knowledge panels, snippets, and voice user interfaces.

A content type is essential for an omnichannel articles strategy, and the model needed conceptual types, which are types of types that are categorized according to their meaning rather than their presentation. Our objective was to allow writers to write articles and use it where necessary. However, as the project progressed, I realized that the entire group had to be aware of a new design in order to support material reuse on the level that my customer needed.

Despite our best motives, we kept drawing from what we were more common with: design techniques. Unlike web-focused material strategies, an holistic information strategy doesn’t rely on WYSIWYG equipment for design and structure. Our inclination to approach the material model using our well-known design-system thinking consistently stifled our attention from one of the main objectives of a willing model: delivering content to audiences across multiple marketing channels.

Two fundamental tenets are necessary for a successful content type

We needed to explain to our designers, developers, and stakeholders that we were doing something completely different from their previous internet projects, where everyone assumed that content would fit into layouts as physical building blocks. The past approach made the designs feel more recognizable and intuitive, at first, at least because it was more common and also more intuitive. We discovered two guiding principles that helped the group grasp how a willing model and the design processes we were familiar with were:

1. Instead of design, content models may establish semantics.
2. And glad models may connect elements that belong together.

Conceptual articles models

A conceptual content type uses form and attribute names that reflect the content’s intended purpose and not its intended display. For instance, in a nonsemantic design, groups may produce varieties like teasers, press blocks, and cards. These types may make it simple to present information, but they do not aid in understanding the meaning of the information, which would have opened the door to the content presented in each marketing channel. To allow each distribution channel to comprehend the information and use it as it sees fit, a conceptual content type uses kind names like product, service, and testimonial.

A great place to start when creating a conceptual content concept is by reviewing the types and qualities that Schema has defined. nonprofit, a community-driven source for type meanings that are comprehensible to platforms like Google search.

A semantic information model has many advantages:

A semantic material type decouples content from its presentation but that teams can change the website’s design without having to restructure its content, even if your team doesn’t worry about omnichannel content. In this way, content can withstand disruptive website redesigns.
• A semantic content model also gives you a competitive advantage. by including schema-based structured data. org’s types and properties, a website can provide hints to help Google understand the content, display it in search snippets or knowledge panels, and use it to answer voice-interface user questions. Potential customers could access your content without ever visiting your website.
• Beyond those practical advantages, you’ll also require an omnichannel content delivery model. Delivery channels must be able to comprehend the same content in order to use it across multiple marketing channels. For instance, if your content model provided a list of questions and answers, it could be easily displayed on a frequently asked questions ( FAQ ) page as well, but it could also be used by a bot that answers frequently asked questions.

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

Content models that connect

Instead of slicing up related content across disparate content components, I’ve come to the realization that the best models are those that are semantic and also connect related content components ( such as a FAQ item’s question and answer pair ). Content that needs to be reused by multiple delivery channels can be connected to each other without having to assemble those pieces again in a good content model.

Write an essay or article about it. An article’s meaning and usefulness depends upon its parts being kept together. Without the full context of the article, would one of the headings or paragraphs have any relevance on their own? Our well-known design-system thinking on our project frequently led us to want to develop content models that would divide content into distinct chunks to fit the web-centric layout. Similar effects could have been felt to an article that had its headline removed. Because we were dividing content into separate pieces based on layout, content that belonged together became challenging to manage and nearly impossible for multiple delivery channels to comprehend.

To illustrate, let’s look at how connecting related content applies in a real-world scenario. A complex layout for a software product page that included multiple tabs and sections was presented by the client’s design team. Our instincts were to follow the content model’s. Shouldn’t we make adding any number of tabs in the future as simple and as flexible as possible?

We felt like we needed a “tab section” content type because our design-system instincts allowed for the addition of multiple tab sections to a page because they were so well-versed. Each tab section would display a variety of content. One tab might provide the software’s overview or its specifications. Another tab might provide a list of resources.

Our tendency to divide the content model into “tab section” pieces would have resulted in a cumbersome editing process, as well as unnecessarily complex content that couldn’t have been digested by additional delivery channels. How would another system have resorted to counting tab sections and content blocks, for instance, if it had been able to identify a product’s “tab section” when referring to its specifications or resource list? This would have prevented the tabs from ever being rearranged, and it would have required adding logic to each other delivery channel to interpret the layout of the design system. Additionally, it would have been difficult to migrate to a new content model in response to the new page redesign if the customer had decided against displaying this content in a tab layout.

We had a breakthrough when we discovered that our customer had a specific purpose in mind for each tab: it would reveal specific information such as the software product’s overview, specifications, related resources, and pricing. Our desire to concentrate on what was visually and historically significant had obscured the purpose of the designs once implementation began. With a little digging, it didn’t take long to realize that the concept of tabs wasn’t relevant to the content model. What was important was the meaning of the content they were planning to display in the tabs.

In fact, the customer could have chosen to display this content elsewhere, without tabs. In response to this realization, we created content types for the software product based on the meaningful attributes the client wanted to display on the web. There were obvious semantic attributes like name and description as well as rich attributes like screenshots, software requirements, and feature lists. The software’s product information stayed together because it wasn’t sliced across separate components like “tab sections” that were derived from the content’s presentation. Any delivery channel—including future ones—could understand and present this content.

Conclusion

In this omnichannel marketing project, we discovered that the best way to maintain the content model’s semantic consistency was by ensuring that it was semantic ( with type and attribute names that reflected the content’s meaning ) and that it maintained content that belonged together ( as opposed to fragmenting it ). These two ideas made it easier for us to decide what to do with the content model based on the design. Remember: If you’re developing a content model to support an omnichannel content strategy, or even if you just want to make sure that Google and other interfaces understand your content, keep in mind:

• A design system isn’t a content model. You should maintain the semantic value and contextual structure of the content strategy throughout the entire implementation process because team members might be tempted to combine them and to make your content model resemble your design system. This will enable each delivery channel to consume the content without the need for a magic decoder ring.
• You can still use Schema if your team is having trouble making this transition. org–based structured data in your website. The benefit of search engine optimization is a compelling reason on its own, even if additional delivery channels aren’t on the horizon in the near future.
• Remind the team that separating the content model from the design will allow them to update the designs more quickly because they won’t be hindered by the cost of content migrations. They will be prepared for the upcoming big thing, and they will be able to create new designs without compromising the compatibility between the content and the design.

By firmly defending these ideas, you’ll help your team treat content the way it deserves as the most important component of your user experience and the best way to engage with your audience.

CSS is all about appearance containers. In fact, the whole website is made of containers, from the website viewport to components on a webpage. However, there are times when we have a fresh element that forces us to reevaluate our design strategy.

Square features, for instance, make it fun to play with round picture areas. Finding the best way to organize articles that stays out of reach with smart screen notches and electronic keyboards is challenging. And two display or portable devices make us reassess how to best utilize available space in a number of various device postures.

These new evolutions of the internet system made it both more demanding and more exciting to design products. They’re fantastic options for us to leave our triangular boxes.

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

Democratic Web Apps are bridging the gap between websites and apps. They combine the best of both worlds. On the one hand, they are flexible, shareable, and stable, just like websites. On the other hand, they provide more effective features, work online, and read documents just like local apps.

PWAs are really exciting as a style area because they challenge us to consider how to combine online and native user interface. On desktop products in certain, we have more than 40 years of history telling us what software may look like, and it can be hard to break out of this mental concept.

PWAs on desktop are ultimately limited to the top of a rectangle with a title bar.

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

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

What if we could look beyond this box and reclaim the entire window of the app? Doing so would give us a chance to make our apps more beautiful and feel more integrated in the operating system.

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

About the window and title bar controls

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

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

Window Controls Overlay removes the physical constraint of the title bar and window controls areas. The title bar and window control buttons are overlayed on top of the application’s web content, allowing for full height to be the app window.

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

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

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

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

Let’s use the feature

We’ll be developing a demo app for the remainder of this article to learn more about how to use the feature.

The demo app is called 1DIV. Users can create designs using CSS and a single HTML element in a simple CSS playground.

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

You can edit and create CSS designs on the second page:

Since I’ve added a simple web manifest and service worker, we can install the app as a PWA on desktop. What it appears to be on macOS is shown below:

And on Windows:

The first page’s white title bar is a waste of space, despite our app’s attractive design. In the second page, it would be really nice if the design area went all the way to the top of the app window.

To enhance this, let’s use the Window Controls Overlay feature.

Enabling Window Controls Overlay

The film is still in its experimental phase right now. To try it, you need to enable it in one of the supported browsers.

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

Using Window Controls Overlay

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

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

The feature appears to be very simple to use. This manifest change is the only thing we need to make the title bar disappear and turn the window controls into an overlay.

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

Here is what the app looks like now:

Our logo, search field, and NEW button are now partially obscured by the window controls because our layout now begins at the top of the window, which is what we wanted.

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

CSS to avoid the window controls

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

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

You can use these variables in conjunction with the CSS env function to position your content where the title bar would have been and make sure it doesn’t overlap with the window controls. In our case, we’ll use two of the variables to position our header, which contains the logo, search bar, and NEW button.

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

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

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

Our header now adapts to its surroundings, and it doesn’t seem like the window control buttons were left out. The app looks a lot more like a native app.

Changing the window controls the background color so that it blends in

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

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

By changing the theme color of the app, we can fix this. There are a couple of ways to define it:

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

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

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

Here is the function we’ll use:

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

With this in place, we can envision how using CSS and color transitions to smoothly transition between the list page and the demo page and make the window control buttons blend in with the rest of the app’s interface.

Dragging the window

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

Users can use the Window Controls Overlay feature to move the window, but this area becomes limited to where the control buttons are, and they must very precisely aim between these buttons to move the window. However, the title bar offers a sizable area for users to click and drag.

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

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

-webkit-app-region: drag;

Additionally, it is possible to specify explicitly that an element be non-draggable:

-webkit-app-region: no-drag; 

These options can be useful for us. We can rename the entire header as a dragging target, but we can also make the NEW button and search field non-draggable so they can still be used as they normally are.

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

...

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

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

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

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

With the above code, users can click and drag where the title bar used to be. Users are expecting to be able to move windows on their desktops, and we don’t violate this expectation, which is good.

Adapting to window resizing

It may be useful for an app to know both whether the window controls overlay is visible and when its size changes. The search field, logo, and button would need to be pushed down a little bit if the user made the window very narrow.

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

Three intriguing things are provided by the API:

• navigator.windowControlsOverlay.visiblelets us know whether the overlay is visible.
• navigator.windowControlsOverlay.getBoundingClientRect()lets us know where the title bar’s area is located and how big it is.
• navigator.windowControlsOverlay.ongeometrychangelets us know when the size or visibility changes.

Use this to check the size of the title bar area and lower the header if it’s too small.

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

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

• It’s only fired when the feature is supported and used, we don’t want to adapt the design otherwise.
• We can see the title bar area on different operating systems, which is great because Mac and Windows have different title bar sizes. Using a media query wouldn’t make it possible for us to know exactly how much space remains.

.narrow header { top: env(titlebar-area-height, 0); left: 0; width: 100%;}

When the window is too small, we can use the above CSS code to move our header down and move the thumbnails down in accordance with this.

Thirty pixel of creative challenge

Using the Window Controls Overlay feature, we were able to take our simple demo app and turn it into something that feels so much more integrated on desktop devices. Something that transcends the traditional window restrictions and offers its users a personalized experience.

In reality, this feature only gives us about 30 pixels of extra room and comes with challenges on how to deal with the window controls. However, these additional space and those difficulties can also serve as creative outlet for creative work.

More devices of all shapes and forms get invented all the time, and the web keeps on evolving to adapt to them. To make it easier for us, web authors, to integrate more and more deeply with those devices, new features are added to the web platform. From watches or foldable devices to desktop computers, we need to evolve our design approach for the web. We can now think beyond the rectangular box when building for the web.

So let’s embrace this. Use the common technologies at our disposal and experiment with new concepts to create personalized experiences for all devices using just one codebase!

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