An agent's time horizon shrinks by half when every retry must succeed, and the gap has not closed across model generations
Frontier AI agent time horizons are usually computed from average success: the task length an agent completes with 50% probability, measured in human expert time. This analysis instead fits a reliability horizon from METR's public run-level records, using the probability that all four attempts on the same task succeed. Across 50 model-benchmark combinations the reliability horizon is always shorter than the capability horizon, with a geometric-mean ratio of about 2.4, and the gap did not narrow significantly between 2023 and early 2026.