AI Product Planning Topics
A self-guided outline of subjects involved in planning an AI product.
This page is not a 30-day launch plan or a tested program. It lists planning topics only; outcomes depend on the product, team, market, and applicable requirements.
Example topics
Problem definition
Describe the user problem and the role an AI component might play.
User research
Questions for interviews and ways to record evidence.
Market and alternatives
Research existing approaches and compare their documented scope.
MVP scope
Define a small hypothesis and the evidence that would test it.
Technical approach
Compare hosted APIs, open-weight models, and non-AI alternatives.
Provider evaluation
Review current terms, pricing, privacy, limits, and service details.
Application architecture
Consider data flow, error handling, and human review.
Public product information
Describe capabilities and limitations without unsupported promises.
Accounts and payments
Review security, payment, tax, and jurisdiction-specific requirements.
Feedback process
Plan how users can report issues and how feedback is handled.
Launch planning
Compare distribution options, costs, and operational readiness.
Post-launch measurement
Choose metrics that reflect user outcomes and system behavior.