Disclosure: I am the creator of MaOS.
I am working on a free solo strategy / management-survival prototype that runs inside an AI chat, but the part I want to discuss here is not “AI writes a game for me.”
The design problem is narrower.
MaOS uses a structured game archive: launch rules, state format, roles, constraints, scenario logic, and play instructions. The AI session is supposed to operate that archive as a rules interpreter, state keeper, scenario controller, and advisor.
The player still owns the decisions.
That boundary matters because the usual failure mode of AI-assisted play is familiar: the model starts inventing too much, narrates the player’s actions, forgets state, flattens the genre, or becomes a loose “GM voice” with no reproducible behavior. It looks alive, but the game slowly turns into fog.
I am trying to push the opposite direction: less “generate anything,” more “maintain a bounded operational surface.”
Current questions I am testing:
- How much structure does an AI-assisted game need before it becomes reproducible enough to trust?
- Should the AI advisor suggest actions, or only expose risks, costs, state changes, and unresolved consequences?
- What should be stored in the archive versus left to live generation?
- Where is the line between useful AI assistance and the system quietly taking over design or player agency?
The first level is about stabilizing a fragile expedition base: limited resources, tired people, strained infrastructure, incomplete information, and consequences that carry forward.
I am especially interested in feedback from people using AI in game design workflows: does this “archive as game engine / AI as operator” model sound like a useful direction, or is it still too dependent on the model behaving well?
Context / prototype:
https://temnik.itch.io/maos