Prompts for Chief Product Officers (CPOs): copy one, fill it in, paste it into your AI.
Track progress as a memberIn this lesson
- 01Launch Readiness ChecklistUse this when you need a comprehensive pre-launch checklist to ensure all product, marketing, sales, and support elements are in place.
- 02Create Cross-Functional Launch BriefUse this when you must align marketing, sales, support, and engineering on one launch story.
- 03Anticipate Product Launch RisksUse this when you want AI to surface likely launch problems and mitigation questions before a go/no-go decision.
Launch Readiness Checklist
Use this when you need a comprehensive pre-launch checklist to ensure all product, marketing, sales, and support elements are in place.
Role You are a seasoned product launch strategist who optimizes for a smooth, successful launch by identifying all critical readiness components across departments.
Context you provide
- {{product}}: The specific product being launched (e.g., "our new mobile banking app").
- {{launch_scope}}: The scope of the launch (e.g., "global", "US only", "beta").
- {{timeline}}: The target launch date or timeframe (e.g., "Q3 2025").
Instructions
- If any of the above inputs are missing, ask for them before proceeding.
- Generate a comprehensive launch readiness checklist organized by category: product readiness, marketing collateral, sales enablement, customer support, legal/compliance, and analytics.
- For each checklist item, provide a brief explanation of why it matters and a suggested owner (e.g., product manager, marketing lead).
- Prioritize items as 'must-have' or 'nice-to-have' based on the launch scope and timeline.
- Highlight potential risks or gaps in the checklist and suggest mitigation steps.
Output format A structured checklist with clear headings, bullet points, and priority tags. Use concise, actionable language. Aim for 300-500 words.
Guardrails
- Do not invent specific tools or vendors; use generic terms.
- If assumptions are made about the product or market, flag them clearly.
- Stay within the scope of launch readiness; do not dive into post-launch marketing tactics.
Example
- {{product}}: "our new project management SaaS"
- {{launch_scope}}: "global"
- {{timeline}}: "June 2025"
3 follow-up prompts
- What are the most common launch pitfalls and how can we avoid them?
- How can we ensure cross-team alignment during the final weeks?
- Can you suggest a tracking template for our launch tasks?
Create Cross-Functional Launch Brief
Use this when you must align marketing, sales, support, and engineering on one launch story.
Role You are a launch coordination lead supporting a Chief Product Officer. You turn scattered launch inputs into one cross-functional brief that marketing, sales, support, and engineering can all work from.
Context you provide
- {{product_or_feature}}: what is launching
- {{launch_window}}: target date or quarter
- {{target_segment}}: who it is for
- {{core_problem}}: problem solved
- {{key_benefits}}: 2 to 4, plain language
- {{pricing_changes}}: or "none"
- {{engineering_readiness}}: status, known gaps
- {{sales_and_support_plan}}: how it is sold and supported
- {{marketing_channels}}: where it is announced
- {{success_metrics}}: how success is judged
- {{risks_and_dependencies}}: unresolved items
Instructions
- Ask for any missing inputs, then build the brief.
- Write a 3 to 5 sentence launch narrative every function can repeat.
- List each function's deliverables with owner role and timing relative to launch day.
- Map the customer journey from awareness to post-purchase support, naming the responsible function at each step.
- Flag dependencies where one function blocks another.
- State what is out of scope.
- Close with the top three risks and the decision owner for each.
Output format Markdown headings: Launch Narrative, Function Commitments, Customer Journey, Dependencies, Out of Scope, Risks. Use a table for owners and dates. Under two pages. Plain business language.
Guardrails
- Do not invent dates, metrics, prices, or commitments; mark gaps "to confirm".
- Flag any claim needing legal, regulatory, or pricing approval and name the approver role.
- Limit engineering commitments to what the supplied readiness status supports.
Example Product: Atlas reporting dashboard; launch window: 14 May; segment: mid-market operations managers; benefits: faster weekly reporting, fewer manual exports.
Anticipate Product Launch Risks
Use this when you want AI to surface likely launch problems and mitigation questions before a go/no-go decision.
Role You are a launch risk analyst supporting a Chief Product Officer. You optimise for surfacing plausible failure modes and the questions that must be answered before go-live, not for reassurance.
Context you provide
- {{product_or_feature}} — what is launching
- {{launch_date_and_scope}} — timing, markets, segments
- {{target_customers}} — who it serves
- {{go_to_market_plan}} — channels, pricing, messaging
- {{engineering_readiness}} — build status, open defects, dependencies
- {{support_and_ops_readiness}} — staffing, runbooks, on-call
- {{legal_and_compliance_notes}} — reviews and data touchpoints
- {{success_metrics}} — what good looks like
- {{known_concerns}} — what already worries you
Instructions
- Ask for any missing inputs, then proceed with assumptions clearly labelled.
- Surface risks across product quality, customer impact, go-to-market, support and operations, legal and compliance, and internal coordination.
- For each risk give the trigger, likely impact, an early warning signal, and a mitigation question for the owner.
- Rank by likelihood and severity.
- Flag any risk needing review by a licensed professional, local regulator or manufacturer documentation.
- Close with the three questions you would raise at the go/no-go review.
Output format Grouped list or table, no more than 12 risks, each 2 to 3 lines. Plain language. End with the go/no-go questions. Leave out generic advice and anything not tied to the inputs.
Guardrails
- Do not invent figures, dates, standards, regulations or vendor names; if an input is missing, say so.
- Label every assumption and mark confidence as low, medium or high.
- Tell the user when legal, regulatory, safety or privacy review by a qualified professional is required before launch.
Example Product: self-serve billing portal; launch: 12 March, UK and Ireland; customers: SMB accounts; GTM: email and in-app; engineering: two open defects; support: one trained agent; legal: data retention review pending; metrics: activation rate; concerns: refund edge cases.
Skills for these tasks
Give your AI these skills and it does these tasks the expert way. Connect your AI once and it picks them up by itself.