Unverified50% confidenceTradeoffExact time
In loop scenarios, each iteration requires feeding the entire conversation history back into the model, causing per-iteration token consumption to increase incrementally due to context accumulation, resulting in a cost curve steeper than linear.
1
Sources
50%
Confidence
Long-term
Relevance
7/19/2026
First Seen
Sources
Loop Engineering：无人监管的AI循环为何危机四伏
Related Claims
UnverifiedWhen an agent is in a loop, each call carries the accumulated conversation history, causing token consumption to grow linearly or even super-linearly with the number of iterations.79% similarUnverifiedMost Agent frameworks adopt a full context replay strategy, requiring the entire conversation history to be passed in with each call, causing token consumption to grow quadratically with the number of loop iterations.76% similarUnverified在智能体工作流中，历史交互作为输入Token累积，导致总Token消耗随任务轮次呈近似平方级增长74% similarUnverified在多轮Agent对话中，每轮都需携带完整上下文，越往后的轮次Token消耗越高73% similarUnverifiedDue to the combination of multiple rounds of iteration, full context carrying, and self-checking mechanisms, token consumption in Loop Engineering is typically 5 to 20 times that of ordinary conversations.73% similar
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