Unverified50% confidenceOpinionExact time
Small models perform strongly on bounded tasks because the prompt can carry most of the intelligence; they degrade on unbounded tasks.
1
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50%
Confidence
Long-term
Relevance
10/19/2026
First Seen
Sources
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Related Claims
UnverifiedExisting models perform excellently on specific tasks but lack truly cross-domain general intelligence.78% similarUnverifiedThe effect of few-shot prompting shows strong task dependence, with task nature being the key variable determining whether examples are effective.78% similarUnverifiedIn automated tasks requiring highly deterministic output, such tools may bring gains, whereas in creative or exploratory conversations, excessive constraints may limit the model's performance.77% similarUnverifiedThe more specific the task and the clearer the feedback signal, the higher the agent's success rate; open-ended tasks with vague descriptions often cause agents to fall into repeated trial and error.75% similarUnverified智能体的智能来自模型本身，工程只是提供一个能持续获取反馈和行动的最小闭环75% similar
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