Unverified50% confidenceFactExact time
The industry usually divides agents into two categories, 'passively responsive' and 'proactively suggesting', where the former still requires user triggering and the latter can initiate actions on its own under certain conditions.
1
Sources
50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedTriggers for the human-in-the-loop mechanism generally include the user actively requesting a transfer to a human agent, the AI's confidence falling below a threshold, high-risk topics such as complaints or refunds, and the number of conversation turns exceeding a preset limit.72% similarUnverifiedThe fundamental difference between agentic commerce and traditional e-commerce recommendation systems lies in where decision-making authority rests: traditional recommendation algorithms only influence what users see, while the final click and purchase are still completed by humans; in agentic commerce, users delegate preferences, budgets and constraints to an agent, and the agent directly executes transactions within the authorized scope.71% similarUnverifiedSecurity risks of agents are typically categorized into two types: prompt injection and runaway behavior.71% similarUnverifiedThe agency ladder, from low to high, is roughly: passive response, rule-based triggering, planning within a goal space, and then having one's own preferences and actively changing the environment.71% similarUnverified若需求描述存在歧义，Agent 自动发起的 PR 可能偏离预期，反而增加 Review 负担70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1037099API
curl https://kongchang.com/api/v1/knowledge/claims/1037099MCP
get_claim(id=1037099)