Christopher K. Wong argues that desirability is a key part of design that helps decide which features users really want:

To give a basic definition, desirability is a strategic part of UX that revolves around a single user question: Have you defined (and solved) the right problem for users?

In other words, before drawing a single box or arrow, have you done your research and discovery to know you’re solving a pain point?

The way the post is written makes it hard to get at a succinct definition, but here’s my take. Desirability is about ensuring a product or feature is truly wanted, needed, and chosen by users—not just visual appeal—making it a core pillar for impactful design decisions and prioritization. And designers should own this.

Coincidentally, I was considering adding a service designer to my headcount plan when this article came across my feeds. Perfect timing. It’s hard to imagine that service design as a discipline is so young—only since 2012 according to the author.

Joe Foley, writing in Creative Bloq:

As a discipline, service design is still relatively new. A course at the Royal College of Art in London (RCA) only began in 2012 and many people haven’t even heard of the term. But that’s starting to change.

He interviews designer Clive Grinyer, whose new book on service design has just come out. He was co-founder of the design consultancy Tangerine, Director of Design and Innovation for the UK Design Council, and Head of Service Design at the Royal College of Art.

Griner:

Great service design is often invisible as it solves problems and removes barriers, which isn’t necessarily noticed as much as a shiny new product. The example of GDS (Government Digital Service) redesigning every government department from a service design perspective and removing many frustrating and laborious aspects of public life from taxing a car to getting a passport, is one of the best.

The key difference between service design and UX is that it’s end product is not something on a screen:

But service design is not just the experience we have through the glass of a screen or a device: it’s designed from the starting point of the broader objective and may include many other channels and touchpoints. I think it was Colin Burns who said a product is just a portal to a service.

In other words, if you open the aperture of what user experience means, and take on the challenge of designing real-world processes, flows, and interaction—that is service design.

Luke Wroblewski, writing in his blog:

Across several of our companies, software development teams are now “out ahead” of design. To be more specific, collaborating with AI agents (like Augment Code) allows software developers to move from concept to working code 10x faster. This means new features become code at a fast and furious pace.

When software is coded this way, however, it (currently at least) lacks UX refinement and thoughtful integration into the structure and purpose of a product. This is the work that designers used to do upfront but now need to “clean up” afterward. It’s like the development process got flipped around. Designers used to draw up features with mockups and prototypes, then engineers would have to clean them up to ship them. Now engineers can code features so fast that designers are ones going back and cleaning them up.

This is what I’ve been secretly afraid of. That we would go back to the times when designers were called in to do cleanup. Wroblewski says:

Instead of waiting for months, you can start playing with working features and ideas within hours. This allows everyone, whether designer or engineer, an opportunity to learn what works and what doesn’t. At its core rapid iteration improves software and the build, use/test, learn, repeat loop just flipped, it didn’t go away.

Yeah, or the feature will get shipped this way and be stuck this way because startups move fast and move on.

My take is that as designers, we need to meet the moment and figure out how to build design systems and best practices into the agentic workflows our developer counterparts are using.

Sonos announced yesterday that interim CEO Tom Conrad was made permanent. From their press release:

Sonos has achieved notable progress under Mr. Conrad’s leadership as Interim CEO. This includes setting a new standard for the quality of Sonos’ software and product experience, clearing the path for a robust new product pipeline, and launching innovative new software enhancements to flagship products Sonos Ace and Arc Ultra.

Conrad surely navigated this landmine well after the disastrous app redesign that wiped almost $500 million from the company’s market value and cost CEO Patrick Spence his job. My sincere hope is that Conrad continues to rebuild Sonos’s reputation by continuing to improve their products.

This is a really well-written piece that pulls the AI + design concepts neatly together. Sharang Sharma, writing in UX Collective:

As AI reshapes how we work, I’ve been asking myself, it’s not just how to stay relevant, but how to keep growing and finding joy in my craft.

In my learning, the new shift requires leveraging three areas

1. AI tools: Assembling an evolving AI design stack to ship fast
2. AI fluency: Learning how to design for probabilistic systems
3. Human-advantage: Strengthening moats like craft, agency and judgment to stay ahead of automation

Together with strategic thinking and human-centric skills, these pillars shape our path toward becoming an AI-native designer.

Sharma connects all the crumbs I’ve been dropping this week:

• Designing for AI interfaces
• Designing for control
• Understanding orchestration and agents
• Prompt and context engineering
• Being AI native

From UX Magazine:

Copilots helped enterprises dip their toes into AI. But orchestration platforms and tools are where the real transformation begins — systems that can understand intent, break it down, distribute it, and deliver results with minimal hand-holding.

Think of orchestration as how “meta-agents” are conducting other agents.

The first iteration of AI in SaaS was copilots. They were like helpful interns eagerly awaiting your next command. Orchestration platforms are more like project managers. They break down big goals into smaller tasks, assign them to the right AI agents, and keep everything coordinated. This shift is changing how companies design software and user experiences, making things more seamless and less reliant on constant human input.

For designers and product teams, it means thinking about workflows that cross multiple tools, making sure users can trust and control what the AI is doing, and starting small with automation before scaling up.

Let’s stay on the train of designing AI interfaces for a bit. Here’s a piece by Rob Chappell in UX Collective where he breaks down how to give users control—something I’ve been advocating—when working with AI.

AI systems are transforming the structure of digital interaction. Where traditional software waited for user input, modern AI tools infer, suggest, and act. This creates a fundamental shift in how control moves through a experience or product — and challenges many of the assumptions embedded in contemporary UX methods.

The question is no longer: “What is the user trying to do?”

The more relevant question is: “Who is in control at this moment, and how does that shift?”

Designers need better ways to track how control is initiated, shared, and handed back — focusing not just on what users see or do, but on how agency is negotiated between human and system in real time.

Most design frameworks still assume the user is in the driver’s seat. But AI is changing the rules. The challenge isn’t just mapping user flows or intent—it’s mapping who holds the reins, and how that shifts, moment by moment. Designers need new tools to visualize and shape these handoffs, or risk building systems that feel unpredictable or untrustworthy. The future of UX is about negotiating agency, not just guiding tasks.

Vitaly Friedman writes a good primer on the design possibilities for users to interact with AI features. As AI capabilities become more and more embedded in the products designers make, we have to become facile in manipulating AI as material.

Many products are obsessed with being AI-first. But you might be way better off by being AI-second instead. The difference is that we focus on user needs and sprinkle a bit of AI across customer journeys where it actually adds value.

Since its debut at Config back in May, Figma has steadily added practical features to Figma Make for product teams. Supabase integration now allows for authentication, data storage, and file uploads. Designers can import design system libraries, which helps maintain visual consistency. Real-time collaboration has improved, giving teams the ability to edit code and prototypes together. The tool now supports backend connections for managing state and storing secrets. Prototypes can be published to custom domains. These changes move Figma Make closer to bridging the gap between design concepts and advanced prototypes.

In my opinion, there’s a stronger relationship between Sites and Make than there is Make and Design. The Make-generated code may be slightly better than when Sites debuted, but it is still not semantic.

Anyhow, I think Make is great for prototyping and it’s convenient to have it built right into Figma. Julius Patto, writing in UX Collective:

Prompting well in Figma Make isn’t about being clever, it’s about being clear, intentional, and iterative. Think of it as a new literacy in the design toolkit: the better you get at it, the more you unlock AI’s potential without losing your creative control.

Ted Goas, writing in UX Collective:

I predict the early parts of projects, getting from nothing to something, will become shared across roles. For designers looking to branch out, code is a natural next step. I see a future where we’re fixing small bugs ourselves instead of begging an engineer, implementing that animation that didn’t make the sprint but you know would absolutely slap, and even building simple features when engineering resources are tight.

Our new reality is that anyone can make a rough draft.

But that doesn’t mean those drafts are good. That’s where our training and taste come in.

I think Goas is right and it echoes the AI natives post by Elena Verna. I wrote a little more extensively in my newsletter over the weekend.

Miquad Jaffer, a product leader at OpenAI shares his 4D method on how to build AI products that users want. In summary, it’s…

• Discover: Find and prioritize real user pain points and friction in daily workflows.
• Design: Make AI features invisible and trustworthy, fitting naturally into users’ existing habits.
• Develop: Build AI systematically, with robust evaluation and clear plans for failures or edge cases.
• Deploy: Treat each first use like a product launch, ensuring instant value and building user trust quickly.

Geoffrey Litt, Josh Horowitz, Peter van Hardenberg, and Todd Matthews writing a paper for research lab Ink & Switch, offer a great, well-thought piece on what they call “malleable software.”

We envision a new kind of computing ecosystem that gives users agency as co-creators. … a software ecosystem where anyone can adapt their tools to their needs with minimal friction. … When we say ‘adapting tools’ we include a whole range of customizations, from making small tweaks to existing software, to deep renovations, to creating new tools that work well in coordination with existing ones. Adaptation doesn’t imply starting over from scratch.

In their paper, they use analogies like kitchen tools and tool arrangement in a workshop to explore their idea. With regard to the current crop of AI prompt-to-code tools…

We think these developments hold exciting potential, and represent a good reason to pursue malleable software at this moment. But at the same time, AI code generation alone does not address all the barriers to malleability. Even if we presume that every computer user could perfectly write and edit code, that still leaves open some big questions.

How can users tweak the existing tools they’ve installed, rather than just making new siloed applications? How can AI-generated tools compose with one another to build up larger workflows over shared data? And how can we let users take more direct, precise control over tweaking their software, without needing to resort to AI coding for even the tiniest change? None of these questions are addressed by products that generate a cloud-hosted application from a prompt.

Kind of a different take than the “personal software” we’ve seen written about before.

I love this from Marc Brooker:

Every organization and industry has watering holes where the whiners hang out. The cynical. The jaded. These spots feel attractive. Everybody has something they can complain about, and complaining is fun. These places are inviting and inclusive: as long as you’re whining, or complaining, or cynical, you’re in. If you’re positive, optimistic, or ambitious, you’re out.

Avoid these places.

I’ve seen this firsthand on Reddit. Seems like the r/graphic_design and r/UXDesign subreddits have been full of posts decrying the state of the job market and attacking AI. Any meaningful conversations about the work or debates about AI are too few and far between.

Brooker again:

My advice: find the yes, and communities, and spend time there. Find the people doing cool stuff you admire, and spend time with them. Find the people doing the work you want to do, or living the life you want to live, and find ways to learn from them.

Those are hard to find online. If you know of any, please let me know!

This piece from Mike Schindler is a good reminder that a lot of the content we see on LinkedIn is written for engagement. It’s a double-edged sword, isn’t it? We want our posts to be read, commented upon, and shared. We see the patterns that get a lot of reactions and we mimic them.

We’re losing ourselves to our worst instincts. Not because we’re doomed, but because we’re treating this moment like a game of hot takes and hustle. But right now is actually a rare and real opportunity for a smarter, more generous conversation — one that helps our design community navigate uncertainty with clarity, creativity, and a sense of shared agency.

But the point that Schindler is making is this: AI is a fundamental shift in the technology landscape that demands nuanced and thoughtful discourse. There’s a lot of hype. But as technologists, designers, and makers of products, we really need to lead rather than scare.

I’ve tried to do that in my writing (though I may not always be successful). I hope you do too.

He has this handy table too…

Designed by Mike Schindler (mschindler.com)

I remember the article from 2016 titled “Hamburger Menus and Hidden Navigation Hurt UX Metrics” where the conclusion from NN/g was:

Discoverability is cut almost in half by hiding a website’s main navigation. Also, task time is longer and perceived task difficulty increases.

Fast forward nearly 10 years later and NN/g says:

Hamburger menus are a more familiar pattern today than 10 years ago, but the same old best practices for hidden navigation still apply.

Kate Kaplan, revisiting her conclusion from nearly a decade ago:

Over the past decade, the hamburger menu — much like its namesake — has become a classic. As mobile-first design took hold, it offered a clean, space-saving solution, and when design leaders like Apple and Amazon adopted it, others followed. Its growing ubiquity helped standardize its meaning: Through repeated exposure, users learned to recognize and interpret the icon with increasing confidence.

I think the hamburger menu grew in popularity despite NN/g’s authoritative finger wagging. As designers, most of the time, we have to balance between the needs of the project and client with known best practices. Many websites, especially e-commerce, don’t have four or fewer main navigation links. We had to put the links somewhere and the hamburger menu made sense.

Christopher Butler writes a wonderful essay about the “best interfaces we never built,” exploring the UIs from sci-fi:

Science fiction, by the way, hasn’t just predicted our technological future. We all know the classic examples, particularly those from Star Trek: the communicator and tricorder anticipated the smartphone; the PADD anticipated the tablet; the ship’s computer anticipated Siri, Alexa, Google, and AI voice interfaces; the entire interior anticipated the Jony Ive glass filter on reality. It’s enough to make a case that Trek didn’t anticipate these things so much as those who watched it as young people matured in careers in design and engineering. But science fiction has also been a fertile ground for imagining very different ways for how humans and machines interact.

He goes on to namecheck 2001: A Space Odyssey, Quantum Leap, Inspector Gadget and others. I don’t know Butler personally, but I’d bet $1 he’s Gen X like me.

As UX designers, it’s very easy to get stuck thinking that UI is just pixels rendered on a screen. But in fact, an interface is anything that translates our intentions into outcomes that technology can deliver.

Vincent Nguyen writing for Yanko Design, interviewing Alan Dye, VP of Human Interface Design at Apple:

This technical challenge reveals the core problem Apple set out to solve: creating a digital material that maintains form-changing capabilities while preserving transparency. Traditional UI elements either block content or disappear entirely, but Apple developed a material that can exist in multiple states without compromising visibility of underlying content. Dye’s emphasis on “celebrating user content” exposes Apple’s hierarchy philosophy, where the interface serves content instead of competing with it. When you tap to magnify text, the interface doesn’t resize but stretches and flows like liquid responding to pressure, ensuring your photos, videos, and web content remain the focus while navigation elements adapt around them.

Since the Jony Ive days, Apple’s hardware has always been about celebrating the content. Bezels got smaller. Screens got bigger and brighter. Even the flat design brought on by iOS 7 and eventually adopted by the whole ecosystem was a way to strip away the noise and focus on the content.

Dye’s explanation of the “glass layer versus application layer” architecture provides insight into how Apple technically implements this philosophy. The company has created a distinct separation between functional controls (the glass layer) and user content (the application layer), allowing each to behave according to different rules while maintaining visual cohesion. This architectural decision enables the morphing behavior Dye described, where controls can adapt and change while content remains stable and prominent.

The Apple platform UI today sort of does that, but Liquid Glass seems to take it even further.

Nguyen about his experience using the Music app on Mac:

The difference from current iOS becomes apparent in specific scenarios. In the current Music app, scrolling through your library feels like moving through flat, static layers. With Liquid Glass, scrolling creates a sense of depth. You can see your album artwork subtly shifting beneath the translucent controls, creating spatial awareness of where interface elements sit in relation to your content. The tab bar doesn’t just scroll with you; it creates gentle optical distortions that make the underlying content feel physically present beneath the glass surface.

Sara Paul writing for NN/g:

The core principles of UX and product design remain unchanged, and AI amplifies their importance in many ways. To stay indispensable, designers must evolve: adapt to new workflows, deepen their judgment, and double down on the uniquely human skills that AI can’t replace.

They spoke with seven UX practitioners to get their take on AI and the design profession.

I think this is great advice and echoes what I’ve written about previously (here and here):

There is a growing misconception that AI tools can take over design, engineering, and strategy. However, designers offer more than interaction and visual-design skills. They offer judgment, built on expertise that AI cannot replicate.

Our panelists return to a consistent message: across every tech hype cycle, from responsive design to AI, the value of design hasn’t changed. Good design goes deeper than visuals; it requires critical thinking, empathy, and a deep understanding of user needs.

“Beating AI” is an interesting framing, but OK. There is a lot of concern out there about how AI will affect the entire design industry, from graphic design to UX. Understandably, designers are worried about their careers.

Georgia Coggan writing for Creative Bloq:

“So are we just cooked?” asks a recent Reddit thread from a designer who is four years out of college. ” Any other jobs i can get with such a degree now that design is kind of becoming obsolete?”

Hundreds of responses poured in from designers with strong and diverse opinions on what AI is doing to the graphic design industry – and it isn’t all as doom and gloom as you might fear. Ranging from advice around what humans can do that AI can’t, to how nothing has really changed regarding what the industry needs from its designers, there’s lots for the OP to feel positive about – as long as they’re happy to stay agile. Head over to the Reddit thread to garner more wisdom from those in the field.

Great reminder from Kai Wong about getting stuck on a solution too early:

Imagine this: the Product Manager has a vision of a design solution based on some requirements and voices it to the team. They say, “I want a table that allows us to check statuses of 100 devices at once.”

You don’t say anything, so that sets the anchor of a design solution as “a table with a bunch of devices and statuses.”