A sprint needs a finish line.
A useful AI sprint starts with one workflow and ends with something the team can test, review, and improve.
01
Scope one workflow
The sprint should avoid vague transformation goals. Choose one workflow with a clear owner and output.
Workflow owner
Inputs
Output
Metric
02
Build the controlled version
The first version should be narrow enough to review and useful enough to change the team's week.
Prototype
Integration
Review path
Training
03
Decide what comes next
At the end, the team should know whether to improve, expand, pause, or move to another workflow.
Adoption check
Results
Backlog
Next sprint
Questions to ask before the first sprint
What can ship in one sprint?
Who reviews the first version?
What would justify a second sprint?
Keep reading on Fabren
External references
Next step
Ship one workflow this month.
Fabren's sprint model helps you move from workflow map to tested AI deployment.
Plan a sprint