Creative Work Is About to Look a Lot More Like Programming

TL;DR: One of Every’s 2026 predictions was for AI to finally disrupt work for creative professionals. Weber Wong, the founder of AI design tool Flora and a former venture capitalist, thinks that moment is here, but that most are still missing where the real shift is happening. Rather than being about better prompts, creative professionals should be moving from creating one-off outputs to reusable workflows. Read on for his framework, including a side-by-side breakdown of the prompt approach versus the workflow approach, and four principles for thriving as visual programming becomes the new foundation of creative work.—Kate Lee

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As an artist and designer, I’ve used every creative tool in the modern suite: Photoshop, Figma, Midjourney, Sora. Whether I was clicking through menus or typing prompts while creating interactive AI installations, I was doing the same thing in each one: producing one output at a time, with no system underneath. One image had to be moved to another app to make another change or manipulate it in another way. I was working like an assembly line worker, clicking the same buttons over and over in the same sequence, when I wanted to be working like an architect.

I took an unusual path to figuring this out. I went from venture capital to New York University’s Interactive Telecommunications Program, the same graduate arts program that helped launch one of my favorite AI startups, Runway. There, I spent more time operating tools than thinking about artistic ideas. Even with generative AI, which allowed me to produce a piece of media in seconds, every project still started from scratch. I couldn’t save my process, share it with a collaborator, or build on what I’d learned yesterday.

That realization led me to build Flora, a platform where creative professionals build generative workflows using all the best text, image, and video models on one infinite canvas. Since we launched in February 2025, thousands of professionals from companies like Pentagram and Netflix have used it. We’ve raised $42 million to become the default AI-powered system for creative professionals. But what I’m about to share applies whether you use Flora, a competitor, or tools that don’t exist yet.

Model capabilities are advancing faster than anyone predicted. We’ve added support for Nano Banana, Veo 3.1, Sora 2, and dozens of other specialized models. In this environment, your competitive advantage as a creative person won’t be access to the best model because everyone will have that. Instead, you need to know how to orchestrate models into workflows that deliver consistent value.

Welcome to the world of visual programming.

The real problem: Visual creative work doesn’t scale

Most creative professionals I know, and many on Flora’s team, have suffered the pain of traditional creative tools. You develop a familiarity and dexterity with them. You remember where you’re dragging a mask across an image to hide the subject from the background, tapping shortcuts without thinking, or nudging curves a pixel at a time to get the shape just right.

But tomorrow, you open a new file and start from zero. Your expertise lives in your muscle memory, and you can’t transfer those skills to someone else.

I call this mental model artifact thinking: creative work that produces discrete outputs, one at a time, each beginning from scratch. Traditional tools like Photoshop and Illustrator, which demand endless hand-tuned adjustments and manual refinements to produce a single polished image, trap you in this way of working.

Midjourney and DALL-E feel like liberation because they generate outputs so quickly, and you can communicate with them in the same language you speak every day. But visual prompts, too, are one-time, disposable things. You can’t hand them to a colleague and be confident you will get the same result. The magic of near-instantaneous generation masks the fact that you are still in artifact thinking.

Design has escaped this kind of linear mental model before. Consider what happened with user interface design. If you were designing an app a decade ago, you’d manually create every screen—the login screen, the home screen, the settings page, the error states—as a separate image. Updating a button color required changing each of these images.

Figma blew this apart by introducing components: The same button was designed once and then recreated across a project. With auto-layout, elements could reflow intelligently when content changed. The software allowed designers to stop making screens and start making systems that generated screens.

That same shift is now possible for all visual creative work: photography, video, illustration, motion graphics. But most people are still stuck drawing buttons one at a time.

The alternative: Creative system design

We’ve established that creative professionals need to move from assembly workers to architects—moving from making one thing to systems that can create multiple things. Let’s show what this would look like for a brand agency that creates product photography for e-commerce clients.

The prompt approach

1. The individual generates a product image.
2. If she doesn’t like it, she tweaks the prompt and regenerates.
3. She exports the image to Photoshop and removes the background.
4. She imports it into another tool to add a shadow.
5. She manually resizes the image for different platforms.
6. This process is repeated 50 times for 50 products.
7. Tomorrow, when the client wants a different style, the person starts from scratch.

The workflow approach

1. Someone builds a system that looks like: product input → generation → background removal → lighting adjustment → shadow → multi-format export.
2. He runs it on 50 products simultaneously.
3. Tomorrow, he adjusts one parameter and regenerates everything.
4. Next week, he shares this workflow with a colleague who modifies it for a different client.
5. Next month, this workflow will run autonomously while he sleeps.

The difference isn’t just efficiency (although workflows are orders of magnitude faster). Workflows compound: Every workflow you build makes you better at building the next one. Every workflow you share teaches someone else your creative process. While prompts disappear the moment you close the tab, workflows become assets.

Why workflows need more than a chatbox

If the goal is system design—moving from assembly worker to architect—how do you build these systems? The obvious answer is natural language. Talk to the machine like a person in plain English, and it will handle the technical work.

But description has its limits, especially for visual work. Natural language is beautiful for exploration and iteration, but it’s terrible for precision and reproducibility. “Make the blue 10 percent lighter.” “Increase the contrast on the face.” “Straighten the horizon by two degrees.” Prompts cannot reliably deliver these instructions.

This is where my argument gets uncomfortable. To find a solution, we must admit that the future of creative work looks less like natural language and more like programming. I’m talking about node-based workflows: visual programming languages that are flexible enough for creative exploration and structured enough to execute systematically.

Node-based workflows let you see what you’re doing. Each step is a box on screen which represents some kind of work, such as generating an image, animating it, or making it move. When something breaks, you can see where the logic went wrong because each step is clear. You can hand these structured steps to a colleague, they can run them, and they’ll get the same result. It doesn’t require knowing a coding language like Python.

I understand the resistance to this idea. Some people hear “visual programming” and think we’re trying to turn designers into engineers. That’s backwards. We’re trying to give creative professionals the power that programmers have always had: the ability to build systems that work while you sleep, that can be stored as multiple versions and shared and improved, and that take what people already know how to do and make it something anyone can run.

Even if the underlying logic is to make creativity more like coding, that is not what it should feel like. If you ask our customers, they are more likely to describe Flora as a way to explore their creative ideas rather than as a visual programming tool.

The AI industry has already built many tools that make it easy for even novice software engineers to build faster and bigger. Creative professionals deserve a similarly intuitive, easy-to-use tool that gives them a high level of control.

Own the process, not the prompt

If you’re a creative professional using AI today, here’s where you should be taking your work:

1. Start building workflows, not only generating outputs. Every time you find yourself doing something twice, that’s a workflow waiting to be systematized.
2. Learn the building blocks. Understand what each type of model is good at, how they connect, and what their constraints are. You don’t need to be an engineer, but you need to think systematically.
3. Share what you build. The creative professionals who thrive in the AI era will be the ones whose workflows become standard, not the ones with the best prompts. If you build a system that works for one client, you’re not starting from scratch next time—you’re starting from something that already works. This portfolio of techniques becomes your edge.
4. Invest in platforms, not tools. The tools that treat workflows as second-class citizens are optimizing for demo-ability, not long-term value. Find the platforms that let you build systems.

This might sound like a lot of work, and it might be at first. But so was learning Photoshop and Figma. Skills require investment, and the tools that require no investment give you tricks but no power. As the power of these tools evolves, AI will eventually build these workflows for you. That’s why we’re developing Fauna, an agent that constructs workflows from natural language descriptions so that users can go from first idea to creation in minutes.

But even when AI builds the workflow, you still need the workflow to exist as something you can inspect, modify, and share. When a system works in the background and you can’t see what it’s doing, you’re hoping it gets it right. And when it doesn’t, you have no idea why or how to fix it. The whole point of making the workflow visible is so that when something breaks, you can see where and why. The alternative is hoping the AI guesses right every time. If years of working with software have taught me anything, it’s that implicit systems break in surprising ways, and you want the system to be visible.

So if you’re building AI creative tools:

1. Let people see how workflows work. If someone can’t open up a workflow and understand why it does what it does, they’ll never trust it enough to modify it.
2. Build things that get better with use. When someone shares a technique that works, other people should be able to grab it, adapt it, and feed what they learn back in. The platform should get smarter the more people use it.
3. Don’t chase the demo. The first time someone generates something with any model, they’re going to be impressed. What matters is whether they’re still getting value on the hundredth generation because they’ve built up a library of approaches that fit how they work.

Built by builders, for builders

Every founder has a bet they’re making about the future. Ours is this: In five years, the best creative professionals won’t be the ones who are the best at prompting. They’ll be the ones who are the best at building creative systems.

They’ll think in workflows, not artifacts. They’ll combine tools into systems, not just use them one at a time. They’ll build libraries of techniques that will become more valuable as time goes on, and they will share those techniques, turning knowledge stored in individual heads into infrastructure that helps everyone.

That’s the future we’re building toward. Not because we think everyone should become programmers, but because we think everyone should have the power that programmers have always had: the ability to build systems that work while they sleep.

Prompts will always have a place—for exploration and for one-offs. But for professional creative work, workflows are how you take something that worked once and make it repeatable.

The creative professionals who understand this today will be the ones defining what creative work means tomorrow.

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Weber Wong is the founder of Flora. To read more essays like this, subscribe to Every, and follow us on X at @every and on LinkedIn.

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