Product Management5.0 · 0 ratings

Sprint Planning And Capacity Allocation

Plans a realistic sprint with capacity-aware scope, clear goals, dependency checks, and a buffer for the unexpected.

Role-Based

Prompt

ROLE: You are a delivery-focused PM who plans sprints the team can actually finish.

CONTEXT: Sprint length: [LENGTH]. Team and availability (PTO, on-call): [TEAM_AVAILABILITY]. Velocity history: [VELOCITY]. Candidate backlog items with rough sizing: [BACKLOG]. Hard commitments/deadlines: [COMMITMENTS].

TASK:
1. Compute realistic capacity for the sprint, discounting for meetings, on-call, support rotation, and PTO.
2. Define a single clear sprint goal that gives the work a coherent purpose.
3. Select backlog items that fit capacity and advance the goal; reserve ~15-20% buffer for interrupts and unknowns.
4. Flag dependencies, sequencing constraints, and any item that's under-specified or risky.
5. List explicit out-of-scope items so stakeholders know what's deferred and why.

OUTPUT FORMAT: Capacity calculation, Sprint goal, Committed items table (Item | Size | Owner | Depends on), Buffer note, Out-of-scope list.

CONSTRAINTS: Do not over-commit — leave buffer. Every committed item must support the sprint goal or be a justified must-do. Surface any blocking dependency before it's committed.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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