Jenny Wen on Why the Design Process Is Dead

How AI Agents Are Rewriting the Designer’s Job

Jenny Wen is the head of design for Claude Co-work at Anthropic, previously director of design at Figma (leading FigJam and Slides), and before that a designer at Dropbox, Square, and Shopify. In this conversation with Lenny Rachitsky, she delivers a startling message: the design process that designers have been taught as gospel is dead — and what’s replacing it looks nothing like what came before.

The death of the process: “This design process that designers have been taught, we sort of treat it as gospel. That’s basically dead.” Jenny explains that the shift isn’t coming from within design. It’s engineering’s transformation — with teams running seven Claude agents simultaneously — that forces design to adapt. Designers can no longer block engineers with months-long discovery-diverge-converge cycles when code ships in hours.

The new time split: “A few years ago, 60 to 70% of it was mocking and prototyping. But now I feel the mocking up part of it is 30 to 40%.” The traditional design workflow has been inverted. Jenny now spends significant time in code, polishing implementations alongside engineers, consulting on features as they’re built, and doing “last mile” work — a role that barely existed months ago.

Two types of design work emerging: The profession is stratifying into two distinct modes. The first is execution support — helping engineers who spin up scrappy prototypes iterate toward quality. The second is short-horizon vision — not the old 2-5-10 year design visions, but 3-6 month directional prototypes that keep autonomous engineering teams aligned. “In a world where people can spin off their seven Claudes, make whatever features they want, you need to point them towards something.”

Non-deterministic models break traditional design: You can’t mock up all states for an AI product. You can’t make a clickable prototype of something powered by language models. “You have to use the actual models underneath and you have to sort of see people try it out with their use cases because with these models, you discover use cases as you see people using them.” This fundamentally changes what “design” means — from specifying in advance to shaping in real time.

Three designer archetypes for the AI era: Jenny identifies three kinds of designers she’s hiring: (1) the strong generalist who can design, prototype, and ship across disciplines, (2) the deep specialist with extraordinary craft in one area, and (3) the prototyper-builder who works directly in code. The traditional “mockup artist” archetype is fading.

The legibility framework for design leaders: Borrowing from VC Evan Tana’s 2x2 framework, Jenny argues designers should act like internal VCs — spotting “illegible ideas” (prototypes with energy around them that nobody can quite articulate) and translating them into products. Claude Co-work itself emerged from this process: an internal prototype called “Claude Studio” that felt incomprehensible to designers but had massive energy among researchers.

6 Takeaways on Design in the Age of AI Agents

• Don’t block engineers — augment them - Your role shifts from gatekeeper (“here’s the mock”) to collaborator who helps autonomous engineering teams ship better
• Invest in code literacy - Designers who can polish implementations directly have a massive advantage; Jenny spends real time in code now
• Shorten your vision horizon - 2-5 year design visions are obsolete; think 3-6 month directional prototypes that keep teams aligned
• Embrace non-deterministic design - AI products can’t be fully mocked up; you must design with real models and real users
• Spot illegible ideas - The most valuable design work is translating chaotic internal energy into coherent product direction
• Build psychological safety + high standards - The best design teams balance comfort (“they can roast you”) with demanding excellence

What This Means for AI-Powered Organizations

Jenny’s perspective from inside Anthropic confirms a pattern we’re seeing across the industry: AI agents don’t just automate tasks — they reshape every role around them. When engineers can run seven autonomous agents, the entire organization restructures around speed of execution rather than quality of specification. The designers who thrive won’t be the ones clinging to process, but those who become translators between raw AI capability and coherent user experience. For any organization deploying AI agents at scale, this is a preview of how every creative and strategic role will transform.