50% of all respondents have pushed AI-generated code to production, including both product and brand designers. Only 20% of respondents identify as design engineers, underscoring how quickly coding capabilities have spread beyond traditionally technical roles.

76% of respondents say they’ve used an AI coding tool that augments developers, like Claude Code, Cursor, OpenAI Codex, and GitHub Copilot. If we include AI app builders like Lovable and Replit, that jumps to 85%.

Early-stage designers are more likely to ship code at 68%, compared to 33% at publicly traded companies.

Founders are the shippy-est group (70%) compared to ICs, managers, and other executives. Some of the strongest designers we know have left design teams entirely in favor of starting their own companies. We think designers are uniquely wired for this path, with a deep sensitivity to users, a bias toward making ideas tangible, and a high bar for quality. Those abilities—combined with AI tools—make it possible to go from idea to prototype to fully shipped product with far less engineering support than before.

We’re also seeing that as many leaders as ICs have pushed code. With AI, they’re able to get in the weeds to quickly prototype an idea or drive a project forward. Nearly half of executives we surveyed are shipping, and in turn, they’re challenging what’s expected of leaders. Read more in Teams.

All types of code. They’re taking over frontend polish, building backend systems, integrating design system architecture, spinning up beta products, adding motion, and more.

A designer who can bridge design and code is especially valuable on small teams, where that versatility accelerates shipping. But this isn’t limited to early-stage companies. As roles merge (more on that in Teams), the expectation for technical fluency is rising across org sizes—without losing what designers uniquely bring: a strong point of view on what to build and how it should work.

Across the companies we surveyed or spoke to, we heard a range of practices around code review or handoff. 

On the high-speed side, companies are using AI to assess the risk level of push requests (PRs) initiated by designers and automatically push low-risk changes. At other companies, designers are deploying to separate sandboxes for engineering review, or handing off prototypes for engineers to rebuild in production code.

At DoorDash, the PR process has stayed the same, says Shali Nguyen, their Head of Consumer Experience Design. “Everything goes through GitHub PR approvals, and designers are held to the same production-quality bar as our engineering counterparts. We’ve added a design review step where designers are tagged to review and approve UI changes before they go to production.” 

With so many more designers cultivating coding capabilities, what will happen to the “design engineer” title? We explore these themes of blurring roles in Teams.

In our 2025 survey, we reported that prototyping was emerging as a key use for AI, and that designers were beginning to skip static mockups to go straight to vibe coding prototypes. This trend has continued. Now, prototypes are an expected design output for 43% of respondents. 

Some designers now do all their exploration work via coded prototypes rather than in a canvas, or they simply incorporate prototyping into a broader process that still includes mockups in Figma.

Prototypes fill a gap in the classic set of design deliverables, because unlike mockups, they make it easy to evaluate states in a user flow. Designers we spoke with say that prototyping helps circulate ideas and align with engineering. Others expressed concern that prolific prototyping invites too many options—and that these options often look alluring enough to miss their poor design.

Designers are faster with AI. But are they better? And who sets the quality bar when everyone—including PMs and engineers—can produce plausible-looking interfaces? 

When we asked respondents about the impact of AI on various aspects of their design work, they said their speed, efficiency, and creative range have benefited the most.

But when we asked survey respondents what they’d miss most if they lost access to AI tomorrow, they were more likely to say they’d miss the ability to build and the breadth of creative expression. Designers have told us they’re now more technically empowered to:

• Implement more frontend polish

• Try more complex designs

• Get up to speed on a new industry

• Improve their accessibility knowledge

• Synthesize disparate data sources to make informed decisions 

• Complete a rebrand in a week 

And for resource-strapped companies in particular, AI has unlocked new levels of capability and quality that were too expensive to reach in the past.

Now that product teams can build features in hours instead of weeks, designers are feeling even more outnumbered by PMs and engineers—and are stretched as they provide quality design guardrails for their prolific teams. 
So what are designers doing about it?

Many designers told us AI helps them iterate faster to match engineering’s pace. But not without cost—we also heard that code forces commitment too early and that speed compresses the open-ended phase where designers develop their judgment.

As product development speeds up with AI, design teams that don’t keep up may risk falling behind or losing influence. They’re balancing this with the cost of letting go of crucial parts of the design process, and they’re finding middle ground by learning to work differently with their counterparts, which we explore in Teams.

Joel Lewenstein, Head of Product Design at Anthropic, says, “There’s a socially interesting dimension, which is that if a feature can now be built in 48 hours, asking for a week-long classic design sprint to explore divergently is a huge ask. 

“At Anthropic, we’ve started to compress design exploration with new internal tools that generate many UI variations, index user research across the company, and enable rapid dogfooding. But there’s still an ineffable, slow part of exploration time that we need to protect—going for a walk, letting the brain relax, letting the neurons connect—and that is a work in progress.”

For about 80% of respondents, AI assists but doesn’t replace their own quality meter, final visual polish skills, and creative direction. 60–70% of designers also reported that they still rely on their judgment for understanding user needs and context, defining the problem, storytelling, systems thinking, and design architecture.

Only 9% of respondents feel that it’s genuinely difficult to separate AI’s input from theirs. Many more feel they have full ownership (40%) over AI-produced work—that the direction and judgment still comes from them—or that it’s “mostly” theirs (43%).

Ryan Mather, Designer at Anthropic, says, “AI is powerful because the tool itself can think and experiment. It's up to the person holding the tool to decide where to direct that. Every good designer has a point of view, and AI is like a point-of-view amplifier."

We were curious how designers feel about their work as AI usage grows. 53% of overall respondents report a positively transformed relationship with their work as a result of AI. 18% say it has decreased their work satisfaction.

This trend was even stronger for designers who “build.” We noticed that designers who ship code or create prototypes with AI were twice as likely to feel more creative and capable at work—while also feeling that the quality bar is higher. The Spring 2026 UX Tools State of Prototyping study echoes this finding.