“Keep the Robots Out of the Gym”

AI/ML

I keep finding myself thinking of this short essay from Daniel Miessler:

Think very carefully about where you get help from AI.

I think of it as Job vs. Gym.

  • If we’re working a manual labor job, it’s fine to have AI lift heavy things for us because the actual goal is to move the thing, not to lift it.
  • This is the exact opposite of going to the gym, where the goal is to lift the weight, not to move it.

He argues for identifying gym tasks (e.g. critical thinking, problem solving), and for those use just your brain (with minimal AI assistance, if any).

My primary metric for this is whether or not I am getting sharper at the skills that are closest to my identity.

The whole essay (2-min read) is worth checking out.

The Rive founders talk interactive animation

After Effects, Design

Having gotten my start in Flash 2.0 (!), and having joined Adobe in 2000 specifically to make a Flash/SVG authoring tool that didn’t make me want to walk into the ocean, I felt my cold, ancient Grinch-heart grow three sizes listening to Guido and Luigi Rosso—the brother founders behind Rive—on the School of Motion podcast:

[They] dig into what makes this platform different, where it’s headed, and why teams at Spotify, Duolingo, and LinkedIn are building entire interactive experiences with it!

Here’s a NotebookLM-made visualization of the key ideas:

Table of contents:

Reflecting on 2025: A Year of Milestones 00:24
The Challenges of a Three-Sided Marketplace 02:58
Adoption Across Designers, Developers, and Companies 04:11
The Evolution of Design and Development Collaboration 05:46
The Power of Data Binding and Scripting 07:01
Rive’s Impact on Product Teams and Large Enterprises 09:18
The Future of Interactive Experiences with Rive 12:36
Understanding Rive’s Mental Model and Scripting 24:32
Comparing Rive’s Scripting to After Effects and Flash
The Vision for Rive in Game Development 31:30
Real-Time Data Integration and Future Possibilities 40:26
Spotify Wrapped: A Showcase of Rive’s Potential 42:08
Breaking Down Complex Experiences 46:18
Creative Technologists and Their Impact 51:07
The Future of Rive: 3D and Beyond 59:30
Opportunities for Motion Designers with Rive 1:11:38

“There will still be smart people, but only those who choose to be”

AI/ML

As AI continues to infuse itself more deeply into our world, I feel like I’ll often think of Paul Graham’s observation here:

Qwen promises images->layers

AI/ML

I initially mistook this tech as text->layers, but it’s actually image->layers. Having said that, if it works well, it might be functionally similar to direct layer output. I need to take it for a spin!

“We Can Imagine It For You Wholesale”

Miscellaneous, Nano Banana

“It’s not that you’re not good enough, it’s just that we can make you better.”

So sang Tears for Fears, and the line came to mind as the recently announced PhotaLabs promised to show “your reality, but made more magical.” That is, they create the shots you just missed, or wish you’d have taken:

Honestly, my first reaction was “ick.” I know that human memory is famously untrustworthy, and photos can manipulate it—not even through editing, but just through selective capture & curation. Even so, this kind of retroactive capture seems potentially deranging. Here’s the date you wish you’d gone on; here’s the college experience you wish you’d had.

I’m reminded of the Nathaniel Hawthorne quote featured on the Sopranos:

No man for any considerable period can wear one face to himself, and another to the multitude, without finally getting bewildered as to which may be the true.

Like, at what point did you take these awkward sibling portraits…? 


And, hey, darn if I can resist the devil’s candy: I wasn’t able to capture a shot of my sons together with their dates, so off I went to a combo of Gemini & Ideogram. I honestly kinda love the results, and so down the cognitive rabbit hole I slide… ¯\_(ツ)_/¯ 

Of course, depending on how far all this goes, the following tweet might prove to be prophetic:

Look at this & tell me Photoshop’s not cooked

AI/ML, Idle Philosophizing, Nano Banana

Sorry-not-sorry to be a bit provocative, but seriously, to highlight one of one million examples:

And in a slightly more demanding case:

For the latter, I used Photoshop to remove a couple of artifacts from the initial Scarface-to-puppy Nano Banana generation, and to resize the image to fit onto a canvas—but geez, there’s almost no world where I’d now think to start in PS, as I would’ve for the last three decades.

Back in 2002, just after Photoshop godfather Mark Hamburg left the project in order to start what became Lightroom, he talked about how listening too closely to existing customers could backfire: they’ll always give you an endless list of nerdy feature requests, but in addressing those, you’ll get sucked up the complexity curve & end up focusing on increasingly niche value.

Meanwhile disruptive competitors will simply discard “must-have” features (in the case of Lightroom, layers), as those had often proved to be irreducibly complex. iOS did this to macOS not by making the file system easier to navigate, but by simply omitting normal file system access—and only later grudgingly allowing some of it.

Steve Jobs famously talked about personal computers vs. mobile devices in terms of cars vs. trucks:

Obviously Photoshop (and by analogy PowerPoint & Excel & other “indispensable” apps) will stick around for those who genuinely need it—but generative apps will do to Photoshop what (per Hamburg) Photoshop did to the Quantel Paintbox, i.e. shove it up into the tip of the complexity/usage pyramid.

Adobe will continue to gamely resist this by trying to make PS easier to use, which is fine (except of course where clumsy new affordances get in pros’ way, necessitating a whole new “quiet mode” just to STFU!). And—more excitingly to guys like me—they’ll keep incorporating genuinely transformative new AI tech, from image transformation to interactive lighting control & more.

Still, everyone sees what’s unfolding, and “You cannot stop it, you can only hope to contain it.” Where we’re going, we won’t need roads.

When life gives you hospitalized lemons…

AI/ML, Illustration

…you waste pass the time screwing around doing competitive AI model featuring the building’s baffling architecture…

…and sketchy chow:

How-to: AI renovation vids

AI/ML

This seems like the kind of specific, repeatable workflow that’ll scale & create a lot of real-world value (for home owners, contractors, decorators, paint companies, and more). In this thread Justine Moore talks about how to do it (before, y’know, someone utterly streamlines it ~3 min from now!):

Google virtual try-on arrives

AI/ML, Try-on

Well, after years and years of trying to make it happen, Google has now shipped the ability to upload a selfie & see yourself in a variety of outfits. You can try it here.


At least in my initial tests, results were kinda weird & off-putting:


I mean, obviously this ancient banger (courtesy of Bryan O’Neil Hughes, c.2003) is the only correct rendering! 🙂

Insane Nano Banana style transfer

AI/ML, Nano Banana

As I’m fond of noting, only thing more incredible than witchcraft like this is just how little notice people now take of it. ¯\_(ツ)_/¯ But Imma keep noticing!

Two years ago (i.e. an AI eternity, obvs), I was duly impressed when, walking around a model train show with my son, DALL•E was able to create art kinda-sorta in the style of vintage boxes we beheld:

I still think that’s amazing—and it is!—but check out how far we’ve come. At a similar gathering yesterday, I took the photo below…

…and then uploaded it to Gemini with the following prompt: “Please create a stack of vintage toy car boxes using the style shown in the attached picture. The cars should be a silver 1990 Mazda Miata, a red 2003 Volkswagen Eurovan, a blue 2024 Volvo XC90, and a gray 2023 BMW 330.” And boom, head shot, here’s what it made:

I find all this just preposterously wonderful, and I hope I always do.

As Einstein is said to have remarked, “There are only two ways to live your life: one is as though nothing is a miracle, the other is as though everything is.”

Content-Aware Fail (and how to avoid it)

AI/ML

Jesús Ramirez has forgotten, as the saying goes, more about Photoshop than most people will ever know. So, encountering some hilarious & annoying Remove Tool fails…


…reminded me that I should check out his short overview on “How To Remove Anything From Photoshop.”

Lucky & Charming

AI/ML, Illustration

This season my alma mater has been rolling out sport-specific versions of the classic leprechaun logo, and when the new basketball version dropped today, I decided to have a little fun seeing how well Nano Banana could riff on the theme.

My quick take: It’s pretty great, though applying sequential turns may cause the style to drift farther from the original (more testing needed).

We like AI—but we don’t like liking AI

AI/ML

Interesting—if not wholly unexpected—finding: People dig what generative systems create, but only if they don’t know how the pixel-sausage was made. ¯\_(ツ)_/¯

You’re not crazy, you’re not dumb, and you’re absolutely right to give a shit.

Idle Philosophizing, Shit That Actually Matters

That’s my core takeaway from this great conversation, which will give you hope.

Slack & Flickr founder Stewart Butterfield, whose We Don’t Sell Saddles Here memo I’ve referenced countless times, sat down for a colorful & wide-ranging talk with Lenny Rachitsky. For the key points, check out this summary, or dive right into the whole chat. You won’t regret it.

Visual summary courtesy of NotebookLM:

(00:00) Introduction to Stewart Butterfield
(04:58) Stewart’s current life and reflections
(06:44) Understanding utility curves
(10:13) The concept of divine discontent
(15:11) The importance of taste in product design
(19:03) Tilting your umbrella
(28:32) Balancing friction and comprehension
(45:07) The value of constant dissatisfaction
(47:06) Embracing continuous improvement
(50:03) The complexity of making things work
(54:27) Parkinson’s law and organizational growth
(01:03:17) Hyper-realistic work-like activities
(01:13:23) Advice on when to pivot
(01:18:36) The importance of generosity in leadership
(01:26:34) The owner’s delusion

Luck o’ the vibe coders

AI/ML

Being crazy-superstitious when it comes to college football, I must always repay Notre Dame for every score by doing a number of push-ups equivalent to the current point total.

In a normal game, determining the cumulative number of reps is pretty easy (e.g. 7 + 14 + 21), but when the team is able to pour it on, the math—and the burn—get challenging. So, I used Gemini the other day to whip up this little counter app, which it did in one shot! Days of Miracles & Wonder, Vol. ∞.

A charming BTS for Apple’s “Friends” holiday spot

Design

There’s almost no limit to my insane love of practical animal puppetry (usually the sillier, the better—e.g. Triumph, The Falconer), so I naturally loved this peek behind the scenes of Apple’s new spot:

Puppeteers dressed like blueberries. Individually placed whiskers. An entire forest built 3 feet off the ground. And so much more.

Bonus: Check out this look into the making of a similarly great Portland tourism commercial:

AI-powered catharsis

AI/ML, Illustration

I can’t think of a more burn-worthy app than Concur (whose “value prop” to enterprises, I swear, includes the amount they’ll save when employees give up rather than actually get reimbursed).

Visualizing conversations with Nano Banana

AI/ML, Illustration, Infographics, Nano Banana

The ever thoughtful Blaise Agüera y Arcas (CTO of Technology & Society at Google) recently sat down for a conversation with the similarly deep-thinking Dan Faggella. I love that I was able to get Gemini to render a high-level view of the talk:

My workflow, FWIW:

  • Use Gemini in Chrome to create a summary.
  • Open it in Gemini & copy it to a Google Doc.
  • Open the doc in NotebookLM & specify infographic creation preferences.
  • Download image, open it in Gemini, and refine likenesses by uploading images of each speaker.
  • Make minor tweaks in Photoshop to deal with the aspect ratio changing (a subtle & intermittent but annoying bug).

Here’s the stimulating chat itself:

Continue reading →

Gemini/Nano Banana promises SVG generation

AI/ML, Illustration, Nano Banana

Creating clean vectors has proven to be an elusive goal. Firefly in Illustrator still (to my knowledge) just generates bitmaps which then get vectorized. Therefore this tweet caught my attention:

In my very limited testing so far, however, results have been, well, impressionistic. 🙂

Here’s a direct comparison of my friend Kevin’s image (which I received as an image) vectorized via Image Trace (way more points than I’d like, but generally high fidelity), vs. the same one converted to SVG via Gemini(clean code/lines, but large deviation from the source drawing):

But hey, give it time. For now I love seeing the progress!

Fried chicken, product obsession, and Richard Feynman

Design

Passion is contagious, and I love when people deeply care what they’re bringing into the world. I had no idea I could find the details of fast-food chicken so interesting, but dang if founder Todd Graves’s enthusiasm doesn’t jump right off the screen. Seriously, give it a watch!

I’m reminded of Richard Feynman’s keen observation:

More tangentially, this gets me thinking back to my actor friends’ appreciation of Don Cheadle’s craft in this scene from Boogie Nights. “I could watch that guy pick out donuts all day!” And even though I can’t grok the work nearly as deeply as they do, I love how much they love it.

AI, outcomes, and closing loops: How Canva thinks

AI/ML

My buddy Bilawal recently sat down with Canva cofounder & Chief Product Officer Cameron Adams for an informative conversation. These points, among others, caught my attention:

  • “Canva is a goal-achievement machine.” That is, users approach it with particular outcomes in mind (e.g. land your first customer, get your first investment), and the feature development team works back from those goals. As the old saying goes, “People don’t want a quarter-inch drill, they want a quarter-inch hole”—i.e. a specific outcome.
  • They seek to reduce the gap between idea & outcome. This reminded me of the first Adobe promo I saw more than 30 years ago: “Imagine what you can create. Create what you can imagine.”
  • Measuring the achievement of goals is critical. That includes gathering insights from audience response.
  • They’re pursuing a three-tiered AI strategy: homegrown foundational models that they need to own (based on deep insight into user behavior); partnerships with state-of-the-art models (e.g. GPT, Veo); and a rich ecosystem and app marketplace (hosting image & music generation and more).
  • “When you think about AI as a collaborator, it opens up a whole palette of different interactions & product experiences you can deliver.” No single modality (e.g. prompting alone) is ideal for everything from ideation to creation to refinement.
  • What’s it like to author at a higher level of abstraction? “It’s a dance,” and it’s still a work in progress.
  • What’s the role of personalization? Responsive content. Personalizing messaging has been a huge driver of Canva’s growth, and they want to bring similar tools & best practices to everyone.
  • “The real crux of Canva is storytelling.” Video is now used by tens of millions of people. Across media (video, images, presentations), the same challenges appear: Properly complete your idea. Make fine-grained edits. Bring in others & get their feedback.
  • “Knowing the start & the end, but less of the middle.” AI-enabled tools can remove production drudgery, but one’s starting point & desired outcome remain essential. Start: Fundamental understanding of what works. Ideas, thinking creatively. Elements of editorship & taste are essential. Later: It’s how you express this, measure impact, take insights into the creation loop.

00:00 – Canva’s $32B Empire the future of Design
02:26 – Design for Everyone: Canva’s Origin Story
04:19 – Why Canva Bet on the Web
07:29 – How Have Canva Users Changed Over the Years?
12:14 – Why Canva Isn’t Just Unbundling Adobe
14:50 – Canva’s AI Strategy Explained
18:12 – What Does Designing With AI Look Like?
22:55 – Scaling Content with Sheets, Data, and AI
27:17 – What is Canva Code?
29:38 – How Does Canva Fit Into Today’s AI Ecosystem?
32:35 – Why Adobe and Microsoft Should Be Worried
37:52 – Will Canva Expand Into Video Creation?
41:10 – Will AI Eliminate or Expand Creative Jobs?

A Brief History of the World (Models)

3D, AI/ML

On Friday I got to meet Dr. Fei-Fei Li, “the godmother of AI,” at the launch party for her new company, World Labs (see her launch blog post). We got to chat a bit about a paradox of complexity: that as computer models for perceiving & representing the world grow massively more sophisticated, the interfaces for doing common things—e.g. moving a person in a photo—can get radically simpler & more intentional. I’ll have more to say about this soon.

Meanwhile, here’s her fascinating & wide-ranging conversation with Lenny Rachitsky. I’m always a sucker for a good Platonic allegory-of-the-cave reference. 🙂

From the YouTube summary:

(00:00) Introduction to Dr. Fei-Fei Li
(05:31) The evolution of AI
(09:37) The birth of ImageNet
(17:25) The rise of deep learning
(23:53) The future of AI and AGI
(29:51) Introduction to world models
(40:45) The bitter lesson in AI and robotics
(48:02) Introducing Marble, a revolutionary product
(51:00) Applications and use cases of Marble
(01:01:01) The founder’s journey and insights
(01:10:05) Human-centered AI at Stanford
(01:14:24) The role of AI in various professions
(01:18:16) Conclusion and final thoughts

And here’s Gemini’s solid summary of their discussion of world models:

  • The Motivation: While LLMs are inspiring, they lack the spatial intelligence and world understanding that humans use daily. This ability to reason about the physical world—understanding objects, movement, and situational awareness—is essential for tasks like first response or even just tidying a kitchen 32:23.
  • The Concept: A world model is described as the lynchpin connecting visual intelligence, robotics, and other forms of intelligence beyond language 33:32. It is a foundational model that allows an agent (human or robot) to:
    • Create worlds in their mind’s eye through prompting 35:01.
    • Interact with that world by browsing, walking, picking up objects, or changing things 35:12.
    • Reason within the world, such as a robot planning its path 35:31.
  • The Application: World models are considered the key missing piece for building effective embodied AI, especially robots 36:08. Beyond robotics, the technology is expected to unlock major advances in scientific discovery (like deducing 3D structures from 2D data) 37:48, games, and design 37:31.
  • The Product: Dr. Li co-founded World Labs to pursue this mission 34:25. Their first product, Marble, is a generative model that outputs genuinely 3D worlds which users can navigate and explore 49:11. Current use cases include virtual production/VFX, game development, and creating synthetic data for robotic simulation 53:05.

Design: Finding your sacred objects

Idle Philosophizing

My old pal Sam is one of the most thoughtful, down-to-earth guys you’re ever likely to meet in the design community, and if you’re looking for a calm but re-energizing way to spend a couple of minutes, I think you’ll really enjoy his seven-minute talk below. I won’t spoil anything, but do trust me. 🙂

And here’s a little visual summary courtesy of NotebookLM:

“How ChatGPT is fueling an existential crisis in education”

AI/ML

I thought this was a pretty interesting & thoughtful conversation. It’s interesting to think about ways to evaluate & reward process (hard work through challenges) and not just product (final projects, tests, etc.). AI obviously enables a lot of skipping the former in pursuit of the latter—but (shocker!) people then don’t build knowhow around solving problems, or even remember (much less feel pride in) the artifacts they produce.

The issues go a lot deeper, to the very philosophy of education itself. So we sat down and talked to a lot of teachers — you’ll hear many of their voices throughout this episode — and we kept hearing one cri du coeur again and again: What are we even doing here? What’s the point?

Links, courtesy of the Verge team:

  • A majority of high school students use gen AI for schoolwork | College Board
  • About a quarter of teens have used ChatGPT for schoolwork | Pew Research
  • Your brain on ChatGPT | MIT Media Lab
  • My students think it’s fine to cheat with AI. Maybe they’re on to something. | Vox
  • How children understand and learn from conversational AI | McGill University
  • File not Found | The Verge

Adobe Research debuts incredibly fast video synthesis

AI/ML

Check out MotionStream, “a streaming (real-time, long-duration) video generation system with motion controls, unlocking new possibilities for interactive content generation.” It’s said to run at 29fps on a single H100 GPU (!).

What I’m really wondering, though, it whether/when/how an interactive interface like this can come to Photoshop & other image-editing environments. I’m not yet sure how the dots connect, but could it be paired with something like this model?

Chocolate-coated glass shards

AI/ML

Oh man, this parody of the messaging around AI-justified (?) price increases is 100% pitch perfect. (“It’s the corporate music that sends me into a rage.”)

 

 
 
 
 
 
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“We Built The Matrix to Train You for What’s Coming”

3D, AI/ML

My friend Bilawal got to sit down with VFX pioneer John Gaeta to discuss “A new language of perception,” Bullet Time, groundbreaking photogrammetry, the coming Big Bang/golden age of storytelling, chasing “a feeling of limitlessness,” and much more.

In this conversation:

— How Matrix VFX techniques became the prototypes for AI filmmaking tools, game engines, and AR/VR systems
— How The Matrix team sourced PhD thesis films from university labs to invent new 3D capture techniques
— Why “universal capture” from Matrix 2 & 3 was the precursor to modern volumetric video and 3D avatars
— The Matrix 4 experiments with Unreal Engine that almost launched a transmedia universe based on The Animatrix
— Why dystopian sci-fi becomes infrastructure (and what that means for AI safety)
— Where John is building next: Escape.art and the future of interactive storytelling

Continue reading →

A cool new Photoshop feature (that’s still kinda dumb)

Typography

I’m pleased to see that as promised back in May, Photoshop has added a “Dynamic Text” toggle that automatically resizes the size of the letters in each line to produce a visually “packed” look:

Results can be really cool, but because the model has no knowledge of the meaning and importance of each word, they can sometimes look pretty dumb. Here’s my canonical example, which visually emphasizes exactly the wrong thing:

I continue to want to see the best of both worlds, with a layout engine taking into account the meaning & thus visual importance of words—like what my team shipped last year:

I’m absolutely confident that this can be done. I mean, just look at the kind of complex layouts I was knocking out in Ideogram a year ago.

The missing ingredient is just the link between image layouts & editability—provided either by bitmap->native conversion (often hard, but doable in some cases), or by in-place editing (e.g. change “Merry Christmas” to “Happy New Year” on a sign, then regenerate the image using the same style & dimensions)—or both.

Bonus points go to the app & model that enable generation with transparency (for easy compositing), or conversion to vectors—or, again, ¿porque no los dos? 🙂

Demo: Flux vs. Nano Banana inside Photoshop

AI/ML, Nano Banana

I recently shared a really helpful video from Jesús Ramirez that showed practical uses for each model inside Photoshop (e.g. text editing via Flux). Now here’s a direct comparison from Colin Smith, highlighting these strengths:

  • Flux: Realistic, detailed; doesn’t produce unwanted shifts in regions that should stay unchanged. Tends to maintain more of the original image, such as hair or background elements.
  • Nano Banana: Smooth & pleasing (if sometimes a bit “Disney”); good at following complex prompts. May be better at removing objects.

These specific examples are great, but I continue to wish for more standardized evals that would help produce objective measures across models. I’m investigating the state of the art there. More to share soon, I hope!

Emu 3.5 looks seriously impressive

3D, AI/ML

Improvements to imaging continues its breakneck pace, as engines evolve from “simple” text-to-image (which we considered miraculous just three years ago—and which I still kinda do, TBH) to understanding time & space.

Now Emu (see project page, code) can create entire multi-page/image narratives, turn 2D images into 3D worlds, and more. Check it out: