OpenAI has just added conversation state in their Response API.

The key insight is that conversation state isn't just memory - it's a persistent computation space that can maintain complex, evolving structures that would traditionally require dedicated databases, game engines, or simulation frameworks. You're essentially getting a stateful computing environment accessible through natural language.

Living Simulations & Game Worlds

Use conversation state as a persistent game engine where entire worlds evolve between API calls. Imagine a civilization simulator where each call advances time by years - cities grow, technologies develop, conflicts arise. The state maintains population dynamics, resource flows, and diplomatic relationships. Players could even fork conversations to explore alternate timelines of their civilization.

Distributed Memory Palace

Create a multi-threaded computation system where different conversation threads act as specialized "memory rooms" - one thread maintains financial models, another tracks experimental results, a third holds creative ideation. They could cross-reference through a coordinator thread, essentially building a distributed cognitive architecture.

Temporal Relationship Graphs

Build a living knowledge graph where entities and relationships evolve over time. Unlike traditional databases, this would understand context and ambiguity - "Remember that John started dating Sarah after the conference but before he moved to Seattle." The state maintains not just current relationships but their entire history and causality chains.

Collaborative Dream Worlds

Multiple users could contribute to a shared narrative universe where the state maintains consistent world rules, character histories, and plot threads. Each interaction adds to the canon, with the AI ensuring consistency and weaving disparate contributions into a coherent mythology.

Time-Loop Narrative Engine

Create stories where characters retain memories across loop iterations. The conversation state tracks what each character has learned in previous loops, allowing for complex narrative structures where knowledge accumulates even as events repeat.