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| Criterion |  Agile Story Splitting |  Product Discovery Dual-Track Agile |  Agile Bucket System |  Product Discovery Product Kata |
|---|---|---|---|---|
Purposedifferent | When a story becomes too large for a clean flow, it breaks scope down along value and risk. It shapes the work into a form that ships earlier and is easier to verify. | When uncertainty and delivery run in parallel, it separates learning work from implementation while keeping both connected. It prevents unvalidated ideas from falling directly into the delivery stream. | When a large batch of work needs a fast, rough estimate, it sorts items into predefined size buckets. It sorts work by value, risk, and delivery ability. The result is captured as a Bucketed Backlog, Relative Estimates, and Split Candidates. | Product Kata helps clarify customer problems, solution ideas, and evidence through a repeatable improvement routine. It captures direction, current metric, target metric, experiment notes, and learning. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 30-60 min | Laufend, Wochen bis Monate | 30-90 min | 1-2 Wochen je Loop |
Participantsdifferent | 2-6 | 4-10 | 3-12 | 3-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Smaller Stories, Acceptance Criteria, Split Rationale | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Bucketed Backlog, Relative Estimates, Split Candidates | Direction, Current metric, Target metric, Experiment note, Learning report |
Tagsno overlap | BacklogIterationDelivery | AgileDiscoveryDelivery | EstimationBacklogRelative sizing | OutcomesDiscoveryLearningIterationCoaching |