Verified65% confidenceSolutionExact time
Setting a maximum number of steps, timeout duration, and cost ceiling for each Agent can prevent Agents from falling into infinite loops that consume tokens and API quotas.
3
Sources
65%
Confidence
Long-term
Relevance
7/16/2026
First Seen
Sources
Related Claims
UnverifiedSetting parameters such as token limits or max_iterations inside an AI agent runtime can define boundaries for a single execution, preventing the agent from falling into infinite loops or uncontrollably consuming resources.78% similarUnverifiedSetting a maximum number of iterations and a maximum token budget for an Agent is a basic measure to prevent runaway costs.77% similarVerifiedEach Agent run incurs actual API call costs, and as the scale of evaluation use cases grows and retries accumulate, costs can mount rapidly.76% similarVerifiedCommon solutions for Agent cost control include: using lightweight models for intermediate reasoning steps, caching results from repetitive tool calls, and setting a maximum number of steps to force truncation—all of which need to be reserved for during the architectural design phase.74% similarUnverifiedGranting each tool in the Agent the minimum necessary permissions, logging every step, and setting limits on steps and cost are key measures for ensuring an Agent can go live safely.74% similar
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