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11 min read
Purple lobster with raised claws on a lit wooden platform in an underwater cave, surrounded by smaller crabs, coral and lanterns

OpenClaw and the Agentic Future

Last week an autonomous AI agent named OpenClaw (fka Clawd, fka Moltbot) took the tech community by storm, including a run on Mac minis as enthusiasts snapped them up to host OpenClaw 24/7. In case you’re not familiar, the app is a mostly unrestricted AI agent that lives and runs on your local machine or on a server—self-hosted, homelab, or otherwise. What can it do? You can connect it to your Google accounts, social media accounts, and others and it can act as your pretty capable AI assistant. It can even code its own capabilities. You chat with it through any number of familiar chat apps like Slack, Telegram, WhatsApp, and even iMessage.

Federico Viticci, writing in MacStories:

To say that Clawdbot has fundamentally altered my perspective of what it means to have an intelligent, personal AI assistant in 2026 would be an understatement. I’ve been playing around with Clawdbot so much, I’ve burned through 180 million tokens on the Anthropic API (yikes), and I’ve had fewer and fewer conversations with the “regular” Claude and ChatGPT apps in the process. Don’t get me wrong: Clawdbot is a nerdy project, a tinkerer’s laboratory that is not poised to overtake the popularity of consumer LLMs any time soon. Still, Clawdbot points at a fascinating future for digital assistants, and it’s exactly the kind of bleeding-edge project that MacStories readers will appreciate.

16 min read
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When the Music Stopped: Inside the Sonos App Disaster

The fall of Sonos isn’t as simple as a botched app redesign. Instead, it is the cumulative result of poor strategy, hubris, and forgetting the company’s core value proposition. To recap, Sonos rolled out a new mobile app in May 2024, promising “an unprecedented streaming experience.” Instead, it was a severely handicapped app, missing core features and broke users’ systems. By January 2025, that failed launch wiped nearly $500 million from the company’s market value and cost CEO Patrick Spence his job.

What happened? Why did Sonos go backwards on accessibility? Why did the company remove features like sleep timers and queue management? Immediately after the rollout, the backlash began to snowball into a major crisis.

A collage of torn newspaper-style headlines from Bloomberg, Wired, and The Verge, all criticizing the new Sonos app. Bloomberg’s headline states, “The Volume of Sonos Complaints Is Deafening,” mentioning customer frustration and stock decline. Wired’s headline reads, “Many People Do Not Like the New Sonos App.” The Verge’s article, titled “The new Sonos app is missing a lot of features, and people aren’t happy,” highlights missing features despite increased speed and customization.

13 min read
A futuristic scene with a glowing, tech-inspired background showing a UI design tool interface for AI, displaying a flight booking project with options for editing and previewing details. The screen promotes the tool with a “Start for free” button.

Beyond the Prompt: Finding the AI Design Tool That Actually Works for Designers

There has been an explosion of AI-powered prompt-to-code tools within the last year. The space began with full-on integrated development environments (IDEs) like Cursor and Windsurf. These enabled developers to use leverage AI assistants right inside their coding apps. Then came a tools like v0, Lovable, and Replit, where users could prompt screens into existence at first, and before long, entire applications.

A couple weeks ago, I decided to test out as many of these tools as I could. My aim was to find the app that would combine AI assistance, design capabilities, and the ability to use an organization’s coded design system.

While my previous essay was about the future of product design, this article will dive deep into a head-to-head between all eight apps that I tried. I recorded the screen as I did my testing, so I’ve put together a video as well, in case you didn’t want to read this.

9 min read
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Generative UI and the Ephemeral Interface

This week, Google debuted their Gemini 3 AI model to great fanfare and reviews. Specs-wise, it tops the benchmarks. This horserace has seen Google, Anthropic, and OpenAI trade leads each time a new model is released, so I’m not really surprised there. The interesting bit for us designers isn’t the model itself, but the upgraded Gemini app that can create user interfaces on the fly. Say hello to generative UI.

I will admit that I’ve been skeptical of the notion of generative user interfaces. I was imagining an app for work, like a design app, that would rearrange itself depending on the task at hand. In other words, it’s dynamic and contextual. Adobe has tried a proto-version of this with the contextual task bar. Theoretically, it surfaces up the most pertinent three or four actions based on your current task. But I find that it just gets in the way.

When Interfaces Keep Moving

Others have been less skeptical. More than 18 months ago, NN/g published an article speculating about genUI and how it might manifest in the future. They define it as:

A generative UI (genUI) is a user interface that is dynamically generated in real time by artificial intelligence to provide an experience customized to fit the user’s needs and context. So it’s a custom UI for that user at that point in time. Similar to how LLMs answer your question: tailored for you and specific to when that you asked the original question.

9 min read
Collection of iOS interface elements showcasing Liquid Glass design system including keyboards, menus, buttons, toggles, and dialogs with translucent materials on dark background.

Breaking Down Apple’s Liquid Glass: The Tech, The Hype, and The Reality

I kind of expected it: a lot more ink was spilled on Liquid Glass—particularly on social media. In case you don’t remember, Liquid Glass is the new UI for all of Apple’s platforms. It was announced Monday at WWDC 2025, their annual developers conference.

The criticism is primarily around legibility and accessibility. Secondary reasons include aesthetics and power usage to animate all the bubbles.

8 min read
Colorful illustration featuring the Figma logo on the left and a whimsical character operating complex, abstract machinery with gears, dials, and mechanical elements in vibrant colors against a yellow background.

Figma Make: Great Ideas, Nowhere to Go

Nearly three weeks after it was introduced at Figma Config 2025, I finally got access to Figma Make. It is in beta and Figma made sure we all know. So I will say upfront that it’s a bit unfair to do an official review. However, many of the tools in my AI prompt-to-code shootout article are also in beta. 

Since this review is fairly visual, I made a video as well that summarizes the points in this article pretty well.

14 min read
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The Design Industry Created Its Own Talent Crisis. AI Just Made It Worse.

This is the first part in a three-part series about the design talent crisis. Read Part II and Part III.

Part I: The Vanishing Bottom Rung

Erika Kim’s path to UX design represents a familiar pandemic-era pivot story, yet one that reveals deeper currents about creative work and economic necessity. Armed with a 2020 film and photography degree from UC Riverside, she found herself working gig photography—graduations, band events—when the creative industries collapsed. The work satisfied her artistic impulses but left her craving what she calls “structure and stability,” leading her to UX design. The field struck her as an ideal synthesis, “I’m creating solutions for companies. I’m working with them to figure out what they want, and then taking that creative input and trying to make something that works best for them.”

Since graduating from the interaction design program at San Diego City College a year ago, she’s had three internships and works retail part-time to pay the bills. “I’ve been in survival mode,” she admits. On paper, she’s a great candidate for any junior position. Speaking with her reveals a very thoughtful and resourceful young designer. Why hasn’t she been able to land a full-time job? What’s going on in the design job market? 

Every team I’ve ever led has had one of these people. The person who writes the doc that gives the project its shape, who closes context gaps in one-on-ones before they turn into conflicts, who somehow keeps six workstreams from drifting apart. They rarely get the credit they deserve because the work, when it’s done well, looks like it just happened on its own.

Hardik Pandya writes about this on his blog. He shares a quote from a founder friend describing his most valuable employee:

“She’s the reason things actually work around here. She just… makes sure everything happens. She writes the docs. She runs the meetings that matter. She talks to people. Somehow everything she touches stays on track. I don’t know how I’d even describe what she does to a person outside the company. But if she left, we’d fall apart in a month. Maybe less.”

I’ve known people like this at every company I’ve worked at. And I’ve watched them get passed over because the performance system couldn’t see them. Pandya nails why:

When a project succeeds, credit flows to the people whose contributions are easy to describe. The person who presented to the board. The person whose name is on the launch email. The person who shipped the final feature. These contributions are real, I’m not diminishing them. But they’re not more real than the work that made them possible. They’re just easier to point at.

Most organizations try to fix this by telling the invisible workers to “be more visible”—present more, build your personal brand internally. Pandya’s advice goes the other direction, and I think he’s right:

If you’re good at the invisible work, the first move isn’t to get better at visibility. It’s to find the leader who doesn’t need you to be visible.

As a leader, I take this as a challenge. If someone on my team is doing the work that holds everything together, it’s my job to make sure the organization sees it too—especially when it doesn’t announce itself.

Sketch portrait, title "THE INVISIBLE WORK" and hvpandya.com/notes on pale blue left; stippled open book and stars on black right.

The Invisible Work

The coordination work that holds projects together disappears the moment it works. On the unfairness of recognition and finding leaders who see it anyway.

hvpandya.com iconhvpandya.com

Earlier this week I linked to Gale Robins’ argument that AI makes execution cheap but doesn’t help you decide what to build. Christina Wodtke is making the same case from the research side.

Christina Wodtke opens with a designer who spent two weeks vibe-coding a gratitude journaling app. Beautiful interface, confetti animations, gentle notifications. Then she showed it to users. “I don’t really journal,” said the first one. “Gratitude journaling felt performative,” said the second. Two weeks building the wrong thing. Wodtke’s diagnosis:

That satisfaction is a trap. You’re accumulating artifacts that may have nothing to do with what anyone needs.

Wodtke draws a line between need-finding and validation that I think a lot of teams blur. Skipping the first and jumping to the second means you’re testing your guess, not understanding the problem:

Need-finding happens before you have a solution. You’re listening to people describe their lives, their frustrations, their workarounds. You’re hunting for problems that actually exist—problems people care enough about that they’re already trying to solve them with spreadsheets and sticky notes and whatever else they’ve cobbled together.

Wodtke’s version of fast looks different from what you’d expect:

The actual fast path is unsexy: sit down with five to ten people. Ask them about their lives. Shut up and listen. Use those three magic words—“tell me more”—every time something interesting surfaces. Don’t show them anything. Don’t pitch. Just listen.

“You’ll build less. It’ll be the right thing.” When building is cheap, the bottleneck moves upstream to judgment, knowing what to build. That judgment comes from listening, not prompting.

Solid black square with no visible details.

Vibe-Coding Is Not Need-Finding

Last month a product designer showed me her new prototype. She’d spent two weeks vibe-coding a tool for tracking “gratitude journaling streaks.” The interface was beautiful. Confe…

eleganthack.com iconeleganthack.com

Earlier I linked to Hardik Pandya’s piece on invisible work—the coordination, the docs, the one-on-ones that hold projects together but never show up in a performance review. Designers have their own version of this problem, and it’s getting worse.

Kai Wong, writing in his Data and Design Substack, puts it plainly. A design manager he interviewed told him:

“It’s always been a really hard thing for design to attribute their hard work to revenue… You can make the most amazingly satisfying user experience. But if you’re not bringing in any revenue out of that, you’re not going to have a job for very much longer. The company’s not going to succeed.”

That’s always been true, but AI made it urgent. When a PM can generate something that “looks okay” using an AI tool, the question is obvious: what do we need designers for? Wong’s answer is the strategic work—research, translation between user needs and business goals. The trouble is that this work is the hardest to see.

Wong’s practical advice is to stop presenting design decisions in design terms. Instead of explaining that Option A follows the Gestalt principle of proximity, say this:

“Option A reduces checkout from 5 to 3 steps, making it much easier for users to complete their purchase instead of abandoning their cart.”

You’re not asking “which looks better?” You’re showing that you understand the business problem and the user problem, and can predict outcomes based on behavioral patterns.

I left a comment on this article when it came out, asking how these techniques translate at the leadership level. It’s one thing to help individual designers frame their work in business terms. It’s another to make an entire design org’s contribution legible to the rest of the company. Product management talks to customers and GTM teams. Engineering delivers features. Design is in the messy middle making sense of it all—and that sense-making is exactly the kind of invisible work that’s hardest to put on a slide.

Figure draped in a white sheet like a ghost wearing dark sunglasses, standing among leafy shrubs with one hand visible.

Designers often do invisible work that matters. Here’s how to show it

What matters in an AI-integrated UX department? Highlighting invisible work

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