Free guide
A responsible offer starts with evidence that a defined customer values a defined result. Technology is part of delivery, not proof of demand.
Quick principle: Treat AI output as a draft that earns trust through review, testing, and evidence.
Target customer and problem
Name a reachable group and the costly, frequent moment they already recognize.
Write down the assumption behind this step, try it with a realistic example, and record what would make the result unsafe or incomplete. Keeping that evidence beside the project makes future AI conversations more consistent and gives another person a practical review path.
Interviews
Ask about recent behavior, current alternatives, cost of the problem, decision process, and constraints—not whether they like your idea.
Write down the assumption behind this step, try it with a realistic example, and record what would make the result unsafe or incomplete. Keeping that evidence beside the project makes future AI conversations more consistent and gives another person a practical review path.
Paid pilot
Offer the smallest real outcome to a few qualified users with a clear end date and learning goal.
Write down the assumption behind this step, try it with a realistic example, and record what would make the result unsafe or incomplete. Keeping that evidence beside the project makes future AI conversations more consistent and gives another person a practical review path.
Scope
Define what is included, excluded, supplied by the customer, and accepted as done.
Write down the assumption behind this step, try it with a realistic example, and record what would make the result unsafe or incomplete. Keeping that evidence beside the project makes future AI conversations more consistent and gives another person a practical review path.
Pricing
Include discovery, build time, tools, risk, revisions, maintenance, support, taxes, and payment fees.
Write down the assumption behind this step, try it with a realistic example, and record what would make the result unsafe or incomplete. Keeping that evidence beside the project makes future AI conversations more consistent and gives another person a practical review path.
Support
State response times, update duties, data handling, ownership, and what happens when a dependency changes.
Write down the assumption behind this step, try it with a realistic example, and record what would make the result unsafe or incomplete. Keeping that evidence beside the project makes future AI conversations more consistent and gives another person a practical review path.
Avoid income promises
Describe the work and evidence honestly. Results depend on demand, execution, timing, costs, competition, and many factors you cannot guarantee.
Write down the assumption behind this step, try it with a realistic example, and record what would make the result unsafe or incomplete. Keeping that evidence beside the project makes future AI conversations more consistent and gives another person a practical review path.
Practical next step
- Choose one small project or current workflow.
- Write the user, desired result, important constraint, and one failure case.
- Make one change and test it with ordinary, edge, keyboard, and recovery paths.
- Save the working version and note the result before continuing.
Remember: Do not paste passwords, private customer information, API keys, payment data, or other secrets into an AI prompt. Obtain qualified review when failure could materially harm people.