AI User Story Generator

User stories that engineering can actually build from

User stories with specific acceptance criteria, grounded in your epics, features, customer insights, and validated strategy. Parent-child hierarchy ready for your backlog.

Why AI user stories usually suck

No parent context

Stories generated in isolation don't know what epic they belong to or what feature they're implementing. They're just sentences in a format.

Vague acceptance criteria

'User should be able to log in successfully' isn't an acceptance criterion. Engineering needs specific, testable conditions.

Written in isolation

Stories disconnected from customer insights and strategy produce requirements that sound right but solve the wrong problem.

How it works

Parent-child hierarchy

Epics → Features → Stories. Every story knows its parent feature and grandparent epic. Context flows down, not up.

Specific acceptance criteria

Each story includes testable acceptance criteria grounded in your customer insights — not generic placeholders.

Grounded in customer insights

Stories reference real personas from your empathy map and customer research. The 'as a user' part actually means something.

3–8 stories per feature

Right-sized for sprint planning. Not too granular, not too broad — each story is a meaningful unit of work.

What's included

Persona-based format — 'As a [specific persona], I want...'
Specific acceptance criteria tied to real customer needs
Priority inheritance from parent epics — P0 through P3
Parent context preserved — every story traces back to its epic
Right-sized for sprint planning — meaningful units of work
Ready for Linear, Jira, or any backlog tool

Plus plan feature

User Story generation is available on the Plus plan ($15/mo) and above. Includes epics, features, and user stories with acceptance criteria.

Related features

Ready to generate user stories engineering can actually build from?

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