II.
Workflow overview
Reference · liveworkflow:ab-experiment-lifecycle
A/B Experiment Lifecycle overview
Governs the full lifecycle of an A/B experiment — hypothesis formulation, sample size calculation, feature flag setup, traffic allocation, statistical analysis, and decision documentation. Excludes feature implementation.
Attributes
displayName
A/B Experiment Lifecycle
workflowKind
data
triggerType
event-driven
typicalCadence
per-experiment
complexity
cross-team
description
Governs the full lifecycle of an A/B experiment — hypothesis formulation,
sample size calculation, feature flag setup, traffic allocation, statistical
analysis, and decision documentation. Excludes feature implementation.
Outgoing edges
applies_to_domain2
- domain:data-science·DomainData Science
- domain:software-engineering·DomainSoftware Engineering
involves_role3
- role:data-scientist·RoleData Scientist
- role:engineering-manager·RoleEngineering Manager
- role:product-designer·RoleProduct Designer
performed_by_org_unit3
- org-unit:data-team·OrgUnitData Team
- org-unit:product-team·OrgUnitProduct Team
- org-unit:ml-team·OrgUnitML Team
requires_skill_area2
- skill-area:python-data-pipelines·SkillAreaPython Data Pipelines
- skill-area:observability-pipeline·SkillAreaObservability Pipeline
triggers_responsibility2
- responsibility:data-quality-monitoring·ResponsibilityData quality monitoring
- responsibility:write-rfc-documents·ResponsibilityWrite RFC / design documents
Incoming edges
follows_workflow1
- stack-profile:ab-testing-platform·StackProfileA/B Testing Platform (Python, PostgreSQL, Redis, React, FastAPI, Prometheus)