When you are done with playing the critic’s role, evolve to that of a coach

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

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

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

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

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

The content

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

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

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

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

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

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

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

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

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

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

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

Or, for the request approach:

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

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

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

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

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

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

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

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

The tone

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

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

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

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

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

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

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

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

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

The format

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

“Any comment?” is probably one of the worst ways to ask for feedback. It’s vague and open ended, and it doesn’t provide any indication of what we’re looking for. Getting good feedback starts earlier than we might expect: it starts with the request. 

It might seem counterintuitive to start the process of receiving feedback with a question, but that makes sense if we realize that getting feedback can be thought of as a form of design research. In the same way that we wouldn’t do any research without the right questions to get the insights that we need, the best way to ask for feedback is also to craft sharp questions.

Design critique is not a one-shot process. Sure, any good feedback workflow continues until the project is finished, but this is particularly true for design because design work continues iteration after iteration, from a high level to the finest details. Each level needs its own set of questions.

And finally, as with any good research, we need to review what we got back, get to the core of its insights, and take action. Question, iteration, and review. Let’s look at each of those.

The question

Being open to feedback is essential, but we need to be precise about what we’re looking for. Just saying “Any comment?”, “What do you think?”, or “I’d love to get your opinion” at the end of a presentation—whether it’s in person, over video, or through a written post—is likely to get a number of varied opinions or, even worse, get everyone to follow the direction of the first person who speaks up. And then... we get frustrated because vague questions like those can turn a high-level flows review into people instead commenting on the borders of buttons. Which might be a hearty topic, so it might be hard at that point to redirect the team to the subject that you had wanted to focus on.

But how do we get into this situation? It’s a mix of factors. One is that we don’t usually consider asking as a part of the feedback process. Another is how natural it is to just leave the question implied, expecting the others to be on the same page. Another is that in nonprofessional discussions, there’s often no need to be that precise. In short, we tend to underestimate the importance of the questions, so we don’t work on improving them.

The act of asking good questions guides and focuses the critique. It’s also a form of consent: it makes it clear that you’re open to comments and what kind of comments you’d like to get. It puts people in the right mental state, especially in situations when they weren’t expecting to give feedback.

There isn’t a single best way to ask for feedback. It just needs to be specific, and specificity can take many shapes. A model for design critique that I’ve found particularly useful in my coaching is the one of stage versus depth.

“Stage” refers to each of the steps of the process—in our case, the design process. In progressing from user research to the final design, the kind of feedback evolves. But within a single step, one might still review whether some assumptions are correct and whether there’s been a proper translation of the amassed feedback into updated designs as the project has evolved. A starting point for potential questions could derive from the layers of user experience. What do you want to know: Project objectives? User needs? Functionality? Content? Interaction design? Information architecture? UI design? Navigation design? Visual design? Branding?

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

• Functionality: Is automating account creation desirable?
• 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: We have two competing bits of information on this page. Is the structure effective in communicating them both?
• UI design: What are your thoughts on the error counter at the top of the page that makes sure that you see the next error, even if the error is out of 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 suggestions to address this?
• Visual design: Are the sticky notifications in the bottom-right corner visible enough?

The other axis of specificity is about how deep you’d like to go on what’s 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 useful from one iteration to the next where it’s important to highlight the parts that have changed.

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

A simple trick is to remove generic qualifiers from your questions like “good,” “well,” “nice,” “bad,” “okay,” and “cool.” For example, asking, “When the block opens and the buttons appear, is this interaction good?” might look specific, but you can spot the “good” qualifier, and convert it to an even better question: “When the block opens and the buttons appear, is it clear what the next action is?”

Sometimes we actually do want broad feedback. That’s rare, but it can happen. 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 maybe 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 expansive, and some areas may have already been explored in detail. In these situations, it might be useful to explicitly say that some parts are already locked in and aren’t open to feedback. It’s not something that I’d recommend in general, but I’ve found it useful to avoid falling again into rabbit holes of the sort that might lead to further refinement but aren’t what’s most important right now.

Asking specific questions can completely change the quality of the feedback that you receive. People with less refined critique skills will now be able to offer more actionable feedback, and even expert designers will welcome the clarity and efficiency that comes from focusing only on what’s needed. 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. Yet a lot of design tools with inline commenting tend to show changes as a single fluid stream in the same file, and those types of design tools make conversations disappear once they’re resolved, update shared UI components automatically, and compel designs to always show the latest version—unless these would-be helpful features were to be 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 best way to approach design critiques, but even if I don’t want to be too prescriptive here: that could 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 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 many advantages:

• 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 visible for future review, and conversations are likewise always available.
• It creates a record of how the design changed over time.
• Depending on the tool, it might also make it easier to collect feedback and act on it.

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

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

1. The goal
2. The design
3. The list of changes
4. The questions

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. So this is something that I’d repeat in every iteration post—literally copy and pasting it. 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. If I want to know about the latest design, the latest iteration post will have all that I need.

This copy-and-paste part introduces another relevant concept: alignment comes from repetition. So having posts that repeat information is actually very effective toward making sure 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. In short, it’s any design artifact. For the final stages of work, I prefer the term blueprint to emphasize that I’ll be showing full flows instead of individual screens to make it easier to understand the bigger picture. 

It can also be useful to label the artifacts with clear titles because that can make it easier to refer to them. Write the post in a way that helps people understand the work. It’s not too different from organizing a good 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.

And finally, as noted earlier, it’s essential that you include a list of the questions to drive the design critique in the direction you want. Doing this as a numbered list can also help make it easier to refer to each question by its number.

Not all iterations are 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 start settling on a solution and refining it until the design process reaches its end and the feature ships.

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

Over time, I also started using specific labels for incremental iterations: i1, i2, i3, and so on. This might look like a minor labelling tip, but it can help in multiple ways:

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

To mark when a design is complete enough to be worked on, even if there might be some bits still in need of attention and in turn more iterations needed, the wording release candidate (RC) could be used to describe it: “with i8, we reached RC” or “i12 is an RC.”

The review

What usually happens during a design critique is an open discussion, with a back and forth between people that can be very productive. This approach is particularly effective during live, synchronous feedback. But when we work asynchronously, it’s more effective to use a different approach: we can shift to 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 major benefits that make asynchronous feedback particularly effective, especially around these friction points:

1. It removes the pressure to reply to everyone.
2. It reduces the frustration from swoop-by comments.
3. It lessens our personal stake.

The first friction point is feeling a pressure to reply to every single comment. Sometimes we write the iteration post, and we get replies from our team. It’s just a few of them, it’s easy, and it doesn’t feel like a problem. 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 person who’s replying is a stakeholder or someone directly involved in the project who we feel that we need to listen to. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. Sometimes replying to all comments can be effective, but if we treat a design critique more like user research, we realize that we don’t have to reply to every comment, and in asynchronous spaces, there are alternatives:

• One is to let the next iteration speak for itself. When the design evolves and we post a follow-up iteration, that’s the reply. You might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement. 
• Another is to briefly reply to acknowledge each comment, such as “Understood. Thank you,” “Good points—I’ll review,” or “Thanks. I’ll include these in the next iteration.” In some cases, this could also be just a single top-level comment along the lines of “Thanks for all the feedback everyone—the next iteration is coming soon!”
• Another 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 second friction point is the swoop-by comment, which is the kind of feedback that comes from someone outside the project or team who might not be aware of the context, restrictions, decisions, or requirements—or of the previous iterations’ discussions. 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 often trigger the simple thought “We’ve already discussed this…”, and it can be frustrating to have to repeat the same reply over and over.

Let’s begin by acknowledging again that there’s no need to reply to every comment. If, however, replying to a previously litigated point might be useful, a short reply with a link to the previous discussion for extra details is usually enough. Remember, alignment comes from repetition, so it’s okay to repeat things sometimes!

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

The third friction point is the personal stake we could have with the design, which could make us feel defensive if the review were to feel more like 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 ultimately, treating everything in aggregated form allows us to better prioritize our work.

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 have to analyze it and make a decision that you can justify, but sometimes “no” is the right answer. 

As the designer leading the project, you’re in charge of that decision. Ultimately, everyone has their specialty, and as the designer, you’re the one who has the most knowledge and the most context to make the right decision. 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 Brie Anne Demkiw and Mike Shelton for reviewing the first draft of this article.

Getting feedback for what you're building or writing, RSS feed reminiscing, Arc browser thoughts, products that didn't make that should have.

The Eastern Nagaland People’s Organisation wants the creation of Frontier Nagaland Territory comprising six districts of the northeastern State bordering Myanmar

Surprised by proposal, scientific experts to ask agency chief to wait for their feedback before finalizing rule

Surprised by proposal, scientific experts to ask agency chief to wait for their feedback before finalizing rule

Calendar Feedback Sunday, May 10, 2020

October 5 marks the 20th anniversary of UNESCO’s World Teachers' Day, a day devoted to “appreciating, assessing and improving educators of the world”. This gives us a great opportunity to reflect again on how schools can celebrate and develop great teaching. One way to do that is through critical exchanges – building constructive feedback systems within the schools.

Across countries and economies participating in the OECD Teaching and Learning International Survey (TALIS), a majority of teachers report receiving feedback on different aspects of their work in their schools.

eChemPortal uses are encouraged to respond to the on-line survey. Your use of the portal, your expectations, information, substance search, property search, structure search, design and layout. Your answers will help us improve eChemPortal - the Global Portal to Information on Chemical Substances, worldwide source of information about chemicals from authorities and international organisations, to meet your needs.

Julian Chollet, Alexander Dünkler, Anne Bäuerle, Laura Vivero-Pol, Medhanie A. Mulaw, Thomas Gronemeyer, and Nils Johnsson

Yeast cells select the position of their new bud at the beginning of each cell cycle. The recruitment of the septins to this prospective bud site is one of the critical events in a complex assembly pathway that culminates in the outgrowth of a new daughter cell. Hereby, the septin-rods follow the high concentration of Cdc42_GTP that is generated by the focused localization of its GEF Cdc24. We show that shortly before budding Cdc24 not only activates Cdc42 but also transiently interacts with Cdc11, the septin subunit that caps both ends of the septin rods. Mutations in Cdc24 reducing the affinity to Cdc11 impair septin recruitment and decrease the stability of the polarity patch. The interaction between septins and Cdc24 thus reinforces bud assembly at sites where septin structures are formed. Once the septins polymerize into the ring, Cdc24 is found at the cortex of the bud and directs its further outgrowth from this position.

Although low-income households consume less energy than wealthier households, they are still keen to learn how to save energy, for both economic and environmental reasons. This is the conclusion of a recent Swedish study which explored the energy-related behaviour of residents on low incomes. It provides insights which could help inform energy-awareness campaigns targeted at this section of the population.

Electricity consumption fell by 22–27% in low-income households participating in an energy-efficiency programme in Cyprus, France, Malta and Spain, reports a new study. Participants were provided with a range of tools and information to help them curb their energy use, including smart meters and customised reports. The results confirm the value of tailoring information to specific demographic groups.

Motivation to practise fuel-efficient driving may be more influenced by environmental concerns than by financial benefits, research suggests. In promoting fuel efficiency, this survey of Dutch motorists highlights the power of providing feedback to drivers – both environmental and economic – on their behaviour.

Belgrad, Daniel, author

More than 30 technology and telecom companies announced this week that they have formed a new alliance, the Open RAN Policy Coalition, that calls for open and interoperable 5G systems.

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Jack Zenger and Joseph Folkman have administered thousands of 360-degree assessments through their consulting firm, Zenger/Folkman. This has given them a wealth of information about who benefits from criticism, and how to deliver it.

Marcus Buckingham, head of people and performance research at the ADP Research Institute, and Ashley Goodall, senior vice president of leadership and team intelligence at Cisco Systems, say that managers and organizations are overestimating the importance of critical feedback. They argue that, in focusing our efforts on correcting weaknesses and rounding people out, we lose the ability to get exceptional performance from them. Instead, we should focus on strengths and push everyone to shine in their own areas. To do that, companies need to rethink the way they review, pay, and promote their employees. Buckingham and Goodall are the authors of the book "Nine Lies About Work: A Freethinking Leader's Guide to the Real World" and the HBR article "The Feedback Fallacy."

YouTube creator Mark Brown shares tips and research on how developers can better manage player feedback to improve their games. ...

Collaboration between Delighted, a Qualtrics company, and Amazon Business empowers organizations of all sizes to listen, understand, and act on customer feedback in real-time

YouTube creator Mark Brown shares tips and research on how developers can better manage player feedback to improve their games. ...

RavenCSI "Pro" plan - a leading survey tool for business intelligence capture, to be offered at no cost through the end of 2020

By Jessica Corbett Common Dreams “We face a stark choice [between] radical, disruptive changes to our physical world or radical, disruptive changes to our political and economic systems to avoid those outcomes.” As people across the globe mobilize to demand … Continue reading →

By Jessica Corbett Common Dreams “The most robust study of the ice mass balance of Antarctica to date,” scientists say, “now puts Antarctica in the frame as one of the largest contributors to sea-level rise.” Scientists are expressing alarm over … Continue reading →

By Jessica Corbett Common Dreams “We face a stark choice [between] radical, disruptive changes to our physical world or radical, disruptive changes to our political and economic systems to avoid those outcomes.” As people across the globe mobilize to demand … Continue reading →

By Jessica Corbett Common Dreams “We face a stark choice [between] radical, disruptive changes to our physical world or radical, disruptive changes to our political and economic systems to avoid those outcomes.” As people across the globe mobilize to demand … Continue reading →

The paper considers constrained linear systems with stochastic additive disturbances and noisy measurements transmitted over a lossy communication channel. We propose a model predictive control (MPC) law that minimizes a discounted cost subject to a discounted expectation constraint. Sensor data is assumed to be lost with known probability, and data losses are accounted for by expressing the predicted control policy as an affine function of future observations, which results in a convex optimal control problem. An online constraint-tightening technique ensures recursive feasibility of the online optimization and satisfaction of the expectation constraint without bounds on the distributions of the noise and disturbance inputs. The cost evaluated along trajectories of the closed loop system is shown to be bounded by the optimal predicted cost. A numerical example is given to illustrate these results.

We derive sufficient conditions for exponential decay of solutions of the delay negative feedback equation with distributed delay. The conditions are written in terms of exponential moments of the distribution. Our method only uses elementary tools of calculus and is robust towards possible extensions to more complex settings, in particular, systems of delay differential equations. We illustrate the applicability of the method to particular distributions - Dirac delta, Gamma distribution, uniform and truncated normal distributions.

A method and apparatus may be used to evaluate a polynomial by initializing a multiply and accumulate feedback apparatus (260) comprising a multiplier stage (264) having an output coupled to an input of an accumulator stage (267) having an accumulator feedback output (269) selectively coupled to an input of the multiplier stage over a plurality of clock cycles; iteratively calculating a final working loop variable z over an additional plurality of clock cycles; multiplying the final working loop variable z and a complex input vector x to compute a final multiplier value; and adding a least significant complex polynomial coefficient to the final multiplier value using the multiplier stage of the multiply and accumulate feedback apparatus to yield a result of the polynomial evaluation.

The present invention generally relates to systems and methods for monitoring and/or providing feedback for drugs or other pharmaceuticals taken by a subject. In one aspect, the present invention is directed to devices and methods for determining a species within the skin of a subject; and producing feedback to a subject based on the determination of the species. The feedback may be, for example, visual, audible, tactile, a change in temperature, etc. In some cases, information regarding the determination of the species may be transmitted to another entity, e.g., a health care provider, a computer, a relative, etc., which may then provide feedback to the subject in some fashion. In some cases, the feedback may be directly indicative of the species, e.g., whether the species is present, the concentration of the species, whether a by-product of a reaction involving the species is present, whether a compound affected by the species is present, etc. However, the feedback may also be indirect in some embodiments. For example, the subject may be presented with an external reward, e.g., based on the determination of the species within the skin. For instance, a reward such as cash, coupons, songs, discounts, personal items, etc., may be offered based on the level of compliance of the subject. Still other aspects of the invention are generally directed to kits involving such devices (with or without the drug to be monitored), methods of promoting such systems, or the like.

A system or method for inferring and selective display of visual and sound media content based on a pet(s)'s level of engagement or reactions to content displayed on any number of content display devices including, but not limited to, television screens, computer monitors, tablets, and cell phones and measured by a sensor. A content selection algorithm takes as input the sensor measurements and historical or pre-computed data to infer the pet(s)'s preference for content. A content modification algorithm interposes algorithmically computed shapes and sounds overlaid on top of the existing content to attract the attention of the pet(s) observing the display.

The Virtual Aggregation Processor enables end user devices to share a common wireless forward path of a multicast communication architecture in which the forward path delivered content is dynamically changed or modified based on a real-time, near-real-time, or delay-time basis via aggregated reverse path feedback from at least one of a plurality of end user devices. The Virtual Aggregation Processor periodically or continuously aggregates the feedback input received via the reverse path (having wired and/or wireless connectivity), modifies the forward path multi-media content, and delivers this dynamically modified multi-media content to the then connected population of end user devices via a wireless forward path multicast in a repetitive closed loop fashion.

An inductive power outlet for providing power to an electric load via an inductive power receiver includes at least one primary inductive coil wired to a power supply via a driver configured to provide a driving voltage across the primary inductive coil such that a secondary voltage is induced in a secondary inductive coil associated with the inductive power receiver. The driver may include a controller configured to receive feedback control signals from the inductive power receiver indicating if more or less power is required. The controller may be further configured to adjust the driving voltage according to the control signals.

A third-order distributed feedback laser has an active medium disposed on a substrate as a linear array of segments having a series of periodically spaced interstices therebetween and a first conductive layer disposed on a surface of the active medium on each of the segments and along a strip from each of the segments to a conductive electrical contact pad for application of current along a path including the active medium. Upon application of a current through the active medium, the active medium functions as an optical waveguide, and there is established an alternating electric field, at a THz frequency, both in the active medium and emerging from the interstices. Spacing of adjacent segments is approximately half of a wavelength of the THz frequency in free space or an odd integral multiple thereof, so that the linear array has a coherence length greater than the length of the linear array.

A self-feedback random generator comprises a digital-to-analog converter, a digital oscillator, a frequency-modulating unit and a first D-type flip-flop. The digital-to-analog converter receives a digital random-code signal and the digital random-code signal is converted to corresponding analog random signal. The frequency-modulating unit modulates frequency of first digital oscillating signal so as to increase random of frequency of first digital oscillating signal according to voltage value of the analog random signal, and accordingly outputs a second digital oscillating signal. The first D-type flip-flop receives the second digital oscillating signal and a clock signal, and reads the second digital oscillating signal through utilizing the clock signal so as to outputs the digital random-code signal, wherein frequency of the clock signal is smaller than frequency of the first digital oscillating signal, and random of frequency of the second digital oscillating signal corresponds to random of the digital random-code signal.

The present invention is directed to signal processing system and electrical circuits. More specifically, embodiments of the present invention provide a DLL system that provides phase correction by determining a system offset based on phase differences among the delay lines. The offset is used as a part of a feedback loop to provide phase corrections for the delay lines. There are other embodiments as well.

To lubricate a length of track, a plurality of lubricating nozzles are provided. Each nozzle is fed by the output of a single positive displacement pump, and all the pumps are controlled by a computer. Vibration sensors, sound sensors, or L/V ratio sensors detect physical qualities which occur as a train passes a given point, and another detector measures the time between successive wheels on the truck of a car as it passes a given point to measure train speed. The computer compares the output readings measured by the detector to a table of outputs in its memory that are indicative of a lubricated track to determine if lubrication is needed.

The present application includes a blade-pitch control system for controlling a pitch angle of each of a plurality of blades on an aircraft rotor. A feedback lever associated with each blade is pivotally mounted to the rotating portion of a swashplate assembly. A pitch link connects an output arm of a lever to a pitch horn of a corresponding blade, and a feedback link connects the input arm of the lever to a yoke. Flapping motion of the yoke causes motion of the feedback link, and this motion causes corresponding rotation of the lever. Rotation of the lever causes motion of the pitch link, which changes the pitch angle of the attached blade. This provides for selected pitch-flap coupling between flapping motion of the yoke and pitch motion of the blades.

A method of treating an object with radiation that includes generating volumetric image data of an area of interest of an object and emitting a therapeutic radiation beam towards the area of interest of the object in accordance with a reference plan. The method further includes evaluating the volumetric image data and at least one parameter of the therapeutic radiation beam to provide a real-time, on-line or off-line evaluation and on-line or off-line modification of the reference plan.

A system that incorporates the subject disclosure may include, for example, a process that includes adjusting a filter in electrical communication between an input terminal and a demodulator. The filter is applied to an information bearing signal, e.g., to mitigate interference, received at the input terminal, resulting in a filtered signal. An error signal is received, indicative of errors detected within information obtained by demodulation of a modulated carrier of the filtered signal. A modified filter state is determined in response to the error signal and the filter is adjusted according to the modified filter state, e.g., to improve mitigation of the interference. Other embodiments are disclosed.

An agricultural system includes an agricultural row unit movable on a field between a first soil condition and a second soil condition, the first soil condition having a different soil hardness than the second soil condition. A down-pressure actuator applies an initial first pressure associated with the first soil condition. A soil-hardness sensing device is positioned at a distance D forward of the row unit and outputs a soil-hardness change signal when detecting a change from the first soil condition to the second soil condition. At least one memory device stores instructions that, when executed by at least one processor, cause the down-pressure actuator to change, in response to receiving the soil-hardness change signal, the initial first pressure to a different second pressure when the row unit encounters the second soil condition.

An amplifier circuit amplifies a signal for wireless transmission. A feedback circuit, including a capacitor, is coupled to the amplifier circuit. Components of the feedback circuit are selected based on a feedback factor such that an input impedance to the amplifier circuit has a same impedance characteristic as a feedback circuit impedance of the feedback circuit.

A system, method, and a computer-readable storage device for sloppy feedback loop compilation are described herein. For example, a dataflow application definition can be obtained. The dataflow application definition may include a feedback loop bounding a compute block. It may then be determined that the feedback loop is to be compiled as a sloppy feedback loop. The dataflow application can then be compiled as an executable object that pipelines the compute block of the dataflow application.

A method for controlling combustion in an engine is provided. The method comprises under a first condition, adjusting an EGR amount of a total cylinder charge in response to engine out NOx levels being below a first threshold. In this way, NOx levels may be used as feedback to control combustion stability.

A dual stage accelerator pedal assembly is provided that is capable of communicating various vehicle operating conditions to the driver as well as notifying the driver of a critical operating condition, such as a low battery pack level, via a change in pedal resistance. The change in pedal resistance is achieved by preloading one of the springs in the accelerator pedal's spring assembly. The spring assembly uses two springs exhibiting different spring force to achieve distinguishable first and second pedal stroke stages.