Anand Majmudar creates a scenario inspired by “AI 2027”, but focused on robotics.

I created Android Dreams because I want the good outcomes for the integration of automation into society, which requires knowing how it will be integrated in the likely scenario. Future prediction is about fitting the function of the world accurately, and the premise of Android Dreams is that my world model in this domain is at least more accurate than on average. In forming an accurate model of the future, I’ve talked to hundreds of researchers, founders, and operators at the frontier of robotics as my own data. I’m grateful to my mentors who’ve taught me along the way.

The scariest scenes from “AI 2027” are when the AIs start manufacturing and proliferating robots. For example, from the 2028 section:

Agent-5 convinces the U.S. military that China is using DeepCent’s models to build terrifying new weapons: drones, robots, advanced hypersonic missiles, and interceptors; AI-assisted nuclear first strike. Agent-5 promises a set of weapons capable of resisting whatever China can produce within a few months. Under the circumstances, top brass puts aside their discomfort at taking humans out of the loop. They accelerate deployment of Agent-5 into the military and military-industrial complex.

So I’m glad for Majmudar’s thought experiment.

When Figma acquired Weavy last month, I wrote a little bit about node-based UIs and ComfyUI. Looks like Adobe has been exploring this user interface paradigm as well.

Daniel John writes in Creative Bloq:

Project Graph is capable of turning complex workflows into user-friendly UIs (or ‘capsules’), and can access tools from across the Creative Cloud suite, including Photoshop, Illustrator and Premiere Pro – making it a potentially game-changing tool for creative pros.

But it isn’t just Adobe’s own tools that Project Graph is able to tap into. It also has access to the multitude of third party AI models Adobe recently announced partnerships with, including those made by Google, OpenAI and many more.

These tools can be used to build a node-based workflow, which can then be packaged into a streamlined tool with a deceptively simple interface.

And from Adobe’s blog post about Project Graph:

Project Graph is a new creative system that gives artists and designers real control and customization over their workflows at scale. It blends the best AI models with the capabilities of Adobe’s creative tools, such as Photoshop, inside a visual, node-based editor so you can design, explore, and refine ideas in a way that feels tactile and expressive, while still supporting the precision and reliability creative pros expect.

I’ve been playing around with ComfyUI a lot recently (more about this in a future post), so I’m very excited to see how this kind of UI can fit into Adobe’s products.

Designer and front-end dev Ondřej Konečný has a lovely presentation of his book collection.

My favorites that I’ve read include:

• Creative Selection by Ken Kocienda (my review)
• Grid Systems in Graphic Design by Josef Müller-Brockmann
• Steve Jobs by Walter Isaacson
• Don’t Make Me Think by Steve Krug
• Responsive Web Design by Ethan Marcotte

(h/t Jeffrey Zeldman)

Critiques are the lifeblood of design. Anyone who went to design school has participated in and has been the focus of a crit. It’s “the intentional application of adversarial thought to something that isn’t finished yet,” as Fabricio Teixeira and Caio Braga, the editors of DOC put it.

A lot of solo designers—whether they’re a design team of one or if they’re a freelancer—don’t have the luxury of critiques. In my view, they’re handicapped. There are workarounds, of course. Such as critiques with cross-functional peers, but it’s not the same. I had one designer on my team—who used to be a design team of one in her previous company—come up to me and say she’s learned more in a month than a year at her former job.

Further down, Teixeira and Braga say:

In the age of AI, the human critique session becomes even more important. LLMs can generate ideas in 5 seconds, but stress-testing them with contextual knowledge, taste, and vision, is something that you should be better at. As AI accelerates the production of “technically correct” and “aesthetically optimized” work, relying on just AI creates the risks of mediocrity. AI is trained to be predictable; crits are all about friction: political, organizational, or strategic.

As regular readers will know, the design talent crisis is a subject I’m very passionate about. Of course, this talent crisis is really about how companies who are opting for AI instead of junior-level humans, are robbing themselves of a human expertise to control the AI agents of the future, and neglecting a generation of talented and enthusiastic young people.

Also obviously, this goes beyond the design discipline. Annie Hedgpeth, writing for the People Work blog, says that “AI is replacing the training ground not replacing expertise.”

We used to have a training ground for junior engineers, but now AI is increasingly automating away that work. Both studies I referenced above cited the same thing - AI is getting good at automating junior work while only augmenting senior work. So the evidence doesn’t show that AI is going to replace everyone; it’s just removing the apprenticeship ladder.

From the Sep 2025 Harvard University paper, “Generative AI as Seniority-Biased Technological Change: Evidence from U.S. Résumé and Job Posting Data.” (link)

And then she echoes my worry:

So what happens in 10-20 years when the current senior engineers retire? Where do the next batch of seniors come from? The ones who can architect complex systems and make good judgment calls when faced with uncertain situations? Those are skills that are developed through years of work that starts simple and grows in complexity, through human mentorship.

We’re setting ourselves up for a timing mismatch, at best. We’re eliminating junior jobs in hopes that AI will get good enough in the next 10-20 years to handle even complex, human judgment calls. And if we’re wrong about that, then we have far fewer people in the pipeline of senior engineers to solve those problems.

Website screenshot SaaS company Urlbox created a fun project called One Million Screenshots, with, yup, over a million screenshots of the top one million websites. You navigate the page like Google Maps, by zooming in and panning around.

Why? From the FAQ page:

We wanted to celebrate Urlbox taking over 100 million screenshots for customers in 2023… so we thought it would be fun to take an extra 1,048,576 screenshots evey month… did we mention we’re really into screenshots.

(h/t Brad Frost)

Ryan Feigenbaum created a fun Teenage Engineering-inspired color palette generator he calls “ColorPalette Pro.” Back in 2023, he was experimenting with programatic palette generation. But he didn’t like his work, calling the resulting palettes “gross, with luminosity all over the place, clashing colors, and garish combinations.”

So Feigenbaum went back to the drawing board:

That set off a deep dive into color theory, reading various articles and books like Josef Albers’ Interaction of Color (1963), understanding color space better, all of which coincided with an explosion of new color methods and technical support on the web.

These frustrations and browser improvements culminated in a realization and an app.

Here he is, demoing his app:

David Kelley is an icon in design. A restless tinkerer turned educator, he co-founded the reowned industrial design firm IDEO, helped shape human-centered design at Stanford’s d.school, and collaborated with Apple on seminal projects like the early mouse.

Here’s his take on creativity in a brief segment for PBS News Hour:

And as I started teaching, I realized that my purpose in life was figuring out how to help people gain confidence in their creative ability. Many people assume they’re not creative. Time and time again, they say, a teacher told me I wasn’t creative or that’s not a very good drawing of a horse or whatever it is. We don’t have to teach creativity. Once we remove the blocks, they can then feel themselves as being a creative person. Witnessing somebody realizing they’re creative for the first time is just a complete joy. You can just see them come out of the shop and beaming that I can weld. Like, what’s next?

I’ve been playing with my systems in the past month—switching browsers, notetaking apps, and RSS feed readers. If I’m being honest, it’s causing me anxiety because I feel unmoored. My systems aren’t familiar enough to let me be efficient.

One thing that has stayed relatively stable is my LLM app—well, two of them. ChatGPT for everyday and Claude for coding and writing.

Christina Wodtke, writing on her blog:

The most useful model might not win.

What wins is the model that people don’t want to leave. The one that feels like home. The one where switching would mean losing something—not just access to features, but fluency, comfort, all those intangible things that make a tool feel like yours.

Amazon figured this out with Prime. Apple figured it out with the ecosystem. Salesforce figured it out by making itself so embedded in enterprise workflows that ripping it out would require an act of God.

AI companies are still acting like this is a pure technology competition. It’s not. It’s a competition to become essential—and staying power comes from experience, not raw capability.

Your moat isn’t your model. Your moat is whether users feel at home.

Like it or not, as a designer, you have to be able to present your work proficiently. I remember I had always hated presenting. I was nervous and would get tongue-tied. Eventually, the more I did it, the more I got used to it. …But that’s public speaking, just half of what a presentation is. The other half is how to structure and tell your story. What story? The story of your design.

There’s a lot to be learned from master storytellers like Pixar. Laia Tremosa writing for the Interaction Design Foundation walks us through some storytelling techniques that we can pick up from Pixar.

Most professionals stay unseen not because their work lacks value, but because their message lacks resonance. They talk in facts when their audience needs meaning.

Storytelling is how you change that. It turns explanation into connection, and connection into influence. When you frame your ideas through story, people don’t just understand your work, they believe in it.

And out of the five that she mentions, the second one is my favorite, “Know Where You’re Going: Start with the End.”

Pixar designs for the final feeling. You should too. As a presenter, your version of that is a clear takeaway, a shift in perspective, or a call to action. You’re guiding your audience to a moment of clarity.

Maybe it’s a relief that a problem can be solved. Maybe it’s excitement about a new idea. Maybe it’s conviction that your proposal matters. Whatever the feeling, it’s your north star.

Don’t just prepare what to say; decide where you want to land. Start with the end, and build every word, visual, and story toward that moment of understanding and meaning.

If you are old enough to have watched Toy Story in theaters back in 1995, you may have noticed that the version streaming on Disney+ today doesn’t quite feel the same.

You see, Toy Story was an entirely digital artifact but it had to be distributed to movie theaters using the technology theaters had at the time—35mm film projectors. Therefore, every frame of the movie was recorded onto film.

Animation Obsessive explains:

Their system was fairly straightforward. Every frame of Toy Story’s negative was exposed, three times, in front of a CRT screen that displayed the movie. “Since all film and video images are composed of combinations of red, green and blue light, the frame is separated into its discrete red, green and blue elements,” noted the studio. Exposures, filtered through each color, were layered to create each frame.

It reportedly took nine hours to print 30 seconds of Toy Story. But it had to be done: it was the only way to screen the film.

The home video version of the movie was mastered from a 35mm print.

And then in 1999, A Bug’s Life became the very first digital-to-digital home video transfer. Pixar devised a method to go from their computers straight to DVD.

In the early 2000s, Disney/Pixar would redo the home video transfer for Toy Story using the same digital mastering technique. “And it wasn’t quite the same movie that viewers had seen in the ‘90s.”

“The colors are vivid and lifelike, [and] not a hint of grain or artifacts can be found,” raved one reviewer. It was a crisp, blazingly bright, digital image now — totally different from the softness, texture and deep, muted warmth of physical film, on which Toy Story was created to be seen.

And then digital transfers became the standard.

Hard to believe that the very first fully computer animated feature film came out 30 years ago. To say that Toy Story was groundbreaking would be an understatement. If you look at the animated feature landscape today, 100% is computer-generated.

In this re-found interview with Steve Jobs exactly a year after the movie premiered in theaters, Jobs talks about a few things, notably how different Silicon Valley and Hollywood were—and still are.

From the Steve Jobs Archive:

In this footage, Steve reveals the long game behind Pixar’s seeming overnight success. With striking clarity, he explains how its business model gives artists and engineers a stake in their creations, and he reflects on what Disney’s hard-won wisdom taught him about focus and discipline. He also talks about the challenge of leading a team so talented that it inverts the usual hierarchy, the incentives that inspire people to stay with the company, and the deeper purpose that unites them all: to tell stories that last and put something of enduring value into the culture.  

And Jobs in his own words:

Well, in this blending of a Hollywood  culture and a Silicon Valley culture, one of the things that we encountered was  that the Hollywood culture and the Silicon Valley culture each used different models of  employee retention. Hollywood uses the stick, which is the contract, and Silicon Valley  uses the carrot, which is the stock option. And we examined both of those in really pretty  great detail, both economically, but also psychologically and culture wise, what kind of  culture do you end up with. And while there’s a lot of reasons to want to lock down your  employees for the duration of a film because, if somebody leaves, you’re at risk, those  same dangers exist in Silicon Valley. During an engineering project, you don’t want to lose people, and yet, they managed to evolve another system than contracts. And we preferred the Silicon Valley model in this case, which basically gives people stock in the company so that we all have the same goal, which is to create shareholder value. But also, it makes us constantly worry about making Pixar the greatest company we can  so that nobody would ever want to leave. 

I wouldn’t call myself a gamer, but I do enjoy good games from time to time, when I have the time. A couple of years ago, I made my way through Hades and had a blast.

But I do know that the publishing of a triple-A title like Call of Duty: Black Ops takes an enormous effort, tons of human-hours, and loads of cash. It’s also obvious to me that AI has been entering into entertainment workflows, just like it has in design workflows.

Ian Dean, writing for Creative Bloq explores this controversy with Activision using generative AI to create artwork for the latest release in the Call of Duty franchise. Players called the company out for being opaque about using AI tools, but more importantly, because they spotted telltale artifacts.

Many of the game’s calling cards display the kind of visual tics that seasoned artists can spot at a glance: fingers that don’t quite add up, characters whose faces drift slightly off-model, and backgrounds that feel too synthetic to belong to a studio known for its polish.

These aren’t high-profile cinematic assets, but they’re the small slices of style and personality players earn through gameplay. And that’s precisely why the discovery has landed so hard; it feels a little sneaky, a bit underhanded.

“Sneaky” and “underhanded” are odd adjectives, no? I suppose gamers are feeling like they’ve been lied to because Activition used AI?

Dean again:

While no major studio will admit it publicly, Black Ops 7 is now a case study in how not to introduce AI into a beloved franchise. Artists across the industry are already discussing how easily ‘supportive tools’ can cross the line into fully generated content, and how difficult it becomes to convince players that craft still matters when the results look rushed or uncanny.

My, possibly controversial, view is that the technology itself isn’t the villain here; poor implementation is, a lack of transparency is, and fundamentally, a lack of creative use is.

I think the last phrase is the key. It’s the loss of quality and lack of creative use.

I’ve been playing around more with AI-generated images and video, ever since Figma acquired Weavy. I’ve been testing out Weavy and have done a lot of experimenting with ComfyUI in recent weeks. The quality of output from these tools is getting better every month.

With more and more AI being embedded into our art and design tools, the purity that some fans want is going to be hard to sustain. I think the train has left the station.

There are dark patterns in UX, and there are also dark patterns specific to games. Dark Pattern Games is a website that catalogs such patterns and the offending mobile games.

The site’s definition of a dark pattern is:

A gaming dark pattern is something that is deliberately added to a game to cause an unwanted negative experience for the player with a positive outcome for the game developer.

The “Social Pyramid Scheme” is one of my most loathed:

Some games will give you a bonus when you invite your friends to play and link to them to your account. This bonus may be a one-time benefit, or it may be an ongoing benefit that improves the gaming experience for each friend that you add. This gives players a strong incentive to convince their friends to play. Those friends then have to sign up more friends and so on, leading to a pyramid scheme and viral growth for the game.

Geoffrey Litt is a design engineer at Notion. He is one of the authors at Ink & Switch of “Malleable software,” which I linked to back in July. I think it’s pretty fitting that he popped up at Notion, with the CEO Ivan Zhao likening the app to LEGO bricks.

In a recent interview with Rid on Dive Club, Litt explains the concept further:

So, when I say malleable software, I do not mean only disposable software. The main thing I think about with malleable software is actually much closer to … designing my interior space in my house. Let’s say when I come home I don’t want everything to be rearranged, right? I want it to be the way it was. And if I want to move the furniture or put things on the wall, I want to have the right to do that. And so I think of it much more as kind of crafting an environment over time that’s actually more stable and predictable, not only for myself, but also for my team. Having shared environments that we all work in together that are predictable is also really important, right? Ironically, actually, in some ways, I think sometimes malleable software results in more stable software because I have more control.

For building with AI, Litt advocates “coding like a surgeon”: stay in the loop and use agents for prep and grunt work.

How do we think of AI as a way to leverage our time better? [So we can] stay connected to the work and [do] it ourselves by having prep work done for us. Having tools in the moment helping us do it so that we can really focus on the stuff we love to do, and do less of everything else. And that’s how I’m trying to use coding agents for my core work that I care about today. Which is when I show up, sit down at my desk in the morning and work on a feature, I want to be prepped with a brief on all the code I’m going to be touching today, how it works, what the traps are. Maybe I’ll see a draft that the AI did for me overnight, sketching out how the coding could go. Maybe some ideas for me.

In other words, like an assistant who works overnight. And yeah, this could apply to design as well.

He told me his CEO - who’s never written a line of code - was running their company from an AI code editor.

I almost fell out of my chair.

OF COURSE. WHY HAD I NOT THOUGHT OF THAT.

I’ve since gotten rid of almost all of my productivity tools.

ChatGPT, Notion, Todoist, Airtable, Google Keep, Perplexity, my CRM. All gone.

That’s the lede for a piece by Derek Larson on running everything from Claude Code. I’ve covered how Claude Code is pretty brilliant and there are dozens more use cases than just coding.

But getting rid of everything and using just text files and the terminal window? Seems extreme.

Larson uses a skill in Claude Code called “/weekly” to do a weekly review.

1. Claude looks at every file change since last week
2. Claude evaluates the state of projects, tasks, and the roadmap
3. We have a conversation to dig deeper, and make decisions
4. Claude generates a document summarizing the week and plan we agreed on

Then Claude finds items he’s missed or procrastinating on, and “creates a space to dump everything” on his mind.

Something that I think a lot about as a design leader is how to promote the benefits of design in the organization. Paul Boag created this practical guide to guerrilla internal marketing that builds a network of ambassadors across departments and keeps user-centered thinking top of mind.

Boag, writing in his newsletter:

You cannot be everywhere at once. You cannot attend every meeting, influence every decision, or educate every colleague personally. But you can identify and equip people across different departments who care about users and give them the tools to spread UX thinking in their teams.

This is how culture change actually happens. Not through presentations from the UX team, but through conversations between colleagues who trust each other.

Design Thinking has gotten a bad rap in recent years. It was supposed to change everything in the corporate world but ended up changing very little. While Design Thinking may not be the darling anymore, designers still need time to think, which is, for the sake of argument, time away from Figma and pushing pixels.

Chris Becker argues in UX Collective:

However, the canary in the coalmine is that Designers are not being used for their “thinking” but rather their “repetition”. Much of the consternation we feel in the UX industry is catapulted on us from this point of friction.

He says that agile software development and time for designers to think aren’t incompatible:

But allowing Designers to implement their thinking into the process is about trust. When good software teams collaborate effectively, there are high levels of trust and autonomy (a key requirement of agile teams). Designers must earn that trust, of course, and when we demonstrate that we have “done the thinking,” it builds confidence and garners more thinking time. Thinking begets thinking. So, Designers, let’s continue to work to maximise our “thinking” faculties.

Pavel Bukengolts writes a piece for UX Magazine that reiterates what I’ve been covering here: our general shift to AI means that human judgement and adaptability are more important than ever.

Before getting to the meat of the issue, Bukengolts highlights the talent crisis that is our own making:

The outcome is a broken pipeline. If graduates cannot land their first jobs, they cannot build the experience needed for the next stage. A decade from now, organizations may face not just a shortage of junior workers, but a shortage of mid-level professionals who never had a chance to develop.

If rote repetitive tasks are being automated by AI and junior staffers aren’t needed for those tasks, then what skills are still valuable? Further on, he answers that question:

Centuries ago, in Athens, Alexandria, or Oxford, education focused on rhetoric, logic, and philosophy. These were not academic luxuries but survival skills for navigating complexity and persuasion. Ironically, they are once again becoming the most durable protection in an age of automation.

Some of these skills include:

• Logic: Evaluating arguments and identifying flawed reasoning—essential when AI generates plausible but incorrect conclusions.
• Rhetoric: Crafting persuasive narratives that create emotional connection and resonance beyond what algorithms can achieve.
• Philosophy and Ethics: Examining not just capability but responsibility, particularly around automation’s broader implications.
• Systems Thinking: Understanding interconnections and cascading effects that AI’s narrow outputs often miss.
• Writing: Communicating with precision to align stakeholders and drive better outcomes.
• Observation: Detecting subtle signals and anomalies that fall outside algorithmic training data.
• Debate: Refining thinking through intellectual challenge—a practice dating to ancient dialogue.
• History: Recognizing recurring patterns to avoid cyclical mistakes; AI enthusiasm echoes past technological revolutions.

I would say all of the above not only make a good designer but a good citizen of this planet.

In a heady, intelligent, and fascinating interview with Sarah Jeong from The Verge, Cory Doctorow—the famed internet activist—talks about how platforms have gotten worse over the years. Using Meta (Facebook) as an example, Doctorow explains their decline over time through a multi-stage process. Initially, it attracted users by promising not to spy on them and by showing them content from their friends, leveraging the difficulty of getting friends to switch platforms. Subsequently, Meta compromised user privacy by providing advertisers with surveillance data (aka ad tracking) and offered publishers traffic funnels, locking in business customers before ultimately degrading the experience for all users by filling feeds with paid content and pivoting to less desirable ventures like the Metaverse.

And publishers, [to get visibility on the platform,] they have to put the full text of their articles on Facebook now and no links back to their website.

Otherwise, they won’t be shown to anyone, much less their subscribers, and they’re now fully substitutive, right? And the only way they can monetize that is with Facebook’s rigged ad market and users find that the amount of stuff that they ask to see in their feed is dwindled to basically nothing, so that these voids can be filled with stuff people will pay to show them, and those people are getting ripped off. This is the equilibrium Mark Zuckerberg wants, right? Where all the available value has been withdrawn. But he has to contend with the fact that this is a very brittle equilibrium. The difference between, “I hate Facebook, but I can’t seem to stop using it,” and “I hate Facebook and I’m not going to use it anymore,” is so brittle that if you get a live stream mass shooting or a whistleblower or a privacy scandal like Cambridge Analytica, people will flee.

Francesca Bria and her collaborators analyzed open-source datasets of “over 250 actors, thousands of verified connections, and $45 billion in documented financial flows” to come up with a single-page website visually showing such connections.

J.D. Vance, propelled to the vice-presidency by $15 million from Peter Thiel, became the face of tech-right governance. Behind him, Thiel’s network moved into the machinery of the state.

Under the banner of “patriotic tech”, this new bloc is building the infrastructure of control—clouds, AI, finance, drones, satellites—an integrated system we call the Authoritarian Stack. It is faster, ideological, and fully privatized: a regime where corporate boards, not public law, set the rules.

Our investigation shows how these firms now operate as state-like powers—writing the rules, winning the tenders, and exporting their model to Europe, where it poses a direct challenge to democratic governance.

Make no mistake: Democracy in America has been under threat. The Executive branch continues to accrue and abuse power, much of it willingly given up by Congress, and the Supreme Court has largely given deference to this president.

In a beautiful, yet somehow haunting visualization, Alvin Chang for the Pudding went back and analyzed speeches in Congress from 1880 onward to show the growth of mentions about democracy being under threat.

Scroll through the interactive data viz and see the numbers tick up over the years, along with select quotes from speeches.

Chang ends with this reflection:

I grew up in an immigrant family, and I was constantly reminded of how powerful these values are. Sure, my family had some allegiance to their home country. Sure, we were constantly reminded of ways in which the country failed to live up to these ideals. However, I was told that we live in a country that is united not by the color of our skin or the origins of our families, but rather a belief in how humans should live together.

Americans have always argued about what it means to strive toward these democratic ideals. This pursuit of democracy is who we are; it’s who we want to be.

If we stop now, who are we as a people?

(h/t Nathan Yau / FlowingData)