Unverified50% confidenceOpinionExact time
AI合规所需的是持续、自动化、可重复的对抗测试流程，而非快照式证据
1
Sources
50%
Confidence
Long-term
Relevance
7/11/2026
First Seen
Sources
Related Claims
VerifiedA more pragmatic testing approach is to use AI to assist the testing process rather than relying on AI for full execution, leveraging AI for efficiency gains in early-stage steps while returning to a stable in-house code framework for the final execution stage.85% similarUnverifiedAI-generated industrial programs still require rigorous manual review and on-site testing before actual production deployment, with AI playing the role of an intelligent co-pilot rather than fully replacing engineers.79% similarVerifiedAI can rapidly generate test cases, write automation scripts, perform simple API debugging, conduct log keyword troubleshooting, carry out basic functional regression testing, and batch-create test data.78% similarUnverifiedBefore deploying AI-generated automation scripts into production, regression testing must be performed with entirely new real-world data that the AI has never seen—this is called acceptance-driven AI deployment.78% similarVerified代理化编程强调测试驱动闭环，测试为AI提供明确的成功信号，是AI自我纠错的关键78% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/474819API
curl https://kongchang.com/api/v1/knowledge/claims/474819MCP
get_claim(id=474819)