Agentic Myopia: Probing the Temporal Awareness of Agents in Simulated Multi-Turn Coding Sessions

Coding agents increasingly operate over long, multi-turn sessions, in which a user and an agent collaborate on a large software task. As these sessions lengthen, agents are delegated increasing autonomy, completing substantial subtasks with limited user oversight. This delegation introduces a coordination cost: a user who intends to plan around, budget for, or intervene in the agent's work requires an accurate estimate of the work that remains. We term an agent's capacity to produce this estimate of remaining work (measured in outstanding turns, wall-clock time, and generated tokens) its temporal awareness. This capacity remains largely unexamined in the multi-turn setting in which coding agents are now deployed, where requirements emerge over the course of a session rather than being fixed at its start. We study coding agent temporal awareness in five frontier-hard software environments, in which a simulated user reveals task instruction to a coding agent incrementally. Using a carefully-designed fork-and-discard probing protocol to estimate five quantities of remaining work in a session, we find that frontier agents largely lack temporal awareness. Their answers are myopic: estimates of remaining work barely move as a session runs down. Given the full list of requirements still to come, agents size the remaining turns almost exactly, with the ratio of predicted to actual rising from 0.27 to 0.97. Curiously, the same list pushes wall-clock estimates to three times the truth. Token estimates climb only from 3% of the truth to about a quarter of it, so the two costs of the remaining work err in opposite directions. An agent that knows how much is left can still misjudge what it will cost, and coding agents cannot yet be trusted to budget the rest of a session.