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.

This post has been swimming in my head since I read it. Elena Verna, who joined Lovable just over a month ago to lead marketing and growth, writing in her newsletter, observes that everyone at the company is an AI-native employee. “An AI-native employee isn’t someone who ‘uses AI.’ It’s someone who defaults to AI,” she says.

On how they ship product:

Here, when someone wants to build something (anything) - from internal tools, to marketing pages, to writing production code - they turn to AI and… build it. That’s it.

No headcount asks. No project briefs. No handoffs. Just action.

At Lovable, we’re mostly building with… Lovable. Our Shipped site is built on Lovable. I’m wrapping hackathon sponsorship intake form in Lovable as we speak. Internal tools like credit giveaways and influencer management? Also Lovable (soon to be shared in our community projects so ya’ll can remix them too). On top of that, engineering is using AI extensively to ship code fast (we don’t even really have Product Managers, so our engineers act as them).

I’ve been hearing about more and more companies operating this way. Crazy time to be alive.

More on this topic in a future long-form post.

Stephen Heller, writing for PRINT magazine, revisits a long out-of-print book called *Visual Persuasion *by Stephen Baker, a creative director from the Mad Men era of advertising.

Although published in 1961, Visual Persuasion has as much relevance, vitality, insight, vision and spunk as any recently published book (including those that I’ve authored). The truth is this: I wish I had written it. Even though it is nearly 65 years out of print (and contains its share of outdated mores and stereotypes), it easily could still serve (with a minute refresh) to provide ideas to ward off what designers fear is the inevitable AI apocalypse—an end to original thinking and making, visual or otherwise.

One maxim, Heller notes:

Eye movements are based on conditioned reflexes. “Left-to-right habit makes our eyes travel clockwise in exploring a [layout],” Baker notes. The optical center of a page is slightly to the left. The tendency is to focus attention on a person’s eyes more than on any other part of their face. This mirrors one’s emotions with fair accuracy.

Read past some of the hyperbole in this piece by Andy Budd. I do think the message is sound.

If you’re working at a fast-growth tech startup, you’re probably already feeling the pressure. Execs want more output with fewer people. Product and engineering are experimenting with AI tooling. And you’re being asked to move faster than ever — with less clarity on what the team should even own.

I will admit that I personally feel this pressure too. Albeit, not from my employer but from the chatter in our industry. I’m observing the younger companies experiment with the process, collapsing roles, and expanding responsilities.

As AI eats into the production layer, the traditional boundaries between design and engineering are starting to dissolve. Many of the tasks once owned by design will soon be handled by others — or by machines.

Time will tell when this becomes widespread. I think designers will be asked to ship more code. And PMs and engineers may ship small design tweaks.

The reality is, we’ll likely need fewer designers overall. But the ones we do need will be more specialised, more senior, and more strategically valuable than ever before.

You’ll want AI-literate, full-stack designers — people who are comfortable working across the entire product surface, from UX to code, and from interface to infrastructure. Designers who can navigate ambiguity, embrace new tooling, and confidently operate in the blurred space between design and engineering.

I don’t know if I agree with the fewer number of designers. At least not in the near-term. The more AI is embedded into app experiences, the trend—I predict—will go in the opposite direction. The term “AI as material” has been floating around for a few months, but I think its meaning will morph. AI will be the new UI, and thus we need designers to help define those experiences.

Tom Scott, giving advice to startups about how to hire designers:

The worst thing for a designer is join a company under the premise they are going to invest in craft and never get serious about it. This results in the designer getting stuck in an average company, making it harder for them to move into a top-tier design-led company afterwards.

The TL;DR is if you’re serious about hiring great talent, put your money where your mouth is, create the right environment and get serious about design like you do with product, eng, marketing etc.

While the post is aimed at startup employers, it’s good for designers to understand the advice they’re being given.

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)

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

Rollup of stats from Figma’s S-1.

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.

Christoph Niemann, in a visual essay about generative AI and art:

…the biggest challenge is that writing an A.I. prompt requires the artist to know what he wants. If only it were that simple.

Creating art is a nonlinear process. I start with a rough goal. But then I head into dead ends and get lost or stuck.

The secret to my process is to be on high alert in this deep jungle for unexpected twists and turns, because this is where a new idea is born.

It’s a fun meditation on the meaning of AI-assisted and AI-generated artwork.

David Singleton, writing in his blog:

Somewhere in the last few months, something fundamental shifted for me with autonomous AI coding agents. They’ve gone from a “hey this is pretty neat” curiosity to something I genuinely can’t imagine working without. Not in a hand-wavy, hype-cycle way, but in a very concrete “this is changing how I ship software” way.

I have to agree. My recent tinkering projects with Cursor using Claude 4 Sonnet (and set to Cursor’s MAX mode) have been much smoother and much more autonomous.

And Singleton has found that Claude Code and OpenAI Codex are good for different things:

For personal tools, I’ve completely shifted my approach. I don’t even look at the code anymore - I describe what I want to Claude Code, test the result, make some minor tweaks with the AI and if it’s not good enough, I start over with a slightly different initial prompt. The iteration cycle is so fast that it’s often quicker to start over than trying to debug or modify the generated code myself. This has unlocked a level of creative freedom where I can build small utilities and experiments without the usual friction of implementation details.

And the larger point Singleton makes is that if you direct the right context to the reasoning model, it can help you solve your problem more effectively:

This points to something bigger: there’s an emerging art to getting the right state into the context window. It’s sometimes not enough to just dump code at these models and ask “what’s wrong?” (though that works surprisingly often). When stuck, you need to help them build the same mental framework you’d give to a human colleague. The sequence diagram was essentially me teaching Claude how to think about our OAuth flow. In another recent session, I was trying to fix a frontend problem (some content wouldn’t scroll) and couldn’t figure out where I was missing the correct CSS incantation. Cursor’s Agent mode couldn’t spot it either. I used Chrome dev tools to copy the entire rendered HTML DOM out of the browser, put that in the chat with Claude, and it immediately pinpointed exactly where I was missing an overflow: scroll.

For my designer audience out there—likely 99% of you—I think this post is informative as to how to work with reasoning models like Claude 4 or o4. This can totally apply to prompt-to-code tools like Lovable and v0. And these ideas can likely apply to Figma Make and Subframe.

Brian Balfour, writing for the Reforge blog:

Speed isn’t just about shipping faster, it’s about accelerating your entire learning metabolism. The critical metric isn’t feature velocity but rather your speed through the complete Insight → Act → Learn loop. This distinction separates products that compound advantages from those that compound technical debt.

The point being that now with AI, product teams are shipping faster. And those who aren’t might get lapped (to use an F1 phrase).

It’s been said that desktop publishing democratized graphic design. For those of you too young to know what the term means, it means the technology that enabled graphic design to go digital. It was an ecosystem, really: the Mac, PostScript, LaserWriter, and PageMaker. But before all that, designers depended on typesetters to set type.

David Langton writing for UX Collective:

A lot was lost when the Macintosh wiped out the traditional typesetting industry. From the art of typography to the craft of typesetting, many essential elements were lost. Typesetters were part of a tradition that stretched back more than 500 years to Gutenberg’s printing press. They understood the basics of type: kerning (spacing between the letters), leading (the space between lines of text), and line breaks (how to avoid widows — those solo words abandoned at the end of a paragraph). They knew about readability (like how to avoid setting type that was too wide to read). There were classic yet limited fonts, with standards for size and leading that assured that everyone working within common ranges maintained a threshold for quality. Yet it was in the craft or business side of typesetting that these services were most under appreciated. Typesetters provided overnight service. They worked overnight, so graphic designers did not have to. We would finish our days specifying the type, and the typesetters would keystroke the manuscripts, proofread, stylize the type, and set up columns following our instructions.

Designers would then pick up the galleys from the typesetters in the morning. The black type was photographically printed on white photo paper. You’d have to cut them up and paste them onto boards, assembling your layout.

Because this was such a physical process, we had to slow down. Langton says:

But since the Macintosh became an in-house tool, the process was reversed. Now, designers design first, then think about it. This shift in process has contributed to a trivialization of the role of graphic designer because anyone can noodle around with the Mac’s sophisticated type tools and make layouts. The design process has been trivialized while the thinking, the evaluation, and the strategic part of the process are often abandoned.

One small thing I’ll point out is that desktop publishing wasn’t popularized until 1985.

• PostScript was released by Adobe in 1984.
• The LaserWriter printer was released by Apple in 1985.
• PageMaker was released by Aldus—later bought by Adobe—in 1985.

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.

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.

In this short piece by Luke Wroblewski, he observes how the chat box is slowly giving way as agents and MCP give AI chatbots a little more autonomy.

When agents can use multiple tools, call other agents and run in the background, a person’s role moves to kicking things off, clarifying things when needed, and making use of the final output. There’s a lot less chatting back and forth. As such, the prominence of the chat interface can recede even further. It’s there if you want to check the steps an AI took to accomplish your task. But until then it’s out of your way so you can focus on the output.

Brad Feld is sharing the Cursor prompts his friend Michael Natkin put together. It is more or less the same that I’ve gleaned from the Cursor forums, but it’s nice to have it consolidated here. If you’re curious to tackle any weekend coding project, follow these steps.

Nate Jones performed a yeoman’s job of summarizing Mary Meeker’s 340-slide deck on AI trends, the “2025 Technology as Innovation (TAI) Report.” For those of you who don’t know, Mary Meeker is a famed technology analyst and investor known for her insightful reports on tech industry trends. For the longest time, as an analyst at Kleiner Perkins, she published the Internet Trends report. And she was always prescient.

Half of Jones’ post is the summary, while the other half is how the report applies to product teams. The whole thing is worth 27 minutes of your time, especially if you work in software.

As a reaction to the OpenAI + io announcement two weeks ago, Christopher Butler imagines a mesh computing device network he calls “personal ambient computing”:

…I keep thinking back to Star Trek, and how the device that probably inspired the least wonder in me as a child is the one that seems most relevant now: the Federation’s wearables. Every officer wore a communicator pin — a kind of Humane Pin light — but they also all wore smaller pins at their collars signifying rank. In hindsight, it seems like those collar pins, which were discs the size of a watch battery, could have formed some kind of wearable, personal mesh network. And that idea got me going…

He describes the device as a standardized disc that can be attached to any enclosure. I love his illustration too:

Christopher Butler: “I imagine a magnetic edge system that allows the disc to snap into various enclosures — wristwatches, handhelds, desktop displays, wearable bands, necklaces, clips, and chargers.”

Essentially, it’s an always-on, always observing personal AI.

Following up on OpenAI’s acquisition of Jony Ive’s hardware startup, io, Mark Wilson, writing for Fast Company:

As Ive told me back in 2023, there have been only three significant modalities in the history of computing. After the original command line, we got the graphical user interface (the desktop, folders, and mouse of Xerox, Mac OS, and Windows), then voice (Alexa, Siri), and, finally, with the iPhone, multitouch (not just the ability to tap a screen, but to gesture and receive haptic feedback). When I brought up some other examples, Ive quickly nodded but dismissed them, acknowledging these as “tributaries” of experimentation. Then he said that to him the promise, and excitement, of building new AI hardware was that it might introduce a new breakthrough modality to interacting with a machine. A fourth modality.

Hmm, it hasn’t taken off yet because AR hasn’t really gained mainstream popularity, but I would argue hand gestures in AR UI to be a fourth modality. But Ive thinks different. Wilson continues:

Ive’s fourth modality, as I gleaned, was about translating AI intuition into human sensation. And it’s the exact sort of technology we need to introduce ubiquitous computing, also called quiet computing and ambient computing. These are terms coined by the late UX researcher Mark Weiser, who in the 1990s began dreaming of a world that broke us free from our desktop computers to usher in devices that were one with our environment. Weiser did much of this work at Xerox PARC, the same R&D lab that developed the mouse and GUI technology that Steve Jobs would eventually adopt for the Macintosh. (I would also be remiss to ignore that ubiquitous computing is the foundation of the sci-fi film Her, one of Altman’s self-stated goalposts.)

Ah, essentially an always-on, always watching AI that is ready to assist. But whatever the form factor this device takes, it will likely depend on a smartphone:

The first io device seems to acknowledge the phone’s inertia. Instead of presenting itself as a smartphone-killer like the Ai Pin or as a fabled “second screen” like the Apple Watch, it’s been positioned as a third, er, um … thing next to your phone and laptop. Yeah, that’s confusing, and perhaps positions the io product as unessential. But it also appears to be a needed strategy: Rather than topple these screened devices, it will attempt to draft off them.

Wilson ends with the idea of a subjective computer, one that has personality and gives you opinions. He explains:

I think AI is shifting us from objective to subjective. When a Fitbit counts your steps and calories burned, that’s an objective interface. When you ask ChatGPT to gauge the tone of a conversation, or whether you should eat better, that’s a subjective interface. It offers perspective, bias, and, to some extent, personality. It’s not just serving facts; it’s offering interpretation.

The entire column is worth a read.

Nick Babich writing for UX Planet:

Because AI design and code generators quickly take an active part in the design process, it’s essential to understand how to make the most of these tools. If you’ve played with Cursor, Bolt, Lovable, or v0, you know the output is only as good as the input.

Well said, especially as prompting is the primary input for these AI tools. He goes on to enumerate his five parts to a good prompt. Worth a quick read.

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.