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In reading Joe Dolson’s recent piece on the intersection of AI and accessibility, I absolutely appreciated the skepticism that he has for AI in general as well as for the ways that many have been using it. In fact, I’m very skeptical of AI myself, despite my role at Microsoft as an accessibility innovation strategist who helps run the AI for Accessibility grant program. As with any tool, AI can be used in very constructive, inclusive, and accessible ways; and it can also be used in destructive, exclusive, and harmful ones. And there are a ton of uses somewhere in the mediocre middle as well.

I’d like you to consider this a “yes… and” piece to complement Joe’s post. I’m not trying to refute any of what he’s saying but rather provide some visibility to projects and opportunities where AI can make meaningful differences for people with disabilities. To be clear, I’m not saying that there aren’t real risks or pressing issues with AI that need to be addressed—there are, and we’ve needed to address them, like, yesterday—but I want to take a little time to talk about what’s possible in hopes that we’ll get there one day.

Alternative text

Joe’s piece spends a lot of time talking about computer-vision models generating alternative text. He highlights a ton of valid issues with the current state of things. And while computer-vision models continue to improve in the quality and richness of detail in their descriptions, their results aren’t great. As he rightly points out, the current state of image analysis is pretty poor—especially for certain image types—in large part because current AI systems examine images in isolation rather than within the contexts that they’re in (which is a consequence of having separate “foundation” models for text analysis and image analysis). Today’s models aren’t trained to distinguish between images that are contextually relevant (that should probably have descriptions) and those that are purely decorative (which might not need a description) either. Still, I still think there’s potential in this space.

As Joe mentions, human-in-the-loop authoring of alt text should absolutely be a thing. And if AI can pop in to offer a starting point for alt text—even if that starting point might be a prompt saying What is this BS? That’s not right at all… Let me try to offer a starting point—I think that’s a win.

Taking things a step further, if we can specifically train a model to analyze image usage in context, it could help us more quickly identify which images are likely to be decorative and which ones likely require a description. That will help reinforce which contexts call for image descriptions and it’ll improve authors’ efficiency toward making their pages more accessible.

While complex images—like graphs and charts—are challenging to describe in any sort of succinct way (even for humans), the image example shared in the GPT4 announcement points to an interesting opportunity as well. Let’s suppose that you came across a chart whose description was simply the title of the chart and the kind of visualization it was, such as: Pie chart comparing smartphone usage to feature phone usage among US households making under $30,000 a year. (That would be a pretty awful alt text for a chart since that would tend to leave many questions about the data unanswered, but then again, let’s suppose that that was the description that was in place.) If your browser knew that that image was a pie chart (because an onboard model concluded this), imagine a world where users could ask questions like these about the graphic:

• Do more people use smartphones or feature phones?
• How many more?
• Is there a group of people that don’t fall into either of these buckets?
• How many is that?

Setting aside the realities of large language model (LLM) hallucinations—where a model just makes up plausible-sounding “facts”—for a moment, the opportunity to learn more about images and data in this way could be revolutionary for blind and low-vision folks as well as for people with various forms of color blindness, cognitive disabilities, and so on. It could also be useful in educational contexts to help people who can see these charts, as is, to understand the data in the charts.

Taking things a step further: What if you could ask your browser to simplify a complex chart? What if you could ask it to isolate a single line on a line graph? What if you could ask your browser to transpose the colors of the different lines to work better for form of color blindness you have? What if you could ask it to swap colors for patterns? Given these tools’ chat-based interfaces and our existing ability to manipulate images in today’s AI tools, that seems like a possibility.

Now imagine a purpose-built model that could extract the information from that chart and convert it to another format. For example, perhaps it could turn that pie chart (or better yet, a series of pie charts) into more accessible (and useful) formats, like spreadsheets. That would be amazing!

Matching algorithms

Safiya Umoja Noble absolutely hit the nail on the head when she titled her book Algorithms of Oppression. While her book was focused on the ways that search engines reinforce racism, I think that it’s equally true that all computer models have the potential to amplify conflict, bias, and intolerance. Whether it’s Twitter always showing you the latest tweet from a bored billionaire, YouTube sending us into a Q-hole, or Instagram warping our ideas of what natural bodies look like, we know that poorly authored and maintained algorithms are incredibly harmful. A lot of this stems from a lack of diversity among the people who shape and build them. When these platforms are built with inclusively baked in, however, there’s real potential for algorithm development to help people with disabilities.

Take Mentra, for example. They are an employment network for neurodivergent people. They use an algorithm to match job seekers with potential employers based on over 75 data points. On the job-seeker side of things, it considers each candidate’s strengths, their necessary and preferred workplace accommodations, environmental sensitivities, and so on. On the employer side, it considers each work environment, communication factors related to each job, and the like. As a company run by neurodivergent folks, Mentra made the decision to flip the script when it came to typical employment sites. They use their algorithm to propose available candidates to companies, who can then connect with job seekers that they are interested in; reducing the emotional and physical labor on the job-seeker side of things.

When more people with disabilities are involved in the creation of algorithms, that can reduce the chances that these algorithms will inflict harm on their communities. That’s why diverse teams are so important.

Imagine that a social media company’s recommendation engine was tuned to analyze who you’re following and if it was tuned to prioritize follow recommendations for people who talked about similar things but who were different in some key ways from your existing sphere of influence. For example, if you were to follow a bunch of nondisabled white male academics who talk about AI, it could suggest that you follow academics who are disabled or aren’t white or aren’t male who also talk about AI. If you took its recommendations, perhaps you’d get a more holistic and nuanced understanding of what’s happening in the AI field. These same systems should also use their understanding of biases about particular communities—including, for instance, the disability community—to make sure that they aren’t recommending any of their users follow accounts that perpetuate biases against (or, worse, spewing hate toward) those groups.

Other ways that AI can helps people with disabilities

If I weren’t trying to put this together between other tasks, I’m sure that I could go on and on, providing all kinds of examples of how AI could be used to help people with disabilities, but I’m going to make this last section into a bit of a lightning round. In no particular order:

• Voice preservation. You may have seen the VALL-E paper or Apple’s Global Accessibility Awareness Day announcement or you may be familiar with the voice-preservation offerings from Microsoft, Acapela, or others. It’s possible to train an AI model to replicate your voice, which can be a tremendous boon for people who have ALS (Lou Gehrig’s disease) or motor-neuron disease or other medical conditions that can lead to an inability to talk. This is, of course, the same tech that can also be used to create audio deepfakes, so it’s something that we need to approach responsibly, but the tech has truly transformative potential.
• Voice recognition. Researchers like those in the Speech Accessibility Project are paying people with disabilities for their help in collecting recordings of people with atypical speech. As I type, they are actively recruiting people with Parkinson’s and related conditions, and they have plans to expand this to other conditions as the project progresses. This research will result in more inclusive data sets that will let more people with disabilities use voice assistants, dictation software, and voice-response services as well as control their computers and other devices more easily, using only their voice.
• Text transformation. The current generation of LLMs is quite capable of adjusting existing text content without injecting hallucinations. This is hugely empowering for people with cognitive disabilities who may benefit from text summaries or simplified versions of text or even text that’s prepped for Bionic Reading.

The importance of diverse teams and data

We need to recognize that our differences matter. Our lived experiences are influenced by the intersections of the identities that we exist in. These lived experiences—with all their complexities (and joys and pain)—are valuable inputs to the software, services, and societies that we shape. Our differences need to be represented in the data that we use to train new models, and the folks who contribute that valuable information need to be compensated for sharing it with us. Inclusive data sets yield more robust models that foster more equitable outcomes.

Want a model that doesn’t demean or patronize or objectify people with disabilities? Make sure that you have content about disabilities that’s authored by people with a range of disabilities, and make sure that that’s well represented in the training data.

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

Want a coding copilot that gives you accessible recommendations from the jump? Train it on code that you know to be accessible.

I have no doubt that AI can and will harm people… today, tomorrow, and well into the future. But I also believe that we can acknowledge that and, with an eye towards accessibility (and, more broadly, inclusion), make thoughtful, considerate, and intentional changes in our approaches to AI that will reduce harm over time as well. Today, tomorrow, and well into the future.

Many thanks to Kartik Sawhney for helping me with the development of this piece, Ashley Bischoff for her invaluable editorial assistance, and, of course, Joe Dolson for the prompt.

I offer a single bit of advice to friends and family when they become new parents: When you start to think that you’ve got everything figured out, everything will change. Just as you start to get the hang of feedings, diapers, and regular naps, it’s time for solid food, potty training, and overnight sleeping. When you figure those out, it’s time for preschool and rare naps. The cycle goes on and on.

The same applies for those of us working in design and development these days. Having worked on the web for almost three decades at this point, I’ve seen the regular wax and wane of ideas, techniques, and technologies. Each time that we as developers and designers get into a regular rhythm, some new idea or technology comes along to shake things up and remake our world.

How we got here

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

The birth of web standards

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

Server-side languages like PHP, Java, and .NET overtook Perl as the predominant back-end processors, and the cgi-bin was tossed in the trash bin. With these better server-side tools came the first era of web applications, starting with content-management systems (particularly in the blogging space with tools like Blogger, Grey Matter, Movable Type, and WordPress). In the mid-2000s, AJAX opened doors for asynchronous interaction between the front end and back end. Suddenly, pages could update their content without needing to reload. A crop of JavaScript frameworks like Prototype, YUI, and jQuery arose to help developers build more reliable client-side interaction across browsers that had wildly varying levels of standards support. Techniques like image replacement let crafty designers and developers display fonts of their choosing. And technologies like Flash made it possible to add animations, games, and even more interactivity.

These new technologies, standards, and techniques reinvigorated the industry in many ways. Web design flourished as designers and developers explored more diverse styles and layouts. But we still relied on tons of hacks. Early CSS was a huge improvement over table-based layouts when it came to basic layout and text styling, but its limitations at the time meant that designers and developers still relied heavily on images for complex shapes (such as rounded or angled corners) and tiled backgrounds for the appearance of full-length columns (among other hacks). Complicated layouts required all manner of nested floats or absolute positioning (or both). Flash and image replacement for custom fonts was a great start toward varying the typefaces from the big five, but both hacks introduced accessibility and performance problems. And JavaScript libraries made it easy for anyone to add a dash of interaction to pages, although at the cost of doubling or even quadrupling the download size of simple websites.

The web as software platform

The symbiosis between the front end and back end continued to improve, and that led to the current era of modern web applications. Between expanded server-side programming languages (which kept growing to include Ruby, Python, Go, and others) and newer front-end tools like React, Vue, and Angular, we could build fully capable software on the web. Alongside these tools came others, including collaborative version control, build automation, and shared package libraries. What was once primarily an environment for linked documents became a realm of infinite possibilities.

At the same time, mobile devices became more capable, and they gave us internet access in our pockets. Mobile apps and responsive design opened up opportunities for new interactions anywhere and any time.

This combination of capable mobile devices and powerful development tools contributed to the waxing of social media and other centralized tools for people to connect and consume. As it became easier and more common to connect with others directly on Twitter, Facebook, and even Slack, the desire for hosted personal sites waned. Social media offered connections on a global scale, with both the good and bad that that entails.

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

Where we are now

In the last couple of years, it’s felt like we’ve begun to reach another major inflection point. As social-media platforms fracture and wane, there’s been a growing interest in owning our own content again. There are many different ways to make a website, from the tried-and-true classic of hosting plain HTML files to static site generators to content management systems of all flavors. The fracturing of social media also comes with a cost: we lose crucial infrastructure for discovery and connection. Webmentions, RSS, ActivityPub, and other tools of the IndieWeb can help with this, but they’re still relatively underimplemented and hard to use for the less nerdy. We can build amazing personal websites and add to them regularly, but without discovery and connection, it can sometimes feel like we may as well be shouting into the void.

Browser support for CSS, JavaScript, and other standards like web components has accelerated, especially through efforts like Interop. New technologies gain support across the board in a fraction of the time that they used to. I often learn about a new feature and check its browser support only to find that its coverage is already above 80 percent. Nowadays, the barrier to using newer techniques often isn’t browser support but simply the limits of how quickly designers and developers can learn what’s available and how to adopt it.

Today, with a few commands and a couple of lines of code, we can prototype almost any idea. All the tools that we now have available make it easier than ever to start something new. But the upfront cost that these frameworks may save in initial delivery eventually comes due as upgrading and maintaining them becomes a part of our technical debt.

If we rely on third-party frameworks, adopting new standards can sometimes take longer since we may have to wait for those frameworks to adopt those standards. These frameworks—which used to let us adopt new techniques sooner—have now become hindrances instead. These same frameworks often come with performance costs too, forcing users to wait for scripts to load before they can read or interact with pages. And when scripts fail (whether through poor code, network issues, or other environmental factors), there’s often no alternative, leaving users with blank or broken pages.

Where do we go from here?

Today’s hacks help to shape tomorrow’s standards. And there’s nothing inherently wrong with embracing hacks—for now—to move the present forward. Problems only arise when we’re unwilling to admit that they’re hacks or we hesitate to replace them. So what can we do to create the future we want for the web?

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

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

Design with care. Whether your craft is code, pixels, or processes, consider the impacts of each decision. The convenience of many a modern tool comes at the cost of not always understanding the underlying decisions that have led to its design and not always considering the impact that those decisions can have. Rather than rushing headlong to “move fast and break things,” use the time saved by modern tools to consider more carefully and design with deliberation.

Always be learning. If you’re always learning, you’re also growing. Sometimes it may be hard to pinpoint what’s worth learning and what’s just today’s hack. You might end up focusing on something that won’t matter next year, even if you were to focus solely on learning standards. (Remember XHTML?) But constant learning opens up new connections in your brain, and the hacks that you learn one day may help to inform different experiments another day.

Play, experiment, and be weird! This web that we’ve built is the ultimate experiment. It’s the single largest human endeavor in history, and yet each of us can create our own pocket within it. Be courageous and try new things. Build a playground for ideas. Make goofy experiments in your own mad science lab. Start your own small business. There has never been a more empowering place to be creative, take risks, and explore what we’re capable of.

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

Go forth and make

As designers and developers for the web (and beyond), we’re responsible for building the future every day, whether that may take the shape of personal websites, social media tools used by billions, or anything in between. Let’s imbue our values into the things that we create, and let’s make the web a better place for everyone. Create that thing that only you are uniquely qualified to make. Then share it, make it better, make it again, or make something new. Learn. Make. Share. Grow. Rinse and repeat. Every time you think that you’ve mastered the web, everything will change.

Picture this. You’ve joined a squad at your company that’s designing new product features with an emphasis on automation or AI. Or your company has just implemented a personalization engine. Either way, you’re designing with data. Now what? When it comes to designing for personalization, there are many cautionary tales, no overnight successes, and few guides for the perplexed. 

Between the fantasy of getting it right and the fear of it going wrong—like when we encounter “persofails” in the vein of a company repeatedly imploring everyday consumers to buy additional toilet seats—the personalization gap is real. It’s an especially confounding place to be a digital professional without a map, a compass, or a plan.

For those of you venturing into personalization, there’s no Lonely Planet and few tour guides because effective personalization is so specific to each organization’s talent, technology, and market position. 

But you can ensure that your team has packed its bags sensibly.

There’s a DIY formula to increase your chances for success. At minimum, you’ll defuse your boss’s irrational exuberance. Before the party you’ll need to effectively prepare.

We call it prepersonalization.

Behind the music

Consider Spotify’s DJ feature, which debuted this past year.

We’re used to seeing the polished final result of a personalization feature. Before the year-end award, the making-of backstory, or the behind-the-scenes victory lap, a personalized feature had to be conceived, budgeted, and prioritized. Before any personalization feature goes live in your product or service, it lives amid a backlog of worthy ideas for expressing customer experiences more dynamically.

So how do you know where to place your personalization bets? How do you design consistent interactions that won’t trip up users or—worse—breed mistrust? We’ve found that for many budgeted programs to justify their ongoing investments, they first needed one or more workshops to convene key stakeholders and internal customers of the technology. Make yours count.

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

Time and again, we’ve seen effective workshops separate future success stories from unsuccessful efforts, saving countless time, resources, and collective well-being in the process.

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

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

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

Set your kitchen timer

How long does it take to cook up a prepersonalization workshop? The surrounding assessment activities that we recommend including can (and often do) span weeks. For the core workshop, we recommend aiming for two to three days. Here’s a summary of our broader approach along with details on the essential first-day activities.

The full arc of the wider workshop is threefold:

1. Kickstart: This sets the terms of engagement as you focus on the opportunity as well as the readiness and drive of your team and your leadership. .
2. Plan your work: This is the heart of the card-based workshop activities where you specify a plan of attack and the scope of work.
3. Work your plan: This phase is all about creating a competitive environment for team participants to individually pitch their own pilots that each contain a proof-of-concept project, its business case, and its operating model.

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

Kickstart: Whet your appetite

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

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

This is all about setting the table. What are the possible paths for the practice in your organization? If you want a broader view, here’s a long-form primer and a strategic framework.

Assess each example that you discuss for its complexity and the level of effort that you estimate that it would take for your team to deliver that feature (or something similar). In our cards, we divide connected experiences into five levels: functions, features, experiences, complete products, and portfolios. Size your own build here. This will help to focus the conversation on the merits of ongoing investment as well as the gap between what you deliver today and what you want to deliver in the future.

Next, have your team plot each idea on the following 2×2 grid, which lays out the four enduring arguments for a personalized experience. This is critical because it emphasizes how personalization can not only help your external customers but also affect your own ways of working. It’s also a reminder (which is why we used the word argument earlier) of the broader effort beyond these tactical interventions.

Each team member should vote on where they see your product or service putting its emphasis. Naturally, you can’t prioritize all of them. The intention here is to flesh out how different departments may view their own upsides to the effort, which can vary from one to the next. Documenting your desired outcomes lets you know how the team internally aligns across representatives from different departments or functional areas.

The third and final kickstart activity is about naming your personalization gap. Is your customer journey well documented? Will data and privacy compliance be too big of a challenge? Do you have content metadata needs that you have to address? (We’re pretty sure that you do: it’s just a matter of recognizing the relative size of that need and its remedy.) In our cards, we’ve noted a number of program risks, including common team dispositions. Our Detractor card, for example, lists six stakeholder behaviors that hinder progress.

Effectively collaborating and managing expectations is critical to your success. Consider the potential barriers to your future progress. Press the participants to name specific steps to overcome or mitigate those barriers in your organization. As studies have shown, personalization efforts face many common barriers.

At this point, you’ve hopefully discussed sample interactions, emphasized a key area of benefit, and flagged key gaps? Good—you’re ready to continue.

Hit that test kitchen

Next, let’s look at what you’ll need to bring your personalization recipes to life. Personalization engines, which are robust software suites for automating and expressing dynamic content, can intimidate new customers. Their capabilities are sweeping and powerful, and they present broad options for how your organization can conduct its activities. This presents the question: Where do you begin when you’re configuring a connected experience?

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

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

The dishes will come from recipes, and those recipes have set ingredients.

Verify your ingredients

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

This isn’t just about discovering requirements. Documenting your personalizations as a series of if-then statements lets the team: 

1. compare findings toward a unified approach for developing features, not unlike when artists paint with the same palette; 
2. specify a consistent set of interactions that users find uniform or familiar; 
3. and develop parity across performance measurements and key performance indicators too. 

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

Compose your recipe

What ingredients are important to you? Think of a who-what-when-why construct: 

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

We first developed these cards and card categories five years ago. We regularly play-test their fit with conference audiences and clients. And we still encounter new possibilities. But they all follow an underlying who-what-when-why logic.

Here are three examples for a subscription-based reading app, which you can generally follow along with right to left in the cards in the accompanying photo below. 

1. Nurture personalization: When a guest or an unknown visitor interacts with  a product title, a banner or alert bar appears that makes it easier for them to encounter a related title they may want to read, saving them time.
2. Welcome automation: When there’s a newly registered user, an email is generated to call out the breadth of the content catalog and to make them a happier subscriber.
3. Winback automation: Before their subscription lapses or after a recent failed renewal, a user is sent an email that gives them a promotional offer to suggest that they reconsider renewing or to remind them to renew.

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

You can think of the later stages of the workshop as moving from recipes toward a cookbook in focus—like a more nuanced customer-journey mapping. Individual “cooks” will pitch their recipes to the team, using a common jobs-to-be-done format so that measurability and results are baked in, and from there, the resulting collection will be prioritized for finished design and delivery to production.

Better kitchens require better architecture

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

When personalization becomes a laugh line, it’s because a team is overfitting: they aren’t designing with their best data. Like a sparse pantry, every organization has metadata debt to go along with its technical debt, and this creates a drag on personalization effectiveness. Your AI’s output quality, for example, is indeed limited by your IA. Spotify’s poster-child prowess today was unfathomable before they acquired a seemingly modest metadata startup that now powers its underlying information architecture.

You can definitely stand the heat…

Personalization technology opens a doorway into a confounding ocean of possible designs. Only a disciplined and highly collaborative approach will bring about the necessary focus and intention to succeed. So banish the dream kitchen. Instead, hit the test kitchen to save time, preserve job satisfaction and security, and safely dispense with the fanciful ideas that originate upstairs of the doers in your organization. There are meals to serve and mouths to feed.

This workshop framework gives you a fighting shot at lasting success as well as sound beginnings. Wiring up your information layer isn’t an overnight affair. But if you use the same cookbook and shared recipes, you’ll have solid footing for success. We designed these activities to make your organization’s needs concrete and clear, long before the hazards pile up.

While there are associated costs toward investing in this kind of technology and product design, your ability to size up and confront your unique situation and your digital capabilities is time well spent. Don’t squander it. The proof, as they say, is in the pudding.

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

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

Use storytelling as a structure to do research

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

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

Act one: setup

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

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

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

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

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

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

Act two: conflict

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

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

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

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

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

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

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

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

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

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

Act three: resolution

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

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

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

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

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

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

• Act one: You meet the protagonists (the users) and the antagonists (the problems affecting users). This is the beginning of the plot. In act one, researchers might use methods including contextual inquiry, ethnography, diary studies, surveys, and analytics. The output of these methods can include personas, empathy maps, user journeys, and analytics dashboards.

• Act two: Next, there’s character development. There’s conflict and tension as the protagonists encounter problems and challenges, which they must overcome. In act two, researchers might use methods including usability testing, competitive benchmarking, and heuristics evaluation. The output of these can include usability findings reports, UX strategy documents, usability guidelines, and best practices.

• Act three: The protagonists triumph and you see what a better future looks like. In act three, researchers may use methods including presentation decks, storytelling, and digital media. The output of these can be: presentation decks, video clips, audio clips, and pictures. 

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

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

The Hulu original series Good American Family premieres this month (March 19). The series stars Ellen Pompeo (Grey’s Anatomy) and is a dramatic retelling of the adoption of Natalia Grace. Inspired by true events, Good American Family follows a midwestern couple who adopts someone they believe to be a young girl with a rare form […]

The post Hulu New Releases: March 2025 appeared first on Den of Geek.

After leaving high school behind in the season 3 finale, Buffy the Vampire Slayer struggled to find its footing in young adulthood. Season 4 was an epic mix of highs and lows, with each episode being a toss-up between a series-defining masterpiece and a well-intended misfire. In the wake of that often disappointing 22-episode run, it was clear that Buffy needed a change of pace. By perfectly blending the show’s signature supernatural elements with relatable, grounded drama, season 5 is brave, moving, and masterful – thanks, in no small part, to the introduction of Buffy’s (Sarah Michelle Gellar) brand-new little sister Dawn, played by Michelle Trachtenberg, who tragically passed away on Feb. 26, 2025.

In what remains one of the best teen drama twists of all time, season 5’s opening episode drops a bombshell before a quick cut-to-black: the young girl briefly shown in Buffy’s room is, according to their mother, her little sister—despite never being part of the series prior to this moment. As the season continues on, Buffy eventually learns that Dawn was created by a group of monks, transformed from a magical key into a person that Buffy herself would ultimately die to protect from an angry god. While this premise is as harebrained as it gets (and par for the course in the series’ supernatural wheelhouse), Dawn’s evolution from annoying little sister to beloved pillar of the show all circles back to the brilliant writing elevated by Trachtenberg’s vulnerable and moving performance. 

Dawn herself could have easily devolved into nothing more than a plot device. Her presence in the fifth season’s story is straightforward and often predictable, and, in less capable hands, it’s easy to see how one-note this key-turned-sister could’ve been. But from her very first full episode on the show (titled “Real Me,” season 5 episode 2), Trachtenberg imbues her with a tangibility that is only matched by Gellar’s early work on the series as Buffy herself. 

There’s a gentle touch behind every move Dawn makes, where her charming, troublemaking streak blends with her heartbreaking, grounded fear layered with a heavy dose of supernatural symbolism. Dawn questions whether or not she’s a real person deserving of love, mirroring the fears of many teenagers as they try to develop into themselves. Dawn acts out when Buffy’s larger-than-life stakes overshadow her teenage drama, injecting an even stronger inferiority complex against Buffy’s godly position within her family and friend group. 

In one of Trachtenberg’s greatest moments on Buffy, Dawn and Buffy regroup after a fight with the season’s Big Bad, and Buffy asks if Dawn is alright. Dawn asks why Buffy cares, she’s not really her sister, after all. She’s just an object that a group of monks made flesh, why should Buffy concern herself with her feelings? Who’s to say she even has them? But when Buffy takes her own blood and clasps Dawn’s bloody hand within her own, it’s clear that these two women are bound for life. Even without the Summers blood running through her veins, Buffy loves Dawn, and no amount of cosmic intervention could change that. 

While Gellar is often the focal point of the scene, Trachtenberg gives such a stunning performance, even after her lines have finished. You can see as she puts up her walls, preemptively shutting Buffy out before her sister can hurt her by insisting that she’s not a person at all. Those walls slowly come down throughout Buffy’s heartfelt speech, genuine love and surprise clouding Trachtenberg’s wide, blue eyes. When Buffy finally hugs her, her face fully collapses, crying into her sister’s shoulder as she finally admits that she’s just a scared kid, facing problems and obstacles far beyond her reach. 

💔 pic.twitter.com/U7JkdUQ8xm

— ໊ (@buffys) February 26, 2025

It’s that admission that defines Dawn’s arc throughout the rest of the season, elevated by the absolutely pitch-perfect performance given in that moment. Nine episodes later, when Buffy tells Dawn that the hardest thing in this world is to live in it before she jumps to her own death to save her sister’s life, it’s that blood-tying moment that Buffy flashes back to. Of course, it’s to explain just how and why Buffy can sacrifice herself in Dawn’s place, but it’s also to remind audiences that Dawn is, truly, just a scared kid who doesn’t believe her life is worth saving, especially over Buffy’s. 

Even if Dawn didn’t believe she was worth Buffy’s sacrifice at the time, Michelle Trachtenberg made us believe she was. She made us believe she was the little sister we never had, but always wanted; she made us believe in the power of teenage whims and the weight of heartache and sorrow on a soul too young to have gone through so much; she made us believe in the magnitude of both being a teenager and being a lynchpin in one of the greatest supernatural stories ever told. 

As the series goes on, Dawn becomes further enmeshed in the canon, despite only appearing in the final three seasons. She becomes Spike’s (James Marsters) odd-couple friend, she becomes Tara (Amber Benson) and Willow’s (Alyson Hannigan) number one shipper before it was cool, and she becomes the narrative’s beating heart, long after Buffy herself lost some of the light that used to shine in her eyes. 

Trachtenberg brought humor, heart, light, and relatability to Dawn that allowed her to become one of the series’ most iconic figures, picking up the baton from Gellar to bring grounded, teenage drama back into a series that knew its hero needed to grow up. While fans have rallied for decades behind their assertions that Dawn was “annoying” and stilted the show’s evolution, this one-dimensional take on this ultimately iconic character diminishes not only importance of the teenage aspects of Buffy to the show’s everlasting legacy, but also the incredible performance Trachtenberg delivered across 66 episodes. 

In the twelfth episode of the final season, Xander (Nicholas Brennan) sits Dawn down for a pep talk. With their house overflowing with potential slayers and an apocalypse looming on the horizon, Dawn is feeling useless and frustrated as her sister and their friends all prepare for battle. He tells her that he knows what it’s like to not be “chosen,” to not be “special.” “You’re not special,” he flat-out tells her. Dawn takes a tearful pause, Trachtenberg plays her humility and disappointment with a marked grace; but Xander isn’t done: “You’re extraordinary.” She’s special not because she has infinite power and a calling to save the world, but simply because she cares enough to stand by those who do. If Buffy herself represents heroism by force, Dawn represents heroism by choice, inspired by her sister to do what is right and good, no matter the cost. 

Extraordinary feels like the perfect word to describe both Dawn and Trachtenberg. The kind of perfect storm created by a character and performance so moving and incredible that it defines the series itself, that it becomes seminal to the genre in a way that is absolutely undeniable. The world is infinitely less bright without Trachtenberg in it, but, at the very least, her performance as Dawn Summers—TV’s greatest little sister, still, to this day—will live on as one of the best to grace both the series and the genre itself. 

The post Buffy the Vampire Slayer’s Dawn Summers Is TV’s Most Important Sister appeared first on Den of Geek.

Anyone who decided to catch up with Anora because of Oscar buzz might find themselves confused early on. The movie begins as a Cinderella story with a sex worker in the princess role and the son of a Russian oligarch as the prince, and then switches to a broad farce that veers between slapstick comedy […]

The post The Power of Anora Comes from Its Last 10 Minutes and Final Scene appeared first on Den of Geek.

After leaving high school behind in the season 3 finale, Buffy the Vampire Slayer struggled to find its footing in young adulthood. Season 4 was an epic mix of highs and lows, with each episode being a toss-up between a series-defining masterpiece and a well-intended misfire. In the wake of that often disappointing 22-episode run, it was clear that Buffy needed a change of pace. By perfectly blending the show’s signature supernatural elements with relatable, grounded drama, season 5 is brave, moving, and masterful – thanks, in no small part, to the introduction of Buffy’s (Sarah Michelle Gellar) brand-new little sister Dawn, played by Michelle Trachtenberg, who tragically passed away on Feb. 26, 2025.

In what remains one of the best teen drama twists of all time, season 5’s opening episode drops a bombshell before a quick cut-to-black: the young girl briefly shown in Buffy’s room is, according to their mother, her little sister—despite never being part of the series prior to this moment. As the season continues on, Buffy eventually learns that Dawn was created by a group of monks, transformed from a magical key into a person that Buffy herself would ultimately die to protect from an angry god. While this premise is as harebrained as it gets (and par for the course in the series’ supernatural wheelhouse), Dawn’s evolution from annoying little sister to beloved pillar of the show all circles back to the brilliant writing elevated by Trachtenberg’s vulnerable and moving performance. 

Dawn herself could have easily devolved into nothing more than a plot device. Her presence in the fifth season’s story is straightforward and often predictable, and, in less capable hands, it’s easy to see how one-note this key-turned-sister could’ve been. But from her very first full episode on the show (titled “Real Me,” season 5 episode 2), Trachtenberg imbues her with a tangibility that is only matched by Gellar’s early work on the series as Buffy herself. 

There’s a gentle touch behind every move Dawn makes, where her charming, troublemaking streak blends with her heartbreaking, grounded fear layered with a heavy dose of supernatural symbolism. Dawn questions whether or not she’s a real person deserving of love, mirroring the fears of many teenagers as they try to develop into themselves. Dawn acts out when Buffy’s larger-than-life stakes overshadow her teenage drama, injecting an even stronger inferiority complex against Buffy’s godly position within her family and friend group. 

In one of Trachtenberg’s greatest moments on Buffy, Dawn and Buffy regroup after a fight with the season’s Big Bad, and Buffy asks if Dawn is alright. Dawn asks why Buffy cares, she’s not really her sister, after all. She’s just an object that a group of monks made flesh, why should Buffy concern herself with her feelings? Who’s to say she even has them? But when Buffy takes her own blood and clasps Dawn’s bloody hand within her own, it’s clear that these two women are bound for life. Even without the Summers blood running through her veins, Buffy loves Dawn, and no amount of cosmic intervention could change that. 

While Gellar is often the focal point of the scene, Trachtenberg gives such a stunning performance, even after her lines have finished. You can see as she puts up her walls, preemptively shutting Buffy out before her sister can hurt her by insisting that she’s not a person at all. Those walls slowly come down throughout Buffy’s heartfelt speech, genuine love and surprise clouding Trachtenberg’s wide, blue eyes. When Buffy finally hugs her, her face fully collapses, crying into her sister’s shoulder as she finally admits that she’s just a scared kid, facing problems and obstacles far beyond her reach. 

💔 pic.twitter.com/U7JkdUQ8xm

— ໊ (@buffys) February 26, 2025

It’s that admission that defines Dawn’s arc throughout the rest of the season, elevated by the absolutely pitch-perfect performance given in that moment. Nine episodes later, when Buffy tells Dawn that the hardest thing in this world is to live in it before she jumps to her own death to save her sister’s life, it’s that blood-tying moment that Buffy flashes back to. Of course, it’s to explain just how and why Buffy can sacrifice herself in Dawn’s place, but it’s also to remind audiences that Dawn is, truly, just a scared kid who doesn’t believe her life is worth saving, especially over Buffy’s. 

Even if Dawn didn’t believe she was worth Buffy’s sacrifice at the time, Michelle Trachtenberg made us believe she was. She made us believe she was the little sister we never had, but always wanted; she made us believe in the power of teenage whims and the weight of heartache and sorrow on a soul too young to have gone through so much; she made us believe in the magnitude of both being a teenager and being a lynchpin in one of the greatest supernatural stories ever told. 

As the series goes on, Dawn becomes further enmeshed in the canon, despite only appearing in the final three seasons. She becomes Spike’s (James Marsters) odd-couple friend, she becomes Tara (Amber Benson) and Willow’s (Alyson Hannigan) number one shipper before it was cool, and she becomes the narrative’s beating heart, long after Buffy herself lost some of the light that used to shine in her eyes. 

Trachtenberg brought humor, heart, light, and relatability to Dawn that allowed her to become one of the series’ most iconic figures, picking up the baton from Gellar to bring grounded, teenage drama back into a series that knew its hero needed to grow up. While fans have rallied for decades behind their assertions that Dawn was “annoying” and stilted the show’s evolution, this one-dimensional take on this ultimately iconic character diminishes not only importance of the teenage aspects of Buffy to the show’s everlasting legacy, but also the incredible performance Trachtenberg delivered across 66 episodes. 

In the twelfth episode of the final season, Xander (Nicholas Brennan) sits Dawn down for a pep talk. With their house overflowing with potential slayers and an apocalypse looming on the horizon, Dawn is feeling useless and frustrated as her sister and their friends all prepare for battle. He tells her that he knows what it’s like to not be “chosen,” to not be “special.” “You’re not special,” he flat-out tells her. Dawn takes a tearful pause, Trachtenberg plays her humility and disappointment with a marked grace; but Xander isn’t done: “You’re extraordinary.” She’s special not because she has infinite power and a calling to save the world, but simply because she cares enough to stand by those who do. If Buffy herself represents heroism by force, Dawn represents heroism by choice, inspired by her sister to do what is right and good, no matter the cost. 

Extraordinary feels like the perfect word to describe both Dawn and Trachtenberg. The kind of perfect storm created by a character and performance so moving and incredible that it defines the series itself, that it becomes seminal to the genre in a way that is absolutely undeniable. The world is infinitely less bright without Trachtenberg in it, but, at the very least, her performance as Dawn Summers—TV’s greatest little sister, still, to this day—will live on as one of the best to grace both the series and the genre itself. 

The post Buffy the Vampire Slayer’s Dawn Summers Is TV’s Most Important Sister appeared first on Den of Geek.

We agree: the computer-generated eyes could be a great fit for personas—but not for the purpose you might think. Ironically, the website highlights the core issue of this very common design method: the person ( a ) does not exist. Personas are deliberately created, just like in the photos. Knowledge is taken out of natural environment and recombined into an isolated preview that’s detached from reality.

However, oddly enough, developers use personalities to inform their designs for the real world.

Personas: A action up

Most manufacturers have created, used, or come across personalities at least once in their profession. The Interaction Design Foundation defines profile as “fictional characters that you create based upon your research in order to represent the various consumer types that might use your company, product, page, or brand,” according to their article” Personas- A Simple Introduction.” In their most complete expression, personas typically consist of a name, profile picture, quotes, demographics, goals, needs, behavior in relation to a certain service/product, emotions, and motivations ( for example, see Creative Companion’s Persona Core Poster ). According to design firm Designit, the goal of personas is to “make the research relateable, ]and ] easy to communicate, digest, reference, and apply to product and service development.”

The decontextualization of identities

Personas are common because they make “dry” research information more realistic, more people. However, this approach places a cap on the study’s ability to analyze the data in a way that excludes the subjects from their particular contexts. As a result, personalities don’t describe important factors that make you know their decision-making method or allow you to connect to users ‘ thoughts and behavior, they lack stories. You are aware of the persona’s actions, but you lack the history knowledge to understand why. You end up with depictions of people that are really less people.

This “decontextualization” we see in identities happens in four way, which we’ll discuss below.

People are assumed to be dynamic, according to people.

Although many companies still try to box in their employees and customers with outdated personality tests ( referring to you, Myers-Briggs ), here’s a painfully obvious truth: people are not a fixed set of features. Depending on how you feel, how you act, think, and think, what you do and do. You appear distinct to different people, you may act pleasant to some, tough to others. And you change your mind all the time about selections you’ve taken.

Current psychologists concur that while individuals typically act in accordance with specific patterns, how people act and make decisions is influenced by a combination of both history and environment. The context—the atmosphere, the effect of other people, your feelings, the whole story that led up to a situation—determines the kind of person you are in each particular time.

Personalities do not account for this variation in their attempt to reduce reality; instead, they present a consumer as a predetermined set of features. Like character testing, personas seize people away from real life. Even worse, individuals are reduced to a brand and categorized as” that kind of guy” with no means to practice their inherent flexibility. This behavior lowers variety, reinforces stereotypes, and doesn’t indicate reality.

Personas rely on people, not the environment

In the real world, you’re creating content for a situation, no an entity. Each individual lives in a community, a group, an habitat, where there are environmental, social, and cultural factors you need to consider. A pattern is not meant for a single customer. Instead, you create a pattern for one or more specific situations where a certain product might be used by a large number of people. Personas, yet, show the customer alone rather than define how the consumer relates to the environment.

Would you choose the exact course of action repeatedly? Maybe you’re a dedicated vegan but also decide to buy some meats when your family are coming across. As they depend on various situations and characteristics, your decisions—and behavior, thoughts, and comments —are no absolute but extremely contextual. Because it doesn’t identify the grounds of your decisions, the image that “represents” you doesn’t take into account this interdependence. It doesn’t provide a rationale of why you act the way you do. People practice the well-known attribution error, which states that they too often attribute others ‘ behavior to their personalities and not to the circumstances.

As mentioned by the Interaction Design Foundation, identities are often placed in a situation that’s a” specific environment with a problem they want to or have to solve “—does that mean environment actually is considered? Unfortunately, what often happens is that you take a fictional character and based on that fiction determine how this character might deal with a certain situation. How could you possibly comprehend how someone you want to represent behave in new circumstances given that you haven’t even fully investigated and understood the current context of the people you want to represent?

Personas are meaningless averages

A persona is depicted as a specific person in Shlomo Goltz’s introduction to Smashing Magazine, according to Shlomo Goltz’s introduction article. It is instead made up of observations from numerous people. A well-known critique to this aspect of personas is that the average person does not exist, as per the famous example of the USA Air Force designing planes based on the average of 140 of their pilots ‘ physical dimensions and not a single pilot actually fitting within that average seat.

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

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

The validity of personas is deceiving.

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

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

To conduct effective design research, we must report the actual situation and make it relatable for our audience, so that everyone can use their own empathy and develop their own interpretation and emotional response.

Dynamic Selves: The alternative to personas

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

Designit suggested utilizing mindsets rather than personas. Each Mindset is a” spectrum of attitudes and emotional responses that different people have within the same context or life experience”. It challenges designers to avoid getting fixated on just one person’s way of being. Unfortunately, while being a step in the right direction, this proposal doesn’t take into account that people are part of an environment that determines their personality, their behavior, and, yes, their mindset. Therefore, Mindsets are also not absolute but change in regard to the situation. What determines a particular Mindset, remains to be seen.

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

We want to change the traditional design process to be context-based by creating an alternative to personas. Contexts are generalizable and have patterns that we can identify, just like we tried to do previously with people. How can we identify these patterns, then? How do we ensure truly context-based design?

Understand real individuals in multiple contexts

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

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

1. Choose the right sample

We frequently get slammed for saying,” Where are you going to find a single person who encapsulates all the information from one of these advanced personas ]” when we debate personas. The answer is simple: you don’t have to. You don’t need to have information about many people for your insights to be deep and meaningful.

In qualitative research, accuracy comes from accurate sampling rather than quantity. You select the people that best represent the “population” you’re designing for. You can infer how the rest of the population thinks and acts if this sample is chosen wisely and you have a deep understanding of the sampled people. There’s no need to study seven Susans and five Yuriys, one of each will do.

Similarly, you don’t need to understand Susan in fifteen different contexts. Once you’ve seen her in a few different settings, you’ve come to understand how Susan responds to various circumstances. Not Susan as an atomic being but Susan in relation to the surrounding environment: how she might act, feel, and think in different situations.

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

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

We were creating an application for those who own a smart thermostat in our example project. In the future, everyone could have a smart thermostat in their house. Right now, though, only early adopters own one. We had to understand the causes behind these early adopters in order to build a significant sample. We therefore recruited by asking people why they had a smart thermostat and how they got it. There were those who had made the decision to purchase it, those who had been influenced by others to do so, and those who had located it in their homes. So we selected representatives of these three situations, from different age groups and geographical locations, with an equal balance of tech savvy and non-tech savvy participants.

2. Conduct your research

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

To gain an in-depth understanding of attitudes and decision-making trade-offs, the research focus was not limited to the interviewee alone but deliberately included the whole family. Each interviewee would provide a story that would later become much more interesting and precise with the additions made by their spouses, partners, kids, or occasionally even pets. We also focused on the relationships with other meaningful people ( such as colleagues or distant family ) and all the behaviors that resulted from those relationships. This extensive field of study gave us the ability to create a vivid mental image of dynamic situations involving multiple actors.

It’s essential that the scope of the research remains broad enough to be able to include all possible actors. Therefore, it normally works best to define broad research areas with macro questions. Follow-up questions will be written down in a way that is best suited for an interview, and they should be conducted in a semi-structured manner. This open-minded “plan to be surprised” will yield the most insightful findings. One of our participants responded,” My wife has not installed the thermostat’s app; she uses WhatsApp instead,” when we asked how his family controlled the house temperature. If she wants to turn on the heater and she is not home, she will text me. I am her thermostat”.

3. Analysis: Create the Dynamic Selves

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

Interviews and notes must be recorded verbatim as much as possible in order to capture precise quotes. This is essential to the truthfulness of the several Selves of each participant. In the case of real-life ethnographic research, photos of the context and anonymized actors are essential to build realistic Selves. As long as these photos are realistic and depict meaningful actions that you associate with your participants, they should be taken directly from field research, but an evocative and representative image can also work. For example, one of our interviewees told us about his mountain home where he used to spend every weekend with his family. Therefore, we depicted him taking a hike with his young daughter.

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

4. Identify creative uses

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

A particularly intriguing finding was made in our example project regarding the concept of humidity. We realized that people don’t know what humidity is and why it is important to monitor it for health: an environment that’s too dry or too wet can cause respiratory problems or worsen existing ones. This made clear that our client had a significant opportunity to train users about the concept and work as a health advisor.

Benefits of Dynamic Selves

When you use the Dynamic Selves approach in your research, you start to notice unique social relations, peculiar situations real people face and the actions that follow, and that people are surrounded by changing environments. One of the participants in our thermostat project, Davide, is described as a boyfriend, dog lover, and tech nut.

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

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

The Dynamic Selves approach aims to dismiss the conflicted dual purpose of personas—to summarize and empathize at the same time—by separating your research summary from the people you’re seeking to empathize with. This is crucial because scale affects how we feel empathy for people and how difficult it is to do so with other people. We feel the strongest empathy for individuals we can personally relate to.

If you take a real person as inspiration for your design, you no longer need to create an artificial character. No more creating new plot devices to “realize” the character, no more implausible biases. It’s simply how this person is in real life. In fact, as we all know, personas quickly turn into nothing more than a name in our priority guides and prototype screens because we all know these characters don’t really exist.

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

Finally, real people in their specific contexts provide a better foundation for anecdotal storytelling and are thus more persuasive. Documentation of real research is essential in achieving this result. It reinforces your design arguments by adding more weight and urgency:” When I met Alessandra, the conditions of her workplace struck me. Noise, bad ergonomics, lack of light, you name it. If we go for this functionality, I’m afraid we’re going to add complexity to her life”.

Conclusion

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

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

It’s high time for design to break away from fiction and use reality as our guide and inspiration, in all of its messy, surprising, and unquantifiable beauty.

But what on earth is a passionate burnout?

Envision a person determined to do it all. She is homeschooling two wonderful children while simultaneously working remotely with her husband. She has a demanding customer fill at work—all of whom she loves. She wakes up early to get some movement in ( or frequently catch up on work ), prepares dinner while the kids are having breakfast, and works while positioning herself near the end of her “fourth grade” to watch as she balances clients, tasks, and budgets. Sound like a bit? Also with a supportive group both at home and at work, it is.

This girl seems to need self-care because she has too many going on. But no, she doesn’t have occasion for that. In truth, she begins to feel as though she’s dropping balloons. Never accomplishing much. There’s not enough of her to be here and that, she is trying to divide her head in two all the time, all day, every day. She begins to question herself. And as those thoughts creep in more and more, her domestic tale becomes more and more important.

She immediately KNOWS what she needs to accomplish! She really Would MORE.

This is a challenging and dangerous period. Know the reasons. Because when she doesn’t end that new purpose, that storyline will get worse. She instantly starts failing. She isn’t doing much. SHE is not enough. She does fail, she might refuse her family, but she’ll discover more to do. She doesn’t nap as much, proceed because much, all in the attempts to do more. Trying to prove herself to herself, but always succeeding in any endeavor. Not feeling “enough”.

But, yeah, that’s what zealous burnout looks like for me. It doesn’t develop immediately in a great gesture; it develops gradually over the course of several weeks and months. My burning out process looks like speeding up, hardly a man losing focus. I move quickly and steadily, but I really quit.

I am the one who was

It’s amusing the things that shape us. Through the camera of my youth, I witnessed the battles, sacrifices, and fears of a person who had to make it all work without having much. I was happy that my mom was so competent and my dad sympathetic, I never went without and also got an extra here or there.

When my mother gave me food stamps as a child, I didn’t think shame; rather, I would have good started any debates about the subject, orally eviscerating anyone who dared to criticize the handicapped girl who was attempting to ensure all of our needs were met with so little. As a child, I watched the way the worry of not making those ends meet impacted persons I love. As the non-disabled people in my home, I did take on many of the real things because I was” the one who was” make our lives a little easier. I soon realized that putting more of myself into it was linked to fears or confusion; I am the one who does. I learned first that when something frightens me, I can double down and work harder to make it better. I am capable of taking on the problem. When individuals have seen this in me as an adult, I’ve been told I seem courageous, but make no mistake, I’m not. If I seem courageous, it’s because this behavior was forged from another people’s worries.

And here I am, more than 30 years later, also feeling the urge to aimlessly force myself forward when faced with daunting tasks in front of me, assuming that I am the one who is and consequently does. I find myself driven to prove that I may make things happen if I work longer hours, take on more duty, and do more.

I don’t see people who struggle economically as problems because I have seen how powerful that sea can be; it pulls you along the way. I really get that I have been privileged to be able to prevent many of the problems that were current in my children. That said, I am also” the one who can” who feels she does, but if I were faced with not having much to make ends meet for my own home, I do see myself as having failed. Despite my best efforts and education, the majority of this is due to chance. I will, yet, permit myself the pride of saying I have been cautious with my options to have encouraged that success. I believe I am” the one who can,” so I feel compelled to do the most because of this. I can choose to halt, and with some pretty precise warm water splashed in my encounter, I’ve made the choice to previously. But that choosing to stop is not my go-to, I move forward, driven by a fear that is so a part of me that I barely notice it’s there until I’m feeling utterly worn away.

Why the long history, then? You see, burnout is a fickle thing. Over the years, I’ve read and heard a lot about burnout. Burnout is real. Especially now, with COVID, many of us are balancing more than we ever have before—all at once! It’s difficult, and the avoidance, shutting down, and procrastination have an impact on so many amazing professionals. There are important articles that relate to what I imagine must be the majority of people out there, but not me. Not at the time of my burnout, though.

The dangerous invisibility of zealous burnout

A lot of work environments see the extra hours, extra effort, and overall focused commitment as an asset ( and sometimes that’s all it is ). They see a person attempting to overcome obstacles, not a person trapped in fear. Many well-meaning organizations have safeguards in place to protect their teams from burnout. However, in situations like this, those alarms don’t always ring, and some organization members are surprised and depressed when the inevitable stop happens. And sometimes maybe even betrayed.

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

Women and burnout

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

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

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

According to what I’ve read, this connection between work stress and health is more dangerous for women than it is for their non-female counterparts.

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

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

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

Do you feel like you have the authority to decline? I have observed in myself and others that when someone is burning out, they no longer feel they can say no to things. Even those who don’t” speed up” feel pressured to say “yes” to avoid apprehension.

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

Are you using justifications? Many of us try to disregard feelings of burnout. Over and over I have heard,” It’s just crunch time”,” As soon as I do this one thing, it will all be better”, and” Well I should be able to handle this, so I’ll figure it out”. And it could be just one more thing you need to learn, or it might just be crunch time. That happens—life happens. Be open to yourself if this continues to happen. If you’ve worked more 50-hour weeks since January than not, maybe it’s not crunch time—maybe it’s a bad situation that you’re burning out from.

Do you have a plan to stop feeling this way? If something is only temporary and you have to push through, it has an exit route and a reward system.
defined end.

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

So now what?

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

• Get enough sleep.
• Eat healthy.
• Work out.
• Leave the house.
• Take a break.
• Practice self-care in general.

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

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

I have come up with a few things that I do when I start to feel like I’m going into a zealous burnout to help me remember the airline attendant advice to put the mask on yourself first.

Cook an elaborate meal for someone!

Okay, since I’m a “food-focused” person, cooking for someone always comes naturally to my mind. There are countless tales in my home of someone walking into the kitchen and turning right around and walking out when they noticed I was” chopping angrily”. But it’s more than that, and you should give it a try. Seriously. It’s the perfect go-to if you don’t feel worthy of taking time for yourself—do it for someone else. Because the majority of us work in a digital world, cooking can pique all of your senses and make you immerse in the moment in all your ways of seeing the world. It can break you out of your head and help you gain a better perspective. In my house, I’ve been known to pick a place on the map and cook food that comes from wherever that is ( thank you, Pinterest ). Because it’s not what I was raised making, I enjoy making Indian food because the smells are warm and the bread only needs a small amount of kneading to keep my hands busy. And in the end, we all win!

Vent like a sniveling jerk.

Be careful with this one!

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

When that is required, turn to a trusted friend and give yourself some pure verbal diarrhea, yelling at you all the way through. You need to trust this friend not to judge, to see your pain, and, most importantly, to tell you to remove your cranium from your own rectal cavity. Seriously, it’s about getting a reality check here! One of the things I admire most about my husband is how he can simplify things down to their simplest bits, despite often after the fact. ” We’re spending our lives together, of course you’re going to disappoint me from time to time, so get over it” has been his way of speaking his dedication, love, and acceptance of me—and I could not be more grateful. Of course, it also required that I take my head out of that rectal cavity. So, again, usually those moments are appreciated in hindsight.

Pick up a book!

There are many books out there that are more like you sharing their stories and how they’ve come to find greater balance than they are self-help. Maybe you’ll find something that speaks to you. Among the titles that have stood out to me are:

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

Or, if I love to read or listen to a book that doesn’t have anything to do with my work-life balance, I can use another tactic. I’ve read the following books and found they helped balance me out because my mind was pondering their interesting topics instead of running in circles:

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

If you’re not into reading, pick up a topic on YouTube or choose a podcast to subscribe to. I’ve watched countless permaculture and gardening topics in addition to how to raise chickens and ducks. For the record, I don’t currently have a particularly large food garden or raise any kind of livestock. I just find the topic interesting, and it has nothing to do with any aspect of my life that needs anything from me.

Give yourself a break.

You are never going to be perfect—hell, it would be boring if you were. It’s OK to be broken and flawed. Being tired, depressed, and worried is human nature. It’s OK to not do it all. You can’t be brave without being imperfect, which is terrifying.

This last one is the most important: allow yourself permission to NOT do it all. You never promised to be everything to everyone at all times. We have greater power than the repressed fears that motivate us.

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

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

Look, I get that none of these ideas will “fix it”, and that’s not their purpose. None of us has complete control over what happens in our environment, but only how we react to it. These suggestions are to help stop the spiral effect so that you are empowered to address the underlying issues and choose your response. They are the things that largely work for me. Maybe they’ll work for you.

Does this sound familiar?

If something resounds familiar to you, it’s not just you. Don’t let your negative self-talk tell you that you “even burn out wrong”. It is not improper. Even if rooted in fear like my own drivers, I believe that this need to do more comes from a place of love, determination, motivation, and other wonderful attributes that make you the amazing person you are. We’re going to be OK, ya know. The lives that come before us might never have the same meaning as the one we’re striving for, which is acceptable because the only way to judge is in the mirror when we stop and look around.

Do you remember that Winnie the Pooh sketch that had Pooh eat so much at Rabbit’s house that his buttocks couldn’t fit through the door? Well, I already have a strong connection to Rabbit, so it was surprising when he unexpectedly declared that this was unacceptable. But do you recall what happened next? He put a shelf across poor Pooh’s ankles and decorations on his back, and made the best of the big butt in his kitchen.

We are resourceful and aware that we can push ourselves when necessary, even when we are exhausted or have a ton of clutter in our room. None of us has to be afraid, as we can manage any obstacle put in front of us. And maybe that means we need to redefine success in order to make room for comfort in human nature, but that doesn’t really sound so bad either.

So, wherever you are right now, please breathe. Do what you need to do to get out of your head. Give thanks and be considerate.

One of the most successful soft knowledge we have at our disposal is the ability to work together to improve our patterns while developing our own abilities and opinions, in whatever form it takes, and whatever it may be called.

Feedback is also one of the most underestimated equipment, and generally by assuming that we’re now great at it, we settle, forgetting that it’s a skill that can be trained, grown, and improved. Bad feedback can cause conflict in jobs, lower motivation, and negatively impact faith and teamwork over the long term. Quality comments can be a revolutionary force.

Practicing our knowledge is absolutely a good way to enhance, but the learning gets yet faster when it’s paired with a good base that programs and focuses the exercise. What are some fundamental components of providing effective opinions? And how can input be adjusted for isolated and distributed function settings?

On the web, we may find a long history of sequential comments: code was written and discussed on mailing lists since the beginning of open source. Currently, engineers engage on pull calls, developers post in their favourite design tools, project managers and sprint masters exchange ideas on tickets, and so on.

Design analysis is often the label used for a type of input that’s provided to make our job better, jointly. So it generally adheres to many of the concepts with comments, but it also has some differences.

The material

The content of the feedback serves as the foundation for every effective criticism, so we need to start there. There are many versions that you can use to design your content. The one that I personally like best—because it’s obvious and actionable—is this one from Lara Hogan.

Although this equation is typically used to provide feedback to individuals, it likewise fits really well in a style criticism because it finally addresses some of the main inquiries that we work on: What? Where? Why? How? Imagine that you’re giving some comments about some pattern function that spans several screens, like an onboard movement: there are some pages shown, a movement blueprint, and an outline of the decisions made. You notice something that needs to 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 included in some feedback, and it might appear reasonable at first glance because it appears to merely fit the equation. But does it?

Not sure about the buttons ‘ styles and hierarchy—it feels off. Can they be altered?

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. Do you offer the user’s viewpoint? Your expert perspective? A business perspective? From the perspective of the project manager? A first-time user’s perspective?

I anticipate that one of these two buttons will go forward and the other will go back when I see them.

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.

I anticipate that one of these two buttons will go forward and the other will go back when I see them. 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, in my experience, going back to the question approach typically leads to the best solutions because designers are generally more at ease in being given an open space to explore.

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

I anticipate that one of these two buttons will go forward and the other will go back when I see them. 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:

I anticipate that one of these two buttons will go forward and the other will go back when I see them. 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.

I anticipate that one of these two buttons will go forward and the other will go back when I see them. 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. I did rounds of anonymous feedback and I reviewed feedback with other people a while back when I was putting a lot of effort into improving my feedback. 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. Surprise surprise, my next round of criticism from a specific person wasn’t very positive. 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. However, there was a member of this other team who 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. Yes, but also no. Let’s explore both sides.

No, this kind of feedback is effective because the length is a byproduct of clarity, and giving this kind of feedback can provide precisely enough information for a sound 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 implement 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 explaining the why, the designer might assume that the change is one of 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.

Therefore, the above equation serves as a mnemonic to reflect and enhance the practice rather than a strict template for feedback. 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 atmosphere

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. It has been demonstrated that only positive feedback can lead to sustained change in people, and tone alone can determine whether content is rejected or welcomed.

Since our goal is to be understood and to have a positive working environment, tone is essential to work on. I’ve tried to summarize the necessary soft skills over the years using a formula that resembles 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 the moment when the feedback occurs. To-the-point feedback doesn’t have much hope of being well received if it’s given at the wrong time. If a new feature’s entire high-level information architecture is about to go live when it’s about to be released, it might still be relevant if that questioning raises a significant blocker that no one saw, but those concerns are much more likely to have to wait for a later revision. So in general, attune your feedback to the stage of the project. Early iteration? Iteration later? Polishing work in progress? Each of these has unique 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 entails checking whether what we have in mind will actually help the person and improve the overall project before writing. This might be a hard reflection at times because maybe we don’t want to admit that we don’t really appreciate that person. Although it’s possible, and that’s okay, it’s hoped not to be the case. 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? What can I do to encourage constructive behavior?

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 could be many reasons for this, including the fact that occasionally certain words may cause specific reactions, that non-native speakers may not be able to comprehend all thenuances of some sentences, that our brains may be different, and that we may perceive the world differently. Neurodiversity is a requirement. 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 was given some sound advice, but I also got a surprise comment. They pointed out that when I wrote” Oh, ]… ]”, I made them feel stupid. That wasn’t my intention at all! 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 quickly changed my situation by adding “oh” to my list of replaced words (your choice between aText, TextExpander, or others ) so that when I typed “oh,” it was immediately 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. A positive attitude doesn’t necessarily mean giving in to criticism; it just means that you give it in a respectful and constructive manner, whether it be in the form of criticism or criticism. 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. The best, most insightful moments for me came when I shared a comment and asked a trusted person how it sounds, how can I do it better, or even” How would you have written it”? I discovered that by seeing the two versions side by side, I’ve learned a lot.

The format

Asynchronous feedback also has a significant inherent benefit: it allows us to spend more time making sure that the suggestions ‘ clarity and actionability meet two main objectives.

Let’s imagine that someone shared a design iteration for a project. You are reviewing it and leaving a comment. Let’s try to think about some factors that might be helpful to consider, as there are many ways to accomplish this, and context is of course a factor.

In terms of clarity, start by grounding the critique that you’re about to give by providing context. This includes specifically describing where you’re coming from: do you have a thorough understanding of the project, or is this your first time seeing it? Are you coming from a high-level perspective, or are you figuring out the details? Are there regressions? Which user’s point of view are you addressing when offering 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?

Even if you’re giving feedback to a team that already has some background information on the project, providing context is helpful. 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 frequently concentrate on the negatives and attempt to list every possible improvement. 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. Although this may seem superfluous, it’s important to remember that design has a number of possible solutions to each 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. Positive feedback can also help to lessen impostor syndrome as an added bonus.

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. There is a significant difference between a critique of a design that is already in good shape and one 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”. Just before sending, review your writing to make changes to this.

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. You might also consider breaking up the feedback into sections or even across multiple comments if it is longer. 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. A red square indicates that it is something I consider blocking, a yellow diamond indicates that it needs to be changed, and a green circle provides a thorough, 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. However, I’d only use this strategy on teams where I’ve already established a high level of trust because it might turn out to be quite demoralizing if I deliver a lot of red squares and change how I communicate that.

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

• 🔶 Navigation—I anticipate that one of these two buttons will go forward and the other will go back when I see them. 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 gives the impression that it’s a positive action because green is typically seen as a confirmation color. Do we need to explore a different color?
• Considering the number of items on the page and the overall page hierarchy, it seems to me that the tiles should use Subtitle 2 instead of Subtitle 1. 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 purpose behind using that?

What about giving feedback directly in Figma or another design tool that allows in-place feedback? These are generally difficult to use because they conceal discussions and are harder to follow, but in the right setting, 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 clearly right or wrong, and 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 fine. 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.

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

Content, tone, and format. Although each of these subjects offers a useful model, focusing on eight areas, including observation, impact, question, timing, attitude, form, clarity, and actionability, is a lot of work 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, followed by 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 opinions. 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. Topic, generation, and analysis. 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 issue may be important, so it might be difficult to get the team to pay attention to it.

But how do we get into this scenario? It’s a combination of various components. One is that we don’t often consider asking as a part of the input approach. Another is how healthy it is to keep the 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 make any improvements to them.

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

There isn’t a second best method to request feedback. It simply needs to be certain, and sensitivity can take several shapes. The level 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 forward to the final design. But within a single stage, one might also examine whether some assumptions are correct and whether there’s been a suitable language of the amassed input into updated designs as the job has evolved. The layers of user experience could serve as a starting point for potential questions. What do you want to know: Project objectives? user requirements? Functionality? Content? Interaction design? 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 error counter at the top of the page, which makes sure you see the next error even if it 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?

The other axis of specificity is determined by how far you’d like to go with the information being presented. 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 spot the “good” qualifier and make the question” When the block opens and the buttons appear, is it clear what the next action is” look like?

Sometimes we actually do want broad feedback. That’s uncommon, but it can occur. In that sense, you might still make it explicit that you’re looking for a wide range of opinions, whether at a high level or with details. Or perhaps 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 further refinement but aren’t currently what matters most.

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

The asynchronous design-critique approach that I find most effective is to create explicit checkpoints for discussion. I’m going to use the term iteration post for this. It refers to a write-up or presentation of the design iteration followed by a discussion thread of some kind. Any platform that can accommodate this type of structure can use this. 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.
• It might also make it simpler to collect and act on feedback depending on the tool.

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

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 every iteration post, I would copy and paste this, so I could do it again. The idea is to provide context and to repeat what’s essential to make each iteration post complete so that there’s no need to find information spread across multiple posts. The most recent iteration post will have everything I need if I want to know about the most recent design.

This copy-and-paste part introduces another relevant concept: alignment comes from repetition. Therefore, repeating information in posts helps to ensure 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 very different from creating a strong live presentation.

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

Finally, as mentioned earlier, 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 design process is complete and the feature is ready.

I want to highlight that even if these iteration posts are written and conceived as checkpoints, by no means do they need to be exhaustive. A post might be just a concept to start a conversation, or it might be a cumulative list of all the features that have been added gradually 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. Attempts must be exploratory, incomplete, or partial.
• Future proof—It resolves the “final” naming problem that you can run into with versions. No more files with the title “final final complete no-really-its-done” Within each project, the largest number always represents the latest iteration.

The wording release candidate (RC ) could be used to indicate when a design is finished enough to be worked on, even if there are some bits that still need work and, in turn, need more iterations:” with i8 we reached RC” or “i12 is an RC” to illustrate this.

The review

What typically occurs during a design critique is an open discussion that can be very productive between two people. This approach is particularly effective during live, synchronous feedback. However, when we work asynchronously, it is more effective to adopt a different strategy: we can adopt 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 of a problem with it. 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 someone directly involved in the project who we feel we need to speak with. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. Responding to all comments at times can be effective, but when we consider a design critique more like user research, we realize that we don’t need to respond to every comment, and there are alternatives in asynchronous spaces:

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

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

Let’s begin by acknowledging again that there’s no need to reply to every comment. However, if responding to a previously litigated point is useful, 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 ). And in the end, presenting everything in aggregated form helps us to prioritize our work more.

Always remember that while you need to listen to stakeholders, project owners, and specific advice, you don’t have to accept every piece of feedback. You must examine it and come up with a rationale for your choice, 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 specialization, and the designer has the most background and knowledge to make the best choice. And by listening to the feedback that you’ve received, you’re making sure that it’s also the best and most balanced decision.

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