When AI makes content creation cheap, what can survive in the long run? This is what the CEO of Figma says.

As generative AI rapidly permeates the fields of design and software development, the “creation” threshold has effectively disappeared, causing content creators to feel anxious. Figma co-founder and CEO Dylan Field and Activision Blizzard Communications Director Lulu Cheng Meservey offer complementary perspectives: “The truly lasting value in the AI era will depend on people’s judgment, taste, and long-term commitment.”

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Dylan Field: Human involvement in “depth” determines product “lifespan”

The more AI-generated content is prevalent, the shorter the product’s lifespan

In Dylan Field’s essay on Figma, he suggests that the higher the probability that a piece of content or product can be fully generated by AI in the future, the shorter its “actual lifespan” will be:

If you want your software, novel, or movie to have a long-lasting lifecycle, you will inject strong ideas into your work, pay attention to the tiniest details, and dedicate yourself fully with careful thought.

He adds, “If you don’t do this, your work won’t be good enough to be passed down. It won’t be loved, nor will it have any influence.”

AI is a tool, not a result-making machine

Field emphasizes the positioning of AI as a “tool.” For short-term, simple, and quickly replaceable products, AI can lead the production process; but when the goal is long-term existence, AI can only serve as an auxiliary tool.

He cites Figma’s Figma Weave feature as an example, pointing out that AI is more like a mold for shaping materials rather than a machine that directly delivers finished products:

In this mode, establishing workflows (Workflow), design judgment, and iterative revisions become new skills worth learning.

When AI enters software design: “Stability” is more important than “change”

Regarding software products, Field specifically mentions users’ resistance to change. He notes that frequent content adjustments are reasonable, but constantly reshaping the core user experience (UX) can provoke annoyance.

He uses a housing analogy: “People can frequently change photos or decorations on their refrigerator, but the structure of the house itself isn’t rebuilt at will.”

His distinction reminds designers that when integrating AI-generated content, they must identify which parts are quick-to-replace “local” elements and which are the “core architecture” that requires long-term stability.

Will software move toward personalization? Field remains reserved

Regarding whether AI will lead software toward “full personalization,” Field remains cautious. He believes that while individuals can create tools for themselves, overly customized products at the brand level may weaken community learning and cultural sharing.

He cites Snapchat as an example, noting that its seemingly unintuitive operation has unexpectedly fostered a “learning through others” usage culture, allowing the product to form a community with a sense of identity, rather than simply pursuing the lowest learning curve.

Lulu Cheng Meservey: AI makes “authenticity and long-term commitment” an advantage

Field’s comments are echoed in Lulu Cheng Meservey’s recent article, where she argues that the current content environment is flooded with false packaging, follower counts, and influence, making “authenticity” a scarce resource:

As the lines between truth and falsehood blur between people, content that can be recognized as genuine will become the most persuasive narrative capital.

She emphasizes that the era of companies and brands using high-cost videos to convey stories and values is waning due to AI’s rise. To gain “attention” in the future, success will depend on their long-term efforts and tangible results:

From now on, investing in taste, showcasing authentic content, staying close to reality, and building genuine relationships with users will become especially important.

Meservey straightforwardly states that truly trustworthy narratives often require continuous actions over 6 to 18 months or more, and may not immediately generate maximum traffic.

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The end of technology is humanity: Creativity in the AI era returns to human input

Combining the perspectives of Dylan Field and Lulu Cheng Meservey, both point out that AI is changing production methods but does not eliminate human responsibility in creation. When generation becomes easy, what truly matters is how creators inject their ideas, taste, and conveyed values.

In an era of rapid growth in software, content, and branding, only through this can long-term survival be achieved.

This article, “When AI makes content creation cheap, what can survive long-term? Figma CEO says,” first appeared in Chain News ABMedia.