In the summer of 2025, a new browser war was brewing. Perplexity launched Comet, and OpenAI followed that fall with ChatGPT Atlas. Both competed with Dia, but I was particularly impressed with Comet and Atlas because they could browse the web for me. I handed them a grocery list and asked them to fill up my Whole Foods shopping cart. Even though the process was slower than if I’d shopped manually, it was an aha moment. I wanted to be able to control my computer, the websites I visited, and the apps I used with plain language.

During my research for this essay, I went to Amazon to see if they’d integrated something like this natively on their site. And they did! Alexa for Shopping helps you shop on Amazon via conversation. I tried my grocery list experiment again. Within 15 seconds, my cart was filled with the dozen items on my list. Last year, Atlas took over 11 minutes and Comet took four.

There were two mistakes, both worthy of no more than a shrug. I’d asked for mild Italian sausage and Alexa found a package of frozen, which I wouldn’t have gotten. But to be fair, its options were slim. It also added two bunches of carrots instead of two loose carrots. Easy to correct in the cart.

The more I use apps in 2026, the more I want to start by telling them what I need. By chat, I mean expressing intent in plain language, typed or spoken. Give it the grocery list. Describe a design to make. Then use the controls when there’s something to inspect or change.

I’ve wanted those controls all along. What’s changed is how often I want to start with plain language.

I’m tired of the discourse. The more I read about how AI disrupts the way we design and build software, the less I want to read and write about it. (Yes, ironically, this is about AI.)

It’s not that there aren’t interesting things happening—there are. Jev, Muse, Grok Bot, Siri AI, continuing revelations about rogue OpenAI swarms. There’s a lot.

However, I think we’ve turned the corner. AI is here to stay, regardless of whether the frontier gets paced or not, or whether data centers continue to proliferate. The models we have today have forever changed how software is made. At this point, I believe the sea changes that have been happening every two to three months have slowed. With each new model release, they might be getting faster, more intelligent, and able to perform longer-running tasks. But the major shifts have already happened. We have agents writing code, creating mockups and prototypes, doing research, and autonomously fixing bugs. Improvements will be more of the same.

For designers and product managers, it’ll be dispatching agents to take on work and then reviewing their work. I already see this on my company’s Slack using the Claude Tag. Everyone in EPD just @mentions Claude, “Fix this” and the agent dutifully does it. How fast a company can build depends on the token budget and human review bottleneck.

I’ve been wandering the wilderness to understand where the software design profession is going. Via this blog and my newsletter, I’ve been exploring the possibilities by reading, commenting, and writing. Many other designers are in the same boat, with Erika Flowers’s Zero Vector design methodology being the most defined. Kudos to her for being one of the first—if not the first—to plant the flag.

Directionally Flowers is right. But for me, working in a team and on B2B software, it feels too simplistic and ignores the realities of working with customers and counterparts in product management and engineering. (That’s her whole point: one person to do it all, no handoff.)

The destination is within view. But it’s hazy and distant. The path to get there is unclear, like driving through soupy fog when your headlights reflecting off the mist are all you can see.

We’ve been talking a lot about agentic engineering, how software is now getting built with AI. As I look to see how design can complement this new development paradigm, a newish methodology called spec-driven development caught my eye. The idea is straightforward: you write a detailed specification first, then AI agents generate the code from it. The specification becomes the source of truth, not the code.

My first reaction when I started reading about SDD was: wait, isn’t this just waterfall?

Seriously. You gather requirements. You write them down in a structured document. You hand that document to someone (or something) that builds to spec. That’s the waterfall pattern. We spent two decades running away from it, and now it’s back wearing a blue Patagonia vest and calling itself a methodology.

I made my first website in Macromedia Dreamweaver in 1999. Its claim to fame was an environment with code on one side and a rudimentary WYSIWYG editor on the other. My site was a simple portfolio site, with a couple of animated GIFs thrown in for some interest. Over the years, I used other tools to create for the web, but usually, I left the coding to the experts. I’d design in Photoshop, Illustrator, Sketch, or Figma and then hand off to a developer. Until recently, with rebuilding this site a couple of times and working on a Severance fan project.

A couple weeks ago, as an experiment, I pointed Claude Code at our BuildOps design system repo and asked it to generate a screen using our components. It worked after about three prompts. Not one-shotted, but close. I sat there looking at a functioning UI—built from our actual components—and realized I’d just skipped the entire part of my job that I’ve spent many years doing: drawing pictures of apps and websites in a design tool, then handing them to someone else to build.

That moment crystallized something I’d been circling all last year. I wrote last spring about how execution skills were being commoditized and the designer’s value was shifting toward taste and strategic direction. A month later I mapped out a timeline for how design systems would become the infrastructure that AI tools generate against—prompt, generate, deploy. That was ten months ago, and most of it is already happening. Product design is changing. Not in the way most people are talking about it, but in a way that’s more fundamental and more interesting.

Last week, B2B software companies tumbled in the stock market, dropping over 10%. Software stocks have been trending down since September 2025, now down 30% according to the IGV software index. The prevailing sentiment is because AI tools like Anthropic’s Claude are now capable of doing things companies used to pay thousands of dollars for.

Chip Cutter and Sebastian Herrara, writing in the Wall Street Journal:

The immediate catalyst for this week’s selloff was the release of new capabilities for Anthropic’s Claude Cowork, an AI assistant that lets users assign agents to perform many types of tasks on their computers using only natural-language prompts. The tools automate workflows and perform tasks across a gamut of job functions with little human input.

The new plug-ins released about a week ago can review legal contracts and perform other industry-specific functions. An update to its model Thursday enhanced capabilities for financial analysis. 

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.

At the beginning of this year, AI prompt-to-code tools were still very new to the market. Lovable had just relaunched in December and Bolt debuted just a couple months before that. Cursor was my first taste of using AI to code back in November of 2024. As we sit here in December, just 12 months later, our profession and the discipline of design has materially changed. Now, of course, the core is still the same. But how we work, how we deliver, and how we achieve results, are different.

When ChatGPT got good (around GPT-4), I began using it as a creative sounding board. Design is never a solitary activity and feedback from peers and partners has always been a part of the process. To be able to bounce ideas off of an always-on, always-willing creative partner was great. To be sure, I didn’t share sketches or mockups; I was playing with written ideas.

Now, ChatGPT or Gemini’s deep research features are often where I start when I begin to tackle a new feature. And after the chatbot has written the report, I’ll read it and ask a lot of questions as a way of learning and internalizing the material. I’ll then use that as a jumping off point for additional research. Many designers on my team do the same.

According to recently unsealed court documents, Meta discontinued its internal studies on Facebook’s impact after discovering direct evidence that its platforms were detrimental to users’ mental health.

Jeff Horwitz reporting for Reuters:

In a 2020 research project code-named “Project Mercury,” Meta scientists worked with survey firm Nielsen to gauge the effect of “deactivating” Facebook, according to Meta documents obtained via discovery. To the company’s disappointment, “people who stopped using Facebook for a week reported lower feelings of depression, anxiety, loneliness and social comparison,” internal documents said.

Rather than publishing those findings or pursuing additional research, the filing states, Meta called off further work and internally declared that the negative study findings were tainted by the “existing media narrative” around the company.

Privately, however, a staffer insisted that the conclusions of the research were valid, according to the filing.

As more and more evidence comes to light about Mark Zuckerberg and Meta’s failings and possibly criminal behavior, we as tech workers and specifically designers making technology that billions of people use, have to do better. While my previous essay written after the assassination of Charlie Kirk was an indictment on the algorithm, I’ve come across a couple of pieces recently that bring the responsibility closer to UX’s doorstep.

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.

The assassination of Charlie Kirk on September 10, 2025, marked a horrifying inflection point in the growing debate over how digital platforms amplify rage and destabilize politics. As someone who had already stepped back from social media after Trump’s re-election, watching these events unfold from a distance only confirmed my decision. My feeds had become pits of despair, grievances, and overall negativity that didn’t do well for my mental health. While I understand the need to shine a light on the atrocities of Trump and his government, the constant barrage was too much. So I mostly opted out, save for the occasional promotion of my writing.

Kirk’s death feels like the inevitable conclusion of systems we’ve built—systems that reward outrage, amplify division, and transform human beings into content machines optimized for engagement at any cost.

I rewatched the 1982 film TRON for the umpteenth time the other night with my wife. I have always credited this movie as the spark that got me interested in computers. Mind you, I was nine years old when this film came out. I was so excited after watching the movie that I got my father to buy us a home computer—the mighty Atari 400 (note sarcasm). I remember an educational game that came on cassette called “States & Capitals” that taught me, well, the states and their capitals. It also introduced me to BASIC, and after watching TRON, I wanted to write programs!

In the 2011 documentary Jiro Dreams of Sushi, then 85 year-old sushi master Jiro Ono says this about craft:

Once you decide on your occupation… you must immerse yourself in your work. You have to fall in love with your work. Never complain about your job. You must dedicate your life to mastering your skill. That’s the secret of success and is the key to being regarded honorably.

Craft is typically thought of as the formal aspects of any field such as design, woodworking, writing, or cooking. In design, we think about composition, spacing, and typography—being pixel-perfect. But one’s craft is much more than that. Ono’s sushi craft is not solely about slicing fish and pressing it against a bit of rice. It is also about picking the right fish, toasting the nori just so, cooking the rice perfectly, and running a restaurant. It’s the whole thing.

In Part I of this series on the design talent crisis, I wrote about the struggles recent grads have had finding entry-level design jobs and what might be causing the stranglehold on the design job market. In Part II, I discussed how industry and education need to change in order to ensure the survival of the profession.

Part III: Adaptation Through Action

Like most Gen X kids, I grew up with a lot of freedom to roam. By fifth grade, I was regularly out of the house. My friends and I would go to an arcade in San Francisco’s Fisherman’s Wharf called The Doghouse, where naturally, they served hot dogs alongside their Joust and TRON cabinets. But we would invariably go to the Taco Bell across the street for cheap pre-dinner eats. In seventh grade—this is 1986—I walked by a ComputerLand on Van Ness Avenue and noticed a little beige computer with a built-in black and white CRT. The Macintosh screen was actually pale blue and black, but more importantly, showed MacPaint. It was my first exposure to creating graphics on a computer, which would eventually become my career.

For my series on the Design Talent Crisis (see Part I, Part II, and Part III) I interviewed five recent graduates from California College of the Arts (CCA) and San Diego City College. I’m an alum of CCA and I used to teach at SDCC. There’s a mix of folks from both the graphic design and interaction design disciplines. 

In Part I of this series, I wrote about the struggles recent grads have had finding entry-level design jobs and what might be causing the stranglehold on the design job market.

Part II: Building New Ladders

When I met Benedict Allen, he had just finished with Portfolio Review a week earlier. That’s the big show all the design students in the Graphic Design program at San Diego City College work toward. It’s a nice event that brings out the local design community where seasoned professionals review the portfolios of the graduating students.

Allen was all smiles and relief. “I want to dabble in different aspects of design because the principles are generally the same.” He goes on to mention how he wants to start a fashion brand someday, DJ, try 3D. “I just want to test and try things and just have fun! Of course, I’ll have my graphic design job, but I don’t want that to be the end. Like when the workday ends, that’s not the end of my creativity.” He was bursting with enthusiasm.

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? 

I was in London last week with my family and spotted this ad in a Tube car. With the headline “Humans Were the Beta Test,” this is for Artisan, a San Francisco-based startup peddling AI-powered “digital workers.” Specifically an AI agent that will perform sales outreach to prospects, etc.

Artisan ad as seen in London, June 2025

I’ve long left the Bay Area, but I know that the 101 highway is littered with cryptic billboards from tech companies, where the copy only makes sense to people in the tech industry, which to be fair, is a large part of the Bay Area economy. Artisan is infamous for its “Stop Hiring Humans” campaign which went up late last year. Being based in San Diego, much further south in California, I had no idea. Artisan wasn’t even on my radar.

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.

I remember two years ago, when my CEO at the startup I worked for at the time, said that no VC investments were being made unless it had to do with AI. I thought AI was overhyped, and that the media frenzy over it couldn’t get any crazier. I was wrong.

Looking at Google Trends data, interest in AI has doubled in the last 24 months. And I don’t think it’s hit its plateau yet.

Four months into his role as interim CEO, Tom Conrad has been remarkably candid about Sonos’ catastrophic app launch. In recent interviews with WIRED and The Verge, he’s taken personal responsibility—even though he wasn’t at the helm, just on the board—acknowledged deep organizational problems, and outlined the company’s path forward.

But while Conrad is addressing more than many expected, some key details remain off-limits.

Product design is going to change profoundly within the next 24 months. If the AI 2027 report is any indication, the capabilities of the foundational models will grow exponentially, and with them—I believe—will the abilities of design tools.

The AI foundational model capabilities will grow exponentially and AI-enabled design tools will benefit from the algorithmic advances. Sources: AI 2027 scenario & Roger Wong

The TL;DR of the report is this: companies like OpenAI have more advanced AI agent models that are building the next-generation models. Once those are built, the previous generation is tested for safety and released to the public. And the cycle continues. Currently, and for the next year or two, these companies are focusing their advanced models on creating superhuman coders. This compounds and will result in artificial general intelligence, or AGI, within the next five years. 

In a recent podcast with partners at startup incubator Y Combinator, Jared Friedman, citing statistics from a survey with their current batch of founders says, “[The] crazy thing is one quarter of the founders said that more than 95% of their code base was AI generated, which is like an insane statistic. And it’s not like we funded a bunch of non-technical founders. Like every one of these people is highly tactical, completely capable of building their own product from scratch a year ago…”

A comment they shared from founder Leo Paz reads, “I think the role of Software Engineer will transition to Product Engineer. Human taste is now more important than ever as codegen tools make everyone a 10x engineer.”

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.

My wife and I are big movie lovers. Every year, between January and March, we race to see all the Oscar-nominated films. We watched A Complete Unknown last night and The Brutalist a couple of weeks ago. The latter far outshines the former as a movie, but both share a common theme: the creative obsession.

Timothée Chalamet, as Bob Dylan, is up at all hours writing songs. Sometimes he rushes into his apartment, stumbling over furniture, holding onto an idea in his head, hoping it won’t flitter away, and frantically writes it down. Adrien Brody, playing a visionary architect named László Tóth, paces compulsively around the construction site of his latest project, ensuring everything is built to perfection. He even admonishes and tries to fire a young worker who’s just goofing off.

There is an all-consuming something that takes over your thoughts and actions when you’re in the groove willing something to life, whether it’s a song, building, design, or program. I’ve been feeling this way lately with a side project I’ve been working on off-hours—a web application that’s been consuming my thoughts for about a week. A lot of this obsession is a tenacity around solving a problem. For me, it has been fixing bugs in code—using Cursor AI. But in the past, it has been figuring out how to combine two disparate ideas into a succinct logo, or working out a user flow. These ideas come at all hours. Often for me it’s in the shower but sometimes right before going to sleep. Sometimes my brain works on a solution while I sleep, and I wake up with a revelation about a problem that seemed insurmountable the night before. It’s exhausting and exhilarating at the same time.