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Atomic User Story Framework

Reusability

A method for breaking complex features into small, independent user stories that can be completed within a single AI context window with clear, testable acceptance criteria

How It Works

Each story must be completable in one iteration (within ~168k token context), have verifiable success conditions, and be independent of other stories to enable parallel or sequential autonomous completion

Components

1

Start with overall feature description in PRD

2

Break into smallest possible independent units

3

Write specific, testable acceptance criteria for each

4

Order stories by logical dependency

5

Ensure each story fits in single context window

6

Validate criteria can be automatically tested

When to Use

When preparing work for autonomous AI agents, when building complex features, when you need clear progress tracking and rollback capability

When Not to Use

For simple one-off tasks, when stories are inherently interdependent, when acceptance criteria cannot be clearly defined

Anti-Patterns to Avoid

Stories too large for single iterationVague acceptance criteria like 'works well'Stories that depend on incomplete previous workAcceptance criteria that require human judgment

Example

Instead of 'Build user dashboard', create atomic stories: 'Add user table with name/email columns', 'Create dashboard route returning user data', 'Add dashboard template displaying user name', 'Implement logout button with session clear'