Unverified50% confidenceOpinionExact time
The real difficulty of industrial Agents lies in engineering rather than the model, with protocol integration, dirty data processing, anomaly detection, and device adaptation being the hard challenges in practice.
1
Sources
50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedIdentifying test coverage gaps requires engineers to simultaneously understand business intent, technical implementation, and user behavior patterns, making it high-value work that AI currently cannot complete independently.71% similarUnverified工程师应向问题定义、方案设计、业务落地等更难被替代的价值链上游环节迁移70% similarUnverifiedMost intelligent agent projects fail not because of the model itself, but because of problems in the tool design.69% similarUnverifiedCore capabilities of industrial Agents such as the safety verification layer, industrial tool library, and manual takeover system must be built in-house, and open-source frameworks should not be relied upon to solve industrial-grade reliability issues.69% similarUnverifiedThe lack of engineering capabilities causes Agent systems to fail in real business scenarios, which is the fundamental reason for not securing high salaries.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/908572API
curl https://kongchang.com/api/v1/knowledge/claims/908572MCP
get_claim(id=908572)