Over the past couple months, I’ve noticed a wave of ASCII-related projects show up on my feeds. WTH is ASCII? It’s the basic set of letters, numbers, and symbols that old-school computers agreed to use for text.

ASCII (American Standard Code for Information Interchange) has 128 characters:

• 95 printable characters: digits 0–9, uppercase A–Z, lowercase a–z, space, and common punctuation and symbols.
• 33 control characters: non-printing codes like NUL, LF (line feed), CR (carriage return), and DEL used historically for devices like teletypes and printers.

Early internet users who remember plain text-only email and Usenet newsgroups would have encountered ASCII art like these:

 /\_/\
( o.o )
 > ^ <

It’s a cat. Artist unknown.

   __/\\\\\\\\\\\\\____/\\\\\\\\\\\\\_______/\\\\\\\\\\\___
    _\/\\\/////////\\\_\/\\\/////////\\\___/\\\/////////\\\_
     _\/\\\_______\/\\\_\/\\\_______\/\\\__\//\\\______\///__
      _\/\\\\\\\\\\\\\\__\/\\\\\\\\\\\\\\____\////\\\_________
       _\/\\\/////////\\\_\/\\\/////////\\\______\////\\\______
        _\/\\\_______\/\\\_\/\\\_______\/\\\_________\////\\\___
         _\/\\\_______\/\\\_\/\\\_______\/\\\__/\\\______\//\\\__
          _\/\\\\\\\\\\\\\/__\/\\\\\\\\\\\\\/__\///\\\\\\\\\\\/___
           _\/////////////____\/////////////______\///////////_____

Dimensional lettering.

Anyway, you’ve seen it before and get the gist. My guess is that with Claude Code’s halo effect, the terminal is making a comeback and generating interest in this long lost artform again. And it’s text-based which is now fuel for AI.

I posted my essay “Product Design Is Changing“ earlier this week and shared it on both LinkedIn and Reddit. The reactions split in a way was entirely predictable: LinkedIn was largely in agreement, Reddit was largely hostile (including some downvotes!). Debate is healthy and I’m glad people are talking about it. What I don’t want is designers willfully ignoring what is happening. To me, this similar to the industry-wide shifts when graphic design went from paste-up to desktop publishing, and then again from print to web. Folks have to adapt. To quote a previous essay of mine from August 2025:

The AI revolution mirrors the previous shifts in our industry, but with a crucial difference: it’s bigger and faster. Unlike the decade-long transitions from paste-up to desktop publishing and from print to web, AI’s impact is compressing adaptation timelines into months rather than years.

Anyway, I want to highlight some comments that widen the aperture a bit.

“I Didn’t Sign Up for This”

Julian Quayle, a brilliant creative director I worked with a long time ago in my agency years, left a comment on LinkedIn: “So much for years of craft and imagination… I didn’t sign up for this.”

He’s right. None of us signed up for it. And I don’t want to be glib about that. There’s a real grief in watching skills you spent years developing get compressed into a prompt. I’ve been doing this for 30 years. I know what it feels like to be proud of a pixel-perfect mockup, to care about the craft of visual design at a level that most people can’t even perceive. That craft isn’t worthless now. But the market is repricing it in real time, and pretending otherwise doesn’t help anyone.

And to be sure, my essay was about software design. I’m sure there’s an equivalent happening in the branding/graphic side of the house, but I can’t speak to it.

(BTW, Julian is one of the funnest and nicest Brits I’ve ever worked with. When we talk about taste, his is insanely good. And he got to work with David Bowie. Yes.)

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.

After posting my essay about Wall Street and the B2B software stocks tumbling, I came across a few items that pulls on the thread even more, to something forward-looking.

Firstly, my old colleague Shawn Smith had a more nuanced reaction to the story. Smith has been both a customer many times over of Salesforce and a product manager there.

On the customer side, without exception, the sentiment was that Salesforce is an expensive partial solution. There were always gaps in what it could do, which were filled by janky workarounds. In every case, the organization at least considered building an in-house solution which would cover all the bases *and* cost less than the Salesforce contract. I think the threat of AI to Salesforce is very real in this sense. Companies will use it to build their own solutions, but this outcome is probably at least 2-5 years out in many cases because switching costs are real, and contracts are an obstacle.

He is less convinced about something like Adobe where individual preferences around tooling are more of the determining factor. The underlying threat in Smith’s analysis—that companies will build their own solutions—points to a deeper question about which software businesses have real moats. Especially with newer, AI-native upstarts.

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.

My first taste of generating art with AI was back in 2021 with Wombo Dream. I even used it to create very trippy illustrations for a series I wrote on getting a job as a product designer. To be sure, the generations were weird, if not even ugly. But it was my first test of getting an image by typing in some words. Both Stable Diffusion and Midjourney gained traction the following year and I tried both as well. The results were never great or satisfactory. Years upon years of being an art director had made me very, very picky—or put another way, I had developed taste.

I didn’t touch generative AI art again until I saw a series of photos by Lars Bastholm playing with Midjourney.

Lars Bastholm created this in Midjourney, prompting “What if, in the 1970s, they had a ‘Bring Your Monster’ festival in Central Park?”

That’s when I went back to Midjourney and started to illustrate my original essays with images generated by it, but usually augmented by me in Photoshop.

In the intervening years, generative AI art tools had developed a common set of functionality that was all very new to me: inpainting, style, chaos, seed, and more. Beyond closed systems like Midjourney and OpenAI’s DALL-E, open source models from Stable Diffusion, Flux, and now a plethora of Chinese models offer even better prompt adherence and controllability via even more opaque-sounding functionality like control nets, LoRAs, CFG, and other parameters. It’s funny to me that for a very artistic field, the associated products to enable these creations are very technical.

In 2025, I published 328 posts with a total of 118,445 words on this blog. Of course, in most of the posts, I’m quoting others, so excluding block quotes—those quoted passages greater than a sentence—I’m down to 76,226 words. Still pretty impressive, I’d say.

I used Claude Code to write a little script that analyzed my posts from last year.

In reviewing data from my analytics package Umami, it is also interesting which posts received the most views. By far it was “Beyond the Prompt,” my AI prompt-to-code shootout article. The others in the top five were:

• My investigative piece on how Sonos’ app disaster unfolded
• My review of the Figma Make beta
• The first part of my three-part series on the design talent crisis
• A reaction to the “AI 2027” scenario

That last one has always surprised me. I must’ve hit the Google lottery on it for some reason.

Speaking of links, since April—no data before—visitors clicked on links mentioned on this blog 2,949 times. I also wanted to see which linked items were most popular, by outbound clicks:

1. AI 2027, naturally
2. Smith & Diction’s catalog of “Usable Google Fonts”
3. Matt Webb’s post on Do What I Mean
4. A visualization called “The Authoritarian Stack” that shows how power, money, and companies connect
5. The New York Times list of the “25 Most Influential Magazine Covers of All Time” (sadly, the gift link has since expired)

And finally, the totals of the year for views were 58,187, with 42,075 visitors. That works out to be an average of about 3,500 visitors per month. Tiny compared with other blogs out there. But my readers mean the world to me.

Anyway, some interesting stats, at least to me. Here’s to more in 2026.

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.

Mark Gurman, writing for Bloomberg:

Meta Platforms Inc. has poached Apple Inc.’s most prominent design executive in a major coup that underscores a push by the social networking giant into AI-equipped consumer devices.

The company is hiring Alan Dye, who has served as the head of Apple’s user interface design team since 2015, according to people with knowledge of the matter. Apple is replacing Dye with longtime designer Stephen Lemay, according to the people, who asked not to be identified because the personnel changes haven’t been announced.

I don’t regularly cover personnel moves here, but Alan Dye jumping over to Meta has been a big deal in the Apple news ecosystem. John Gruber, in a piece titled “Bad Dye Job“ on his Daring Fireball blog, wrote a scathing takedown of Dye, excoriating his tenure at Apple and flogging him for going over to Meta, which is arguably Apple’s arch nemesis.

Putting Alan Dye in charge of user interface design was the one big mistake Jony Ive made as Apple’s Chief Design Officer. Dye had no background in user interface design — he came from a brand and print advertising background. Before joining Apple, he was design director for the fashion brand Kate Spade, and before that worked on branding for the ad agency Ogilvy. His promotion to lead Apple’s software interface design team under Ive happened in 2015, when Apple was launching Apple Watch, their closest foray into the world of fashion. It might have made some sense to bring someone from the fashion/brand world to lead software design for Apple Watch, but it sure didn’t seem to make sense for the rest of Apple’s platforms. And the decade of Dye’s HI leadership has proven it.

I usually appreciate Gruber’s writing and take on things. He’s unafraid to tell it like it is and to be incredibly direct. Which makes people love him and fear him. But in paragraph after paragraph, Gruber just lays in on Dye.

It’s rather extraordinary in today’s hyper-partisan world that there’s nearly universal agreement amongst actual practitioners of user-interface design that Alan Dye is a fraud who led the company deeply astray. It was a big problem inside the company too. I’m aware of dozens of designers who’ve left Apple, out of frustration over the company’s direction, to work at places like LoveFrom, OpenAI, and their secretive joint venture io. I’m not sure there are any interaction designers at io who aren’t ex-Apple, and if there are, it’s only a handful. From the stories I’m aware of, the theme is identical: these are designers driven to do great work, and under Alan Dye, “doing great work” was no longer the guiding principle at Apple. If reaching the most users is your goal, go work on design at Google, or Microsoft, or Meta. (Design, of course, isn’t even a thing at Amazon.) Designers choose to work at Apple to do the best work in the industry. That has stopped being true under Alan Dye. The most talented designers I know are the harshest critics of Dye’s body of work, and the direction in which it’s been heading.

Designers can be great at more than one thing and they can evolve. Being in design leadership does not mean that you need to be the best practitioner of all the disciplines, but you do need to have the taste, sensibilities, and judgement of a good designer, no matter how you started. I’m a case in point. I studied traditional graphic design in art school. But I’ve been in digital design for most of my career now, and product design for the last 10 years.

Has UI over at Apple been worse over the last 10 years? Maybe. I will need to analyze things a lot more carefully. But I vividly remember having debates with my fellow designers about Mac OS X UI choices like the pinstriping, brushed metal, and many, many inconsistencies when I was working in the Graphic Design Group in 2004. UI design has never been perfect in Cupertino.

Alan Dye isn’t a CEO and wasn’t even at the same exposure level as Jony Ive when he was still at Apple. I don’t know Dye, though we’re certainly in the same design circles—we have 20 shared connections on LinkedIn. But as far as I’m concerned, he’s a civilian because he kept a low profile, like all Apple employees.

The parasocial relationships we have with tech executives is weird. I guess it’s one thing if they have a large online presence like Instagram’s Adam Mosseri or 37signals’ David Heinemeier Hansson (aka DHH), but Alan Dye made only a couple appearances in Apple keynotes and talked about Liquid Glass. In other words, why is Gruber writing 2,500 words in this particular post, and it’s just one of five posts covering this story!

Anyway, I’m not a big fan of Meta, but maybe Dye can bring some ethics to the design team over there. Who knows. Regardless, I am wishing him well rather than taking him down.

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.

Like many people, I tried OpenAI’s ChatGPT Atlas browser last week. I immediately made it my daily driver, seeing if I could make the best of it. Tl;dr: it’s still early days and I don’t believe it’s quite ready for primetime. But let’s back up a bit.

The Era of the AI Browser Is Here

Back in July, I reviewed both Comet from Perplexity and Dia from The Browser Company. It was a glimpse of the future that I wanted. I concluded:

The AI-powered ideas in both Dia and Comet are a step change. But the basics also have to be there, and in my opinion, should be better than what Chrome offers. The interface innovations that made Arc special shouldn’t be sacrificed for AI features. Arc is/was the perfect foundation. Integrate an AI assistant that can be personalized to care about the same things you do so its summaries are relevant. The assistant can be agentic and perform tasks for you in the background while you focus on more important things. In other words, put Arc, Dia, and Comet in a blender and that could be the perfect browser of the future.

There were also open rumors that OpenAI was working on a browser of their own, so the launch of Atlas was inevitable.

Since I finished migrating my site from Next.js/Payload CMS to Astro, I’ve been wanting to redo the tag taxonomy for my posts. They’d gotten out of hand over time, and the tag tumbleweed grew to more than 80 tags. What the hell was I thinking when I had both “product design” and “product designer”?

Anyway, I tried a few programmatic ways to determine the best taxonomy, but ultimately manually culled it down to 29 tags. Then, I really didn’t want to have to manually go back and re-tag more than 350 posts. So I turned to AI. It took two attempts. The first one that Cursor planned for me used ML to discern the tags, but that failed spectacularly because it was using frequency of words, not semantic meaning.

So I ultimately tried an LLM approach and that worked. I spec’d it out and had Claude Code write it for me. Then after another hour or so of experimenting and seeing if the resulting tags worked, I let it run concurrently in four terminal windows to process all the posts from the past 20 years. Et voila!

I spot-checked at least half of all the posts manually and made some adjustments. But I’m pretty happy with the results.

See the new tags on the Search page or just click around and explore.

Two weekends ago, I quietly relaunched my blog. It was a heart transplant really, of the same design I’d launched in late March.

The First Iteration

Back in early November of last year, I re-platformed from WordPress to a home-grown, Cursor-made static site generator. I’d write in Markdown and push code to my GitHub repository and the post was published via Vercel’s continuous deployment feature. The design was simple and it was a great learning project for me.

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.

For men of a certain age, Pink Floyd represents a milieu—brooding, melancholy, emo before emo had a name. I started listening to Floyd in high school and being a kid who always felt like an outsider, The Wall really resonated with me. In college, I started exploring their back catalog and Animals and Wish You Were Here became my favorites. Of course, as a designer, I have always loved the album covers. Storm Thorgerson and Hipgnosis’ surreal photos were mind-bending and added to the music’s feelings of alienation, yearning, and the aching beauty of being lost.

I hadn’t listened to the music in a while but the song “Two Suns in the Sunset” from *The Final Cut *periodically pops into my head. I listened to the full album last Sunday. On Tuesday, I pulled up their catalog again to play in the background while I worked and to my surprise, all the trippy cover art was replaced by white type on a black surface!

Today’s Apple keynote opened with a classic quote from Steve Jobs.

Then a video played, focused on the fundamental geometric shapes that can be found in Apple’s products: circles in the HomePod, iPhone shutter button, iPhone camera, MagSafe charging ring, Digital Crown on Apple Watch; rounded squares in the charging block, Home scene button, Mac mini, keycaps, Finder icon, FaceID; to the lozenges found in the AirPods case, MagSafe port, Liquid Glass carousel control, and the Action button on Apple Watch Ultra.

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!

President Trump signed an executive order creating America by Design, a national initiative to improve the usability and design of federal services, both digital and physical. The order establishes a National Design Studio inside the White House and appoints Airbnb co-founder and RISD graduate Joe Gebbia as the first Chief Design Officer. The studio’s mandate: cut duplicative design costs, standardize experiences to build trust, and raise the quality of government services. Gebbia said he aims to make the U.S. “the most beautiful, and usable, country in the digital world.”

Ironically, this follows the gutting of the US Digital Service, left like a caterpillar consumed from within by parasitic wasp larvae, when it was turned into DOGE. And as part of the cutting of thousands from the federal workforce, 18F, the pioneering digital services agency that started in 2014, was eliminated.

Ethan Marcotte, the designer who literally wrote the book on responsive design and worked at 18F, had some thoughts. He points out the announcement web page weighs in at over three megabytes. Very heavy for a government page and slow for those in the country unserved by broadband—about 26 million. On top of that, the page is full of typos and is an accessibility nightmare.

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?