# Architecture and Concurrency Model for Persistent Generative Entities in Real-Time Multiplayer State

- **Report ID:** `esp-34-multiplayer-npc-concurrency-architecture`
- **Group:** `espionage`
- **Classification:** `public-safe-research`
- **SHA-256:** `ca7145d6924286cba0f1cd5fa0802f3be933a2b7f9e058c5821e3843a218fdb1`

## Safe public summary

The integration of generative Large Language Models (LLMs) into live, server-authoritative multiplayer environments introduces profound synchronization challenges that threaten to shatter the illusion of a cohesive, shared digital reality. Traditional real-time game architectures rely on high-frequency, deterministic state updates—often processing at 60 to 128 ticks per second—to maintain strict synchronization across all connected clients1. Conversely, LLM inference is intrinsically non-deterministic and highly latent, frequently introducing multi-second delays that decouple the entity's cognitive process from the real-time physical simulation3. When multiple uncoordinated human participants interact concurrently with latency-bound generative entities, the system enter…

## Incorporated areas

- detail tiers and runtime budgets
- NPC state ownership
- optimistic revision and memory compaction

## Source boundary

The full report is retained in the downloadable site package for project research and audit. It is not served as a public runtime resource. Generated personas and public APIs apply the classification-specific safe-use boundary recorded above.