If you're a designer working with product teams, your workflow probably looks something like this. You get a brief, you open Figma, you design something beautiful, you share it around, and then you wait for a developer to build it. Sometimes what ships looks exactly like what you designed. Sometimes it doesn't.
I want to show you how AI speeds up that workflow with tools like Fusion. Not in a revolutionary way where everything you know becomes useless, but in a way that lets you design and ship the same day. And what ships is exactly what you designed.
Let me walk you through how you work today in Figma versus how you'd work in Fusion, step by step.
You craft the interface carefully, thinking through user flows, visual hierarchy, and interaction patterns. You work with the content you have available, sometimes real, sometimes placeholder. You make smart assumptions about edge cases and different user scenarios. Every spacing decision, color choice, and layout adjustment has reasoning behind it.
You make the same thoughtful design decisions, but now you see them immediately play out with real data. You describe what you want in plain English, like "create a card layout for user profiles," and the AI generates it in seconds using your actual components and design system. Or you start visually building just like in Figma.
The difference is validation. That card design you're creating works with actual user data from the start. You immediately see if your layout breaks with real names or when content varies. You're still the designer making every decision, but now you know exactly how those decisions perform in reality.
When you need to iterate or try something different, you duplicate a frame or create a new page. It's your safe space to experiment. You can go wild with that new navigation design and if it doesn't work out, you just delete the frame and pretend it never happened.
You create a branch, which gives you your own copy of the entire site to play with. Just like duplicating a frame, it's your safe space to experiment with changes. The difference is that you're not working on a static mockup. You're adjusting the actual components that users interact with. If your experiment doesn't work out, you just delete the branch. The main site never even knows you were there.
You meticulously set up your component variants: default state, hover state, active state, and disabled state. You create them all as separate variants and hope the developer implements each one correctly.
You describe all the states you want and the AI creates them exactly as specified. "Add an empty state with icon, text and CTA.” or “ Make the disabled state 50% opacity with no pointer events." The AI implements each state perfectly using your design tokens. Then you test these states on the actual component in a real browser. You see the exact transition timing, how the color shifts, how it interacts with other elements.
If something feels off, you fix it right there. Maybe that hover effect looked smooth in your head, but it feels too aggressive in reality, so you adjust it until it feels right. You're designing and refining states on the live component, not hoping they'll work when implemented.
You design at specific breakpoints and test how auto-layout responds when you drag the frame size. It gives you a good sense of how things should reflow. But you're still testing with static content that behaves predictably. You also need to design all the key breakpoints so developers understand exactly how the layout should adapt at each size.
You're seeing real content that varies in length. When user names in different languages cause text to wrap differently, you see it happening. You're testing responsive design with the same messy, unpredictable content your users will actually have.
Plus, you can simply prompt the AI to handle responsive variations. "Make this grid stack on mobile" or "adjust the navigation for tablet view" and you get the changes in seconds.
You create a prototype, add all your interactions, generate a link, and drop it in Slack. People click through it, leave comments, and you iterate.
You have the same preview links for sharing, but you also create something called a pull request. It sounds technical, but it's really just a formal way of saying "here are my changes, please review them." The beauty is that reviewers are looking at the actual implementation and not a prototype. When your PM clicks through the flow, they're seeing exactly what customers will see. When developers review it, they can see both the visual changes and how it affects the code.
Feedback comes in, you go back to your file, make updates, and re-share the link. You may add a comment explaining what changed. Everyone needs to remember to look at the new version.
You make changes directly in the same branch you were working on. Everyone who was reviewing your pull request automatically sees the updates right away. There's a clear history of what changed and when. You don't need to manage multiple versions or wonder if everyone's looking at the latest design.
The feature finally ships and you compare it to your Figma file. The padding's off here, the spacing is slightly wrong there, the hover state doesn't match. You write up bugs, take screenshots with red arrows pointing at problems, and hope they get fixed in the next sprint.
If something's not right, you fix it yourself. The padding needs to be 24px instead of 20px? You adjust it. The hover state needs to be more subtle? You edit it. You fix it yourself instead of filing bugs about your own design. You're making sure it's right before it ships.
Shipping means handing off your design and waiting. Waiting for developer availability, waiting for implementation, waiting for review, waiting for deployment. Your beautiful design sits in Figma while you move on to the next thing, hoping it eventually makes it to production looking the way you intended.
When everyone approves your changes, they get merged and deployed. Your design goes live. Your design goes live exactly as you built and tested it, without any interpretation or approximation.
The AI workflow steps are similar because that's how designers work. You still experiment, iterate, get feedback, and refine. The difference is that in Fusion, you're working with the real thing the entire time. You're directly crafting what users will experience instead of creating a simulation for someone else to rebuild.
Developers are already using AI to write code faster than ever. When your engineering team is using AI to build at light speed, you need to be right there with them, designing on the actual product. Otherwise, you're designing for last week's build while they're already three iterations ahead.
It feels weird at first, especially creating that first pull request. But once you fix your first spacing issue directly in production, once you see your design working with real data, once you ship something the same day you designed it, you start to realize this is how it should have always worked.
You're still a designer. You're still thinking about user experience, visual hierarchy, and interaction patterns. You're just doing it in a place where your decisions immediately become reality.
