Agent step limits should produce a controlled handover

Step, time and cost limits help bound automated work. Their value depends on what the application does at the boundary.

Define limits around the task

Identify which operations consume the budget and which actions require an earlier stop. A low-consequence retrieval loop differs from repeated attempts to modify an external record.

AWS Step Functions’ error-handling documentation demonstrates explicit handling of workflow failures. An agent design similarly needs an explicit route when its permitted work is exhausted.

An illustrative research assistant can retain collected sources and unresolved questions when time expires. It should not fabricate a conclusion merely to return a complete-looking answer.

Preserve the decision state

Record completed steps, pending actions and any uncertain external outcomes. Avoid saving only a narrative summary if a reliable continuation requires structured identifiers.

Tell the user whether continuing would repeat work, incur more cost or require additional authority. A limit should not become a hidden permission to keep trying through another path.

Where a task cannot safely pause, design that constraint before deployment. Some operations require a controlled completion or compensation sequence.

Review repeated limit events

Frequent exhaustion may reveal an unsuitable task, poor tool design or inadequate input. Increasing the limit can postpone the symptom while raising cost and risk.

Include the remaining permitted work in the handover. A user should understand whether the agent exhausted its search scope, reached a technical limit or lacks authority for the next action. Those conditions call for different decisions and should not all produce the same vague request to continue.

GAT’s AI pilot guide connects capability to operational readiness. A controlled handover at the limit is part of that readiness: the system should remain useful and accountable even when it cannot finish automatically.