Unverified50% confidenceOpinionExact time
Boge believes that "using prompts well can significantly improve the application effect of large models," and prompts are the key variable determining application effectiveness.
1
Sources
50%
Confidence
Long-term
Relevance
10/17/2026
First Seen
Sources
Related Entities
Related Claims
Unverified作者认为决定最终优化效果的主要是提示词和使用的大模型型号，提示词越具体Agent执行越到位79% similarUnverified使用高能力模型进行优化的推荐交互模式包括：明确定义成功指标、提供基线方案、让模型提出改进假设并预估收益、将执行结果反馈给模型迭代调整76% similarUnverifiedThe quality of tool descriptions directly affects the accuracy with which large models invoke them; the clearer the description and the more detailed the parameter explanations, the more correctly the model can match and call them.76% similarUnverified大多数扩散模型对提示词中靠前位置的描述赋予更高的权重，因此将最重要的视觉元素放在提示词开头是有效的实践技巧72% similarUnverifiedCalibrating quantization parameters with data relevant to the target task can significantly improve the model's performance on that task72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1050963API
curl https://kongchang.com/api/v1/knowledge/claims/1050963MCP
get_claim(id=1050963)