For nearly three years, Arc from The Browser Company has been my daily driver. To be sure, there was a little bit of a learning curve. Tabs disappeared after a day unless you pinned them. Then they became almost like bookmarks. Tabs were on the left side of the window, not at the top. Spaces let me organize my tabs based on use cases like personal, work, or finances. I could switch between tabs using control-Tab and saw little thumbnails of the pages, similar to the app switcher on my Mac. Shift-command-C copied the current page’s URL. 

All these little interface ideas added up to a productivity machine for web jockeys like myself. And so, I was saddened to hear in May that The Browser Company stopped actively developing Arc in favor of a new AI-powered browser called Dia. (They are keeping Arc updated with maintenance releases.)

They had started beta-testing Dia with college students first and just recently opened it up to Arc members. I finally got access to Dia a few weeks ago. 

But before diving into Dia, I should mention I also got access to another AI browser, Perplexity’s Comet about a week ago. I’m on their Pro plan but somehow got an invite in my email. I had thought it was limited to those on their much more expensive Max plan only. Shhh.

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.

Here we go. Figma has just dropped their S-1, or their registration for an initial public offering (IPO).

While a lot of the risk factors are boilerplate—legalese to cover their bases—the one about AI is particularly interesting, “Competitive developments in AI and our inability to effectively respond to such developments could adversely affect our business, operating results, and financial condition.”

Developments in AI are already impacting the software industry significantly, and we expect this impact to be even greater in the future. AI has become more prevalent in the markets in which we operate and may result in significant changes in the demand for our platform, including, but not limited to, reducing the difficulty and cost for competitors to build and launch competitive products, altering how consumers and businesses interact with websites and apps and consume content in ways that may result in a reduction in the overall value of interface design, or by otherwise making aspects of our platform obsolete or decreasing the number of designers, developers, and other collaborators that utilize our platform. Any of these changes could, in turn, lead to a loss of revenue and adversely impact our business, operating results, and financial condition.

There’s a lot of uncertainty they’re highlighting:

• Could competitors use AI to build competing products?
• Could AI reduce the need for websites and apps which decreases the need for interfaces?
• Could companies reduce workforces, thus reducing the number of seats they buy?

These are all questions the greater tech industry is asking.

Darragh Burke and Alex Kern, software engineers at Figma, writing on the Figma blog:

Building code layers in Figma required us to reconcile two different models of thinking about software: design and code. Today, Figma's visual canvas is an open-ended, flexible environment that enables users to rapidly iterate on designs. Code unlocks further capabilities, but it’s more structured—it requires hierarchical organization and precise syntax. To reconcile these two models, we needed to create a hybrid approach that honored the rapid, exploratory nature of design while unlocking the full capabilities of code.

The solution turned out to be code layers, actual canvas primitives that can be manipulated just like a rectangle, and respects auto layout properties, opacity, border radius, etc.

The solution we arrived at was to implement code layers as a new canvas primitive. Code layers behave like any other layer, with complete spatial flexibility (including moving, resizing, and reparenting) and seamless layout integration (like placement in autolayout stacks). Most crucially, they can be duplicated and iterated on easily, mimicking the freeform and experimental nature of the visual canvas. This enables the creation and comparison of different versions of code side by side. Typically, making two copies of code for comparison requires creating separate git branches, but with code layers, it’s as easy as pressing ⌥ and dragging. This automatically creates a fork of the source code for rapid riffing.

In my experience, it works as advertised, though the code layer element will take a second to render when its spatial properties are edited. Makes sense though, since it's rendering code.

Crazy. Methinks there’s a non-zero chance that someone at v0 read my article and decided to give us designers the control we want.

Can’t wait to try it out.

Peter Yang has been doing some amazing experiments with gen AI tools. There are so many models out there now, so I appreciate him going through and making this post and video.

I made a video testing Claude 4, ChatGPT O3, and Gemini 2.5 head-to-head for coding, writing, deep research, multimodal and more. What I found was that the "best" model depends on what you're trying to do.

Here’s a handy chart to whet your appetite.

I’ve been focused a lot on AI for product design recently, but I think it’s just as important to talk about AI for web design. Though I spend my days now leading a product design team and thinking a lot about UX for creating enterprise software, web design is still a large part of the design industry, as evidenced by the big interest in Framer in the recent Design Tools Survey.

Eric Karkovack writing for The WP Minute:

Several companies have released AI-based site generators; WordPress.com is among the latest. Our own Matt Medeiros took it for a spin. He “chatted” with a friendly bot that wanted to know more about his website needs. Within minutes, he had a website powered by WordPress.

These tools aren’t producing top agency-level websites just yet. Maybe they’re a novelty for the time being. But they’ll improve. With that comes the worry of their impact on freelancers. Will our potential clients choose a bot over a seasoned expert?

Karkovack is right. Current AI tools aren’t making well-thought custom websites yet. So as an agency owner or a freelance designer, you have to defend your position of expertise and customer service:

Those tools have a place in the market. However, freelancers and agencies must position themselves as the better alternative. We should emphasize our expertise and attention to detail, and communicate that AI is a helpful tool, not a magic wand.

But Karkovack misses an opportunity to offer sage advice, which I will do here. Take advantage of these tools in your workflow so that you can be more efficient in your delivery. If you’re in the WordPress ecosystem, use AI to generate some layout ideas, write custom JavaScript, make custom plugins, or write some copy. These AI tools are game-changing, so don’t rest on your laurels.

Tommy Geoco and team are finally out with the results of their 2024 UX Design Tools Survey.

First, two quick observations before I move on to longer ones:

• The respondent population of 2,200+ designers is well-balanced among company size, team structure, client vs. product focus, and leadership responsibility 
• Predictably, Figma dominates the tools stacks of most segments

Surprise #1: Design Leaders Use AI More Than ICs

Some fun, free tools for designers, curated by Danil Vladimirov.

Josh Miller, writing in The Browser Company’s substack:

After a couple of years of building and shipping Arc, we started running into something we called the “novelty tax” problem. A lot of people loved Arc — if you’re here you might just be one of them — and we’d benefitted from consistent, organic growth since basically Day One. But for most people, Arc was simply too different, with too many new things to learn, for too little reward.

“Novelty tax” is another way of saying using non-standard patterns that users just didn’t get. I love Arc. It’s my daily driver. But, Miller is right that it does have a steep learning curve. So there is a natural ceiling to their market.

Miller’s conclusion is where things get really interesting:

Let me be even more clear: traditional browsers, as we know them, will die. Much in the same way that search engines and IDEs are being reimagined [by AI-first products like Perplexity and Cursor]. That doesn’t mean we’ll stop searching or coding. It just means the environments we do it in will look very different, in a way that makes traditional browsers, search engines, and IDEs feel like candles — however thoughtfully crafted. We’re getting out of the candle business. You should too.

“You should too.”

And finally, to bring it back to the novelty tax:

New interfaces start from familiar ones. In this new world, two opposing forces are simultaneously true. How we all use computers is changing much faster (due to AI) than most people acknowledge. Yet at the same time, we’re much farther from completely abandoning our old ways than AI insiders give credit for. Cursor proved this thesis in the coding space: the breakthrough AI app of the past year was an (old) IDE — designed to be AI-native. OpenAI confirmed this theory when they bought Windsurf (another AI IDE), despite having Codex working quietly in the background. We believe AI browsers are next.

Sad to see Arc’s slow death, but excited to try Dia soon.

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.

I was recently featured on the Design of AI podcast to discuss my article that pit eight AI prompt-to-code tools head to head. We talked through the list but I also offered a point of view on where I see the gap.

Arpy Dragffy and Brittany Hobbs close out the episode this way (emphasis mine):

So it's great that Roger did that analysis and that evaluation. I honestly am a bit shocked by those results. Again, his ranking was that Subframe was number one, Onlook was two, v0 number three, Tempo number four. But again, if you look at his matrix, only two of the tools scored over 70 out of 100 and only one of the tools he could recommend. And this really shines a dark light on AI products and their maturity right now. But I suspect that this comes down to the strategy that was used by some of these products. If you go to them, almost every single one of them is actually a coding tool, except the two that scored the highest.

Onlook, its headline is “The Cursor for Designers.” So of course it's a no brainer that makes a lot of sense. That's part of their use cases, but nonetheless it didn't score that good in his matrix.

The top scoring one from his list Subframe is directly positioned to designers. The title is “Design meet code.” It looks like a UI editor. It looks like the sort of tool that designers wish they had. These tools are making it easier for product managers to run research programs, to turn early prototypes and ideas into code to take code and really quick design changes. When you need to make a change to a website, you can go straight into one of these tools and stand up the code.

Listen on Apple Podcasts and Spotify.

I tried early versions of Stable Diffusion be ended up using exclusively Midjourney because of the quality. I’m excited to check out the full list. (Oh, and of course I’ve used DALL-E as well via ChatGPT. But there’s not a lot of control there.)

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.

Karri Saarinen, writing for the Linear blog:

Unbounded AI, much like a river without banks, becomes powerful but directionless. Designers need to build the banks and bring shape to the direction of AI’s potential. But we face a fundamental tension in that AI sort of breaks our usual way of designing things, working back from function, and shaping the form.

I love the metaphor of AI being the a river and we designers are the banks. Feels very much in line with my notion that we need to become even better curators.

Saarinen continues, critiquing the generic chatbox being the primary form of interacting with AI:

One way I visualize this relationship between the form of traditional UI and the function of AI is through the metaphor of a ‘workbench’. Just as a carpenter's workbench is familiar and purpose-built, providing an organized environment for tools and materials, a well-designed interface can create productive context for AI interactions. Rather than being a singular tool, the workbench serves as an environment that enhances the utility of other tools – including the ‘magic’ AI tools.

Software like Linear serves as this workbench. It provides structure, context, and a specialized environment for specific workflows. AI doesn’t replace the workbench, it's a powerful new tool to place on top of it.

It’s interesting. I don’t know what Linear is telegraphing here, but if I had to guess, I wonder if it’s closer to being field-specific or workflow-specific, similar to Generative Fill in Photoshop. It’s a text field—not textarea—limited to a single workflow.