Work · GPT Task
Develop a High-Ticket Offer
Turn a real client problem, delivery capability, proof, resources, and constraints into a premium offer concept with scope, outcomes, delivery model, proof requirements, boundaries, pricing hypotheses, sales questions, and next actions.
Context → structured prompt → explicit AI handoff
Runs in this browser. No upload by this page. External AI handoff is explicit. Review before sharing.
Configure task
Additional options
What you’ll need
- Ideal client/problem plus the capabilities, proof, delivery resources, and constraints you can actually support
- Ideal client, problem, and desired outcome
- Capabilities, proof, and delivery reality
What you’ll get
- Ideal-fit and non-fit criteria
- Offer outcome and value logic
- Scope and deliverables
- Delivery model and responsibilities
- Boundaries, exclusions, and dependencies
Prompt preview
Review or edit the generated prompt before you copy it or explicitly open an AI chat.
ChatGPT opens with the current prompt prepared. Gemini copies the current prompt, then opens Gemini so you can paste it. Keep secrets and sensitive information out of URL-carried prompts.
Examples
1. Premium consulting project
Context: A consultant supplies a well-defined client problem, verified experience, prior proof, a realistic delivery process, capacity limits, and current project ranges.
Goal: Shape a premium project offer without inventing outcomes.
Useful output: Fit criteria, scope, delivery model, proof needs, pricing hypothesis, discovery questions, boundaries, and validation steps.
2. Ongoing advisory retainer
Context: An advisor supplies actual expertise, the ongoing client decisions they support, availability, response-time limits, existing pricing context, and non-included services.
Goal: Design a reviewable retainer concept.
Useful output: Core promise boundaries, responsibilities, cadence, exclusions, proof, pricing hypotheses, questions, and risks.
3. Structured service program
Context: A small team supplies a repeatable service process, target client context, existing proof, delivery capacity, and optional add-ons.
Goal: Create a core program plus add-ons.
Useful output: Program outcome, modules/deliverables, add-ons, responsibilities, proof gaps, pricing/packaging hypotheses, and next actions.
Expected output
- Ideal-fit and non-fit criteria
- Offer outcome and value logic
- Scope and deliverables
- Delivery model and responsibilities
- Boundaries, exclusions, and dependencies
- Proof/evidence requirements
- Pricing and packaging hypotheses
- Sales/discovery questions
- Risks and unsupported claims
- Priority next actions
Truth boundary
Do not promise income, conversions or business results. Do not invent proof, scarcity, testimonials, legal terms or delivery capability. Pricing and positioning are planning suggestions, not guarantees or financial/legal advice.
Overlap guard: Owns the design of a premium offer package: fit, scope, delivery model, proof needs, boundaries, and commercial hypotheses. Use Startup Business Plan for the whole venture, Client Proposal/SOW for a client-specific scoped document, Pricing Strategy for systematic price-model testing, and Value Proposition for reusable message positioning.
Privacy and handoff
Runs in this browser. No upload by this page. Copy/download locally or explicitly open ChatGPT or Gemini. Source files are attached in the chosen AI service, not uploaded by Mycelgrid. Review the generated prompt and AI output before using or sharing it.