Story splitting
Story splitting is the practice of breaking a large user story into smaller stories that each independently deliver value. The smaller the stories, the smoother the flow — and the easier they are to estimate, review, and ship.
Richard Lawrence's splitting patterns are the canonical guide: by workflow step, by data variation, by interface, by happy-path-vs-edge-case, by major effort. A useful test: if a story is going to take more than 2-3 days for one engineer, split it. Splitting often surfaces hidden complexity — a 13-point story that 'feels' simple usually contains 2-3 stories the team didn't see until they tried to split it.
Long-form posts that explore story splitting in depth — when to use it, common failure modes, how AI helps.
Related terms
- Story points
A story-point estimate is a unit-less measure of relative effort assigned to a user story.
- Acceptance criteria
Acceptance criteria are the conditions a story must satisfy to be considered complete — testable, bounded statements describing what the system does.
- Sprint goals
A sprint goal is a one-sentence outcome the team commits to delivering in the sprint — not a list of stories, but the customer or business outcome those stories produce.