Sprint planning

Overview

Sprint planning selects a time-boxed slice of the backlog for the team to execute next. In GrowthOS you can build that slice manually, item by item, or use the AI planning wizard to get a first recommendation in seconds.

The AI planner looks at your backlog priority, rough estimates, and team capacity to propose a scope that is ambitious but realistic. You are never locked into its suggestion; add or remove items until the sprint goal actually matches what the team can commit to.

Once a sprint is confirmed, it drives the sprint board and My Tasks: every item in scope shows up for its assignee, and progress rolls up into Team Analytics for the rest of the sprint.

What you can do here

Create a new sprint with dates and a clear goal.
Run the AI planning wizard to get a capacity-aware recommended scope.
Accept, adjust, or fully replace the recommended scope with manual picks.
Confirm the plan and open the resulting sprint board.
Compare planned scope against team capacity before committing.

When to use

At the start of every sprint cadence.
When re-planning mid-sprint after a significant scope change.
When you want a fast, capacity-aware starting point instead of planning from a blank sprint.

Prerequisites

A signed-in member account with product access.
A Planner seat to create or edit a sprint plan.
A backlog with items marked ready to pull from.

Where to find it

Sidebar: project Sprint area, or /sprint-backlog
AI planning wizard: from the project, open sprint AI planning

Step-by-step

Open the project sprint area or /sprint-backlog.
Create a new sprint with start and end dates and a one-line goal.
Open AI planning, or add backlog items to the sprint manually.
Review the recommended scope against your team capacity.
Swap out any item that does not fit the sprint goal.
Confirm the plan once the scope feels realistic.
Open the sprint board to start execution.

What success looks like

The sprint has a clear, one-line goal everyone can repeat.
The confirmed scope roughly matches team capacity, not an optimistic best case.
Every item in scope has a clear assignee before day one of the sprint.

Tips & best practices

Set a crisp sprint goal before accepting the AI-recommended scope; it makes trade-off calls easier mid-sprint.
Re-run AI planning if the backlog changes significantly right before the sprint starts.
Leave a small capacity buffer for unplanned work instead of scheduling at 100 percent.

Common mistakes

Accepting the AI-recommended scope without checking it against real team capacity.
Planning a sprint from a backlog that has not been reviewed for readiness first.
Changing sprint scope mid-sprint without updating the sprint goal or notifying the team.