After Generation
Yuan Fang’s editorial observations on the AIGC content industry
These eight essays are neither a tool tutorial nor a certain forecast. They begin with questions that recur in content-industry practice: as generation becomes easier, what helps creators retain value; and when characters, works, organisations and digital versions of people can all be generated, how should we think about judgment, memory, relationships, assets and responsibility?
Editorial note — This series presents the author’s observations and questions from content-industry practice. It is not a research report, performance claim, legal advice or a forecast of industry outcomes.
Questions about
what remains.
Eight essays on creative judgment, characters and IP, organisation, digital identity and responsibility.
Deciding what is worth keeping when generation expands the field of options.
Why Is Taste More Valuable When AI Makes More Possible?
As generation turns “I can’t make it” into “I can’t choose among it all,” taste is becoming the judgment to know when to reject—and why to keep something.
In the AI Era, a Risk for Ordinary People Is Having Nothing of Their Own
As tools become more alike, experience, judgment, taste, relationships, trust, and assets one genuinely owns may be what create lasting differences.
After Generation, What Do We Have Left?
After generation, choice, memory, relationships, and responsibility still need to be carried forward by people; as capability is amplified, so are choice and responsibility.
Moving from a recognisable image toward recurring characters, relationships and worlds.
Why Do So Many AI Characters End Up as Nothing More Than Animated Faces?
A consistent face only solves recognition; a character’s past, relationships, and continuity are what lead audiences to believe they are the same person.
The Real Asset in AI Content Is Not the Viral Video
Once the view count is hidden, what remains—characters, relationships, a world, methods, and audience understanding—determines whether a viral hit has become an asset.
Could One Hundred Million People See One Hundred Million Different Versions of the Same IP?
When the same IP can generate different versions for different people, creators need to define more clearly what may change—and what must never change.
Reconsidering content systems, organisational roles and the conditions for scale.
Writing the boundary of ownership, consent and responsibility as AI begins to replicate people.
When AI can generate more, what do we choose to leave behind?
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