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As the world awaits the announcement of the seventh thespian who will wear the famous tux, the debate over who that person’s status and identity has rekindled: [ …] Despite the fact that only six actors have officially played the British secret agent James Bond over the course of 63 years ( with apologies to non-canon outliers David Niven and Barry Nelson ),

The second article on Den of Geek was The James Bond Bounce: How the Tuxedo impacted Each Actor’s Career.

The Conjuring: Final Rites, a picture in the Conjuring Universe, will be released this week. Life and death are at stake for the fictionalized types of paranormal researchers Ed and Lorraine Warren, who are portrayed onscreen by Vera Farmiga and Patrick Wilson in all four of the major Conjuring shows. It was never good that company administrators James Wan or Michael Chaves may resort to a Tarantino-esque traditional trickery in which Ed is killed by a beast and dragged to heaven because Judy Warren and Lorraine Warren’s relationships with the Conjuring Universe movies had been so important. The Labyrinths are known to have survived all of their trials.

Despite this, we asked star Farmiga and Wilson how they keep pulling off the magic trick of involving the audience in the Warrens &#8217, fate in these high-tension horror stories.

&#8220, It&#8217, s a great topic, &#8221, Wilson says. &#8220, They both went on. After this, Lorraine had about 40 more times, and Ed was about 30. How do you move the market along, I don’t understand? I believe that it is always life and death for the people and that it is also life and death for them. We had worked so hard on Ed’s heart harm, particularly with him. I was quite aware that “men, we can’t keep going up to the well on that.” &#8217, It&#8217, s got to become innovative. We need a new beast, to be feign. &#8221,

Choose which real-life haunting case the Warrens investigated, according to line producer and author James Wan, is the key to piqueing viewers ‘ and series’s rooting interest with each film in the series. This meant tying in the death of the Warrens ‘ personal child, Judy, with the Smurl family’s, a new bedeviled cast whose scenario forms the center of the movie. In the beginning scene of the movie, their baby almost dies at birth, and two decades later, she becomes a part of the Smurl investigation along with her own impending marriage.

According to Pale,” One of the main things we look into is whether a particular situation is A) well known enough, and B) has a connection to the psychological significance of the Warrens &#8217, active. &#8221,

&#8220, It was n&#8217, t up to us, &#8221, Farmiga information”. It’s a pretty interesting question to ask. It’s difficult with clues and all that, but it’s up to the authors to decide. A couple’s pregnancy had to be decided between life and death. The story of this includes both life and death, and this is the bloodiest beast they may include written that has a very private grudge. It was up to the authors to create it with honesty, emotion, and personalized touch. &#8221,

Wilson continues,” You know what it is too, Vera,” and says,” #8220, You know what it is too, Vera.” Right in terms of decline? Because of the nature of rearranging a movie, you want to find a low level for your character, which is frequentlytimes an imminent death, and take away what’s true and what’s not. But they are trying to figure out “are we losing a child?” because it’s such a decline. &#8217, It&#8217, s like in every parental film with a child that &#8217, s about to get married. Do you gain a child but lose your child? A very life-changing tragedy like that is present in this movie right away. It has some truly life-changing occasions. You always get over it, so you’re already giving them a sense of loss, so it’s all about wins and losses in this film. We always have that in terms of demons, but you also have that in terms of family, so it’s not as clean as it’s like. And this man will pass away in this movie. ‘ &#8221, &nbsp,

Farmiga did appear to concur.

” I think what’s unique about this, particularly for Lorraine, is that Lorraine has always tried to protect Judy,” Farmiga says. She&#8217 has always covered her in metaphysical bubble wrap to keep the noise out and the shadows at bay. But now it &#8217, s unique. She&#8217, s really unique. &#8221,

Mia Tomlinson, who replaces Sterling Jerins and Mckenna Grace in the role of Judy, was given first-hand accounts of the paranormal minefields of &#8220 growing up as a Warren from the real Judy ( now Judy Spera ). &#8221,

&#8220, Judy &#8217, s very guarded, &#8221, Tomlinson explains. &#8220, She&#8217, s silent, she&#8217, s keeping it to herself. She is attempting to keep it up, but it is like a soft, unraveling rope. I applied Judy’s advice in the way that she uses the words “don’t look it in the eye, don’t give it reputation,” or “don’t look it in the eye.” &#8217, That&#8217, s how she approached Annabelle. Because I am a very lively man, I used it as a mantra on the set to keep me grounded. You &#8217, ve got to get. There is a way to balance it because we are kind of performing in between what Judy has done in her career and what Judy has done in this movie. &#8221,

The fading between fact and fiction even gives the players the chance to explore deeper, general principles that come with being a parent or child.

There is that paternal damage when your infants grow up, Farmiga says. You raised them to become independent, but now she is and you are, and she has a head of her own. Judy has long been in religious WiFi thanks to Lorrainee’s efforts to keep the child in &#8216, flight mode&#8217. She desires to receive that sign. That’s how Lorraine described it to me. She thought of it primarily as a sign. Judy was kept in the safe area by Lorraine for a long time, and this one’s plot is quite different from hers. She is aware of how exhausting it can be to “tap into” the other side. &#8221,

To his credit, director Michael Chaves ( in his fourth go-round producing a Conjuring Universe movie ) consistently places all the demonic sturm und drang in the background of Judy’s and her engagement to Tony Spera ( played by Ben Hardy ). The haunting’s bad mirror is just as effective as Ed and Lorraine’s. &nbsp,

Chaves continues,” I am so glad of all the character work in it and the figure account that we tell.” For Ed and Lorraine, I believe that’s the real reason folks keep returning to this company. It&#8217 ;s because of the fantastic characters that Patrick and Vera have created. You’re returning to this in any excellent set. You’re returning to the figures and seeing them go through this second stage of their journey.

It would be fascinating to observe Judy and Tony take center stage in a future episode as the history of Ed and Lorraine apparently coming to an &#8220, close &#8221, with The Conjuring: Next Customs. &nbsp,

&#8220, I&#8217, d like that, I&#8217, m certain, &#8221, admits Tomlinson. &#8220, You would as well, Ben, straight? We would really like to collaborate and carry the torch!

&#8220, Sure, yeah, move us the earth, &#8221, Ben Hardy laughs. &#8220, They also run the household company, as far as I&#8217, m aware, but yeah. Who is aware? &#8221,

&#8220, Fingers crossed, &#8221, adds Tomlinson. &nbsp,

On Friday, September 5, The Conjuring: Last Rites premieres in theaters everyday.

The Conjuring: Next Customs Stars on Fact vs. Fiction in Warrens &#8217, Next Case appeared initially on Den of Geek.

Spoilers for winter 3 event 9 were included in this Star Trek: Odd New Worlds review. It’s perhaps because you’ve seen the season three finale of Star Trek: Odd New Worlds. Sort of. stories with forced proximity, forced enemies to instantly coexist, or other forms of forced proximity […]

On Den of Geek, the initial evaluation of Star Trek: Odd New Worlds Season 3 Episode 9 Review — Terrarium appeared.

The Conjuring: Final Rites, the Conjuring: Final, and Final, respectively, video, is due out this week in the Conjuring Universe. Life and death are at stake for the fictionalized types of paranormal researchers Ed and Lorraine Warren, who are portrayed onscreen by Vera Farmiga and Patrick Wilson in all four of the major Conjuring shows. It was never likely that company stewards James Wan or Michael Chaves would succumb to Tarantino-esque traditional trickery where Ed is killed by a beast and dragged to heaven because Judy Warren and the late Lorraine Warren were involved in the Conjuring Universe movies. We are certain that the Warrens will survive all of their legal battles.

Despite this, we asked star Farmiga and Wilson how they keep pulling off the magic trick of involving the audience in the Warrens &#8217, fate in these high-tension horror stories.

&#8220, It&#8217, s a good topic, &#8221, Wilson says. &#8220, They both went on. After that, Lorraine had about 40 more times, and Ed was about 30. How do you move the market along, I don’t understand? I believe that there is always life and death for individuals and that there is also life and death for them. We had done a lot of work on Ed’s brain harm, particularly with him. I was quite aware that “men, we can’t keep going up to the well on that.” &#8217, It&#8217, s got to be innovative. We must possess a brand-new monster, so to speak. &#8221,

Choose which real-life haunting case the Warrens investigated, according to line producer and author James Wan, is the key to piqueing viewers ‘ and series’s rooting interest with each film in the series. This meant tying in the death of the Warrens ‘ individual child, Judy, with the death of the Smurl home, a new bedeviled set of characters whose situation is the center of the movie. In the beginning scene of the movie, their baby almost dies at birth, and two decades later, she becomes a part of the Smurl investigation along with her own impending marriage.

According to Wan,” One of the main things we look into is whether a particular situation is A) well known enough, and B) has a connection to the psychological significance of the Warrens &#8217, active. &#8221,

&#8220, It was n&#8217, t up to us, &#8221, Farmiga information”. It’s a pretty interesting question to ask. It’s difficult with clues and all that, but it’s up to the authors to decide. A couple’s miscarriage had to be decided between life and death. The story of this includes life and death events, and this is the bloodiest beast they may include written that has a very private grudge. The authors had to craft it in a way that was authentic, emotional, and private. &#8221,

Wilson continues,” You know what it is too, Vera,” and says,” Right in terms of lost? Because if you’re structuring a movie, take ahead what’s real and what’s not, you want to find a low level for your personality, and a lot of times it’s impending death. But there’s such a loss of them trying to answer the question,” Are we losing a daughter?” &#8217, It&#8217, s like in every parental film with a girl that &#8217, s about to get married. Do you have a child but also lose your kid? A very life-changing horror is like that, and there are life-changing times in this movie right from the beginning. You never get over it, so you’re now giving them a sense of loss, so it’s all about wins and losses in this film. It’s not as cut and dry as it’s of, and this man will perish in this movie because we always have that in terms of spirits, but you always have that in terms of family here as well. ‘ &#8221, &nbsp,

Farmiga appears to agree with Farmiga.

” I think what’s unique about this, especially for Lorraine, is that Lorraine has always tried to protect Judy,” Farmiga says. She has always been covered in metaphysical bubble wrap to keep the noise out and the shadows at bay. But now it &#8217, s unique. She&#8217, s quite unique. &#8221,

Mia Tomlinson, who replaces Sterling Jerins and Mckenna Grace in the role of Judy, was given first-hand accounts of the paranormal minefields of &#8220 growing up as a Warren from the real Judy ( now Judy Spera ). &#8221,

&#8220, Judy &#8217, s very guarded, &#8221, Tomlinson explains. &#8220, She&#8217, s silent, she&#8217, s keeping it to herself. She&#8217 is attempting to keep it up, but it &#8217 is just like a soft, unraveling rope. I used Judy’s advice in the way that she uses the words &#8216, don’t look it in the eye, don’t give it reputation. &#8217, That&#8217, s how she approached Annabelle. Because I am a very ambitious man, I used it as a mantra on the set to keep me grounded. You &#8217, ve got to get. There is a way to balance Judy’s real life and Judy’s in this picture, and we are sort of playing in there. &#8221,

The players even have the opportunity to explore more profound universal truths that come with being a family or child as a result of the blurring between fact and fiction.

There is that paternal damage when your infants grow up, Farmiga says. You raised them to become independent, but now she is and you are, and she has a head of her own. Judy was kept in &#8216, flight mode for a while, and now the child has moral WiFi, thanks to Lorrainee’s efforts. She desires to receive that message. That&#8217 is how Lorraine described it to me. She thought of it as a message in particular. Judy was kept in the safe area by Lorraine for a long time, and this one’s plot is quite different from hers. She is aware of how exhausting pressing into the other side may actually be. &#8221,

To his credit, director Michael Chaves ( who is currently working on a Conjuring Universe movie for his fourth go-round ) keeps all the demonic sturm und drang atop Judy’s and her engagement to Tony Spera ( played by Ben Hardy ) as a secondary focus. The camera at the center of the disturbing has an even greater power than the wicked mirror that has impacted Ed and Lorraine. &nbsp,

Chaves continues,” I am so proud of the personality work in it and the figure account that we tell.” For Ed and Lorraine, I believe that’s the real reason people keep returning to this company. It&#8217 ;s for the incredible characters that Patrick and Vera have made. In any excellent collection, you’re returning to this. You’re returning to the figures so that you can follow them on this crucial stage of their journey.

It would be fascinating to observe Judy and Tony take center stage in a subsequent installment as Ed and Lorraine’s story is apparently coming to an end in The Conjuring: Next Ceremonies. &nbsp,

&#8220, I&#8217, d like that, I&#8217, m certain, &#8221, admits Tomlinson. &#8220, You would as well, Ben, best? We would really like to collaborate and carry the torch!

&#8220, Sure, yeah, pass us the earth, &#8221, Ben Hardy laughs. &#8220, They also run the household company, as far as I&#8217, m aware, but yeah. Who is aware? &#8221,

&#8220, Fingers crossed, &#8221, adds Tomlinson. &nbsp,

On Friday, September 5, The Conjuring: Last Rites will be available in theaters everyday.

The Conjuring: Next Customs Stars on Fact vs. Fiction in Warrens &#8217, Next Case appeared initially on Den of Geek.

The “final” picture in the Conjuring Universe, The Conjuring: Next Customs, will be released this week ( or so they say ). There are life and death bets for the fictionalized types of paranormal researchers Ed and Lorraine Warren, who are portrayed onscreen by Vera Farmiga and Patrick Wilson in all four of the major Conjuring shows. Given ]… ]

The Conjuring: Last Customs Actors on Fact vs. Fiction in Warrens ‘ Last Case first appeared on Den of Geek.

The Conjuring: Next Rites, the Conjuring: Final, and Final, respectively, movie, is due out this week in the Conjuring Universe. There are life and death bets for the fictionalized types of paranormal researchers Ed and Lorraine Warren, who are portrayed onscreen by Vera Farmiga and Patrick Wilson in all four of the major Conjuring shows. It was never likely that brand stewards James Wan or Michael Chaves would succumb to Tarantino-esque traditional trickery where Ed is killed by a beast and dragged to heaven because Judy Warren and the late Lorraine Warren were involved in the Conjuring Universe movies. The Labyrinths are known to have been successful in every case.

Despite this, we asked star Farmiga and Wilson how they keep pulling off the magic trick of involving the audience in the Warrens &#8217, fate in these high-tension horror stories.

&#8220, It&#8217, s a great topic, &#8221, Wilson says. &#8220, They both went on. After that, Lorraine and Ed had about 30 times. How do you draw the audience in, I don’t understand? I believe that there is always life and death for individuals and that there is also life and death for them. We had done a lot of work on Ed’s heart harm, particularly with him. I was quite aware that “men, we can’t keep going up to the well on that.” &#8217, It&#8217, s got to be innovative. We need a fresh monster, to be feign. &#8221,

Choose which real-life haunting case the Warrens investigated, according to line producer and author James Wan, is the key to piqueing viewers ‘ and series’s rooting interest with each film in the series. This meant tying in the death of the Warrens ‘ individual child, Judy, with the death of the Smurl home, a new bedeviled set of characters whose situation is the center of the movie. In the beginning scene of the movie, their baby almost passes away in the infant’s death, and two decades later, along with her own impending marriage, she becomes a part of the Smurl investigation.

According to Thin,” One of the major factors we look into is if a particular event is A) also known plenty, and B) if it ties in with the personal account of what we want to show with the Warrens &#8217, powerful.” &#8221,

&#8220, It was n&#8217, t up to us, &#8221, Farmiga information”. It’s a pretty interesting question to ask. It&#8217 is difficult with clues and all that, but it is up to the authors to decide. A couple’s miscarriage had to be decided between life and death. The story of this includes both life and death, and this is the bloodiest beast they could include written that has a very private grudge. The authors had to craft it in a way that was authentic, emotional, and private. &#8221,

Wilson continues,” You know what it is too, Vera,” and says,” Right in terms of lost? Because of the nature of rearranging a movie, you want to find a lower level for your personality, and a lot of times it means dying, take away what is real and what is not. But there’s such a loss of them trying to answer the question,” Are we losing a daughter?” &#8217, It&#8217, s like in every parental film with a girl that &#8217, s about to get married. Do you have a child but also lose your kid? A very life-changing drama is like that, and there are some life-changing times in this movie right away. You always get over it, so you’re now giving them a sense of loss, so in this movie it’s all about wins and losses. It’s not as cut and dry as it’s of, and this guy will perish in this movie because we always have that in terms of spirits, but you always have that in terms of family here as well. ‘ &#8221, &nbsp,

Farmiga did appear to concur.

” I think what’s unique about this, especially for Lorraine, is that Lorraine has always tried to protect Judy,” Farmiga says. She has always been covered in metaphysical bubble wrap to keep the noise out and the shadows at bay. But now it &#8217, s unique. She&#8217, s quite unique. &#8221,

Mia Tomlinson, who replaces Sterling Jerins and Mckenna Grace in the role of Judy, was given first-hand accounts of the paranormal minefields of &#8220 growing up as a Warren from the real Judy ( now Judy Spera ). &#8221,

&#8220, Judy &#8217, s very guarded, &#8221, Tomlinson explains. &#8220, She&#8217, s calm, she&#8217, s keeping it to herself. She is attempting to keep it up, but it is like a soft, unraveling rope. I applied Judy’s advice in the way that she uses the words “don’t look it in the eye, don’t give it reputation,” or “don’t look it in the eye.” &#8217, That&#8217, s how she approached Annabelle. Because I am a very ambitious man, I used it as a slogan on set to keep me grounded. You &#8217, ve got to get. There is a way to balance Judy’s real life and Judy’s in this picture, and we are kind of playing in there. &#8221,

The players even have the opportunity to explore more profound universal truths that come with being a family or child as a result of the blurring between fact and fiction.

There is that paternal reduction when your infants grow up, Farmiga says. You raised them to become independent, but now she is and you are, and she has a head of her own. Judy has long been in religious WiFi thanks to Lorrainee’s efforts to keep the child in &#8216, flight mode&#8217. She desires to receive that sign. That&#8217 is how Lorraine described it to me. She thought it was a sign in a way. Judy was kept in the secure zone by Lorraine for a long time, and this one’s plot is quite different from hers. She is aware of how exhausting pressing into the other side may actually be. &#8221,

To his credit, director Michael Chaves ( in his fourth go-round producing a Conjuring Universe movie ) consistently places all the demonic sturm und drang in the background of Judy’s and her engagement to Tony Spera ( played by Ben Hardy ). The haunting’s wicked mirror is just as effective as Ed and Lorraine’s. &nbsp,

Chaves continues,” I am so glad of all the character work in it and the figure account that we tell.” I believe that is the real reason folks keep returning to this series in favor of Ed and Lorraine. It&#8217 ;s for the incredible characters that Patrick and Vera have made. In any excellent set, you’re returning to what you’re doing. You’re returning to the figures so that you can follow them on this crucial stage of their journey.

It would be fascinating to observe Judy and Tony take center stage in a subsequent installment as Ed and Lorraine’s story is apparently coming to an end in The Conjuring: Next Ceremonies. &nbsp,

&#8220, I&#8217, d like that, I&#8217, m certain, &#8221, admits Tomlinson. &#8220, You would as well, Ben, straight? We would really like to collaborate and carry the torch!

&#8220, Sure, yeah, move us the earth, &#8221, Ben Hardy laughs. &#8220, They also run the household company, as far as I&#8217, m aware, but yeah. Who is aware? &#8221,

&#8220, Fingers crossed, &#8221, adds Tomlinson. &nbsp,

On Friday, September 5, The Conjuring: Last Rites will be available in theaters outside.

The Conjuring: Last Rites Stars on Fact vs. Fiction in Warrens &#8217, Last Case appeared first on Den of Geek.

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.

” Any post” you might have? is perhaps one of the worst ways to ask for suggestions. It’s obscure and unreliable, and it doesn’t give a clear picture of what we’re looking for. Getting good opinions starts sooner than we might hope: it starts with the demand.

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

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

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

The query

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

But how do we get into this scenario? A number of elements are involved. One is that we don’t often consider asking as a part of the input approach. Another is how healthy it is to leave the question open and assume that everyone else will agree. Another is that in nonprofessional debate, there’s usually no need to be that exact. In summary, we tend to undervalue the value of the issues, and we don’t work to improve them.

The work of asking good questions guidelines and focuses the criticism. It’s even a form of acceptance because it specifies what kind of comments you’d like to receive and how you’re open to them. It puts people in the right emotional state, especially in situations when they weren’t expecting to give opinions.

There isn’t a second best way to ask for opinions. It simply needs to be certain, and precision may take several shapes. The stage than depth model for design critique has been a particularly helpful tool for my coaching.

” Stage” refers to each of the steps of the process—in our event, the design process. 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 translation of the amassed feedback into updated designs as the project has evolved. The layers of user experience could serve as a starting point for future inquiries. What do you want to know: Project objectives? User requirements? Functionality? the content Interaction design? Information architecture UI design? navigation planning Visual design? branding?

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

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

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

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

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

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

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

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 visible part of the design work, and they provide 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. In addition, these kinds of design tools automatically update shared UI components, make conversations disappear and require designs 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 approach to design critiques is probably not the best approach, but some teams might benefit from it even if I don’t want to be too prescriptive.

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

Using iteration posts has a number of benefits:

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

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

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

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

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

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

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

Because it makes it easier to refer to the objects, it might also be helpful to have clear names on 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 an efficient discussion, you should also include a bullet list of the changes from the previous iteration to let people focus on what’s new, which can be especially useful for larger pieces of work where keeping track, iteration after iteration, could become a challenge.

Finally, as mentioned earlier, a list of the questions must be included in order to help you guide the design critique in the desired direction. Doing this as a numbered list can also help make it easier to refer to each question by its number.

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

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

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

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

The wording release candidate (RC ) could be used to 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 review

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

This shift has some significant advantages, making asynchronous feedback particularly effective, especially around these friction points:

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

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 just a few of them, it’s simple, and there isn’t much to worry about. But other times, some solutions might require more in-depth discussions, and the amount of replies can quickly increase, which can create a tension between trying to be a good team player by replying to everyone and doing the next design iteration. This might be especially true if the respondent is a stakeholder or a person who is directly involved in the project and whom we feel we need to speak with. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. 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. The response is received when the design changes and a follow-up iteration is made. You might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement.
• Another tactic is to formally acknowledge each comment in a brief response, such as” Understood. Thank you”,” Good points— I’ll review”, or” Thanks. These will be included in the upcoming iteration. In some cases, this could also be just a single top-level comment along the lines of” Thanks for all the feedback everyone—the next iteration is coming soon”!
• One more thing is to quickly summarize the comments before proceeding. Depending on your workflow, this can be particularly useful as it can provide a simplified checklist that you can then use for the next iteration.

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

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

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

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, presenting everything in aggregated form helps us to prioritize our work more.

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

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

Thanks to Mike Shelton and Brie Anne Demkiw for their contributions to the initial draft of this article.

Although I’m not certain when I first heard this statement, it has over the centuries stuck in my mind. How do you generate solutions for scenarios you can’t think? Or create products that are functional on products that have not yet been created?

Flash, Photoshop, and flexible pattern

When I first started designing sites, my go-to technology was Photoshop. I started by making a design for a 960px canvas that I would later add glad to. The growth phase was about attaining pixel-perfect precision using set widths, fixed levels, and absolute placement.

All of this was altered by Ethan Marcotte’s speak at An Event Apart and the subsequent article in A Checklist Off in 2010. I was sold on reactive style as soon as I heard about it, but I was even terrified. The pixel-perfect models full of special figures that I had formerly prided myself on producing were no longer good enough.

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

A new way to style

Making flexible or smooth websites has always been about removing restrictions and creating content that can be viewed on any system. It relies on the use of percentage-based design, which I immediately achieved with local CSS and power groups:

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

Therefore with Sass but that I could use @includes to re-use repeated blocks of code and transition to more semantic html:

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

Media concerns

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

Media concerns 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 little- to medium-sized companies, to larger in-house teams where I worked across a collection of related sites. In those positions, I began to work more frequently with washable parts.

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

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

Container queries: our savior or a false dawn?

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

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

In other words, responsive elements are meant to replace responsive layouts.

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

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

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

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

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

Without reliable cross-browser support for them, it’s difficult to say for certain whether container queries will be successful. Responsive component libraries would definitely evolve how we design and would improve the possibilities for reuse and design at scale. However, we might need to modify these elements in order to fit our content.

CSS is changing

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

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

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

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

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

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

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

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

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

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

Intrinsic layouts

I’d be remiss not to mention intrinsic layouts, a term used by Jen Simmons to describe a mix of contemporary and traditional CSS features to create layouts that respond to available space.

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

frunits is a statement that says,” I want you to distribute the extra space in this way, but… don’t ever make it smaller than the content that is inside of it.”

—Jen Simmons,” Designing Intrinsic Layouts”

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

What makes intrinsic design stand out is that it not only creates designs that can withstand future devices but also helps scale design without losing flexibility. Without having to have the same breakpoints or content as in the previous implementation, components and patterns can be removed and reused.

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

Another 2010 moment?

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

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

One possible explanation for that 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. Nowadays, projects use existing tools and frameworks and are often improvements to existing websites with an existing codebase.

Another possibility is that I’m now more prepared for change. In 2010 I was new to design in general, the shift was frightening and required a lot of learning. Additionally, an intrinsic approach isn’t exactly new; it’s a different way to use existing skills and CSS knowledge.

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

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

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

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

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

How do you do that now, with each component responding to content and layouts flexing as and when they need to? Personally, I’m a big fan of this kind of design in the browser.

The debate about “whether designers should code” is another that has rumbled on for years. When designing a digital product, we should, at the very least, design for a best- and worst-case scenario when it comes to content. It’s not ideal to do this in a graphics-based software package. In code, we can add longer sentences, more radio buttons, and extra tabs, and watch in real time as the design adapts. Still in use? Is the design too reliant on the current content?

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

Content should come first

Content is not constant. After all, to design for the unanticipated or unexpected, we must take into account changes in content, such as in our earlier Subgrid card illustration, which allowed the cards to make adjustments to both their own and 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. In the past, this was often achieved with Sass mixins but was often limited to switching from left-to-right to right-to-left orientation.

Directional variables must be set in the Sass version.

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

These variables can be used as values—

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

—or as real estate.

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

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

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

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

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

Fluid and fixed

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

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

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

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

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

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

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

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

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

This time, the element’s width will be 50 % of its container’s preferred value, with no exceptions for 300px and 600px.

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

First, the circumstances

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

Rather than someone using a mobile phone and moving through a crowded street in glaring sunshine, it’s a very different design to be done for someone using a desktop computer. Situations and environments are hard to plan for or predict because they change as people react to their own unique challenges and tasks.

Choice is so crucial because of this. One size never fits all, so we need to design for multiple scenarios to create equal experiences for all our users.

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

Responsible design

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

On a 50 MB budget, I spent a day surfing the web.

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. 

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

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

So how can we put users in control?

The media queries are now being returned.

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

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

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

For instance, a light-level option lets you alter a user’s style when they are in the dark or in the sun. Paired with custom properties, these features allow us to quickly create designs or themes for specific environments.

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

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

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

Expect the unexpected

In the end, we should always anticipate that things will change. Devices in particular change faster than we can keep up, with foldable screens already on the market.

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

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

When it comes to unexpected circumstances, we need to make sure our goods are 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.

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

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

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

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

Spoken language lacks this 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. Our spoken language conveys much more than the written word could ever contain, whether it be rapid-fire, low-pitched, or high-decibel, sarcastic, stilted, or sighing. So when it comes to voice interfaces—the machines we conduct spoken conversations with—we face exciting challenges as designers and content strategists.

Voice-to-text 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 ( ). We typically strike up a conversation as a result:

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

A single conversation from beginning to end that achieves some outcome for the user, starting with the voice interface’s first greeting and ending with the user exiting the interface, also fits into these three categories, which I refer to as transactional, informational, and prosocial. Note here that a conversation in our human sense—a chat between people that leads to some result and lasts an arbitrary length of time—could encompass multiple transactional, informational, and prosocial voice interactions in succession. In other words, a voice interaction is a conversation, but it must not be one particular voice interaction.

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

That leaves two different types of conversations we can have with one another that a voice interface can also have easily, such as one that focuses on a transactional voice interaction ( buying iced tea ) and another on learning something new ( discuss a musical ).

Transactional voice interactions

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

How are things going, Alison?

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

Alison, can I get a pineapple-onion pizza in Hawaii?

Burhan: Sure, what size?

Large, Alison.

Burhan: Anything else?

Alison: No, that’s it.

Burhan: Something to drink?

Alison: I’ll have a bottle of Coke.

Burhan: You got it. That will cost$ 13.55 and take 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 exhibit a few key characteristics: they’re direct, to the point, and economical. They quickly dispense with pleasantries.

Informational voice interactions

Meanwhile, some conversations are primarily about obtaining information. Alison might visit Crust Deluxe with the sole intention of placing an order, but she might not want to leave with a pizza at all. She might be just as interested in whether they serve halal or kosher dishes, gluten-free options, or something else. Even though we have a prosocial mini-conversation once more at the beginning to practice politeness, we are after much more.

How are things going, Alison?

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

Alison: Can I ask a few questions?

Burhan: Of course! Go right ahead.

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

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

Alison: What about gluten-free pizzas?

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

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

Burhan: Anytime, come back soon!

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

Voice Interfaces

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

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

IVR ( interactive voice response ) systems

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

IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. These systems, which are commonplace in the corporate world, were primarily intended as metaphorical switchboards to direct customers to real phone agents (” Say Reservations to book a flight or check an itinerary” ), and it is likely that when you call an airline or hotel conglomerate, you will have the opportunity to have a conversation with one. Despite their functional issues and users ‘ frustration with their inability to speak to an actual human right away, IVR systems proliferated in the early 1990s across a variety of industries (, PDF).

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

Screen readers

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

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

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

There is a big draw for screen readers: they’re challenging to use and relentlessly verbose, despite being incredibly instructive for voice interface designers. The visual structures of websites and web navigation don’t translate well to screen readers, sometimes resulting in unwieldy pronouncements that name every manipulable HTML element and announce every formatting change. Working with web-based interfaces takes a cognitive toll for many screen reader users.

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

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

In many cases, well-designed voice interfaces can speed users to their destination better than long-winded screen reader monologues. After all, users of the visual interface have the advantage of freely scurrying around the viewport to find information without getting too close to it. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Users with disabilities who have long had no choice but to use clumsy screen readers might find that voice interfaces, especially more contemporary voice assistants, provide a more streamlined experience.

Voice assistants

Many of us immediately associate voice assistants with the popular subset of voice interfaces found in living rooms, smart homes, and offices with the film A Space Odyssey or with Majel Barrett’s voice as the omniscient computer from 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 because of their assistive potential, they are quickly receiving more attention from accessibility advocates.

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

There are a lot of variations in the programmability and customization of some voice assistants compared to others ( Fig. 1 ). As a result of the breadth of voice assistants available today ( Fig. 1 ). At one extreme, everything except vendor-provided features is locked down, for example, at the time of their release, the core functionality of Apple’s Siri and Microsoft’s Cortana couldn’t be extended beyond their existing capabilities. There are no other means by which developers can interact with Siri at a low level, aside from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and other things, which are still unavoidable today.

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

As businesses like Amazon, Apple, Microsoft, and Google continue to occupy their positions, they’re also selling and open-sourcing an unheard array of tools and frameworks for designers and developers that aim to make creating voice interfaces as simple as possible, even without code.

Often by necessity, voice assistants like Amazon Alexa tend to be monochannel—they’re tightly coupled to a device and can’t be accessed on a computer or smartphone instead. In contrast, many development platforms, such as Google’s Dialogflow, have omnichannel capabilities that allow users to create 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. Voice content must be free-flowing, organic, contextless, and concise in order to preserve what makes human conversation so compelling in the first place.

Our world is replete with voice content in various forms: screen readers reciting website content, voice assistants rattling off a weather forecast, and automated phone hotline responses governed by IVR systems. We’re most concerned with the audiobook content being delivered as a requirement rather than an option.

For many of us, our first foray into informational voice interfaces will be to deliver content to users. One issue is that any content we already have isn’t in any way suitable for this new environment. So how do we make the content trapped on our websites more conversational? And how do we create fresh copy that works with voice movements?

Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many ways, colossal vaults of what I call macrocontent: lengthy prose that can last for 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:

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

I would update Dash’s definition of microcontent to include all instances of bite-sized content that transcends written communiqués. After all, today we encounter microcontent in interfaces where a small snippet of copy is displayed alone, unmoored from the browser, like a textbot confirmation of a restaurant reservation. The best way to learn how your content can be stretched to the limits of its potential is through microcontent, which will inform both established and new delivery channels.

As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can instantly see when the next train is coming from a digital sign underground, but voice interfaces keep our attention occupied for so long that screen reader users are all too familiar.

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, how voice content manifests in perceived time and space both affect the legibility and discoverability of our voice content.

In the 1950s, some members of the wealthy running group had come to accept the idea that it was impossible to run a hour in less than four hours. 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 people 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 then knew that the four-minute hour was possible 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, a year later, three runners all managed to cross the four-minute challenge in the same competition. 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 accomplish a lot more when we think something is possible, and we only think it can be done when we see someone else doing it after all. As for human running speed, we also think there are the strictest requirements for how a website should do.

Establishing requirements for a green website

The key environmental performance indicators for the majority of major industries are pretty 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. However, in the world of websites and apps, we aren’t held to any specific environmental standards, and we have only recently developed the tools and methods we need to also conduct an environmental assessment.

The main objective in green web layout is to reduce carbon emissions. However, it’s nearly impossible to accurately assess the CO₂ output of a online product. We didn’t measure the pollutants coming out of the exhaust valves on our laptops. The pollution coming from power plants that burn coal and oil are considerably away, out of sight, and out of mind. 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. So what do we accomplish then?

If we can‘t measure the actual carbon pollution, therefore we need to get what we can measure. The following are the main elements that could be used as coal pollution gauges:

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 carbon 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 the majority of technologies, including the web’s underlying technology 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 vague suggestions, much like speed limits while driving, so the goal should always be to come in 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 often depends more on the user’s perception of load times than it does on how effective the underlying system is.

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 competitor page weights and the website’s current layout to compare it to. 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 will likely have a high percentage of the files cached in their browser, which means they won’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, 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” (gCO₂/k Wh ) is used to describe how much carbon dioxide is produced for each kilowatt-hour of electricity ). 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 energy from a variety of sources is combined with various levels of carbon intensity. The distributed nature of the internet means that a single user of a website or app might be using energy from multiple different grids simultaneously, a website user in Paris uses electricity from the French national grid to power their home internet and devices, but the website’s data center could be in Dallas, USA, pulling electricity from the Texas grid, while the telecoms networks use energy from everywhere between Dallas and Paris.

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. Danish startup Tomorrow reports and maps the user-provided data, and a look at their map demonstrates how, for instance, choosing a data center in France will have 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 a lot of energy to transmit data through the telecom’s networks, and the more energy is used, the further the data travels. 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 between that location and the data center that our hosting company uses 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. The method my team developed converts the amount of electricity transferred when loading a web page into a CO₂ figure ( Fig. ₂.4), and then converts that data into a figure for the tool. 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 one step further and tailor the data more precisely to the unique aspects of your project.

We could even expand our page weight budget by establishing carbon budgets as well with the ability to calculate carbon emissions for our projects. 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 smart TVs, tablets, laptops, phones, tablets, laptops, or other front-end web technologies. 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 either 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 know what happens when your computer’s cooling fans start spinning so frantically that you suspect 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 how much CPU is used and how long it takes to load the web page. 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.

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

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

The process for inclusive safety

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

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

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

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

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

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

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

Step 1: Conduct research

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

Broad research

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

Specific research: Survivors

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

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

Specific research: Abusers

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

Step 2: Create archetypes

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

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

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

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

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

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

Step 3: Brainstorm problems

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

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

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

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

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

Step 4: Design solutions

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

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

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

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

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

Step 5: Test for safety

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

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

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

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

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

Abuser testing

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

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

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

Survivor testing

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

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

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

Stress testing

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

However, how can a content management system ( CMS ) be set up to reach your audience both now and in the future? 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 content versions that are semantic and even join related content, you can avoid that result.

A Fortune 500 company recently tapped me to guide the CMS application. 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.

For our information to be understood by many systems, the unit needed semantic types, which are names given based on their meaning rather than their presentation. This is crucial for an multichannel content strategy. Our aim was to allow writers to produce original content and use it where necessary. But as the job proceeded, I realized that supporting material utilize at the range that my client needed required the whole group to identify a new pattern.

Despite our best efforts, we remained influenced by what we were more familiar with: design systems. An omnichannel content strategy cannot rely on WYSIWYG design and layout tools, unlike web-focused content strategies. Our tendency to approach the content model with our familiar design-system thinking constantly led us to veer away from one of the primary purposes of a content model: delivering content to audiences on multiple marketing channels.

Two fundamental tenets are necessary for a successful content model

We had to explain to our designers, developers, and stakeholders that their previous web projects had taught them that content should be treated as visual building blocks that fit into layouts. The previous approach was not only more familiar but also more intuitive—at least at first—because it made the designs feel more tangible. We discovered two guiding principles that helped the team understand how a content model and the design processes we were familiar with were:

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

Semantic content models

A semantic content model uses type and attribute names that reflect the content’s intended purpose and not how it will be displayed. For example, in a nonsemantic model, teams might create types like teasers, media blocks, and cards. These types may make it simple to present content, but they do not aid in understanding the meaning of the content, which would have opened the door to the content presented in each marketing channel. In contrast, a semantic content model employs type names like product, service, and testimonial to allow for each delivery channel to interpret the content and use it as necessary.

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

A semantic content model has a number of advantages:

Even if your team doesn’t care about omnichannel content, a semantic content model decouples content from its presentation so that teams can evolve the website’s design without needing to refactor its content. In this way, content can withstand irrational website redesigns.
• A competitive advantage can also be gained by a semantic content model. By adding structured data based on Schema. Using its 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 respond to voice-interface user questions. Potential visitors could access your content without ever walking into your website.
• Beyond those practical benefits, you’ll also need a semantic content model if you want to deliver omnichannel content. Delivery channels must be able to understand 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 used as a voice interface or by a bot to answer frequently asked questions ( FAQ ) pages.

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 ). A good content model connects content that should remain together so that multiple delivery channels can use it without needing to first put those pieces back together.

Consider creating an essay or article. The meaning and usefulness of an article depend on how well its components are kept together. Would one of the headings or paragraphs be meaningful on their own without the context of the full article? 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. This had a similar effect to an article that had its headline removed. Because we were slicing content into standalone pieces based on layout, content that belonged together became difficult to manage and nearly impossible for multiple delivery channels to understand.

Let’s take a look at how connecting related content works in a real-world setting to illustrate. 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 suit with the content model. Shouldn’t we make adding any number of tabs in the future as simple and flexible as possible?

We felt like we needed a content type called “tab section” because our design-system instincts were so well-known, so that multiple tab sections could be added to a page. Each tab section would display various types of content. The software’s overview or specifications might be available in one tab. A second tab might provide a list of sources.

Our inclination to break down the content model into “tab section” pieces would have led to an unnecessarily complex model and a cumbersome editing experience, and it would have also created content that couldn’t have been understood by additional delivery channels. 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. Furthermore, if the customer were to have no longer wanted to display this content in a tab layout, it would have been tedious to migrate to a new content model to reflect the new page redesign.

Our customer had a breakthrough when we realized that for each tab, their customer had a specific purpose in mind: it would reveal specific information like the software product’s overview, specifications, related resources, and pricing. Once implementation began, our inclination to focus on what’s visual and familiar had obscured the intent of the designs. It wasn’t long after a little digging that it became clear that the idea of tabs wasn’t applicable 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 decided to display this content in a different way—without tabs—somewhere else. Based on the meaningful attributes the customer had desired to display on the web, we created content types for the software product. There were both obvious semantic attributes like name and description and rich ones 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. This content could be understood and presented by any delivery channel, including those that come up in the future.

Conclusion

In this omnichannel marketing project, we discovered that the best way to keep our content model on track was to ensure that it was semantic ( with type and attribute names that reflected the meaning of the content ) and that it kept content together that belonged together ( instead of fragmenting it ). These two 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 Google and other interfaces understand your content, remember:

• 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 drawn to conflate them and force your content model to resemble your design system. This will enable each delivery channel to consume the content without the need for a magic decoder ring.
• If your team is struggling to make this transition, you can still reap some of the benefits by using Schema. Your website uses structured data from org. The advantage of search engine optimization is a compelling argument on its own, even if additional delivery channels are not in the works.
• Additionally, remind the team that decoupling the content model from the design will let them update the designs more easily because they won’t be held back by the cost of content migrations. They will be prepared for the upcoming big thing, and they will be able to create new designs without compromising compatibility between the design and the content.

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.