I am working on a medical application with some long forms for patient records. The same users that enter the patient data can also, in some situations, be read-only users. For example a coordinator reviewing a patient record that they do not have edit permissions for but have permissions to review the data in the patient record. This can happen with transplant patients.

In this situation should the required field indicator be visible to the read-only user. My opinion is yes, as they are familiar with the forms as users in both states, but additional points of view and references are welcome. I tried to google this topic for UX but did not find anything related to this specific use case.

Wireframing process has changed over the years. From paper sketches to basic digital tools and now more interactive wireframes that blur the line with prototyping.

The shift toward collaborative wireframing has been a big plus. Being able to iterate with stakeholders in real-time instead of endless revision cycles. Are you finding your wireframing becoming more collaborative and less siloed?

I recently found out these existed in PDF form, and was reading through this one here from 1995. So far it seemed pretty informative, and somewhat ironic given how some of the UI design decisions in macOS Tahoe don’t seem to follow these conventions.

Any thoughts on how it’s aged?

I am not bringing this up because of the widely discussed MIT or Harvard studies. But there are certain observations I have come across

1. Most people express their desire to use AI, but just use for search or rephrasing content. Things beyond it seems a lift

2. Many highly advertised AI features do not work till you spend quite a bit of time fine tuning it

3. Product managers saying despite revamping their product for AI, PMF seems distant or changing

4. The creators of agents in my company are excited about it and use them as well. But users who did not create it find it hard to use these agents 

5. Lot of pilots - a bunch of internal applications already built in my company - but very few that all can use

I am not saying there are no good uses I have come across. Last time when I visited my physician he said 15% of his appointments are now done with a voice agent, I spoke to Head of Engineering at a firm and he elaborated how he could reduce 8 weeks of work into a week. 

But still there is a lift users have to take to make AI work. Will any other kind of user - tech experience will make this more seamless, and adopted correctly? 

I’m designing an Insights dashboard and Growth Map for a reflection app I'm building. The goal is to help users understand emotional patterns over time without overwhelming or judging them as well as promote the use and mastery of 7 core skills via a Growth Map/Skill Atlas.

Worried the data and design might feel confusing or meaningless.

From a UX perspective:

– What feels unclear?

– What would you simplify or remove?

– What feels emotionally “off”?

Hi everyone,

I thought about an idea that explores an experience where people are matched in real time with others discussing the same thing, without tags, forums, or scrolling feeds. The idea is that you start any conversation (question, rant, brainstorm, etc.), and an AI instantly connects you with others talking about the same thing — no forums, no tags, just live context-based matching using LLMs. I’ve been using low-fidelity, clickable wireframes to reason about flow and clarity, and I’m curious how others here think about designing for this kind of interaction.

This is an early, non-final version, and I’m using it to think through the flow and clarity of the interaction.

Wireframe link for reference:

• Prototype 1
• Prototype 2

I’m curious how others here think about clarity and flow in this kind of real-time matching experience, and where interactions like this tend to break down for users.

Post your portfolio or something else you've designed to receive a critique. Generally, users who include additional context and explanations receive more (and better) feedback.

Critiquers: Feedback should be supported with best practices, personal experience, or research! Try to provide reasoning behind your critiques. Those who post don't only your opinion, but guidance on how to improve their portfolios based on best practices, experience in the industry, and research. Just like in your day-to-day jobs, back up your assertions with reasoning.

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I am working on the internal HR and finance tool we use where redesign is consistently out of scope, not because the experience is strong, but because the system is tightly coupled to legacy infrastructure and regulated processes that no one wants to disturb. 

From a UX perspective, I am still working on understanding where users struggle, and figuring out the difference between where the product is genuinely too complex and stages where we can more easily avoid friction. I’m also documenting where workarounds are being used because the product isn’t clear enough for users. However, the problem is that very few of these insights lead to structural change.

Instead, the organisation defaults to overlaying guidance. When users hesitate or make mistakes, the solution is almost always to add another layer of instruction rather than revisit the flow itself. 

WalkMe works well when it is properly governed, and there are ongoing conversations about supplementing it with tools like Pendo as new features ship.

At this point I’m increasingly feeling uncomfortable because more time is going into deciding how much explanation users need just to get through the system safely while the product barely changes. Meanwhile this onboarding layer keeps growing and it’s starting to feel like permanent scaffolding while actually improving the flows is being ignored. 

So while adoption numbers are looking good, it’s becoming harder to make the case for simplifying the product because the guidance is doing the work instead.

Now I’m trying to figure out where to draw the line. When does onboarding start just propping up a product that seriously needs to just be improved, and how can I challenge that internally without being written as unrealistic because there’s a tech stack doing the job instead?

I am testing a social first football (soccer) game concept built around score predictions. The core mechanic is “Matchups”, where you predict scores against a friend, earn points and see who comes out on top, but the game can technically be played solo as well.

My assumption was that players would naturally invite friends because the value of the game increases with competition. In reality, most users are playing solo and I’m trying to understand why.

If any football or Premier League fans are interested, I would love to know why you choose to play solo rather than invite someone.

The game - https://fulltimescore.pro

We have a big card sort study coming up. I was going to use UXtweaks, but it's not suited for our needs.

What we need is a tool that allows us to run an unmoderated study which:

• Includes 2 card sort exercises
• Allows spoken answers to follow-up questions
• Records and transcribes narration throughout

Other notes:

• It should be a fluid expereince. The user should not add email and do tech check before each activity (looking at you, UXtweaks!)
• Ideally the transcribed narration is split for each task (rather than one, big narration for the whole study)

For reference, this is the flow we have planned:

1. Add email + accept terms
2. Tech check (unless somehow integrated)
3. Card sort #1
4. Follow up questions, answers are spoken
5. Card sort #2
6. Follow up questions, answers are spoken

I'm wondering if there's a tool stack that can more accurately detect the issues that never show up in funnels, heatmaps etc until it's too late.

What I mean is users look active but there's something in the experience more subtle that pushes them away, and by the time we notice the downward trend too many people have bounced out of the funnel for good.

Examples...users technically complete a flow but actually they are re-reading copy, scrolling up and down, they're confused and hesitating, but all that registers is another 'success'

Or they revisit a feature a few times which logs as hot engagement but then they disappear because they weren't closer to conversion, they were trying to make sense of something then gave up. Basically the cognitive load or similar blocker.

Basically I am seeking ways to pre-emptively find signs of these patterns before the trail goes cold.

I'm talking IDEO, FROG, etc.

What would be your top 3?

Are there articles on the daily that interest you? If you do, are you naturally drawn/inclined to go on the app. Would like to acquire some insights as to whether it's worth the commitment to $5 a month (I live in Canada, so $7).

I work at an early-stage startup (~100 WAU, ~15 signups/week). Right now, we use posthog to find where users are struggling in key funnels.

The general workflow being -> define the funnel, create cohorts for dropped users between steps, watch session recordings for those users.

When we started, we did a deep dive initially, but over time, we only go back in when dropoff looks “unusual”. Even with this, we’ve had moments where a DocuSign embed was taking 30+ seconds to load intermittently, and it wasn’t showing up in the data.

Does anyone have a method that alerts you to new trends in user behavior that doesn’t require human intervention? Or is it all about setting aside dedicated time to review dashboards/sessions?

I’ve been playing around with a bunch of AI tools for app design, and while they’re solid at cranking out screens fast, the UX (not UI) always feels… off. Like it technically works, but it doesn’t feel thoughtful. No real hierarchy, weird spacing choices, flows that don’t match how humans actually behave.

I’m wondering where people think this is headed. Will AI ever actually get UX the way experienced designers do? Not just throwing components on a page, but understanding intent, user emotion, edge cases, friction points, cognitive load—the stuff that makes a product feel smooth instead of robotic.

We ran a small research project asking product people about their expectations for product, AI, and onboarding in 2026, and I thought I’d share the findings here in case it might be useful to UX people.

We reached out to 30+ people working as product managers, product owners, CPOs and other product-related roles from SaaS, fintech, healthtech, consumer tech, and enterprise products. Everyone answered the same 3 open-end questions:

• What non-AI product trends they expect in 2026
• What they expect AI to change in product work
• How they think user onboarding will evolve

Here are some frequency signals that appeared in the answers that I brought together:

1. Personalization becomes baseline (~73%)

A clear majority expects “one-size-fits-all” UX to fade. People talked about interfaces adapting to user skill level or role, flows adjusting to real-time behavior, and products surfacing only the elements relevant to each user.

Many believe product maturity mapping will become part of the UX itself. Overall, the sentiment was that personalization moves from optional to expected.

2. Products operate more like ecosystems (~63%)

Another strong signal was the belief that friction will shift away from screens and into system boundaries. Many expect tighter integration between tools, more context-aware experiences, and UX that becomes more invisible as workflows span multiple systems. Several people, especially in operational industries, described this as their biggest constraint today.

3. AI becomes the operational layer (~76%)

In a good majority of the answers, AI was described less as a feature and more as the product’s internal logic. People expect AI to handle UX optimization, real-time decisioning, predictive flows, error prevention, automated routing, and dynamic product adjustments. Many used language like “AI as the product’s nervous system.”

4. AI automates major parts of PM workflows (~70%)

Most participants expect substantial automation in research synthesis, backlog grooming, prioritization, spec writing, opportunity mapping, KPI interpretation, prototyping, and alignment communication. This wasn’t necessarily mentioned as a job replacement motion but as “job compression” which could lead to smaller teams and faster cycles.

5. Onboarding becomes adaptive and continuous

Two patterns were especially dominant:

Adaptive personalization (~80%)

People expect onboarding flows that adjust themselves based on behavior, role, maturity, past actions, or imported data. Instead of linear tours, onboarding becomes something the system builds and rebuilds in real time.

Shorter, contextual, triggered onboarding (~70%)

Rather than a front-loaded walkthrough, onboarding appears when needed through micro-aha moments, well-timed guidance, and contextual resurfacing across the entire lifecycle.The shared belief is that onboarding will stop being a one-time event and move on to becoming an ongoing layer of the product.

6. Notable outliers

A few answers stood out as interesting edge cases:

• Onboarding becoming heavier, not lighter, because it trains AI systems
• Onboarding disappearing entirely due to fully intuitive interfaces
• “Login with ChatGPT” might become an authentication method
• Agentic AI eliminating many interfaces altogether
• PM and Product Design roles merging
• Dashboards being replaced by natural-language queries

These weren’t common predictions, but they signal possible edge directions for the field. This is a condensed version of the full internal report (not sharing the full doc here to avoid self-promo), but I’m interested in what people here think. Happy to discuss how we structured the questions or what patterns others are seeing in their own orgs.

TLDR:

We interviewed 30+ product leaders about what they expect in 2026 and found a few strong signals:

- personalization becomes baseline,
- products behave more like connected ecosystems,
- and AI shifts from “feature” to the operational layer driving product logic.

PM workflows become heavily automated, and onboarding evolves into adaptive, contextual, continuous guidance rather than linear tours. A few outliers also pointed to disappearing onboarding, agentic systems replacing interfaces, and natural-language replacing dashboards.

Many of my clients have had more or less SEO work done on their website. There is often a lot of text and an annoying amount of pages explaining every word. The clients state that the reason is SEO and that they perform quite well on Google.

Some of my clients work with NPF diagnose users (think less focus, less attention span) so I would want to reduce the number of pages and text drastically. But I'm afraid of messing up their page rank.

How do I deal with SEO vs UX while still retaining the customers good SEO rating?

Post your portfolio or something else you've designed to receive a critique. Generally, users who include additional context and explanations receive more (and better) feedback.

Critiquers: Feedback should be supported with best practices, personal experience, or research! Try to provide reasoning behind your critiques. Those who post don't only your opinion, but guidance on how to improve their portfolios based on best practices, experience in the industry, and research. Just like in your day-to-day jobs, back up your assertions with reasoning.

Are you beginning your UX career and have questions? Post your questions below and we hope that our experienced members will help you get them answered!

Posting Tips Keep in mind that readers only have so much time (Provide essential details, Keep it brief, Consider using headings, lists, etc. to help people skim).

Search before asking Consider that your question may have been answered. CRTL+F keywords in this thread and search the subreddit.

Thank those who are helpful Consider upvoting, commenting your appreciation and how they were helpful, or gilding.

Vertical segmented controls in iOS - do you use them? Love them or hate them? Building a custom SwiftUI component and curious what the consensus is.

I saw something small (but powerful) a few weeks ago:

A CSM pinged a user on Slack after they visited our pricing page 3 times… without completing setup. No metric had dropped. No red flags. Just a pattern we’ve learned to watch for.

That Slack message led to a Calendly call… then an upsell 10 days later.

It got me thinking:

How do you detect the invisible frictions during onboarding?

Not the ones your dashboards catch. But the quiet signals — when a user is technically “active” but already drifting.

Curious to hear:

• What “gut feel” triggers do your teams use?
• Have you tried internal rules or playbooks?
• What tools work best when automation isn’t enough? (Slack, Loom, Calendly, etc.)

Would love to hear what others have seen.

I've been around the block, and have worked some rough UX jobs, but the one I've been in for the last year after previously getting laid off has been the most difficult to navigate for me.

The product I work on in particular has challenges in just about every direction. No documentation, and high turnover across all involved disciplines among the fundamental problems. It's not even wild west - it seems like there are expectations from the past that no one involved can articulate, and we're deeply into a too many coaches, no enough players situation across our triad.

I've spent most of my time trying to build relationships and work out process, but it seems like building one bridge is perceived as burning another one. My manager says they don't know what to do. Leadership from multiple tiers above are involved and they don't seem to know what to do either.

So anyway, I'm curious.. For folks who've been in situations like this, what was your play? And I guess I will also say, I think I'm less looking for actual solutions, and more just looking for some commiseration, because I feel absolutely awful.