Verified65% confidenceFactExact time
AI agents typically generate database queries or API calls dynamically via large language models, rather than using parameterized queries pre-written by engineers.
3
Sources
65%
Confidence
Long-term
Relevance
8/12/2026
First Seen
Sources
Related Claims
UnverifiedAI-based automatic test case generation primarily relies on large language models to semantically understand requirements documents, interface definitions, or code logic, and automatically derive test scenarios such as equivalence classes, boundary values, and exception paths.80% similarUnverifiedA single AI coding request often consists of a series of sub-calls triggered autonomously by the agent (querying context, invoking tools, multi-round reasoning) forming a complete execution chain, rather than a single API call.78% similarUnverified在AI代理编程领域，搜索能力直接决定系统表现，因为搜索本质上是为语言模型提供上下文数据78% similarUnverifiedAIMA covers search algorithms, logical reasoning, machine learning, and natural language processing, providing a panoramic understanding of artificial intelligence, with each chapter being relatively self-contained.77% similarUnverifiedThe system performs intelligent interpretation of historical training or backtesting data by calling AI interfaces such as Tongyi Qianwen and ERNIE Bot.76% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/735006API
curl https://kongchang.com/api/v1/knowledge/claims/735006MCP
get_claim(id=735006)