Adobe, Apple, Canva and the transition from tools → templates → prompts → intent
For decades, some of the most important companies in technology won by building better tools.
Adobe gave creative professionals Photoshop, Illustrator, Premiere and an entire ecosystem for turning ideas into finished work.
Apple transformed complicated computing into beautifully designed products that ordinary people could understand.
Canva took design in another direction, making it accessible to millions of people who would never consider themselves designers.
These companies didn't just build successful products.
They helped define how we create.
But artificial intelligence is beginning to challenge something much deeper than their individual products.
What happens when the tool itself becomes less important?
Because I believe we are moving from an era of tools to an era of intent.
And the timing of that question suddenly feels impossible to ignore.
Two Leadership Changes, One Very Interesting Moment
On September 1, John Ternus officially became CEO of Apple, succeeding Tim Cook, who moved into the role of executive chairman.
Two days later, Adobe announced that Anil Chakravarthy will become its next president and CEO on December 1, with Shantanu Narayen moving to executive chair.
I find the timing fascinating.
These are not struggling companies replacing failed leaders. Cook and Narayen were enormously successful. Cook took the company Steve Jobs rebuilt and scaled it into one of the most powerful businesses in history. Narayen led Adobe through its historic transition from boxed software to Creative Cloud subscriptions.
They mastered the era they were given.
And now their successors inherit something very different.
AI isn't merely asking Apple and Adobe to make their existing products smarter. It may force them to reconsider some of the assumptions those products were built around.
For Apple, John Ternus inherits a company whose modern success has been built around devices, apps and interfaces at the exact moment AI may begin making the interface less visible.
For Adobe, the choice of Anil Chakravarthy is especially interesting. He comes from the side of Adobe focused on customer experience, orchestration and worldwide field operations—not from the traditional creative-products path many people might have expected.
I don't pretend to know what either appointment ultimately means.
But I do think the question facing both companies is much bigger than, How do we add AI?
What parts of the last era still matter when the interface becomes intent?
For Most of My Career, We Learned the Tool
I have watched this evolution personally.
I started teaching computers when using a computer meant learning commands.
DOS.
WordStar.
Lotus 1-2-3.
WordPerfect.
Eventually graphical interfaces arrived and software became easier to use.
Later, during my years at Adobe, I had a front-row seat to the extraordinary power professional software could put into the hands of creative people.
But the basic relationship remained the same.
You had an idea.
You opened a tool.
And you had to know how to operate that tool well enough to produce the result.
Photoshop is an extraordinary example.
If you wanted to manipulate an image professionally, Photoshop gave you incredible power.
But that power came with a requirement:
You had to learn Photoshop.
Layers.
Masks.
Selections.
Curves.
Blend modes.
Filters.
Keyboard shortcuts.
Every new capability needed somewhere to live—a menu, panel, toolbar, dialog box, mode or preference.
The software was the interface between your imagination and the finished result.
And becoming good at the software became part of becoming good at the craft.
For decades, that made perfect sense.
I'm no longer convinced it will.
The Interface Is Becoming Language
Something fundamental happens when I can simply describe what I want.
Instead of asking:
Which tool should I use?
I can say:
Here's what I'm trying to accomplish.
That sounds like a small distinction.
It isn't.
It may represent one of the biggest changes in the history of personal computing.
The interface is moving from menus, buttons, palettes and commands toward something humans already know how to use:
language.
And once language becomes the interface, the value begins moving somewhere else.
From knowing how to operate the tool
to knowing what you want the tool to accomplish.
That's the shift from tools to intent.
Adobe May Already Be Showing Us the Transition
This is why Adobe's recent moves are so interesting to me.
Adobe has been bringing Photoshop, Illustrator, Premiere, Firefly, Acrobat and other capabilities directly into conversational AI environments.
Think about how different that is from the traditional software model.
For decades, Adobe's relationship with the customer was essentially:
Here are the tools. Learn them.
The emerging model is:
Tell me what you want.
Perhaps the future isn't always convincing people to come into Photoshop.
Perhaps Adobe's technology increasingly has to go where the intent already exists.
That doesn't mean Photoshop disappears. Professionals will still need precision, control and deep editing capabilities.
But it does change where the creative process can begin.
And that may be one of the biggest challenges facing Anil Chakravarthy when he takes over Adobe.
Is the future a smarter Creative Cloud?
Or is Adobe's real opportunity to become the creative intelligence and infrastructure behind outcomes—even when the customer never thinks about which Adobe application produced them?
That is a very different strategic question.
Apple Faces a Different Version of the Same Question
Apple's great genius has always been the interface.
The Macintosh.
The mouse.
The iPod click wheel.
Multi-touch on the iPhone.
Apple repeatedly took complicated technology and created an interface that made it feel obvious.
Which is why John Ternus taking over Apple at this particular moment is so interesting.
What happens when the ultimate interface is no longer something designed on a screen?
What happens when the interface becomes conversation?
Or context?
Or an intelligent system that understands what you're trying to accomplish before you ever open an app?
There is another fascinating piece to this story.
Jony Ive, the designer whose work helped define the physical language of the iMac, iPod, iPhone, iPad and Apple Watch, is now deeply involved with OpenAI in developing a new generation of AI products.
I can't help but appreciate the symbolism.
One of the people who helped perfect the smartphone era is now working on what may come after it.
The question may no longer be:
What does the next computer look like?
It may be:
What does computing look like when we stop thinking about the computer?
That's a question John Ternus may have to answer while protecting one of the most successful device ecosystems ever created.
Tim Cook's job was, in large part, to scale and protect Apple's greatest inventions.
Ternus may have to decide which assumptions behind those inventions still belong in the next era.
And Then There's Canva
Canva solved a very different problem.
Instead of teaching millions of people how to become designers, it gave them an enormous library of professionally designed templates.
Need an Instagram post?
Choose a template.
Need a presentation?
Choose a template.
Need a flyer?
Choose a template.
Change the photo.
Change the headline.
Change the colors.
Done.
It was brilliant because Canva dramatically reduced the amount of design knowledge required to create something that looked reasonably good.
The template became a layer between the user and the complexity of design.
But now Canva is explicitly challenging the very idea that made it famous.
Canva describes AI 2.0 as its most significant product evolution since the company launched in 2013, transforming Canva into what it calls a “conversational, agentic platform.” Its description of where creation now begins is even more revealing: rather than starting with a template or blank page, Canva says we can begin with an idea, a goal, a brief, a rough sketch or even an unfinished thought, then develop it through conversation.
And then I saw the phrase that immediately caught my attention.
Canva says AI 2.0 “understands intent.”
Intent.
The very word that had been running through my mind while writing this article.
The company that helped move millions of people from tools to templates is now building a future where we may not need to choose the template at all.
Canva may be disrupting its own disruption.
I had to try it.
So while writing this article, I opened Canva AI 2.0, uploaded a photograph of one of my Jacquez Art masterpieces, and decided to conduct a simple experiment.
I wasn't going to choose a template.
I wasn't going to tell Canva how to design anything.
I was only going to tell it what I wanted the design to accomplish.
I Never Chose a Template
I explained that Jacquez Art is a luxury custom sports jersey framing studio.
I wanted an Instagram post that made the craftsmanship feel exceptional and positioned the piece as a one-of-one work of art rather than ordinary sports memorabilia.
I told it the framed masterpiece should be the hero.
I wanted a serious collector to see it and immediately feel that this was something special.
Then I stopped.
I didn't choose a template.
I didn't choose a font.
I didn't pick a color palette.
I didn't position the photograph.
I didn't tell Canva how to design it.
I told it what I wanted the design to accomplish.
And Canva started designing.
That's when the idea behind this article stopped feeling theoretical.
The company that became famous for making templates accessible had just allowed me to bypass the template almost entirely.
Tools → Templates → Prompts → Intent.
I was watching the transition happen in front of me.
Then Something Even Stranger Happened
The first result was surprisingly good, but it still felt too much like an advertisement.
So I told Canva that.
I didn't tell it which font to change or which element to move.
I said I wanted the piece to feel more like a beautifully photographed one-of-one artwork in a luxury editorial magazine. I wanted the masterpiece to create the emotion, not the marketing copy.
Canva interpreted the criticism.
It removed much of the advertising language. It introduced more negative space. It changed the environment and made the overall presentation quieter.
Then I noticed something else.
Canva appeared to be looking for context about Jacquez Art. Among the references it surfaced was content from our existing online presence.
That stopped me.
I hadn't spent twenty minutes explaining our brand. I hadn't built a mood board. I hadn't selected one of Canva's templates and tried to make Jacquez Art fit inside it.
I didn't browse Canva looking for something that resembled Jacquez Art. Canva went looking for Jacquez Art.
That is a very different relationship with creative software.
And somewhere during this experiment, I realized something strange.
I had stopped thinking about Canva.
I wasn't thinking about templates, menus, layers or tools.
I was talking about craftsmanship, restraint, authenticity, hierarchy, storytelling and what Jacquez Art believes good design should be.
The software had disappeared from the conversation. The work had taken its place.
Maybe that's what it really means for the interface to become intent.
And Then Canva Screwed Up My Jersey
This is where the experiment became much more interesting.
In trying to reinterpret the presentation, Canva also regenerated parts of the masterpiece itself.
The JAMES lettering changed.
The number 6 changed.
Details inside the finished artwork were no longer faithful to the original.
For Jacquez Art, that's unacceptable.
The masterpiece isn't raw material for AI to reinterpret.
It's the product.
So I told Canva that the photograph needed to remain completely unchanged. The environment around it could change. Typography could change. Presentation could change.
But the masterpiece itself needed to be treated as a locked asset.
Canva eventually told me it understood.
It even described the photograph as a locked product asset.
Then it generated another version.
And changed the jersey again.
In fact, the JAMES lettering and number 6 looked even worse.
And this is where something on Canva's own AI 2.0 announcement becomes particularly interesting.
Canva describes what it calls “layered object intelligence.” The idea is that designs are constructed from individual editable objects rather than simply generated as flat images. Canva says that when you ask AI 2.0 to change something, “only that changes.”
That's exactly what professional creative AI needs to be able to do.
It just didn't happen in my experiment.
I asked Canva to change the presentation around the masterpiece.
It changed the masterpiece.
And strangely enough, that failure may have taught me more than a perfect result would have.
Intent Without Constraints Isn't Enough
For decades, professional creative software gave us explicit control.
If I lock a layer in Photoshop, Photoshop doesn't have to understand why I locked it.
The layer is locked.
AI changes that relationship.
Now we're asking the software to interpret not only:
What do I want?
but also:
What must never change?
Those are very different problems.
The traditional interface could be complicated, but it was precise.
The emerging intent interface can feel almost effortless, but it is interpretive.
And interpretation introduces uncertainty.
Canva describes the ambition of AI 2.0 as closing the gap between imagination and finished work without taking away the control creators want along the way.
I think that's exactly the right destination.
My experiment simply showed me how difficult the last part of that promise may be.
And this is where I began reconsidering some of my concern about my old employer, Adobe.
Perhaps the future of creative software isn't replacing precision with intent.
Perhaps it's putting intent on top of precision.
That may turn out to be one of Adobe's greatest opportunities.
Adobe has spent decades building the infrastructure of professional creative control: layers, masks, selections, vectors, typography, color management, non-destructive editing and precise object-level manipulation.
What happens if all that precision remains underneath while AI makes the complexity increasingly invisible?
Imagine saying:
Make this feel like a luxury editorial photograph, but the framed masterpiece is a locked product asset. Do not alter a single pixel inside it.
AI understands the intention.
The underlying creative system enforces the constraint.
Intent on top. Precision underneath.
That may be a far more interesting future than simply replacing Photoshop with a prompt box.
And perhaps that's the real opportunity for Adobe—not abandoning the professional tools it spent decades building, but making all that precision available through an entirely different interface.
Then I Asked Canva What It Had Learned About Me
This may have been my favorite part of the experiment.
Instead of asking Canva to generate another design, I asked it to explain what it believed my design philosophy was.
Its response surprised me.
Among the principles it identified were ideas like:
The jersey is a cultural object, not just sports memorabilia.
Design begins with understanding, not decoration.
Every detail has to earn its place.
Luxury should feel quiet and assured.
Those weren't menu choices.
They were principles.
And then I asked Canva to critique its own work based on the philosophy it had just identified.
That's when things became even more interesting.
It admitted that it had confused generic signals of luxury—dark environments, gold accents and dramatic presentation—with Jacquez Art's actual philosophy.
In other words, it had learned the difference between making something look luxurious and understanding what luxury means to us.
And then it arrived at a sentence I couldn't have written much better myself:
Present the masterpiece; do not redesign the masterpiece.
Think about what happened there.
AI generated something.
My experience told me something was wrong.
I articulated why.
AI incorporated that context and developed a better understanding of the principles behind my judgment.
That is a very different creative relationship than clicking buttons in software.
But there's an important caveat.
Canva could now articulate the principle beautifully while still having failed to execute it reliably.
Understanding the principle and reliably executing the principle are not the same thing.
And once again, human judgment remained essential.
What Happens When the Software Remembers?
There's another AI 2.0 capability Canva announced that became much more interesting to me after this experiment.
Canva calls it Memory Library.
The idea is that the system can remember how you work, learn your preferences and use previous interactions as context for future work. Canva describes each interaction as becoming another building block for what the system understands about you.
That has enormous implications.
At the beginning of my experiment, Canva's idea of luxury was relatively generic.
Dark.
Dramatic.
Polished.
By the end of our conversation, it understood something much closer to what Jacquez Art actually believes.
Restraint.
Authenticity.
Craftsmanship.
The jersey is the hero.
Every element has to earn its place.
Present the masterpiece. Don't redesign it.
Now imagine those lessons don't disappear when the session ends.
Imagine they compound.
The AI doesn't merely become better at generating.
It becomes better at understanding how you think.
And that may turn out to be one of the most important changes of all.
Infinite Possibility Still Creates a Problem
None of this means design becomes easy.
In some ways, it may become harder.
AI can generate ten designs.
Then one hundred.
Then one thousand.
Different layouts.
Different typography.
Different colors.
Different photographs.
Different directions.
Which brings me back to something I've become increasingly convinced matters enormously in the AI era.
Judgment.
The machine can generate possibilities.
Someone still has to decide which possibility deserves to exist.
And that decision comes from somewhere.
Experience.
Taste.
Context.
Domain knowledge.
Understanding the customer.
Understanding the problem.
Knowing what to remove.
Knowing when something is finished.
Canva generated an impressive design.
But I knew the jersey was wrong.
It could articulate my philosophy beautifully.
But it still couldn't reliably execute one of its most important constraints.
Understanding the principle and reliably executing the principle are not the same thing.
Which is why the disappearance of technical barriers doesn't necessarily diminish expertise.
It may make expertise more valuable.
Three Companies, One Question
Adobe.
Apple.
Canva.
Their businesses are very different.
But underneath the surface, I think they are confronting versions of the same transition.
Adobe has to ask whether the creative application remains the center of the creative experience.
Apple has to ask whether the app and screen remain the center of personal computing.
Canva has to ask whether the template remains necessary when AI can create around intent.
And all three have to wrestle with something I experienced firsthand while writing this article:
How do you make technology disappear without making control disappear with it?
That may be the real challenge.
Not tools versus AI.
Not professionals versus prompts.
Not Photoshop versus Canva.
Intent and precision.
The companies that figure out how to combine the two may define the next era of creative computing.
When the Tool Disappears
I don't believe Photoshop disappears.
I don't believe apps disappear tomorrow.
I don't believe templates suddenly become useless.
And I certainly don't believe design expertise becomes irrelevant.
The opposite may happen.
The tools may simply become increasingly invisible.
We won't spend as much time telling computers how to do something.
We'll spend more time telling them what we're trying to accomplish.
And when that happens, the scarce skill won't necessarily be operating the software.
It will be articulating intent.
Establishing constraints.
Recognizing quality.
Providing context.
Making decisions.
And ultimately exercising judgment.
For most of my career in technology, we designed interfaces that helped people tell computers what to do.
While writing this article, I got a small glimpse of what comes next.
For a few minutes, I stopped thinking about the software altogether.
I was simply talking about the work.
Maybe the next great interface isn't an interface at all.
Maybe it's understanding what the person intended in the first place.
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