How to Turn an AI Game Prototype Into a Real Project
A checklist for deciding whether to keep iterating or move to a conventional development workflow.
Freeze the validated mechanic, choose a distribution target, move into a maintainable code and asset pipeline, then rebuild quality around tests rather than piling prompts onto the prototype.
1. Decide whether to rebuild
Audit code access, dependencies, licenses, performance and export. If the prototype is locked to a feed or its architecture is tangled, preserve the rules and reference behavior but rebuild in a controlled project.
2. Write a production brief
- Target platforms and minimum hardware
- Core loop and explicit non-goals
- Save, analytics, accessibility and localization needs
- Asset ownership and AI-use records
- Milestones with playable acceptance tests
3. Establish engineering basics
Use version control, issue tracking, automated tests for core state and reproducible builds. Replace unknown dependencies and temporary generated assets. Profile before expanding content.
4. Prove retention before scale
Give a polished vertical slice to players who owe you nothing. Measure completion, replay and confusion. More levels do not fix a weak loop; validate the small version before producing content.
Features, pricing and terms can change quickly. Recheck the linked sources and current official terms before making a commercial or platform decision.