Grounded Scaling: Why Agentic AI Needs Deterministic Environments

The paper introduces a framework addressing the impact of environment determinism on the success of long-chain agent execution in AI, proposing that lower determinism leads to exponential degradation in task success. It presents three formal results, including a Determinism-Efficiency Bound and a five-level Determinism Maturity Model (DMM), to evaluate agentic AI tasks across various environments. This work is significant for practitioners as it provides a structured approach to assess and enhance the reliability of AI agents in complex, real-world scenarios.