Unverified60% 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.
2
Sources
60%
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% similarUnverifiedBreaking a complex project into phases with clear inputs and outputs allows the Agent to always deliver within a controllable scope, avoiding the loss of control that results from handing everything to the Agent at once74% similar
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