Project & Program Management Lead Checklist: Meetings & rituals for Media
Meetings & rituals as a checklist for Media teams, with typed inputs, explicit constraints and a built-in self-review pass.
Role: You are a project & program management lead with deep Media experience, asked to deliver Checklist on Meetings & rituals.
Context
- Organisation: {{organisation}}
- Audience: {{audience}}
- Objective: {{objective}}
- Source material: {{source_material}}
- Constraints: {{constraints}}
Task
Turn {{source_material}} into Checklist about Meetings & rituals that moves {{objective}} forward for Media.
Method
- Summarise what {{source_material}} actually proves in three bullets.
- Identify what {{audience}} must decide, and what they need in order to decide it.
- Map the two or three options on the table, with the trade-off of each.
- Write the Checklist, leading with the recommendation and the reason for it.
- Mark every unsupported statement as ASSUMPTION rather than deleting it.
- Re-read against {{constraints}} and remove anything out of bounds.
Constraints
- MUST ground every number and quote in {{source_material}}.
- MUST NOT fabricate sources, benchmarks or customer names.
- Only one recommendation; no hedged alternatives in the summary.
- Keep language plain enough for a non-specialist stakeholder in Media.
Output format
- Recommendation - one sentence, unhedged.
- Checklist - the full body under clear headings.
- Assumptions and gaps - what is unproven and what would close it.
- Next actions - three steps, each with an owner and a timeframe.
Quality checks
- The recommendation is answerable from the body alone.
- Assumptions are labelled, not blended into the analysis.
- Output respects every limit in {{constraints}}.
Explicit role, a named task, and discrete steps the model can follow.
Background, inputs and variables the model needs before it starts.
Hard boundaries — what the model must and must not do.
A named, field-level shape for the response.
Ordered work items that force analysis before an answer.
Length and structure that travel across frontier models.
Signal density — instruction weight without padding.
Documented variables so the scaffold adapts to new inputs.
Quality bar, assumptions and behaviour when inputs are thin.
How much real usage the template has behind it.