Unverified60% confidenceFactExact time
Large language models can only answer questions and cannot proactively initiate system calls or network requests, whereas agents can perceive needs, determine a course of action, and execute operations to complete end-to-end tasks.
2
Sources
60%
Confidence
Long-term
Relevance
7/20/2026
First Seen
Sources
Related Claims
UnverifiedThe key difference between an agent and large-model question answering lies in autonomy: it can not only answer questions but also plan steps according to goals, call tools (such as search, calculation, APIs), observe results and adjust the next action.79% similarUnverified通过系统提示词约束智能体只回答知识库中有的问题,可有效防止智能体回答无关问题并引导转人工76% 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.72% similarUnverifiedKeep tasks small enough: one agent, one clear task, one reviewable diff. Huge AI-generated pull requests do not get truly reviewed—they only get approved.72% similarUnverifiedTraditional large models such as ChatGPT are essentially intelligent question-answering systems whose capability stops at the answering level and cannot truly execute operations.71% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/573164API
curl https://kongchang.com/api/v1/knowledge/claims/573164MCP
get_claim(id=573164)