How do you write user stories for AI-generated content?
Describe AI features through user intent and add acceptance criteria for review, failure, and saved output.
How do you write user stories for AI-generated content?
A user story explains who needs a capability and why. It should describe an outcome without dictating every implementation detail.
Make the value explicit
An example is: “As a creator, I want to edit a generated script before narration so that the spoken content matches my intended message.” This identifies the user, action, and reason. Avoid stories such as “Add an AI endpoint,” which describe internal work without explaining the experience it enables.
Add observable acceptance criteria
Specify that the creator can see the draft, change it, save it, and generate narration from the saved version. Include an empty-script response and a failed-save state. Define how the application handles an older narration after the script changes. Keep content-quality expectations separate from technical completion: saving text does not prove its claims are correct. Review the story by demonstrating it with a sample script and deliberately interrupting one step to check that the user can recover.
No. The story states intent; acceptance criteria define how you verify the required behavior.
Only when a provider is a real constraint. Otherwise describe the capability and keep implementation choices separate.
Edits can invalidate downstream audio and video, so the expected dependency behavior must be clear.
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