Silent Experiments: How Cloud AI Rollouts Break Session Reproducibility

Hosted LLM reproducibility is being silently compromised by undisclosed A/B testing that routes different sessions through different experimental code paths. Longer sessions accumulate greater variation as they're exposed to multiple concurrent experiments simultaneously, making the 'model ID' a meaningless guarantee of consistency. For anyone building production agents on hosted models, this reveals that consistency depends entirely on vendor transparency, not technical implementation.